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Anthropic's Claude is an AI bot that keeps up a steady pace when it comes to pushing out new features, and the latest upgrade of note sees three useful features make their way down to free users, having previously been exclusive to the paid-for plans. If you're choosing between AIs and comparing the features available on the free plans, then there's now more of a case to be made for choosing Claude over a competitor like ChatGPT or Gemini for your next batch of AI tasks. The three new features now available to free users on Claude are file creation, external plug-ins called Connectors, and bundles of instructions called Skills. Here's how you can make use of them. File creation in ClaudeClaude's file creation capabilities let you create Word documents, PowerPoint slideshows, Excel spreadsheets, and PDFs from right inside a conversation. You can either supply the bot with all text, data, and other information you want included, get Claude to invent everything itself, or something in between. For example, if you've got a long list of names and scores, Claude can put them into a spreadsheet for you. If you've got a series of images, Claude can combine them into a PDF and describe them. You can get it to analyze and visualize data, produce presentations based on reports, and create summary documents. A simple prompt can create a file in Claude. Credit: Lifehacker To enable file creation for your account, click your profile icon (bottom left) in Claude on the web, then select Settings > Capabilities and enable Code execution and file creation. With that done, you just have to prompt Claude with the type of file you want to make and what you want included, supplying any information as needed (or telling the AI where to find it online). As usual with these AI bots, the more detail and specificity you can provide, the better—the end result is then more likely to be closer to what you were aiming for. I got it to quickly come up with the results of a fictional sports day race, and produce a spreadsheet from it. While it's not the most demanding of tasks, Claude completed it correctly. Claude ConnectorsConnectors can hook Claude up to a variety of other apps, sites, and services: So if you want to get it to design something for you in Canva, or manage your messages in Slack, or find some travel deals on Trivago, then Claude can do that for you. The full list of current Connectors gives you some idea of what's possible. To get to the Connectors from the Claude prompt box, click the small + (plus) icon in the lower left corner, then choose Add connectors. You can search through Connectors by name, and filter them by type and category. When you select one you like, you'll need to supply your account credentials and give Claude permission to access your account. Use Connectors to connect Claude to other apps. Credit: Lifehacker Your Connectors of choice are then available from the same sub-menu in the prompt box: You can add more plug-ins and remove existing ones from there. You can either select an app, or specify the name of it in your prompt and Claude should understand what you mean. You can ask for outputs, run searches, and communicate through your connected services. Connectors can give Claude some handy extra talents. With the Canvas Connector, for example, I was able to create a basic bit of artwork for a birthday party flyer—something that the AI wouldn't have been able to do on its own. I find that access was spotty, however, perhaps a sign of a lot of free users now making use of these tools. Claude SkillsWith Skills, you can "teach Claude how to complete specific tasks in a repeatable way" (in the words of the official support document). In old-school computer talk, they might be referred to as macros: batches of set instructions that Claude can repeat whenever you need something doing in a particular way. Templates are a good example, whether they're for emails or documents. Rather than just getting Claude to write an email for you, you can set down some basic parameters for the job that include guidelines on tone, length, and style, as well as crucial bits of information (such as your contact details) that always need to be included. You've got three options for creating Skills. Credit: Lifehacker Click your account profile icon (bottom left) in Claude on the web, then choose Settings > Capabilities and click Add under Skills to get started. You can create a Skill through a Claude conversation, by writing out the instructions, or by uploading a Skills file (which is handy for including extra items such as code snippets, as described here). I took the Create with Claude route to put together a basic way of summarizing PDF reports, with specific guidelines on how many paragraphs and headings to use, and the tone of voice to apply. In the future, rather than typing out those instructions every time I need something summarized, I can just invoke the Skill. View the full article

Rand Fishkin just published the most important piece of primary research the AI visibility industry has seen so far. His conclusion – that AI tools produce wildly inconsistent brand recommendation lists, making “ranking position” a meaningless metric – is correct, well-evidenced, and long overdue. But Fishkin stopped one step short of the answer that matters. He didn’t explore why some brands appear consistently while others don’t, or what would move a brand from inconsistent to consistent visibility. That solution is already formalized, patent pending, and proven in production across 73 million brand profiles. When I shared this with Fishkin directly, he agreed. The AI models are pulling from a semi-fixed set of options, and the consistency comes from the data. He just didn’t have the bandwidth to dig deeper, which is fair enough, but the digging has been done – I’ve been doing it for a decade. Here’s what Fishkin found, what it actually means, and what the data proves about what to do about it. Fishkin’s data killed the myth of AI ranking position Fishkin and Patrick O’Donnell ran 2,961 prompts across ChatGPT, Claude, and Google AI, asking for brand recommendations across 12 categories. The findings were surprising for most. Fewer than 1 in 100 runs produced the same list of brands, and fewer than 1 in 1,000 produced the same list in the same order. These are probability engines that generate unique answers every time. Treating them as deterministic ranking systems is – as Fishkin puts it – “provably nonsensical,” and I’ve been saying this since 2022. I’m grateful Fishkin finally proved it with data. But Fishkin also found something he didn’t fully unpack. Visibility percentage – how often a brand appears across many runs of the same prompt – is statistically meaningful. Some brands showed up almost every time, while others barely appeared at all. That variance is where the real story lies. Fishkin acknowledged this but framed it as a better metric to track. The real question isn’t how to measure AI visibility, it’s why some brands achieve consistent visibility and others don’t, and what moves your brand from the inconsistent pile to the consistent pile. That’s not a tracking problem. It’s a confidence problem. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with AI systems are confidence engines, not recommendation engines AI platforms – ChatGPT, Claude, Google AI, Perplexity, Gemini, all of them – generate every response by sampling from a probability distribution shaped by: What the model knows. How confidently it knows it. What it retrieved at the moment of the query. When the model is highly confident about an entity’s relevance, that entity appears consistently. When the model is uncertain, the entity sits at a low probability weight in the distribution – included in some samples, excluded in others – not because the selection is random but because the AI doesn’t have enough confidence to commit. That’s the inconsistency Fishkin documented, and I recognized it immediately because I’ve been tracking exactly this pattern since 2015. City of Hope appearing in 97% of cancer care responses isn’t luck. It’s the result of deep, corroborated, multi-source presence in exactly the data these systems consume. The headphone brands at 55%-77% are in a middle zone – known, but not unambiguously dominant. The brands at 5%-10% have low confidence weight, and the AI includes them in some outputs and not others because it lacks the confidence to commit consistently. Confidence isn’t just about what a brand publishes or how it structures its content. It’s about where that brand stands relative to every other entity competing for the same query – a dimension I’ve recently formalized as Topical Position. I’ve formalized this phenomenon as “cascading confidence” – the cumulative entity trust that builds or decays through every stage of the algorithmic pipeline, from the moment a bot discovers content to the moment an AI generates a recommendation. It’s the throughline concept in a framework I published this week. Dig deeper: Search, answer, and assistive engine optimization: A 3-part approach Every piece of content passes through 10 gates before influencing an AI recommendation The pipeline is called DSCRI-ARGDW – discovered, selected, crawled, rendered, indexed, annotated, recruited, grounded, displayed, and won. That sounds complicated, but I can summarize it in a single question that repeats at every stage: How confident is the system in this content? Is this URL worth crawling? Can it be rendered correctly? What entities and relationships does it contain? How sure is the system about those annotations? When the AI needs to answer a question, which annotated content gets pulled from the index? Confidence at each stage feeds the next. A URL from a well-structured, fast-rendering, semantically clean site arrives at the annotation stage with high accumulated confidence before a single word of content is analyzed. A URL from a slow, JavaScript-heavy site with inconsistent information arrives with low confidence, even if the actual content is excellent. This is pipeline attenuation, and here’s where the math gets unforgiving. The relationship is multiplicative, not additive: C_final = C_initial × ∏τᵢ In plain English, the final confidence an AI system has in your brand equals the initial confidence from your entity home multiplied by the transfer coefficient at every stage of the pipeline. The entity home – the canonical web property that anchors your entity in every knowledge graph and every AI model – sets the starting confidence, and then each stage either preserves or erodes it. Maintain 90% confidence at each of 10 stages, and end-to-end confidence is 0.9¹⁰ = 35%. At 80% per stage, it’s 0.8¹⁰ = 11%. One weak stage – say 50% at rendering because of heavy JavaScript – drops the total from 35% to 19% even if every other stage is at 90%. One broken stage can undo the work of nine good ones. This multiplicative principle isn’t new, and it doesn’t belong to anyone. In 2019, I published an article, How Google Universal Search Ranking Works: Darwinism in Search, based on a direct explanation from Google’s Gary Illyes. He described how Google calculates ranking “bids” by multiplying individual factor scores rather than adding them. A zero on any factor kills the entire bid, no matter how strong the other factors are. Google applies this multiplicative model to ranking factors within a single system, and nobody owns multiplication. But what the cascading confidence framework does is apply this principle across the full 10-stage pipeline, across all three knowledge graphs. The system provides measurable transfer coefficients at every transition and bottleneck detection that identifies exactly where confidence is leaking. The math is universal, but the application to a multi-stage, multi-graph algorithmic pipeline is the invention. This complete system is the subject of a patent application I filed with the INPI titled “Système et procédé d’optimisation de la confiance en cascade à travers un pipeline de traitement algorithmique multi-étapes et multi-graphes.” It’s not a metaphor, it’s an engineered system with an intellectual lineage going back seven years to a principle a Google engineer confirmed to me in person. Fishkin measured the output – the inconsistency of recommendation lists. But the output is a symptom, and the cause is confidence loss at specific stages of this pipeline, compounded across multiple knowledge representations. You can’t fix inconsistency by measuring it more precisely. You can only fix it by building confidence at every stage. The corroboration threshold is where AI shifts from hesitant to assertive There’s a specific transition point where AI behavior changes. I call it the “corroboration threshold” – the minimum number of independent, high-confidence sources corroborating the same conclusion about your brand before the AI commits to including it consistently. Below the threshold, the AI hedges. It says “claims to be” instead of “is,” it includes a brand in some outputs but not others, and the reason isn’t randomness but insufficient confidence. The brand sits in the low-confidence zone, where inconsistency is the predictable outcome. Above the threshold, the AI asserts – stating relevance as fact, including the brand consistently, operating with the kind of certainty that produces City of Hope’s 97%. My data across 73 million brand profiles places this threshold at approximately 2-3 independent, high-confidence sources corroborating the same claim as the entity home. That number is deceptively small because “high-confidence” is doing the heavy lifting – these are sources the algorithm already trusts deeply, including Wikipedia, industry databases, and authoritative media. Without those high-authority anchors, the threshold rises considerably because more sources are needed and each carries less individual weight. The threshold isn’t a one-time gate. Once crossed, the confidence compounds with every subsequent corroboration, which is why brands that cross it early pull further ahead over time, while brands that haven’t crossed it yet face an ever-widening gap. Not identical wording, but equivalent conviction. The entity home states, “X is the leading authority on Y,” two or three independent, authoritative third-party sources confirm it with their own framing, and the AI encodes it as fact. This fact is visible in my data, and it explains exactly why Fishkin’s experiment produced the results it did. In narrow categories like LA Volvo dealerships or SaaS cloud computing providers – where few brands exist and corroboration is dense – AI responses showed higher pairwise correlation. In broad categories like science fiction novels – where thousands of options exist and corroboration is thin – responses were wildly diverse. The corroboration threshold aligns with Fishkin’s findings. Dig deeper: The three AI research modes redefining search – and why brand wins Authoritas proved that fabricated entities can’t fool AI confidence systems Authoritas published a study in December 2025 – “Can you fake it till you make it in the age of AI?” – that tested this directly, and the results confirm that Cascading Confidence isn’t just theory. Where Fishkin’s research shows the output problem – inconsistent lists – Authoritas shows the input side. Authoritas investigated a real-world case where a UK company created 11 entirely fictional “experts” – made-up names, AI-generated headshots, faked credentials. They seeded these personas into more than 600 press articles across UK media, and the question was straightforward: Would AI models treat these fake entities as real experts? The answer was absolute: Across nine AI models and 55 topic-based questions – “Who are the UK’s leading experts in X?” – zero fake experts appeared in any recommendation. Six hundred press articles, and not a single AI recommendation. That might seem to contradict a threshold of 2-3 sources, but it confirms it. The threshold requires independent, high-confidence sources, and 600 press articles from a single seeding campaign are neither independent – they trace to the same origin – nor high-confidence – press mentions sit in the document graph only. The AI models looked past the surface-level coverage and found no deep entity signals – no entity home, no knowledge graph presence, no conference history, no professional registration, no corroboration from the kind of authoritative sources that actually move the needle. The fake personas had volume, they had mentions, but what they lacked was cascading confidence – the accumulated trust that builds through every stage of the pipeline. Volume without confidence means inconsistent appearance at best, while confidence without volume still produces recommendations. AI evaluates confidence — it doesn’t count mentions. Confidence requires multi-source, multi-graph corroboration that fabricated entities fundamentally can’t build. Get the newsletter search marketers rely on. See terms. AI citability concentration increased 293% in under two months Authoritas used the weighted citability score, or WCS, a metric that measures how much AI engines trust and cite entities, calculated across ChatGPT, Gemini, and Perplexity using cross-context questions. I have no influence over their data collection or their results. Fishkin’s methodology and Authoritas’ aren’t identical. Fishkin pinged the same query repeatedly to measure variance, while Authoritas tracks varied queries on the same topic. That said, the directional finding is consistent. Their dataset includes 143 recognized digital marketing experts, with full snapshots from the original study by Laurence O’Toole and Authoritas in December 2025 and their latest measurement on Feb. 2. The pattern across the entire dataset tells a story that goes far beyond individual scores. The top 10 experts captured 30.9% of all citability in December. By February, they captured 59.5% – a 92% increase in concentration in under two months. The HHI, or Herfindahl-Hirschman Index, the standard measure of market concentration, rose from 0.026 to 0.104 – a 293% increase in concentration. This happened while the total expert pool widened from 123 to 143 tracked entities. More experts are being cited, the field is getting bigger, and the top is pulling away faster. Dominance is compounding while the long tail grows. This is cascading confidence at population scale. The experts who actively manage their digital footprint – clean entity home, corroborated claims, consistent narrative across the algorithmic trinity – aren’t just maintaining their position, they’re accelerating away from everyone else. Each cycle of AI training and retrieval reinforces their advantage – confident entities generate confident AI outputs, which build user trust, which generate positive engagement signals, which further reinforce the AI’s confidence. It’s a flywheel, and once it’s spinning, it becomes very, very hard for competitors to catch up. At the individual level, the data confirms the mechanism. I lead the dataset at a WCS of 23.50, up from 21.48 in December, a gain of +2.02. That’s not because I’m more famous than everyone else on the list. It’s because we’ve been systematically building my cascading confidence for years – clean entity home, corroborated claims across the algorithmic trinity, consistent narrative, structured data, deep knowledge graph presence. I’m the primary test case because I’m in control of all my variables – I have a huge head start. In a future article, I’ll dig into the details of the scores and why the experts have the scores they do. The pattern across my client base mirrors the population data. Brands that systematically clean their digital footprint, anchor entity confidence through the entity home, and build corroboration across the algorithmic trinity don’t just appear in AI recommendations. They appear consistently, their advantage compounds over time, and they exit the low-confidence zone to enter the self-reinforcing recommendation set. Dig deeper: From SEO to algorithmic education: The roadmap for long-term brand authority AI retrieves from three knowledge representations simultaneously, not one AI systems pull from what I call the Three Graphs model – the algorithmic trinity – and understanding this explains why some brands achieve near-universal visibility while others appear sporadically. The entity graph, or knowledge graph, contains explicit entities with binary verified edges and low fuzziness – either a brand is in, or it’s not. The document graph, or search engine index, contains annotated URLs with scored and ranked edges and medium fuzziness. The concept graph, or LLM parametric knowledge, contains learned associations with high fuzziness, and this is where the inconsistency Fishkin documented comes from. When retrieval systems combine results from multiple sources – and they do, using mechanisms analogous to reciprocal rank fusion – entities present across all three graphs receive a disproportionate boost. The effect is multiplicative, not additive. A brand that has a strong presence in the knowledge graph and the document index and the concept space gets chosen far more reliably than a brand present in only one. This explains a pattern Fishkin noticed but didn’t have the framework to interpret – why visibility percentages clustered differently across categories. The brands with near-universal visibility aren’t just “more famous,” they have dense, corroborated presence across all three knowledge representations. The brands in the inconsistent pool are typically present in only one or two. The Authoritas fake expert study confirms this from the negative side. The fake personas existed only in the document graph, press articles, with zero entity graph presence and negligible concept graph encoding. One graph out of three, and the AI treated them accordingly. What I tell every brand after reading Fishkin’s data Fishkin’s recommendations were cautious – visibility percentage is a reasonable metric, ranking position isn’t, and brands should demand transparent methodology from tracking vendors. All fair, but that’s analyst advice. What follows is practitioner advice, based on doing this work in production. Stop optimizing outputs and start optimizing inputs The entire AI tracking industry is fixated on measuring what AI says about you, which is like checking your blood pressure without treating the underlying condition. Measure if it helps, but the work is in building confidence at every stage of the pipeline, and that’s where I focus my clients’ attention from day one. Start at the entity home My experience clearly demonstrates that this single intervention produces the fastest measurable results. Your entity home is the canonical web property that should anchor your entity in every knowledge graph and every AI model. If it’s ambiguous, hedging, or contradictory with what third-party sources say about you, it is actively training AI to be uncertain. I’ve seen aligning the entity home with third-party corroboration produce measurable changes in bottom-of-funnel AI citation behavior within weeks, and it remains the highest ROI intervention I know. Cross the corroboration threshold for the critical claims I ask every client to identify the claims that matter most: Who you are. What you do. Why you’re credible. Then, I work with them to ensure each claim is corroborated by at least 2-3 independent, high-authority sources. Not just mentioned, but confirmed with conviction. This is what flips AI from “sometimes includes” to “reliably includes,” and I’ve seen it happen often enough to know the threshold is real. Dig deeper: SEO in the age of AI: Becoming the trusted answer Build across all three graphs simultaneously Knowledge graph presence (structured data, entity recognition), document graph presence (indexed, well-annotated content on authoritative sites), and concept graph presence (consistent narrative across the corpus AI trains on) all need attention. The Authoritas study showed exactly what happens when a brand exists in only one – the AI treats it accordingly. Work the pipeline from Gate 1, not Gate 9 Most SEO and GEO advice operates at the display stage, optimizing what AI shows. But if your content is losing confidence at discovery, selection, rendering, or annotation, it will never reach display consistently enough to matter. I’ve watched brands spend months on display-stage optimization that produced nothing because the real bottleneck was three stages earlier, and I always start my diagnostic at the beginning of the pipeline, not the end. Maintain it because the gap is widening The WCS data across 143 tracked experts shows that AI citability concentration increased 293% in under two months. The experts who maintain their digital footprint are pulling away from everyone else at an accelerating rate. Starting now still means starting early, but waiting means competing against entities whose advantage compounds every cycle. This isn’t a one-time project. It’s an ongoing discipline, and the returns compound with every iteration. See the complete picture of your search visibility. Track, optimize, and win in Google and AI search from one platform. Start Free Trial Get started with Fishkin proved the problem exists. The solution has been in production for a decade. Fishkin’s research is a gift to the industry. He killed the myth of AI ranking position with data, he validated that visibility percentage, while imperfect, correlates with something real, and he raised the right questions about methodology that the AI tracking vendors should have been answering all along. But tracking AI visibility without understanding why visibility varies is like tracking a stock price without understanding the business. The price is a signal, and the business is the thing. AI recommendations are inconsistent when AI systems lack confidence in a brand. They become consistent when that confidence is built deliberately, through: The entity home. Corroborated claims that cross the corroboration threshold. Multi-graph presence. Every stage of the pipeline that processes your content before AI ever generates a response. This isn’t speculation, and the evidence comes from every direction. The process behind this approach has been under development since 2015 and is formalized in a peer-review-track academic paper. Several related patent applications have been filed in France, covering entity data structuring, prompt assembly, multi-platform coherence measurement, algorithmic barrier construction, and cascading confidence optimization. The dataset supporting the work spans 25 billion data points across 73 million brand profiles. In tracked populations, shifts in AI citability have been observed — including cases where the top 10 experts increased their share from 31% to 60% in under two months while the overall field expanded. Independent research from Authoritas reports findings that align with this mechanism. Fishkin proved the problem exists. My focus over the past decade has been on implementing and refining practical responses to it. This is the first article in a series. The second piece, “What the AI expert rankings actually tell us: 8 archetypes of AI visibility,” examines how the pipeline’s effects manifest across 57 tracked experts. The third, “The ten gates between your content and an AI recommendation,” opens the DSCRI-ARGDW pipeline itself. View the full article

The Rev. Jesse L. Jackson, a protege of the Rev. Martin Luther King Jr. and two-time presidential candidate who led the Civil Rights Movement for decades after the revered leader’s assassination, died Tuesday. He was 84. As a young organizer in Chicago, Jackson was called to meet with King at the Lorraine Motel in Memphis shortly before King was killed and he publicly positioned himself thereafter as King’s successor. Jackson led a lifetime of crusades in the United States and abroad, advocating for the poor and underrepresented on issues from voting rights and job opportunities to education and health care. He scored diplomatic victories with world leaders, and through his Rainbow/PUSH Coalition, he channeled cries for Black pride and self-determination into corporate boardrooms, pressuring executives to make America a more open and equitable society. And when he declared, “I am Somebody,” in a poem he often repeated, he sought to reach people of all colors. “I may be poor, but I am Somebody; I may be young; but I am Somebody; I may be on welfare, but I am Somebody,” Jackson intoned. It was a message he took literally and personally, having risen from obscurity in the segregated South to become America’s best-known civil rights activist since King. Santita Jackson confirmed that her father died at home in Chicago, surrounded by family. “Our father was a servant leader — not only to our family, but to the oppressed, the voiceless, and the overlooked around the world,” the Jackson family said in a statement posted online. “We shared him with the world, and in return, the world became part of our extended family.” Fellow civil rights activist the Rev. Al Sharpton said his mentor “was not simply a civil rights leader; he was a movement unto himself.” “He taught me that protest must have purpose, that faith must have feet, and that justice is not seasonal, it is daily work,” Sharpton wrote in a statement, adding that Jackson taught “trying is as important as triumph. That you do not wait for the dream to come true; you work to make it real.” Despite profound health challenges in his final years including a rare neurological disorder that affected his ability to move and speak, Jackson continued protesting against racial injustice into the era of Black Lives Matter. In 2024, he appeared at the Democratic National Convention in Chicago and at a City Council meeting to show support for a resolution backing a ceasefire in the Israel-Hamas war. “Even if we win,” he told marchers in Minneapolis before the officer whose knee kept George Floyd from breathing was convicted of murder, “it’s relief, not victory. They’re still killing our people. Stop the violence, save the children. Keep hope alive.” Calls to action, delivered in a memorable voice Jackson’s voice, infused with the stirring cadences and powerful insistence of the Black church, demanded attention. On the campaign trail and elsewhere, he used rhyming and slogans such as: “Hope not dope” and “If my mind can conceive it and my heart can believe it then I can achieve it,” to deliver his messages. Jackson had his share of critics, both within and outside of the Black community. Some considered him a grandstander, too eager to seek out the spotlight. Looking back on his life and legacy, Jackson told The Associated Press in 2011 that he felt blessed to be able to continue the service of other leaders before him and to lay a foundation for those to come. “A part of our life’s work was to tear down walls and build bridges, and in a half century of work, we’ve basically torn down walls,” Jackson said. “Sometimes when you tear down walls, you’re scarred by falling debris, but your mission is to open up holes so others behind you can run through.” In his final months, as he received 24-hour care, he lost his ability to speak, communicating with family and visitors by holding their hands and squeezing. “I get very emotional knowing that these speeches belong to the ages now,” his son, Jesse Jackson Jr., told the AP in October. A student athlete drawn to the Civil Rights Movement Jesse Louis Jackson was born on Oct. 8, 1941, in Greenville, South Carolina, the son of high school student Helen Burns and Noah Louis Robinson, a married man who lived next door. Jackson was later adopted by Charles Henry Jackson, who married his mother. Jackson was a star quarterback on the football team at Sterling High School in Greenville, and accepted a football scholarship from the University of Illinois. But after he reportedly was told Black people couldn’t play quarterback, he transferred to North Carolina A&T in Greensboro, where he became the first-string quarterback, an honor student in sociology and economics, and student body president. Arriving on the historically Black campus in 1960 just months after students there launched sit-ins at a whites-only diner, Jackson immersed himself in the blossoming Civil Rights Movement. By 1965, he joined the voting rights march King led from Selma to Montgomery, Alabama. King dispatched him to Chicago to launch Operation Breadbasket, a Southern Christian Leadership Conference effort to pressure companies to hire Black workers. Jackson called his time with King “a phenomenal four years of work.” Jackson was with King on April 4, 1968, when the civil rights leader was slain at the Lorraine Motel in Memphis, Tennessee. Jackson’s account of the assassination was that King died in his arms. With his flair for the dramatic, Jackson wore a turtleneck he said was soaked with King’s blood for two days, including at a King memorial service held by the Chicago City Council, where he said: “I come here with a heavy heart because on my chest is the stain of blood from Dr. King’s head.” However, several King aides, including speechwriter Alfred Duckett, questioned whether Jackson could have gotten King’s blood on his clothing. There are no images of Jackson in pictures taken shortly after the assassination. In 1971, Jackson broke with the Southern Christian Leadership Conference to form Operation PUSH, originally named People United to Save Humanity. The organization based on Chicago’s South Side declared a sweeping mission, from diversifying workforces to registering voters in communities of color nationwide. Using lawsuits and threats of boycotts, Jackson pressured top corporations to spend millions and publicly commit to diversifying their workforces. The constant campaigns often left his wife, Jacqueline Lavinia Brown, the college sweetheart he married in 1963, taking the lead in raising their five children: Santita Jackson, Yusef DuBois Jackson, Jacqueline Lavinia Jackson Jr., and two future members of Congress, U.S. Rep. Jonathan Luther Jackson and Jesse L. Jackson Jr., who resigned in 2012 but is seeking reelection in the 2026 midterms. The elder Jackson, who was ordained as a Baptist minister in 1968 and earned his Master of Divinity in 2000, also acknowledged fathering a child, Ashley Jackson, with one of his employees at Rainbow/PUSH, Karen L. Stanford. He said he understood what it means to be born out of wedlock and supported her emotionally and financially. Presidential aspirations fall short but help ‘keep hope alive’ Despite once telling a Black audience he would not run for president “because white people are incapable of appreciating me,” Jackson ran twice and did better than any Black politician had before President Barack Obama, winning 13 primaries and caucuses for the Democratic nomination in 1988, four years after his first failed attempt. His successes left supporters chanting another Jackson slogan, “Keep Hope Alive.” “I was able to run for the presidency twice and redefine what was possible; it raised the lid for women and other people of color,” he told the AP. “Part of my job was to sow seeds of the possibilities.” U.S. Rep. John Lewis said during a 1988 C-SPAN interview that Jackson’s two runs for the Democratic nomination “opened some doors that some minority person will be able to walk through and become president.” Jackson also pushed for cultural change, joining calls by NAACP members and other movement leaders in the late 1980s to identify Black people in the United States as African Americans. “To be called African Americans has cultural integrity — it puts us in our proper historical context,” Jackson said at the time. “Every ethnic group in this country has a reference to some base, some historical cultural base. African Americans have hit that level of cultural maturity.” Jackson’s words sometimes got him in trouble. In 1984, he apologized for what he thought were private comments to a reporter, calling New York City “Hymietown,” a derogatory reference to its large Jewish population. And in 2008, he made headlines when he complained that Obama was “talking down to Black people” in comments captured by a microphone he didn’t know was on during a break in a television taping. Still, when Jackson joined the jubilant crowd in Chicago’s Grant Park to greet Obama that election night, he had tears streaming down his face. “I wish for a moment that Dr. King or (slain civil rights leader) Medgar Evers … could’ve just been there for 30 seconds to see the fruits of their labor,” he told the AP years later. “I became overwhelmed. It was the joy and the journey.” Exerting influence on events at home and abroad Jackson also had influence abroad, meeting world leaders and scoring diplomatic victories, including the release of Navy Lt. Robert Goodman from Syria in 1984, as well as the 1990 release of more than 700 foreign women and children held after Iraq’s invasion of Kuwait. In 1999, he won the freedom of three Americans imprisoned by Yugoslav President Slobodan Milosevic. In 2000, President Bill Clinton awarded Jackson the Presidential Medal of Freedom, the country’s highest civilian honor. “Citizens have the right to do something or do nothing,” Jackson said, before heading to Syria. “We choose to do something.” In 2021, Jackson joined the parents of Ahmaud Arbery inside the Georgia courtroom where three white men were convicted of killing the young Black jogger. In 2022, he hand-delivered a letter to the U.S. Attorney’s Office in Chicago, calling for federal charges against former Chicago Police Officer Jason Van Dyke in the 2014 killing of Black teenager Laquan McDonald. Jackson, who stepped down as president of Rainbow/PUSH in July 2023, disclosed in 2017 that he had sought treatment for Parkinson’s, but he continued to make public appearances even as the disease made it more difficult for listeners to understand him. Earlier this year doctors confirmed a diagnosis of progressive supranuclear palsy, a life-threatening neurological disorder. He was admitted to a hospital in November. During the coronavirus pandemic, he and his wife survived being hospitalized with COVID-19. Jackson was vaccinated early, urging Black people in particular to get protected, given their higher risks for bad outcomes. “It’s America’s unfinished business — we’re free, but not equal,” Jackson told the AP. “There’s a reality check that has been brought by the coronavirus, that exposes the weakness and the opportunity.” Former Associated Press writer Karen Hawkins, who left The Associated Press in 2012, contributed to this report. Associated Press writers Amy Forliti in Minneapolis and Aaron Morrison in New York contributed. —Sophia Tareen, Associated Press View the full article

When you think about customer service, consider its direct impact on your business’s success. Effective customer service not only retains customers but likewise encourages their loyalty, which is essential for sustainable growth. By addressing concerns and personalizing interactions, you can improve your brand’s reputation considerably. This discussion will explore various aspects of customer service, highlighting key benefits and strategies that can help your business thrive in a competitive market. Let’s examine how these elements come together. Key Takeaways Exceptional customer service builds trust and loyalty, leading to repeat business and reduced customer acquisition costs. Satisfied customers are more likely to recommend your business, enhancing brand reputation and attracting new clients. Good service can significantly increase customer spending, driving revenue growth and improving average order values. Retaining existing customers is more cost-effective than acquiring new ones, with high-quality service boosting retention rates. Happy employees provide better customer service, resulting in positive interactions that enhance overall customer experience and satisfaction. Understanding Customer Service Customer service is a fundamental component of any business, as it encompasses the assistance and support offered to customers throughout their purchasing experience. The customer service definition includes the guidance provided before, during, and after a purchase, ensuring that clients feel valued and supported. This support serves as the primary point of contact for customers, where representatives work diligently to address concerns swiftly and effectively. Streamlined service processes are essential for resolving issues efficiently, whereas effective follow-up is critical when transferring inquiries to other departments. A strong focus on customer service greatly influences customer perceptions of your company and its products, ultimately impacting overall satisfaction levels. The Importance of Customer Service Customer service plays an essential role in building trust and loyalty among your customers, which can lead to repeat business and lower acquisition costs. By enhancing your brand’s reputation through positive interactions, you not just attract new customers but additionally retain existing ones who are likely to recommend your services. In the end, effective customer service drives revenue growth, making it a critical component of any successful business strategy. Building Trust and Loyalty When businesses prioritize excellent service, they not merely improve customer satisfaction but furthermore cultivate trust and loyalty among their clientele. The importance of customer care is evident, as 70% of repeat sales come from customers who feel valued. Honest communication boosts confidence, with 97% of loyal customers likely to recommend your business. High-quality service nurtures loyalty, with 89% of customers likely to repurchase after a positive experience. Retaining existing customers is likewise more cost-effective than acquiring new ones, which can be 5 to 25 times pricier. Customer Experience Impact on Loyalty Positive Interaction 89% Likely to Repurchase Honest Communication 97% Likely to Recommend Friendly Service 73% Remain Loyal Enhancing Brand Reputation Building on the foundation of trust and loyalty, enhancing brand reputation plays a pivotal role in a business’s long-term success. Exceptional customer service considerably contributes to this reputation, with 81% of people trusting recommendations from friends and family. When customers experience good service, 89% are likely to repurchase, linking customer satisfaction directly to brand loyalty. Loyal customers, nurtured through excellent service, have a 97% chance of giving positive recommendations, further improving public perception. Companies prioritizing customer service see a direct correlation between customer satisfaction and reputation, as satisfied customers often leave authentic reviews. In the end, a strong reputation founded on great customer service leads to competitive advantages, increasing customer retention and market share. Driving Revenue Growth Excellent customer service can greatly drive revenue growth, making it a crucial aspect of any successful business strategy. The importance of customer support is evident, as good service can lead to a 140% increase in customer spending. When customers experience excellent service, about 89% are likely to repurchase, directly impacting your revenue. Furthermore, loyal customers often share their positive experiences, providing free advertising that boosts sales. Retaining existing customers is more cost-effective, as acquiring new ones can be 5 to 25 times more expensive. Personalized interactions can further improve loyalty, with a 42% increase in customers willing to pay a premium. In the end, a strong focus on customer service is critical for sustainable revenue growth. Retaining Your Customers Retaining your customers is crucial for any business, especially since keeping existing clients is much more cost-effective than acquiring new ones, costing five to twenty-five times more. Approximately 70% of repeat sales come from existing customers, underscoring the importance of client service in driving revenue. Fast and effective customer support can prevent 68% of customers from leaving because of poor treatment, highlighting the need for responsive assistance. When you provide good customer service, your retention rate can soar to 89%, as satisfied customers are more likely to repurchase. In addition, loyal customers often become brand advocates, with 97% willing to recommend your business based on their positive experiences. Encouraging Customer Loyalty To encourage customer loyalty, it’s crucial to build trust and rapport with your clients. By implementing personalized engagement strategies, you can create memorable experiences that make customers feel valued. Furthermore, reward and incentive programs can further strengthen their commitment to your brand, making them more likely to return and recommend your services to others. Building Trust and Rapport Building trust and rapport with customers is vital for encouraging loyalty, as strong relationships can greatly impact your business’s bottom line. The importance of guest service can’t be overstated; excellent customer service can increase repeat sales by about 70% for existing customers, compared to just 5-20% for new ones. Honest communication about products and pricing builds confidence, making customers 89% more likely to repurchase after a positive experience. Additionally, loyal customers, who develop through strong rapport, have a 97% chance of providing positive recommendations, enhancing your brand’s reputation. Even negative interactions can become opportunities for loyalty, as effective conflict resolution can turn dissatisfied customers into brand advocates, solidifying the trust necessary for long-term success. Personalized Engagement Strategies Strong relationships with customers create a foundation for loyalty, but how you engage with them on a personal level can greatly improve that bond. Personalized engagement strategies, like customized communications and recommendations, can drive a 140% increase in customer spending based on past positive experiences. When customers receive personalized service, they’re 42% more likely to pay a premium for friendly interactions. Furthermore, 89% of customers are likely to repurchase after a positive service experience, showcasing the impact of effective customer service definition and examples. By utilizing customer feedback to create personalized experiences, you boost overall satisfaction, leading to long-term relationships. Reward and Incentive Programs Reward and incentive programs play a vital role in nurturing customer loyalty by encouraging repeat business and improving overall engagement. By implementing these programs, you can greatly boost retention, as acquiring new customers is 5 to 25 times more expensive than keeping existing ones. Customers who engage in rewards programs often spend 140% more after positive interactions, highlighting the benefits of customer service in this situation. Personalized discounts that align with customer preferences can further strengthen loyalty, as 73% of consumers view customer experience as critical in their buying decisions. Moreover, loyal customers are 97% more likely to recommend your brand, creating organic growth and free advertising, making rewards programs a smart investment for your business. Building a Strong Culture and Reputation Establishing a positive company culture is essential for improving customer experience, as it greatly influences how customers perceive your brand. When your customer service department prioritizes employee well-being, you create a positive work environment that reflects in the quality of service provided. Research shows that 73% of consumers consider customer experience a key factor in their purchasing decisions, which emphasizes the need for a strong company culture. Having a clear brand identity and defined values helps differentiate your business from competitors, promoting customer loyalty and advocacy. Positive interactions with your staff can boost your brand’s reputation, as 97% of loyal customers are likely to recommend your services to others. Moreover, implementing rewards programs and discounts strengthens customer loyalty, encouraging repeat purchases. By focusing on these elements, you not only build a solid reputation but also create lasting relationships with your customers. Generating Referrals Positive customer experiences play a crucial role in generating referrals, as satisfied customers are more likely to recommend your brand to others. In fact, loyal customers who enjoy their interactions with your business are 97% likely to provide referrals to friends and family, which can greatly boost your customer acquisition through word-of-mouth marketing. The importance of customer service is evident here; 81% of consumers trust recommendations from family and friends over traditional advertising, making referrals a formidable tool for growth. When you provide excellent customer service, you not only promote satisfaction but also encourage positive online reviews. Approximately 92% of consumers read reviews before purchasing, further illustrating how critical customer service is to your reputation. Furthermore, customers who’ve great experiences are likely to share them, with 72% discussing their positive experiences with at least six others, amplifying your brand’s exposure and enhancing potential referrals. Boosting Sales When customers receive timely and effective support, they’re less likely to abandon their online purchases, which can greatly boost sales. By providing excellent customer care, you can prevent up to 52% of potential cart abandonments, directly improving your sales opportunities. Satisfied customers tend to spend more; positive experiences can increase their spending by nearly 140%. With around 68% of customers leaving a business because of poor treatment, the benefits of customer care become clear—it’s crucial for retaining your sales. Engaging with existing customers through personalized service not merely nurtures loyalty but can also reveal cross-sell opportunities, further increasing revenue. Moreover, happy customers often share their experiences through word-of-mouth, acting as a significant marketing tool that drives new sales and elevates your brand reputation. As a result, investing in customer service is a strategic move that can lead to substantial financial benefits for your business. Upselling Products When you focus on effective communication techniques, your chances of successfully upselling products increase greatly. Customized recommendations can guide your customers toward complementary items they may have overlooked, enhancing their overall experience. Effective Communication Techniques Effective communication techniques are crucial for successful upselling in customer service. By comprehending customer needs and preferences, you can greatly improve your upselling efforts. Here are some effective strategies: Ask open-ended questions to identify what customers truly want. Use empathy and product knowledge to make relevant suggestions. Leverage data from past purchases to tailor your offers. When you skillfully apply these techniques, you increase the likelihood of conversion by up to 30%. Moreover, providing a rewards program can cultivate loyalty, as 89% of customers are more likely to return after a positive experience. Tailored Recommendations Strategies Customized recommendations are a potent strategy for enhancing upselling efforts in customer service. By integrating customer service with CRM systems, you can access order histories, allowing for personalized suggestions that resonate with existing customers. Since current customers are 60-70% more likely to buy again, leveraging these relationships can greatly boost your sales. Upselling during interactions can increase average order values by up to 30%, especially when you personalize offers based on previous purchases and preferences. Furthermore, 42% of customers are willing to pay a premium for friendly, personalized service. Utilizing customer feedback from service interactions helps you better understand their needs, paving the way for relevant upselling opportunities, aligning perfectly with the customer service definition. Improving Employee Happiness Improving employee happiness is crucial for improving customer service outcomes and driving overall business success. Happy employees are 73% more likely to provide exceptional customer service, which boosts customer satisfaction and loyalty. A positive work environment helps reduce stress and burnout, greatly improving morale and productivity among your customer service team. Consider these key factors for improving employee happiness: Continuous training and recognition boost confidence and job satisfaction. Providing tools and resources empowers agents, allowing them to handle more interactions effectively. An engaged workforce can lead to a 21% increase in profitability, showcasing the importance of customer service. When your employees feel valued and supported, they’re more likely to deliver outstanding service, eventually benefiting your business. Prioritizing employee happiness not just improves service delivery but also creates a thriving workplace culture that contributes to long-term success. Staying Competitive in the Marketplace In today’s competitive marketplace, delivering exceptional customer service is crucial if you want to stand out from your rivals. Why is customer service important? It’s simple: excellent service can lead to a 70% likelihood of repeat sales from existing customers. When your business is known for great service, you attract more customers and retain the ones you have, enhancing your brand reputation and giving you a competitive edge. Furthermore, prioritizing customer experience can result in a 140% increase in spending from satisfied customers, helping you stay ahead. Remember, 89% of customers are likely to repurchase after a positive service experience, highlighting the need for a loyal customer base. By focusing on customer service, you not only meet expectations but exceed them, ensuring you remain a strong contender in your industry. With such significant benefits, it’s clear that investing in customer service is crucial for lasting success. Proactive Customer Engagement Proactive customer engagement plays a significant role in improving the overall customer experience by anticipating potential issues and addressing them before they escalate. When you focus on this approach, you’re not just solving problems; you’re building a strong foundation for customer loyalty. This is what great customer service means. It increases the likelihood of repeat sales from existing customers up to 70%. By actively seeking customer feedback, you can identify strengths and weaknesses in your service. Implementing support centers and detailed FAQs minimizes customer effort, boosting satisfaction scores. With proactive outreach, you reduce incoming inquiries and improve customer effort scores, making interactions smoother. Brands that excel in this area cultivate loyalty and positive word-of-mouth, with 89% of customers likely to repurchase after a good service experience. Gathering and Analyzing Feedback Gathering and analyzing feedback is essential for businesses aiming to improve their customer service. By using surveys and focus groups, you can pinpoint strengths and weaknesses in your offerings, allowing targeted improvements that boost customer satisfaction and retention. Anonymous feedback mechanisms encourage honest responses, leading to accurate insights into customer perceptions. Feedback Method Benefits Key Metrics Surveys Identify strengths and weaknesses Customer Satisfaction (CSAT) Focus Groups Gain deeper insights Net Promoter Score (NPS) Anonymous Feedback Encourage honest responses Customer Effort Score (CES) Regularly evaluating customer satisfaction metrics provides actionable insights that drive strategic decisions. Proactive engagement in soliciting feedback can prevent issues from escalating, eventually enhancing what customer service means for your business and nurturing long-term loyalty. Providing Effective Training Effective training is crucial for enhancing customer service skills among employees, as it directly impacts their ability to interact positively with customers. When you invest in effective training, you reap several advantages of customer care that can lead to improved outcomes for your business. Ongoing training keeps staff updated on new products and service best practices, enhancing their effectiveness. Well-trained employees are 73% more likely to create positive customer interactions, boosting loyalty and retention. A structured training schedule nurtures confidence, resulting in better service quality and customer satisfaction. Furthermore, continuous improvement in training helps identify weaknesses and empowers agents to handle inquiries more efficiently. Personalized coaching can greatly improve agent performance, raising customer satisfaction scores and encouraging brand advocacy. Essentially, effective training is a cornerstone of exceptional customer service, contributing to a better overall customer experience. Real-World Examples of Good Customer Service In relation to customer service, real-world examples can provide valuable insights into effective practices that lead to success. Companies like Amazon exemplify the best definition of customer service by leveraging customer feedback to innovate their offerings, resulting in high satisfaction and loyalty rates. Research shows that 89% of customers are likely to repurchase after experiencing good service, underscoring the link between exceptional support and increased sales. Zappos stands out with its free shipping and 365-day return policy, encouraging a loyal customer base. Starbucks personalizes experiences through its rewards program, achieving a 24% increase in retention and spending. The Ritz-Carlton empowers employees to spend up to $2,000 to resolve issues on the spot, showcasing the effectiveness of proactive customer service in enhancing satisfaction and brand reputation. These examples highlight how good customer service can transform customer relationships and drive business success. Frequently Asked Questions What Are the Benefits of Good Customer Service to a Business? Good customer service offers numerous benefits to your business. It increases customer retention, as satisfied customers are likely to return, which is often more cost-effective than acquiring new ones. By providing excellent service, you can boost repeat purchases, leading to higher sales. In addition, loyal customers tend to refer others, enhancing your brand’s reputation. In the end, strong customer service can give you a competitive advantage, as it encourages recommendations and strengthens customer loyalty. What Are the 5 Most Important Things in Customer Service? In customer service, five important elements stand out. First, effective communication guarantees clarity and comprehension. Second, responsiveness to inquiries and issues promotes customer satisfaction. Third, product knowledge allows you to provide accurate information, enhancing trust. Fourth, empathy helps you connect with customers on a personal level, nurturing loyalty. Ultimately, consistency in service reinforces reliability, encouraging repeat business. What Is the 3 Key of Customer Service? The three key elements of customer service are responsiveness, empathy, and communication. Responsiveness guarantees you address inquiries swiftly, which can improve customer retention. Empathy allows you to understand customer emotions and needs, nurturing trust and loyalty. Effective communication assures clarity about your products and services, boosting customer confidence. What Are the Key Benefits of Customer Experience to Our Business? The key benefits of customer experience to your business include increased customer retention, as satisfied customers are more likely to return. A strong customer experience improves your brand’s reputation, leading to positive recommendations that attract new clients. Happy customers tend to spend more, boosting your revenue considerably. Furthermore, investing in excellent customer service creates long-term relationships, which reduces competition and cultivates loyalty, ultimately driving consistent growth for your business. Conclusion In summary, effective customer service is vital for your business’s success. By prioritizing customer satisfaction, you improve retention and loyalty, leading to increased revenue and a strong reputation. Proactively engaging with customers and gathering feedback allows you to identify areas for improvement, whereas providing effective training guarantees your team delivers exceptional service. In the end, investing in customer service cultivates long-term relationships that contribute to sustained growth and profitability, making it a pivotal aspect of any successful business strategy. Image via Google Gemini and ArtSmart This article, "Key Benefits of Customer Service for Your Business" was first published on Small Business Trends View the full article

Recruiting, for beginners, involves grasping how to identify and attract the right candidates for job openings in an organization. It starts with creating clear job descriptions and sourcing candidates through various channels. As you progress, you’ll learn to conduct interviews that assess both qualifications and cultural fit. Acquiring effective communication and organization is vital, but there’s much more to explore in the recruitment process, including strategies and metrics that can improve your approach. Key Takeaways Recruiting is the process of attracting, interviewing, selecting, and onboarding candidates for job openings in an organization. It involves analyzing job roles to create clear descriptions of responsibilities and expectations. Effective candidate sourcing includes promoting from within, posting jobs online, and using social media and university connections. Screening and interviewing assess candidates’ qualifications and cultural fit, often using structured methods for fairness. Recruitment metrics, like time to fill and offer acceptance rates, help evaluate and improve the recruitment process. Understanding Recruitment and Its Importance When you think about recruitment, it’s critical to recognize its pivotal role in shaping an organization’s workforce. Recruitment is defined as the process of identifying, attracting, interviewing, selecting, and onboarding employees to fill specific job vacancies. So, what does recruiting mean? It involves not just filling positions but ensuring that the right candidates are chosen to improve organizational success and employee performance. Comprehending recruitment means appreciating the strategies used to create detailed job descriptions, advertise openings, and maintain clear communication with candidates throughout their expedition. Effective recruitment strategies aim to hire the best candidates on time and within budget, which is fundamental. Moreover, metrics like time to fill and offer acceptance rates help evaluate recruitment effectiveness, ensuring that talent acquisition is efficient. Staying informed about trends, such as the growing use of AI and the focus on candidate experience, is crucial for adapting to the evolving hiring environment. The Recruitment Process: Key Steps When you start the recruitment process, the first step is analyzing the job to create a clear description that outlines responsibilities and expectations. Next, you’ll need to source candidates using various methods, such as job boards and social media, to attract a wide range of applicants. After that, you’ll screen and interview candidates to determine who best fits the qualifications and culture of your organization. Job Analysis and Description To effectively recruit the right candidates, comprehension of job analysis and creating accurate job descriptions are vital steps in the recruitment process. Job analysis involves systematically gathering information about a job’s responsibilities, required skills, and working conditions. This process helps you understand what does recruit mean regarding aligning candidates with your organizational goals. A well-crafted job description outlines key duties, qualifications, and expectations, serving as a significant tool for attracting suitable candidates. It should reflect not merely the fundamental functions but also your company culture and values. Regularly updating job descriptions as roles evolve improves the recruitment process, ensuring potential candidates clearly understand the position and its requirements, simplifying recruitment for everyone involved. Candidate Sourcing Methods Comprehending job analysis and crafting precise job descriptions sets the foundation for effective candidate sourcing methods. To attract the right talent, you’ll want to use various strategies. Consider promoting from within your organization, posting jobs online, or reaching out via social media. Recognizing your ideal candidate’s skills and cultural fit is essential. An applicant tracking system (ATS) can help manage applications and track the effectiveness of your sourcing channels. Engaging with local universities and professional organizations can similarly enrich your talent pool. Finally, implementing a diverse recruitment strategy will lead to a more inclusive workforce. Sourcing Method Description Internal Promotions Promoting existing employees for new roles. Online Job Postings Posting vacancies on job boards and websites. Social Media Outreach Leveraging platforms like LinkedIn for sourcing. University Engagement Tapping into fresh talent from local institutions. Screening and Interviewing Process The screening and interviewing process is an essential component of recruitment, serving as a bridge between sourcing candidates and making a final hiring decision. First, you’ll review resumes and applications to identify candidates who meet the basic qualifications outlined in the job description. Those who pass this screening stage are typically invited for interviews, where you’ll assess their skills, experience, and cultural fit. Using structured interviews, which follow predetermined questions, guarantees consistency and fairness. Furthermore, you may conduct assessments like skills evaluations or personality tests to further gauge compatibility. Effective communication during this process is critical, as it provides candidates with timely feedback and helps maintain a positive candidate experience, reflecting well on your organization. Types of Recruiting Explained Comprehending the various types of recruiting is vital for anyone looking to fill job vacancies effectively. Here are five key types to take into account: Internal Recruiting: This focuses on promoting or transferring existing employees, often improving morale and retention. External Recruiting: By seeking candidates from outside the organization, you gain access to a broader range of specialized skills and fresh perspectives. Online Recruiting: Utilizing digital platforms like job boards and social media helps you reach potential candidates efficiently and effectively. Referral Recruitment: Encouraging current employees to recommend candidates from their networks often leads to higher-quality hires because of pre-existing trust. Diversity Recruitment: This approach aims to create a more inclusive workforce by intentionally seeking candidates from underrepresented backgrounds, which can improve company culture and performance. Understanding these types helps you tailor your recruiting efforts to meet organizational needs. Effective Recruiting Strategies When you aim to improve your recruitment efforts, implementing effective strategies is essential for attracting the right candidates. Start by clearly defining job roles and responsibilities. This clarity helps you draw in candidates who align with your organization’s needs and culture. Utilize a variety of sourcing channels, like job boards, social media, and employee referrals, to augment the diversity and quality of your candidate pool. Consider implementing an applicant tracking system (ATS) to streamline the recruitment process, manage applications, and track candidate communications efficiently. Moreover, cultivating a positive candidate experience is key; provide timely feedback and maintain clear communication to boost your company’s reputation and increase offer acceptance rates. Lastly, regularly analyze recruitment metrics, such as time to fill and first-year attrition rates. This practice allows you to refine your strategies and improve hiring outcomes over time, ensuring you attract the best talent for your organization. Essential Recruitment Metrics When you’re recruiting, tracking crucial metrics can greatly improve your process. Key metrics like application completion rate, offer acceptance rate, and time to fill provide valuable insights into how well your recruitment strategies are working. Comprehending these numbers not merely helps you assess the effectiveness of your hiring methods but likewise guides improvements to attract the right candidates for your organization. Key Recruitment Metrics Comprehending key recruitment metrics is crucial for optimizing your hiring process and making informed decisions. By tracking these metrics, you can improve efficiency and attract top talent. Here are four important metrics to monitor: Application Completion Rate: Measures the percentage of candidates who finish the application process, helping identify barriers. Applicants per Opening: Tracks the number of candidates for each job vacancy, offering insights into recruitment effectiveness. Offer Acceptance Rate: Reflects the percentage of job offers accepted, indicating job attractiveness. Time to Fill: Measures the duration taken to fill a vacancy, allowing you to assess recruitment efficiency. Importance of Metrics Comprehending the importance of metrics in recruitment can greatly improve your hiring strategy. Metrics provide clear insights into your recruitment process, allowing you to make informed decisions. Here are some crucial metrics to evaluate: Metric Description Importance Application Completion Rate Measures the percentage of applicants who finish the application process Gauges job posting effectiveness Applicants per Opening Tracks the number of candidates applying for each vacancy Indicates job competitiveness and market demand Time to Fill Measures the duration from job opening to offer acceptance Assesses recruitment efficiency Skills Needed for Successful Recruitment Successful recruitment hinges on a blend of important skills that recruiters must conquer to effectively connect with candidates and fulfill organizational needs. Here are four fundamental skills to develop: Communication Skills: You need to convey job expectations clearly and engage candidates throughout the recruitment process. Listening Skills: Grasping the organization’s needs and candidates’ aspirations will help guarantee a better fit for both parties. Technological Proficiency: Familiarity with applicant tracking systems (ATS) streamlines the recruitment process, making it easier to manage candidate data efficiently. Organizational Skills: You’ll juggle multiple tasks, from scheduling interviews to screening applicants and maintaining communication with stakeholders. Additionally, cultural awareness is crucial for promoting diversity and inclusivity, attracting a wider range of qualified candidates who align with the company’s values. Conquering these skills will greatly improve your effectiveness as a recruiter. Frequently Asked Questions What Is the Simple Definition of Recruitment? Recruitment is the process of finding and hiring the right candidates for job openings within an organization. You identify potential candidates, attract them through job postings, and evaluate their qualifications through interviews. The goal is to select individuals who best fit the company’s needs. Recruitment can happen internally, using current employees, or externally, seeking new talent. This process is essential, as it directly influences your organization’s overall performance and success. What Are the Basics of Recruitment? Recruitment basics involve identifying job needs, creating clear job descriptions, and attracting suitable candidates. You’ll use various methods, like internal promotions, external searches, and online platforms, to find talent. The process includes screening resumes, conducting interviews, and evaluating candidates to guarantee a good fit. It’s crucial to maintain a positive experience for applicants during tracking metrics, such as time to fill and offer acceptance rates, to improve your recruitment efforts. What Does Recruiting Mean in a Job? Recruiting in a job context involves identifying and selecting candidates for specific roles within an organization. You analyze job requirements, create descriptions, and advertise vacancies. After attracting applicants, you screen resumes, conduct interviews, and evaluate candidates to find the best fit for the company’s needs and culture. Effective recruiting measures metrics like time to fill and offer acceptance rates, often utilizing technology like applicant tracking systems to improve efficiency and candidate experience. What Are the 5 C’s of Recruitment? The 5 C’s of recruitment are vital criteria for evaluating candidates. First, you assess Character, focusing on integrity and ethics. Next, you look at Competence, ensuring candidates possess the required skills and experience. Then, evaluate Compatibility, considering how well they fit into team dynamics. Commitment follows, gauging their dedication to the role and organization. Finally, Cultural Fit examines alignment with the company’s values, which is critical for long-term success and employee satisfaction. Conclusion In summary, recruiting for beginners involves acquiring the fundamental steps of identifying and selecting candidates. By grasping the recruitment process, utilizing effective strategies, and tracking crucial metrics, you can improve your efforts in finding the right talent. Developing key skills, such as communication and organization, will further support your success in this field. In the end, focusing on these elements will help you contribute to your organization’s growth and guarantee that you attract candidates who align with its values and goals. Image via Google Gemini and ArtSmart This article, "What Does Recruiting Mean for Beginners?" was first published on Small Business Trends View the full article

Google Ads is rolling out a beta feature that lets advertisers connect external data sources directly inside conversion action settings, tightening the link between first-party data and campaign measurement. How it works. A new section in conversion action details — labeled “Get deeper insights about your customers’ behavior to improve measurement” — prompts advertisers to connect external databases to their Google tag. Supported integrations include platforms like BigQuery and MySQL The goal is to enrich conversion metrics and improve performance signals The feature appears in a highlighted prompt within data attribution settings Rollout is gradual and currently marked as Beta Why we care. Direct integrations could reduce friction in syncing offline or backend data with ad measurement. This beta from Google Ads makes it easier to connect first-party data directly to conversion tracking, which can improve measurement accuracy and campaign optimization. By integrating sources like BigQuery or MySQL, brands can feed richer customer data into their signals, helping offset data loss from privacy changes. In practical terms, better data in means smarter bidding, clearer attribution, and potentially stronger ROI. Between the lines. Embedding data connections inside conversion settings — rather than requiring separate pipelines — makes advanced measurement more accessible to everyday advertisers, not just enterprise teams. Zoom out. As ad platforms compete on measurement accuracy, native data integrations are becoming a key differentiator, especially for brands investing heavily in proprietary customer data. View the full article

This should come as a shock to very few people, but Krispy Kreme doughnuts, which typically needs very little reason to give away its doughnuts, is giving away free doughnuts today. This time, the free doughnut giveaway is in honor of Fat Tuesday 2026. But there’s a catch. Here’s what you need to know. What is Fat Tuesday? Today (Tuesday, February 17) is Fat Tuesday, otherwise known as Mardi Gras. The holiday always falls on the final Tuesday before the Christian holy day of Ash Wednesday, which is the beginning of the Lent observance period. Traditionally, Christians refrain from eating certain foods during Lent, particularly rich and fatty ones. As a result, the Tuesday before the Lenten fasting period began has historically been a day when followers binged on sweet and fatty foods—their last chance to do so for over a month. This Tuesday thus became known as Fat Tuesday. Why is Krispy Kreme giving away doughnuts on Fat Tuesday? The ubiquitous doughnut chain never seems to miss an opportunity to give away free doughnuts. While this practice may appear anathema to a profitable business model, Krispy Kreme knows that giving away a few doughnuts will likely spur customers to spend more in-store than the chain is losing by giving away carefully formulated dough that costs it just a few cents each. After all, who can eat just one glazed doughnuts and not want to wash it down with a cup of (high-margin) coffee? What is Krispy Kreme giving away on Fat Tuesday 2026? Participating Krispy Kreme doughnuts locations will be giving away a free original glazed doughnut to those who go to their shops today. However, there’s a catch. How can I get my free doughnut on Fat Tuesday? In order to get the free doughnut, you’ll need to wear beads, the traditional accessory that people adorn themselves with during Mardi Gras celebrations. As Krispy Kreme notes on its website, “Bring your celebration spirit, and your shiniest beads, to a Krispy Kreme shop near you for a FREE Original Glazed doughnut per guest.” The offer is available to those who physically enter a participating Krispy Kreme store or use its drive-through. Unfortunately, the offer isn’t available for online orders. A disclaimer on Krispy Kreme’s website also notes that the offer is valid for today only and “while supplies last.” View the full article

Hospital intensive care units are notoriously noisy, with medical equipment emitting alarms, beeps, and other alerts designed to grab the attention of overextended healthcare workers. That constant barrage can lead to what experts call alarm fatigue, causing stress and exhaustion for doctors and nurses who must distinguish between routine signals and those indicating a patient is in urgent distress. Patients, too, often struggle to rest amid the cacophony, even though sleep is critical to recovery. To Ophir Ronen, a serial tech entrepreneur who sold his IT alert-handling startup Event Enrichment HQ to PagerDuty, the problem sounded familiar. Ronen first encountered the ICU alarm issue while volunteering in search and rescue, and he realized that although “alarm fatigue” has been widely discussed in scientific literature, no one had yet developed a comprehensive solution. “I thought to myself, ‘wow, we certainly experienced the problem of alarm fatigue in operations and enterprise IT—I wonder if it’s the same pattern,’” he says. Betting the problem might have a similar fix, Ronen founded CalmWave in 2022, with early backing from the Allen Institute for AI’s incubator program. The startup aims to help hospitals silence unnecessary alarms, prioritize those that truly demand action, and build datasets that make it easier for computers to tell the difference. Like other complex IT operations, Ronen found that critical information in hospitals is siloed across at least two systems: electronic medical records (EMR), which track diagnoses and treatments, and networks of sensors and monitoring systems that log vital signs and trigger alarms. Those monitoring data points typically never make it into EMR systems, which aren’t designed to handle that volume of information, Ronen says. CalmWave’s technology integrates both streams. The system presents staff with a unified view of patient vital signs alongside treatment timelines, such as medication administration, reducing the need to toggle between records to assess a patient’s status. Drawing on its accumulated data, CalmWave can also recommend how to adjust alarm thresholds for specific patients, backed by clinical evidence explaining its reasoning. That might mean widening acceptable ranges to reduce unnecessary noise or tightening thresholds to catch problems earlier, according to Ronen. “We don’t just reduce alarms,” he says. “We restructure which alarms fire when and why, giving the nurses the clinical evidence of why this makes sense.” While the system is based on machine learning, it’s not powered by large-language models or other similarly inscrutable generative AI tools, Ronen emphasizes. That’s helped win acceptance from even skeptical medical professionals, and the technology is currently deployed in 14 hospitals. The company has also raised money from a number of investors, including in a follow-on round announced last June that brought in $4.4 million from Third Prime, Bonfire Ventures, Catalyst by Wellstar, and Silver Circle. An early pilot study with Wellstar Health System found CalmWave’s system could lead to a 58% reduction in non-actionable alarms—reducing clinician interruptions and cutting by approximately 10 hours the time the average patient is exposed to alarms. On Tuesday, the company announced a new feature called Recovery State, designed to help hospitals identify patterns suggesting a patient may be ready for transfer or discharge from the ICU. Like its alarm-configuration tools, Recovery State draws on data from monitoring systems and EMRs, matching patient profiles to recovery patterns while leaving final decisions to clinicians. CalmWave hopes to roll out the feature this year. Ideally, Ronen says, it will help move patients out of stressful ICUs—and potentially out of the hospital—sooner, freeing up resources and reducing costs. More broadly, he argues, it offers hospitals a way to measure when patients are improving, not just when they are deteriorating. “Healthcare has always known how to detect when things go wrong,” he says. “What it’s never had is an objective, continuous way to confirm when things are going right.” View the full article

In a perfect world, you could call up a top customer to pick their brain about a piece of content. But in reality, it can be extremely difficult and time-consuming to conduct audience interviews every time you need to create a new topic or refresh an old piece. A few years ago, content marketing was simpler – keyword intent and quality content was enough to rank at the top of Google’s SERP to get clicks. But in the new era of AI, expectations are different. Audience research has become critical. However, some companies may not have the resources to perform it. One way to better understand your target audience is to create a custom GPT in ChatGPT, configured with your persona research. These aren’t replacements for audience research or interviews, but they can help you quickly identify what might be missing or wrong in your content. Below, I’ll explain how GPTs work so you can use them for audience research. Perform audience research Now that the SEO landscape is evolving, audience research is one of your strongest tools to understand the “why” behind search intent. Here are several easy-to-use methods and tools to get you started on research. SparkToro: Search by website, interest, or specific URL to segment different audience types. Research can be in-depth or give an overview of your audience. Review mining: Create automations through various tools and scrape reviews of your company or competitors to see what users are saying, and then analyze them. What does your target customer like? Why did they like it? What didn’t they like? Why? Listen to calls/review leads: Listen to sales team interactions with customers to hear questions in real time and what led up to a call with a particular client. Dig deeper: How to do audience research for SEO Create a customer persona After completing your research, create a persona – a representation of your target audience. Figma and FigJam are strong tools for building them. Your persona should include: Name, bio, and trait slider. Interests, influences, goals, pain points. User stories. The emotional journey during and after. Content focus, trigger words, and calls to action (CTAs). Full customer journey steps. Reviews that support data. Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with Create a custom GPT of your persona Now that you have all your research and your persona, it’s time to make a GPT. First, log in to ChatGPT, then go to Explore GPTs in the sidebar. In the upper right corner, click on Create. Once there, prompt ChatGPT with your audience research data and persona information. You can paste in screenshots of your data to make it easier. Once all your data is in and a GPT is created, you can start talking to it. Under the Configure tab, you can use conversation starters to ask it about changes, updates, and copy. These GPTs, like all AI models, aren’t 100% accurate. They don’t replace a real audience survey or interview, but they can help you quickly identify issues with a piece of content and how it might not connect with your audience. Here’s an example of an optimized page. GPT “Hank” helped make sure the section above the fold did what was intended. Hank has said what’s working, what isn’t working, and where to improve. But should you take his advice 100% of the time? Of course not. But the GPT helps quickly identify issues you may have missed. That’s where the real benefit of using a GPT comes in. Dig deeper: 7 custom GPT ideas to automate SEO workflows Get the newsletter search marketers rely on. See terms. Ensure data from your GPT is accurate Nothing analyzed or generated by AI is conclusive evidence. If you’re unsure your GPT is giving you accurate information, double-check by prompting it to provide evidence from the sources you gave it. The GPT can correct itself if the information sounds off. When it does, again ask for evidence from the persona information you provided to double-check the new information. Update your persona-based GPT You can always add more information to your GPT to make it more robust. To do this, go back to Explore GPTs in ChatGPT. Instead of Create, go to My GPTs in the top right-hand corner. Click on your persona. Click on Configure to update, add, or delete your current information. Remember that a persona is never a one-and-done situation. The more you learn about your audience and the more information you give a GPT, the better, to keep it up to date. Leverage persona GPTs for SEO content Personas aren’t absolute, and AI can hallucinate. But both tools can still help you optimize content. Once you’re comfortable creating personas, you can build them for your general audience, specific segments, and individual campaigns. SEO and marketing are always changing, and you can’t just set it and forget it. As you gain audience insights or if audience intent shifts, update information or delete anything no longer relevant in your GPT. When leveraged correctly, these tools can work with SEO to drive traffic and gain more conversions. View the full article

Files show Andrew Mountbatten-Windsor exchanged messages about secret plan with sex offender Jeffrey EpsteinView the full article

A few weeks ago, we reported Google was exploring ways to allow sites to opt out of showing up in Google's AI features, like AI Mode and AI Overviews. Google's Sulina Connal said at the FT Strategies News in the Digital Age conference that this is a "huge engineering project."View the full article

There is a new Google Ads help document named About the Results tab in Google Ads Recommendations. It explains that in the Results tab, you can now view the performance impact after you apply them.View the full article

Google AI Mode has this feature where you can ask about a specific product, it is called "Ask about." Now when you hover over a product, the "Ask about" will overlay so you can more easily trigger the feature.View the full article

Google seems to be testing links in AI Overviews, that link to more AI Overview responses. These recipe AI Overviews linked to entities that then load a hybrid knowledge panel with an AI Overviews.View the full article

Did you know that the Google AI Overviews link citation paperclip icons are blue before you click to see more of the overviews and then after you click on them, that icon turns to a gray color.View the full article

Netflix grants weeklong waiver to rival bidder in high-stakes battle for controlView the full article

Too many years ago, I remember slotting a 3.5-inch disk into my PC. With my allowance, I’d bought $5 video game design software from a catalog. And as I looked at the terminal, lost without some familiar GUI . . . my coding efforts died. Game design became an abstract concept even as I became a game journalist—a topic sketched in notebooks, theoretically discussed, critically observed. That was, until I loaded Moonlake AI. With $30 million in funding from investors including Nvidia, AIX, Google’s Chief Scientist Jeff Dean, and YouTube founder Steve Chen, the 15-person startup founded by two Stanford PhD students dreams of building complete games—from first person shooters to 2D puzzles—via a single, one-shot prompt. Yes, vibe-coding apps like Claude Code and Replit make it possible to build games, too, but Moonlake is purpose-built for the task. It will never ask you to copy a snippet of code, offers templates to start with if you’d like, and has straightforward paths to bring in your own assets, too. It remembers your vision and constantly works to improve it alongside you. For a $40/mo subscription (though you can technically try the platform for free), you type what you want to play, and presto, it’s coded, bug tested, and appears into existence. Sun Fan-YunSharon Lee Launching to the public in beta today, the Moonlake AI team knows they aren’t a one-shot game generator yet—while I was playtesting my first draft game in minutes, it took hours of going back and forth with the machine to polish it much further. And in fact, the longer term goals for Moonlake AI stretch well beyond the lofty goal of vibe-coding video games. Their larger plan isn’t just to build Moonlake to be more capable, but to leverage the process of video game design itself to build a frontier AI model for the world. Building my game in Moonlake AI Am I the only one who, staring at the prompt, facing this machine that can do anything, suddenly can’t think of doing anything? It was this lack of creativity that sunk me the first time I’d taken Moonlake for a test-drive. I couldn’t come up with anything unique, so I suggested a 3D dungeon crawler. Despite having no original ideas, I walked through my vision in a multi-paragraph, explicit prompt. It felt too taxing to the system, too grand in scope, and too out of touch with what I imagined. My prompt was realized as one big broken room filled with pill shaped characters and no simple way forward. When I recount this story to Moonlake AI cofounder Sun Fun-Yun, he suggested starting smaller. Focusing on smaller interactions and building from there. (Even though he shared a few single-shot projects that he’d made in one day, including this Centipede clone and postapocalyptic simulator). So I did the human work, and racked my brain for days before landing on a new concept: A miniature chef runs back and forth with a giant ice cream cone, catching falling scoops of ice cream. They stack and get harder and harder to balance. From here, I could pursue all sorts of game loops, depending on what felt fun about it (maybe you got points for each scoop, maybe some flavor combinations introduced bonuses, maybe ice cream scoops you didn’t catch got in the way). But for now, I focused on this simple introduction. I typed this request into the prompt on the left side of the interface. And much like ChatGPT, Moonlake got to work, praising me for my brilliant creative idea, and then breaking down the tasks that would need to be taken to bringing it to life. Moonlake offered me an estimate of 15–20 minutes to finish the job. Then it launched: Faster than I could possibly parse, the system created and worked through a checklist of to-dos. It needed to create graphic meshes, wobble mechanics, and sprites for my graphics. It researched topics it didn’t readily understand. A mix of plain language explanations, and then hundreds of lines of code, populated into the chatbox, expanding and then consolidating away from my eyes. I was impressed by the decisions it made on its own, not just breaking down necessary tasks for a minimum viable product, but introducing a bouncy animation when the ice cream hit the cone (a detail I figured I’d add in a polishing pass later). The system even said it was loading the game, and testing it—spotting and squashing a few bugs—before that magical button appeared in the big center box making up most of the UI: Play Game. The moment reminded me of the first time I tried gen AI; this actually worked! Sort of! My first draft felt something out of the early PC gaming era. My chef was too big, cone was too small. And the ice creams wouldn’t stack. But gosh, it got so much right about my simple pitch. The core vision was there. Ice cream fell at just the right pace from the sky. The scale of the entire scene felt right. The controls were all mapped without me needing to explain which key should do what. My chef . . . was something of a white blob stuck to a cone. He needed work. But Moonlake even did a decent job of creating a white tile kitchen background, with subtle sundaes printed upon it like murals. From there, I began lecturing the machine to fix the ice cream so it stacked. That created other issues. Ice cream started stacking, but would fall with any movement. Negotiating the feel led me to try all sorts of new prompts, and even as it failed and failed again, I started recognizing how the AI was translating ideas like stickiness into its own annotated code. Hours of casual updates in a tab in my browser followed. Fixing the physics of the scoops was vexing. I ended up in a loop of not quite solved problems. But I also asked for a new chef, this one with a proper, giant hat, with little sweat marks poking out every time he changed directions. This entire idea, Moonlake nailed out of the gate. My exact preferred aesthetic? No. But it captured the vibe. I found myself pleased, but also realizing that polishing this experience into something that felt delightful would take a lot of work. Another day? A week? It was tough to tell. The next morning, in a final ditch effort (I did have an article to file!), I decided to add a bunch of my lingering requests in one final push just to see what Moonlake could do. I wanted big multiplier scoring, a Kawaii graphic upgrade, and a few more fixes to my vexing scoop physics. It was unfair to request all these updates at once, and almost sure to break something. Fifteen minutes of coding followed, while I grabbed a coffee. What I returned to? Largely my brief! A few new issues around ice cream slippage! A game over screen I didn’t ask for! But, at last, a true game—built for about 950 of my 1,500 monthly credits—and published for you to try with a button press. (Moonlake is still determining pricing on extra credits.) Creating the frontier model Like a lot of AI companies, Moonlake is only charging customers its cost of computing—which is why the base subscription comes with a limited amount of credits to run the AI. Everyone believes that cost should go over time, which could either widen Moonlake’s margins on subscriptions, or simply be reinvested to make the platform more capable. But only when I ask how Moonlake trained its model do I really learn how it all works, and to some extent, why this video game generator even exists as a business. Moonlake is an ever-growing AI model. However, it’s also really a video game building agent that takes your task and coordinates it with several specialized third party AI models that might handle anything from physics to asset generation. And it’s also growing into something even more ambitious as a result of sitting on top of so much existing AI power. “Ours is an orchestrator that learns to fuse these modalities together,” says Fan-Yun. “And over time, our model can actually be more and more capable and incorporate other models’ capabilities into our own.” But that’s only the start of the strategy. As you vibecode in Moonlake, you are creating your own video game. You are also training Moonlake’s own frontier model—what falls into a very hyped segment of “world models” or what Moonlake qualifies as “multimodal models”—that don’t just rearrange words and concepts LLMs, but have a deep understanding of what the world is, how it works, and how all of its surfaces and touchpoints respond to inputs across physical space. That means when I correct Moonlake, saying an ice cream scoop should stack and stick atop another scoop of ice cream, it effectively learns that scoops of ice cream stick atop one another. Multiply that across millions of highly specific user requests, and as Moonlake AI cofounder Sharon Lee explains, game design could provide a perfect training loop to feed countless data points about how we expect the world to work into these world models. No, many or even most games don’t operate on real world physics which would translate 1:1 in some simulation. But in some cases they do, and Moonlake could extract such real physics for their own simulations. Furthermore, the founders believe the aforementioned causal relationships it’s mapping will still add a clarity to world models that’s otherwise hard to pin down. “There’s a gap between large language models today and semantics they understand, versus actually building [a] world out,” says Lee. And they believe that gap can be closed with more, intentional data. Today, researchers are trying to get these world inputs by renting Airbnbs and scanning the rooms with lasers, but that is relatively static information that is hard to scale. AI can also analyze videos to draw conclusions, but those lack the sharpness of human contextualization. As for video games? “If you train a model on just a lot of Fortnite data, you know that you’re not going to really generalize to real world data,” says Lee. “[Our] data will just scale exponentially compared to hand curated data or collected data.” Even Google’s Genie AI can generate a slew of amazing 3D worlds with some interactivity, but the interactions they afford are superficial at best. “I think the difference is sort of observing the world as it is, versus observing and understanding the world with causality,” says Fan-Yun. And so causality is what Moonlake is after. Gaming is a task for V1 of Moonlake’s model because the user feedback loop can teach it so much, but in the future, the team imagines applying a more mature version of this model to other fields. They see opportunities to train the next generation of robotics or improving driverless cars. Lee says they’ve even fielded calls from manufacturing companies, that imagine understanding the human side of the equation could help identify human factors issues in product design and assembly line production. The challenge, of course, is building Moonlake well enough that it produces games up to the standards of gamers, and that it continues investing in the product, so that people can restyle the entire graphics package with a button press, or easily export these games to sell on PC, iOS, or any other platform they would like. These ideas are all on the road map. But for now, Moonlake AI offers an accessible trip into the vibe-coding era, all through the lens of fun. View the full article

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When you’re designing customer feedback surveys, it’s crucial to look at effective examples that can guide your approach. Various companies have adopted unique methods to gather insights, from HubSpot‘s mixed-scale questions to Miro‘s unobtrusive surveys. These examples illustrate how different formats can boost engagement and yield valuable data. Comprehending these strategies can greatly improve your survey design. What specific elements will you incorporate to meet your feedback goals? Key Takeaways HubSpot’s survey combines a 1-7 scale with open-ended questions for both quantitative and qualitative insights. Userpilot’s NPS survey uses a 0-10 scale, followed by a question to gather actionable customer sentiment. Slack’s overall customer satisfaction survey emphasizes brevity with multiple-choice questions for quick analysis. Jira’s in-app survey utilizes an emoji rating scale for immediate feedback after feature engagement, enhancing user experience. Miro’s passive survey allows for unobtrusive, continuous feedback through simple rating systems, ensuring consistent customer engagement. HubSpot’s Customer Satisfaction Score Survey HubSpot’s Customer Satisfaction Score Survey is an effective tool for measuring customer satisfaction through a straightforward 1-7 point scale. This simplicity encourages higher response rates, making it easy for you to collect data after significant interactions. If you’re wondering how to ask feedback from a client, consider timing your survey right after a key service experience—this guarantees the feedback is relevant and fresh. While the numerical ratings provide valuable quantitative insights, you might want to improve your surveys by learning how to ask for feedback from customers through open-ended questions. Nevertheless, HubSpot’s model demonstrates that a focused, quick survey can still yield actionable results. By examining customer feedback survey examples, you can see how this concise format balances simplicity with the need for useful insights, making it a solid choice for businesses aiming to improve their customer satisfaction metrics. Userpilot’S NPS Survey With a Follow-Up Question When you’re looking to measure customer loyalty effectively, Userpilot’s NPS survey stands out for its simplicity and effectiveness. This survey asks customers to rate their likelihood of recommending the product on a scale from 0 to 10. What sets it apart is the follow-up question that invites respondents to explain their rating, allowing you to gather qualitative insights. Here are some key benefits of Userpilot’s approach: Two-part structure: It not only gauges customer sentiment but likewise gathers actionable feedback for improvement. High response rates: The survey’s simplicity encourages customers to participate without feeling overwhelmed. Commitment to improvement: Userpilot uses this feedback to understand customer needs better and refine product offerings. Slack’s Overall Customer Satisfaction Survey Example How effectively can a company gauge customer satisfaction? Slack’s Overall Customer Satisfaction Survey provides a clear example of how to achieve this. The survey is designed to collect feedback at various touchpoints, ensuring that you receive timely insights about your experiences with the platform. Primarily utilizing multiple-choice questions, it simplifies responses and facilitates quick data analysis, making it user-friendly for you and other respondents. By sending these surveys regularly, Slack can assess overall satisfaction and pinpoint areas needing improvement in service and features. The survey emphasizes brevity, respecting your time, which encourages higher completion rates thanks to its straightforward format. The feedback gathered informs product development and helps maintain strong relationships by effectively addressing user concerns. This systematic approach not only improves user experience but additionally contributes to the continuous evolution of Slack’s offerings, ensuring alignment with customer expectations. Jira’s Customer Satisfaction Survey Regarding a New Issue Jira’s Customer Satisfaction Survey offers a contextual in-app experience that captures your feedback right after you engage with a new feature. Using a straightforward emoji rating scale, it allows you to quickly express your satisfaction without lengthy explanations, making the process efficient. This streamlined user experience not just encourages more responses but likewise helps the development team identify specific areas for improvement based on your insights. Contextual In-App Survey To effectively gather user feedback on new features, contextual in-app surveys like the Customer Satisfaction Survey provide a timely and relevant method for collecting insights immediately after users interact with specific functionalities. This guarantees you receive feedback right when it matters most, leading to actionable outcomes. The survey uses a quick emoji-based scoring system, making it easy for you to express satisfaction levels. Feedback is gathered in real-time, allowing for swift identification of user sentiment and potential issues. The non-intrusive design integrates seamlessly into the user interface, maximizing participation rates without disrupting your experience. Emoji Rating Scale The emoji rating scale in the Customer Satisfaction Survey offers a visually engaging and straightforward method for users to share their opinions on new features in Jira. By using emojis, the survey simplifies the feedback process, allowing you to quickly express your feelings without having to write detailed responses. This playful and informal approach encourages higher response rates compared to traditional numerical scales. Integrating the emoji rating scale immediately after your interaction with new features helps Jira capture timely feedback, making it more relevant. This context allows the company to identify pain points and areas needing improvement, ultimately driving continuous improvements to their product based on your sentiments, ensuring your experience is prioritized and refined. Streamlined User Experience How can a streamlined user experience improve your interaction with new features? Jira’s Customer Satisfaction Survey is aimed at improving your feedback process. By making it quick and user-friendly, you can share your thoughts immediately after using a new feature. This survey employs an emoji-based scoring system, which simplifies your feedback and makes it more engaging. The survey triggers contextually, appearing right after you engage with specific features. It captures real-time user sentiment, allowing for immediate improvements. Integrating the survey seamlessly into the interface minimizes disruption, maximizing response rates. Miro’s Passive Customer Satisfaction Survey Example As many companies struggle to gather meaningful customer feedback, Miro’s passive customer satisfaction survey stands out as an effective solution that integrates smoothly into its user interface. This survey is always accessible, allowing you to provide feedback without disrupting your workflow, which greatly increases participation. Its simple and intuitive design encourages quick responses, often using emoji or star rating systems for ease of use. Miro continuously collects feedback in real-time as you interact with the platform, leading to more immediate and relevant data. This approach helps Miro maintain a pulse on customer satisfaction levels and identify areas for improvement. Postfity’s New Feature Survey What if you could provide valuable feedback on new features without interrupting your workflow? Postfity’s New Feature Survey does just that with its non-intrusive slideout format. This design encourages user engagement as you’re actively using the platform. Here’s how it works: It focuses on newly released features, gathering targeted insights on their effectiveness and user satisfaction. The survey combines quantitative and qualitative questions, allowing you to give numeric ratings and detailed comments. Its visually appealing and user-friendly layout improves participation, making it easy for you to share your thoughts. Wise’s Transactional NPS Survey Following the trend of innovative feedback mechanisms, Wise’s Transactional NPS Survey presents a timely approach to gauging customer satisfaction right after a transaction. By sending the survey immediately post-purchase, Wise effectively captures customer sentiment at a critical touchpoint. The survey employs a straightforward 0-10 scale, asking customers how likely they’re to recommend Wise to others, yielding clear, quantifiable data. Additionally, the survey includes an open-ended follow-up question, allowing customers to provide qualitative insights into their experiences. This combination of quantitative and qualitative feedback enriches the data collected, offering a deeper comprehension of customer sentiments. The concise format of the survey respects customers’ time, encouraging higher response rates and ensuring the feedback is relevant and timely. Frequently Asked Questions What Are Some Good Customer Service Survey Questions? Good customer service survey questions often include a satisfaction rating scale from 1 to 10, helping you quantify experiences. You might ask about the responsiveness of your customer service team on a scale from 1 to 5, which gauges effectiveness. Open-ended questions like, “What can we do to improve?” invite specific feedback. Furthermore, inquiring about the likelihood of recommending your service can measure customer loyalty, whereas questions on self-service resources identify areas needing support. What Are 5 Good Survey Questions? To create effective survey questions, consider these five examples: First, ask, “How satisfied are you with our service?” using a Likert scale. Second, include a multiple-choice question like, “Which product features do you value most?” Third, inquire, “What improvements would you suggest for our service?” as an open-ended question. Fourth, implement a Net Promoter Score (NPS) question: “On a scale of 0 to 10, how likely are you to recommend us?” Finally, ask, “What is your preferred communication method?” What Is an Example of a Customer Survey? A customer survey typically gathers feedback about a product or service. For example, you might encounter a Net Promoter Score (NPS) survey that asks you to rate your likelihood of recommending a service on a scale from 0 to 10. Following that, it may prompt you to explain your rating, allowing for more in-depth insights. This format helps companies understand customer loyalty and identify areas needing improvement, ultimately improving their offerings. What Are the 3 C’s of Customer Satisfaction? The 3 C’s of customer satisfaction are Clarity, Consistency, and Connection. Clarity guarantees you communicate product details and expectations clearly, reducing confusion. Consistency focuses on delivering the same quality experience at every customer touchpoint, which builds trust in your brand. Connection involves creating emotional engagement with customers, nurturing loyalty and advocacy. When you implement these principles effectively, you can expect improved customer satisfaction, higher retention rates, and positive word-of-mouth referrals. Conclusion Incorporating effective customer feedback surveys is crucial for gathering valuable insights. By examining successful examples like HubSpot, Userpilot, and Slack, you can identify key elements that improve engagement and clarity. Utilizing varied formats, such as scales, open-ended questions, and in-app prompts, allows you to capture diverse customer sentiments. In the end, designing your survey with these strategies in mind can lead to more meaningful feedback, helping you enhance your offerings and better meet customer needs. Image via Google Gemini This article, "7 Effective Examples of Customer Feedback Surveys to Inspire Your Design" was first published on Small Business Trends View the full article

When you’re designing customer feedback surveys, it’s crucial to look at effective examples that can guide your approach. Various companies have adopted unique methods to gather insights, from HubSpot‘s mixed-scale questions to Miro‘s unobtrusive surveys. These examples illustrate how different formats can boost engagement and yield valuable data. Comprehending these strategies can greatly improve your survey design. What specific elements will you incorporate to meet your feedback goals? Key Takeaways HubSpot’s survey combines a 1-7 scale with open-ended questions for both quantitative and qualitative insights. Userpilot’s NPS survey uses a 0-10 scale, followed by a question to gather actionable customer sentiment. Slack’s overall customer satisfaction survey emphasizes brevity with multiple-choice questions for quick analysis. Jira’s in-app survey utilizes an emoji rating scale for immediate feedback after feature engagement, enhancing user experience. Miro’s passive survey allows for unobtrusive, continuous feedback through simple rating systems, ensuring consistent customer engagement. HubSpot’s Customer Satisfaction Score Survey HubSpot’s Customer Satisfaction Score Survey is an effective tool for measuring customer satisfaction through a straightforward 1-7 point scale. This simplicity encourages higher response rates, making it easy for you to collect data after significant interactions. If you’re wondering how to ask feedback from a client, consider timing your survey right after a key service experience—this guarantees the feedback is relevant and fresh. While the numerical ratings provide valuable quantitative insights, you might want to improve your surveys by learning how to ask for feedback from customers through open-ended questions. Nevertheless, HubSpot’s model demonstrates that a focused, quick survey can still yield actionable results. By examining customer feedback survey examples, you can see how this concise format balances simplicity with the need for useful insights, making it a solid choice for businesses aiming to improve their customer satisfaction metrics. Userpilot’S NPS Survey With a Follow-Up Question When you’re looking to measure customer loyalty effectively, Userpilot’s NPS survey stands out for its simplicity and effectiveness. This survey asks customers to rate their likelihood of recommending the product on a scale from 0 to 10. What sets it apart is the follow-up question that invites respondents to explain their rating, allowing you to gather qualitative insights. Here are some key benefits of Userpilot’s approach: Two-part structure: It not only gauges customer sentiment but likewise gathers actionable feedback for improvement. High response rates: The survey’s simplicity encourages customers to participate without feeling overwhelmed. Commitment to improvement: Userpilot uses this feedback to understand customer needs better and refine product offerings. Slack’s Overall Customer Satisfaction Survey Example How effectively can a company gauge customer satisfaction? Slack’s Overall Customer Satisfaction Survey provides a clear example of how to achieve this. The survey is designed to collect feedback at various touchpoints, ensuring that you receive timely insights about your experiences with the platform. Primarily utilizing multiple-choice questions, it simplifies responses and facilitates quick data analysis, making it user-friendly for you and other respondents. By sending these surveys regularly, Slack can assess overall satisfaction and pinpoint areas needing improvement in service and features. The survey emphasizes brevity, respecting your time, which encourages higher completion rates thanks to its straightforward format. The feedback gathered informs product development and helps maintain strong relationships by effectively addressing user concerns. This systematic approach not only improves user experience but additionally contributes to the continuous evolution of Slack’s offerings, ensuring alignment with customer expectations. Jira’s Customer Satisfaction Survey Regarding a New Issue Jira’s Customer Satisfaction Survey offers a contextual in-app experience that captures your feedback right after you engage with a new feature. Using a straightforward emoji rating scale, it allows you to quickly express your satisfaction without lengthy explanations, making the process efficient. This streamlined user experience not just encourages more responses but likewise helps the development team identify specific areas for improvement based on your insights. Contextual In-App Survey To effectively gather user feedback on new features, contextual in-app surveys like the Customer Satisfaction Survey provide a timely and relevant method for collecting insights immediately after users interact with specific functionalities. This guarantees you receive feedback right when it matters most, leading to actionable outcomes. The survey uses a quick emoji-based scoring system, making it easy for you to express satisfaction levels. Feedback is gathered in real-time, allowing for swift identification of user sentiment and potential issues. The non-intrusive design integrates seamlessly into the user interface, maximizing participation rates without disrupting your experience. Emoji Rating Scale The emoji rating scale in the Customer Satisfaction Survey offers a visually engaging and straightforward method for users to share their opinions on new features in Jira. By using emojis, the survey simplifies the feedback process, allowing you to quickly express your feelings without having to write detailed responses. This playful and informal approach encourages higher response rates compared to traditional numerical scales. Integrating the emoji rating scale immediately after your interaction with new features helps Jira capture timely feedback, making it more relevant. This context allows the company to identify pain points and areas needing improvement, ultimately driving continuous improvements to their product based on your sentiments, ensuring your experience is prioritized and refined. Streamlined User Experience How can a streamlined user experience improve your interaction with new features? Jira’s Customer Satisfaction Survey is aimed at improving your feedback process. By making it quick and user-friendly, you can share your thoughts immediately after using a new feature. This survey employs an emoji-based scoring system, which simplifies your feedback and makes it more engaging. The survey triggers contextually, appearing right after you engage with specific features. It captures real-time user sentiment, allowing for immediate improvements. Integrating the survey seamlessly into the interface minimizes disruption, maximizing response rates. Miro’s Passive Customer Satisfaction Survey Example As many companies struggle to gather meaningful customer feedback, Miro’s passive customer satisfaction survey stands out as an effective solution that integrates smoothly into its user interface. This survey is always accessible, allowing you to provide feedback without disrupting your workflow, which greatly increases participation. Its simple and intuitive design encourages quick responses, often using emoji or star rating systems for ease of use. Miro continuously collects feedback in real-time as you interact with the platform, leading to more immediate and relevant data. This approach helps Miro maintain a pulse on customer satisfaction levels and identify areas for improvement. Postfity’s New Feature Survey What if you could provide valuable feedback on new features without interrupting your workflow? Postfity’s New Feature Survey does just that with its non-intrusive slideout format. This design encourages user engagement as you’re actively using the platform. Here’s how it works: It focuses on newly released features, gathering targeted insights on their effectiveness and user satisfaction. The survey combines quantitative and qualitative questions, allowing you to give numeric ratings and detailed comments. Its visually appealing and user-friendly layout improves participation, making it easy for you to share your thoughts. Wise’s Transactional NPS Survey Following the trend of innovative feedback mechanisms, Wise’s Transactional NPS Survey presents a timely approach to gauging customer satisfaction right after a transaction. By sending the survey immediately post-purchase, Wise effectively captures customer sentiment at a critical touchpoint. The survey employs a straightforward 0-10 scale, asking customers how likely they’re to recommend Wise to others, yielding clear, quantifiable data. Additionally, the survey includes an open-ended follow-up question, allowing customers to provide qualitative insights into their experiences. This combination of quantitative and qualitative feedback enriches the data collected, offering a deeper comprehension of customer sentiments. The concise format of the survey respects customers’ time, encouraging higher response rates and ensuring the feedback is relevant and timely. Frequently Asked Questions What Are Some Good Customer Service Survey Questions? Good customer service survey questions often include a satisfaction rating scale from 1 to 10, helping you quantify experiences. You might ask about the responsiveness of your customer service team on a scale from 1 to 5, which gauges effectiveness. Open-ended questions like, “What can we do to improve?” invite specific feedback. Furthermore, inquiring about the likelihood of recommending your service can measure customer loyalty, whereas questions on self-service resources identify areas needing support. What Are 5 Good Survey Questions? To create effective survey questions, consider these five examples: First, ask, “How satisfied are you with our service?” using a Likert scale. Second, include a multiple-choice question like, “Which product features do you value most?” Third, inquire, “What improvements would you suggest for our service?” as an open-ended question. Fourth, implement a Net Promoter Score (NPS) question: “On a scale of 0 to 10, how likely are you to recommend us?” Finally, ask, “What is your preferred communication method?” What Is an Example of a Customer Survey? A customer survey typically gathers feedback about a product or service. For example, you might encounter a Net Promoter Score (NPS) survey that asks you to rate your likelihood of recommending a service on a scale from 0 to 10. Following that, it may prompt you to explain your rating, allowing for more in-depth insights. This format helps companies understand customer loyalty and identify areas needing improvement, ultimately improving their offerings. What Are the 3 C’s of Customer Satisfaction? The 3 C’s of customer satisfaction are Clarity, Consistency, and Connection. Clarity guarantees you communicate product details and expectations clearly, reducing confusion. Consistency focuses on delivering the same quality experience at every customer touchpoint, which builds trust in your brand. Connection involves creating emotional engagement with customers, nurturing loyalty and advocacy. When you implement these principles effectively, you can expect improved customer satisfaction, higher retention rates, and positive word-of-mouth referrals. Conclusion Incorporating effective customer feedback surveys is crucial for gathering valuable insights. By examining successful examples like HubSpot, Userpilot, and Slack, you can identify key elements that improve engagement and clarity. Utilizing varied formats, such as scales, open-ended questions, and in-app prompts, allows you to capture diverse customer sentiments. In the end, designing your survey with these strategies in mind can lead to more meaningful feedback, helping you enhance your offerings and better meet customer needs. 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