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The AI-Driven Marketing Playbook Reshaping Modern Retail

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By Al Sefati

Retail marketing has changed drastically in recent years. Consumers no longer discover brands only through search ads, visiting stores or browsing social media. Today’s shoppers move from Google, TikTok, marketplaces, AI assistants, review platforms and influencer content before buying anything.

This change has created both a challenge and opportunity for retailers.

Many times, the most successful brands don’t carry the biggest advertising budgets. They are the ones connecting digital ecosystems including SEO, AI visibility, paid media, AI automation, reputation management and customer retention into one strategy.​

The Customer Journey Is No Longer Linear

The traditional retail funnel is no more. Customers no longer move from awareness to consideration to purchase. Instead, they jump between devices, apps, AI assistants, marketplaces, reviews and social channels in a fragmented buying journey.

Someone shopping for sneakers might find a product on TikTok, search Google for reviews, ask ChatGPT for alternatives, compare prices on Amazon and then finally make a purchase after seeing a retargeting ad days later.

This behaviour applies to all retail segments. Visibility alone is no longer enough. Retailers must have consistency across every digital touchpoint.

SEO Has Expanded Into AI Visibility

SEO still matters, but retail brands are now competing for visibility inside AI-generated answers, not traditional rankings. Platforms like ChatGPT, Gemini, Perplexity and Google AI Overviews are changing how consumers research products.

Instead, customers are asking conversational questions like, “What are the best sustainable clothing brands?” or “Which standing desk is best for small apartments?”

This is where answer engine optimization (AEO) and generative engine optimization (GEO) enter the picture. To capture the visibility retailers need, AI-generated responses need fast websites, strong product data, new content, authentic reviews and FAQ-driven pages.

Brands relying only on traditional SEO tactics are becoming invisible in AI-driven searches.

AI Automation Is Becoming Essential

AI is rapidly becoming one of the biggest competitive advantages in retail.

Retailers are using AI to automate customer support, product recommendations, CRM automation, email and SMS workflows and lead qualification, among other things. From what I’ve seen, this doesn’t just reduce manual work; using AI improves speed, personalization and scalability across the business.

In my experience, companies are moving beyond experimentation and focusing on operational AI systems that directly improve efficiency, customer experience and revenue growth.

AI automation is a differentiator for businesses in a crowded market.

Product Pages Have Become Conversion Hubs

One of the biggest mistakes retailers still make is treating product pages like static catalogues.

Modern product pages must function as full conversion environments, meaning they include customer reviews, FAQ sections, rich media, shipping transparency and user-generated content. AI systems are pulling directly from these pages when generating recommendations. Pages with thin or repetitive content lose visibility and trust.

Retailers I’ve worked with who invest in detailed, conversion-focused product pages tend to see stronger organic traffic and higher conversion rates simultaneously.

Reviews And Reputation Influence Discovery

Reviews no longer only influence conversions. They now influence visibility. Search engines and AI evaluate trust signals across Google Reviews, Trustpilot, Reddit, YouTube, TikTok and other marketplace ratings.

Peer validation always beats polished advertising. That is why modern retail brands are investing heavily in review acquisition, social proof and real customer experiences.

From what I’ve seen, brands generating authentic customer conversations online tend to perform better in both search visibility and conversion rates.

Retail Marketing Is No Longer Just About Driving Traffic

Retail marketing in 2026 is not about simply driving traffic. The focus is now on visibility across search engines, AI platforms, marketplaces and social ecosystems. ​

Growing brands are the ones creating connected systems that combine modern SEO, AI visibility, paid media, AI automation, customer trust and operational speed into a unified strategy. Retailers that are still relying on disconnected tools and outdated marketing playbooks risk becoming increasingly invisible in the modern digital buying journey.​

Feature image credit: Getty

By Al Sefati

COUNCIL POST | Membership (fee-based)

Al Sefati is an enterprise SEO, AEO\GEO, and digital marketing expert, and CEO of Clarity Digital with over two decades of experience. Read Al Sefati’s full executive profile here. Find Al Sefati on LinkedIn and X. Visit Al’s website.

Sourced from Forbes

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Dentsu brings back 360i brand as social-first solution primed for AI

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By Peter Adams

The digital marketing services provider, which was folded into Dentsu’s creative banner in 2022, has an updated logo and will work on a fixed-fee pricing model.

Dive Brief:

  • Dentsu has resurrected its 360i brand in the U.S. as a social-first solution equipped for the artificial intelligence era of marketing, according to a press release shared with Marketing Dive.
  • The offering, which previously folded into Dentsu’s creative banner in 2022, has received an updated logo and will work on a fixed-fee pricing model. It will not operate as a standalone agency from Dentsu Creative, but rather as an agile team that can tap into the full range of Dentsu’s creative, media, data and technology capabilities.
  • The unit will be led by Chrstine Cotter, who joins the group from Ogilvy as managing director of 360i and head of social innovation at Dentsu. Currently without any clients, 360i is in active talks for new business, the release said.

Dive Insight:

Rather than build or acquire another agency specialized in social-first expertise, Dentsu is bringing back a legacy name and refitting it as a “focused branded solution” that is built around AI and additive to its existing roster.

Included in the relaunch is a new 360i logo inspired by modular designs and fresh leadership in Cotter, who previously acted as Ogilvy’s president of social innovation. Dentsu said the modernized 360i is targeted at brands looking to invest more heavily in social, creators and commerce, as well as those that are navigating significant changes in their business, such as category disruption. The network repeatedly emphasized technology shifts driven by AI and algorithms as a justification for the move, underscoring 360i’s AI-powered workflows and ability to leverage the dentsu.Connect AI operating system.

Debuted in 1998, 360i began as a search specialist before branching into social, where it became well-known for its real-time activations and pop culture savvy. Among its most noteworthy work was Oreo’s response to a Super Bowl blackout in 2013, when the cookie brand quickly put up a Twitter post noting that “You can still dunk in the dark.” The fast online response turned an unwelcome moment during advertising’s biggest night into a major brand win.

Such reactivity was novel at the time, but has become commonplace in a media ecosystem increasingly oriented around fast-scrolling, algorithmically driven feeds. The revamped 360i recognizes this new reality, promising “lean, integrated teams, fewer approval layers, and a fixed-fee model exclusively” to ensure agility, per the release.

The fixed-fee aspect marks a break from typical agency billing structures based on hours worked, and is an approach Dentsu Creative has been championing more broadly. Among marketing and procurement decision-makers, roughly two-thirds express concern about a lack of connection between agency pricing and outcomes, according to a Forrester study conducted with Dentsu.

The 360i brand returns at a point of contraction for Japan-based Dentsu, which recently tried to sell its sizable international business before those talks reportedly collapsed. While Dentsu has been relatively resilient in its home market, organic revenue declined 3% year over year in the Americas in Q1, with weakness in creative.

By Peter Adams

Sourced from MarketingDive

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LinkedIn Networking Feels Fake Now. Here’s What Actually Works in the Age of AI DMs

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By NICOLE RAMIREZ

As AI-powered outreach explodes, the value of genuine, deliberate LinkedIn networking has only increased.

Something has changed about the LinkedIn DM. If you spend any time on the platform, you have probably felt it: the messages that arrive with suspicious precision, perfectly referencing your job title and recent post, yet somehow feeling like nobody actually wrote them. The timing is right, the personalization is surface-level, and the human being is somewhere else entirely.

More than 50 percent of businesses now use an AI assistant to build connection request messages within the first month of creating LinkedIn outreach campaigns. The LinkedIn automation tools market has reached an estimated $850 million annually in 2026, growing 42 percent year over year. The result is a platform where the volume of outreach has exploded, and the signal value of any individual message has collapsed. Everyone is “connecting,” but are they truly connecting?

Alexander Smith has watched this play out from multiple sides. He built his career at Facebook, Google, and the Obama White House. He grew a 68,000-person audience on LinkedIn by posting career advice so consistently and specifically that recruiters started reaching out to him rather than the other way around. And he is now writing a book about networking — one he could not have written three years ago, because the environment has changed that dramatically.

“People are flooding DMs with networking messages,” he says, “and now we have AI tools automating those messages. What does it look like to build real relationships right now?”

His answer starts with understanding what automated outreach actually costs the people sending it.

The spray and pray problem

When Smith was at Facebook and Google, he received an overwhelming number of LinkedIn messages from people trying to break into tech. Most of them had one thing in common: they were sent to the wrong person.

“I was in trust and safety and policy work,” he says. “I got messages from software engineers, data analysts. There was one person who sent me a message asking about specific coding languages. I had to say, I don’t know what that means. That’s not my role.”

The instinct behind those messages is understandable. You see someone at a company you want to work for, and you reach out. But the strategy to reach out to anyone at the company and hope for the best is precisely the one that AI has made both easier to execute and easier to ignore. More than 11,000 job applications are submitted on LinkedIn every minute. Recruiters and hiring managers are receiving more outreach than at any point in the platform’s history. The messages that get ignored fastest are the ones that feel like they could have been sent to anyone.

“I really encourage people to take four or five minutes, read someone’s LinkedIn profile, and see if they’re relevant to your career path,” Smith says. “Are they relevant to your field? Do they have similar experiences? That extra step of trying to find people who are relevant is really helpful versus a spray-and-pray approach where you’re just reaching out to someone because they work at Netflix or Nike.”

Professionals who focus on fostering a smaller number of high-value connections consistently outperform those still using spray-and-pray tactics. The idea is not to send fewer messages, but more about sending the right ones to the right people, with the right context, at the right moment.

Why human networking has never mattered more

The counterintuitive implication of AI-automated outreach is that genuine human connection has become a scarce resource precisely because automation has made it so easy to fake.

AI has made it effortless to send hundreds of personalized-looking messages without writing a single one. The result is a platform flooded with outreach that feels human on the surface and hollow underneath. Recruiters and hiring managers have become extraordinarily good at spotting it and also quick at ignoring it. Which means the actual competitive advantage right now belongs to the person who does the opposite. More deliberate messaging is the key to standing out in a sea of automated connection requests. A message that is clearly written by a real person who has done their homework and actually gives a reason to respond is so uncommon, it’s a pleasant surprise to those who receive it.

Smith experienced this directly as he was building his own presence on LinkedIn. “There were recruiters reaching out to me from different companies,” he says. “When I was networking or reaching out to people, they would recognize me from my content. That’s when I started to realize that your personal brand is more important than the company you’re working at.”

That statement lands differently coming from someone who has worked at Facebook and Google. The implication is not that prestigious employers do not matter. It is the network you build, the reputation, the relationships, the presence that precedes you that travels in ways that a company name on a resume does not. The company can disappear. The job can be eliminated. The personal brand stays.

The human touch still closes the deal. AI is already saving hours and lifting reply rates, but through 2026, human connection remains decisive at the point of conversion. What that means practically is that AI can help you find the right people to reach out to, draft a starting point for a message, or analyse which connections are worth prioritizing. What it cannot do is replace the moment when someone recognizes your name, remembers your content, and decides they want to talk to you.

The investment frame

Smith has a way of thinking about networking that changes the entire practice, from something you do when you need something to something you build before you ever do.

“I really view LinkedIn as investing,” he says. “If you consistently put time into building your profile, posting, talking to people, it is a social media platform, and if you start creating content, pay attention to the people who are commenting and engaging. If you do those extra steps, you’re going to see it pay off.”

The investment frame matters because it changes the time horizon. Most people approach networking as something you do when you need something like when you are job searching, when you are trying to close a deal, when you are trying to get into a room you have not been invited to. That approach is the equivalent of trying to open a bank account and immediately withdraw from it.

What Smith is describing instead is the slow accumulation of deposits, a message checked in on, a comment responded to, a connection made with a former colleague, that compounds quietly until the moment you actually need it. “It’s not just how do you network quickly when you urgently need a job,” he says. “How do you build something that is really sustainable and you can really grow from long term?”

LinkedIn generates 80 percent of all B2B leads from social media, surpassing Facebook, X, and Instagram combined. The platform is where professional decisions are being made, researched, and influenced at a scale that has no precedent. The people who have been building there consistently, not automating, not spraying, not praying, are the ones with the accounts that have been compounding the longest.

The blooper reel nobody shows

One of the reasons most people’s networking feels transactional is that they only show up in public when they have something to announce. The new job. The promotion. The speaking gig. The wins.

Smith argues this is a missed opportunity, and not just strategically.

“LinkedIn shows you the final product,” he says, “but you’re not seeing the bloopers. You’re not seeing the roadblocks that went into things.” He has made a deliberate practice of sharing the roadblocks, the hundreds of unanswered networking messages, the opportunities that did not work out, the finalist positions he did not get. Even the time he got rejected from a volunteer mentor program.

“I got somebody who reached out and said, I also got rejected for that too,” he says. “It was just funny. And I think it really breaks the ice when you can just not take yourself too seriously and tell people about your journey and all the things that go on behind the scenes.”

The professional case for sharing failure is not sentimental. It is strategic. When someone sees you navigate rejection with transparency and humour, they learn something about how you operate under pressure that a polished announcement never reveals. The connection that forms around a blooper is more durable than the one formed around a highlight, because the blooper is where the real person shows up.

What good networking actually looks like

For job seekers specifically, Smith’s advice runs counter to the dominant narrative. The viral LinkedIn post that says “shoot your shot” is aspirational and largely useless. The realistic version is harder to hear.

“I truly think the bar to match the job description with your experience, depending on the company, is at least 80 percent, but sometimes it’s 100 percent,” he says. “Think about the recruiter and think about the competition. What did they look like? What’s their background? And do you feel like you have the skills and experience where you can match up with those people?”

The networking that actually moves applications forward is not the cold message to a random employee at a company you want to work for. It is the relationship built over time with the people who would actually be your future colleagues. The ones who know if the team is expanding, who understand what specific experience would be helpful to highlight, and who can tell you whether the culture is genuinely a fit.

“Those future co-workers, future teammates, are the people that are going to know if the team’s hiring,” he says. “They’re going to know what specific experiences might be helpful to highlight. They’re going to be the people that are relevant to help you assess if you like the company.”

In the Visibility Economy, that is what networking has always been at its best, not a transaction, not a numbers game, not something you automate. It is a sustained investment in relationships with people who matter to where you are going. The people who understand that, and who have been building those relationships before they needed them, are the ones who are finding that the job market, as brutal as it is, still has a place for them.

AI can send the message. It cannot build the relationship. That part is still yours.

The opinions expressed here by Inc.com columnists are their own, not those of Inc.com.

Feature image credit: Getty Images

By NICOLE RAMIREZ

Sourced from Inc.

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How the UK’s social media ban could transform graphic design hiring

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An under-16s ban on TikTok and Instagram might do more than protect children – it could reshape who gets hired by agencies.

There’s a moment that’s become familiar to anyone hiring creatives over the past decade. You’re looking at someone’s portfolio. It’s solid enough. Then you spot the line: “50K followers on TikTok.” Suddenly, the conversation changes.

When that happens, those of us of a certain age, who came up during the days of print, have felt the fear. The fear of no longer being relevant. Maybe it’s paranoia, maybe it’s realism. Either way, if you’ve not a died-in-the-wool social native, it’s tempting to feel your “old-school” skills are no longer adequate, and the algorithm has become the new resume. But what if that era is about to fade? The path to getting your first design job might soon look very different.

A close-up of a young woman looking down at her smartphone, overlaid with text in a stylized window box that reads "GOVERNMENT ANNOUNCES BAN ON SOCIAL MEDIA COMPANIES PROVIDING SERVICES FOR UNDER 16s."

(Image credit: Gov.uk)

Is the tide turning?

The assumption that social fluency equals creative value made sense when social media sat at the centre of cultural life. Increasingly, though, that centrality appears to be weakening.

Ofcom data published in April found that fewer than half of UK adult social media users are now actively posting, sharing or commenting, down from 61% in 2024. Meanwhile, only 36% believe social platforms are good for their mental health, and a third have deleted an app because it was affecting their wellbeing.

The mood is shifting. This week’s announcement that the UK will ban under-16s from using TikTok, Instagram, Snapchat, YouTube, Facebook and X feels like another sign of that change. What’s striking isn’t simply the policy itself, but how little public resistance it appears to have generated, compared with the debates that surrounded social media a decade ago.

Whether the legislation succeeds remains to be seen. But culturally, it reflects a growing willingness to question assumptions that once seemed untouchable. And that’s where things get interesting for creative industries.

Rebalancing, not revolution

Two young designers look at a a computer screen using the best graphic design software

(Image credit: Gilaxia via Getty Images)

None of this means social media skills are about to become irrelevant. Clients will still want social content. Agencies will still need people who understand how visual culture moves online. And teenagers will inevitably find ways around restrictions, just as they’ve done elsewhere. But there’s a difference between circumventing a platform and being shaped by it from childhood.

For over a decade, social media has acted as a powerful formative influence on aspiring creatives. It’s shaped not only what they consume, but how they think about creativity itself: what gets attention, what gets shared, what succeeds.

If future generations spend less of their developmental years optimising content for algorithms, they’ll arrive at design school (and eventually at job interviews) with different instincts.

They may be less conditioned by the high-stimulation, short-form aesthetics that platforms reward. They may be more willing to explore slower, deeper and more varied forms of creative practice. In some ways, it could feel a little like stepping back into the pre-2010s creative landscape (but with better WiFi).

What this means for hiring

If you’re responsible for hiring designers, it’s worth thinking now about what this shift means for the talent pipeline. The candidates you’ll see in five to ten years will have grown up differently. Their portfolios may look different too: less platform-optimised, potentially richer in other ways. The instinct to reject someone because they don’t have a strong social presence may start to look, frankly, as outdated as rejecting someone for not knowing QuarkXPress.

Maybe I’m a hopeless optimistic, but I think there’s a broader opportunity here to restate what design education is actually for. If the appetite for digital natives has put pressure on colleges to teach content creation over craft, a cultural shift away from social media could ease that pressure.

None of this is inevitable, of course. Industries don’t change hiring habits easily or quickly. But the UK’s ban challenges a long-standing assumption: that the people best equipped to navigate social platforms are necessarily the most creatively valuable.

They never were, of course. It just took a piece of legislation, and the beginnings of a cultural retreat from the doom scroll, to remind us.

Feature image credit: Galina Zhigalova via Getty Images

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Tom May is an award-winning journalist specialising in art, design, photography and technology. He is the author of the books The 50 Greatest Designers (Arcturus) and Great TED Talks: Creativity (Pavilion). Tom was previously editor of Professional Photography magazine, associate editor at Creative Bloq, and deputy editor at net magazine.

Sourced from CREATIVE BLOQ

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Half of AI Job Cuts Will Be Reversed by 2027, Gartner Says. Here’s the Real Lesson

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By SOREN KAPLAN

Research firm Gartner predicts half of all AI workforce cuts will reverse by 2027. The reason tells you everything about what AI still can’t do—and what talent is needed now.

Half of the companies that cut workers for AI-related reasons will hire those roles back by 2027, according to Gartner. Forrester’s Predictions 2026 report had already documented the underlying cause: Fifty-five percent of employers who restructured for AI now regret the decision.

The pattern points to a specific mistake. As I’ve explored before, the question of when to trust data versus judgment matters more than most executives acknowledge. The companies reversing course replaced jobs with AI that required human judgment and got information retrieval instead. Research into how AI is actually being used inside organizations shows that humans need to be in the loop when real judgment of trade-offs is required.

Don’t assume that because AI can access everything your people know, it can do everything people do. Those are two entirely different things. And that’s the leadership mistake underlying both the Gartner projection and the Forrester data.

The Cost of Getting This Wrong

Consider what it would mean to hire a surgeon who had only read surgery textbooks. The information is complete and the reading is thorough, yet the surgeon has never operated on anyone. You’d never hire that surgeon. But companies across industries made the equivalent decision when they replaced workers whose value came from having done the job under real pressure, thousands of times.

Klarna ran this experiment at scale. In 2024, the Swedish fintech claimed its AI chatbot did the equivalent work of 700 customer service agents and projected tens of millions in savings. By May 2025, they publicly acknowledged that while automation takes on more of the high-volume, simpler queries, they still needed human agents equipped for complex, sensitive cases like fraud disputes, complex billing issues, and emotionally charged customer situations, a different profile than traditional outsourced support. They began directly hiring a small number of high-skilled humans into the customer service process to identify where the human touch brings the most value to customers.

AI is indeed a transformative technology. People are scared it’s going to take their jobs. When jobs are lost to AI, it’s disruptive to the organization. But then to reverse course shortly thereafter, it creates a whipsaw effect that can have negative effects on the people who remain, and the culture.

The Human Gaps in AI Technology

AI can categorize problems and retrieve policies at speeds no human can match. Sitting with a frustrated customer, rebuilding trust after a systemic failure, and deciding in the moment that this person needs an exception are calls it has never made. The distance between those two categories is the same one that opened up when Klarna’s chatbot was given jobs that required having experienced something nuanced before and needing to draw on personal judgment about it.

There’s a profound difference between reading about surgery a thousand times and having done surgery a thousand times. Same goes for customer service when it comes to upset customers. One produces knowledge, and the other requires  judgment. Many organizations confuse the two.

Three Things to Get Right

The leaders closing this gap are deploying AI for what it’s built for and protecting the people who supply what it can’t access. Here’s what to do:

  • Audit AI Capabilities. Ask honestly whether the roles you’ve automated require simple task execution, experience under pressure, or trade-offs requiring judgment.
  • Treat Experience as Infrastructure. The pattern recognition, institutional memory, and client trust carried by experienced workers are harder to rebuild than most leaders realize until those assets are gone.
  • Design for Human-AI Teams. The most effective deployments use AI to process what’s routine and protect the people who handle what requires a depth of experience.

What This Moment Is Really About

Underneath the Gartner projection and the Forrester data is a deeper truth about what AI is and does. It’s the most powerful information system ever built, and information and judgment are different things entirely.

AI has read everything. But it’s lived nothing, and providing it with “rules” that replace human judgment based on experience may not ever be feasible, or desired.

The judgment behind a complex customer decision, a high-stakes negotiation, or a leadership call in the middle of a crisis comes from having navigated those situations before under real consequences. That lives in the kind of intelligence that only experience builds.

This Week

In my latest book, Experiential Intelligence, I describe all this as the intelligence built from everything you’ve actually lived through — which includes your mindsets, abilities, and practical know-how. Before your next AI deployment decision, ask yourself whether the role you’re considering automating actually  requires the kind of judgment that only comes from experience. Then, identify one person on your team whose experience is the actual source of the value of that process, and make sure your AI approach protects it.

Your collective experience is the only competitive advantage that competitors  can’t download.

Feature image credit: Getty Images

By SOREN KAPLAN

Soren Kaplan helps leaders leapfrog to what’s next by cutting through noise, aligning faster, and making smarter decisions. He speaks at corporate events and conferences worldwide. Learn more at https://sorenkaplan.com.

Sourced from Inc.

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These fake AI ads are perfectly soulless

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By Hunter Schwarz

These ads might be fake, but they skewer a real problem: AI ‘slop voice’ that made nonsense the new normal.

There’s a specific voice and vagueness to technology advertising today.

The ads are often for startups you’ve never heard of selling a service or software that’s somehow related to AI. And while the ad voice is direct, in that it’s written as if it’s speaking directly to you, the viewer, the copy is intentionally cryptic. “Own Your Inference.” “Put AI Agents to Work for People.” Sometimes it’s menacing. “Stop Hiring Humans.”

These kinds of ads seem to be everywhere lately, but that doesn’t mean that they make much sense. Now, comedians Harris Alterman and Dave Ross are emphasizing just how banal and meaningless the AI ad age is turning out to be by creating their own fake tech ads that skewer the medium simply by amping up its tropes: AI industry gobbledegook and design minimalism.

[Photo: courtesy Harris Alterman and Dave Ross]

The ads, which they put up as banners in a New York City subway station (much like the controversial, real ads for the AI companion Friend last fall) ask asinine questions. “What if forks were spoons?,” “What if Texas was upside-down?,” and “What if the Rizzler was purple?” One fake ad is for a company with a human name, “Dennis.”

[Photo: courtesy Harris Alterman and Dave Ross]

Another advertises a faux company that recently rebranded. “Zipline is now Froggle,” the ad says matter-of-factly. “The cloud-based online safety you know and love, now in the palm of your hand.” An ad for a brand called Fivetable confidently states “We Put the Q in QR1777,” and Wireflow promises “you pay us, we pay you.”

[Photo: courtesy Harris Alterman and Dave Ross]

Alterman and Ross were especially inspired by a real ad for the product development software company Linear, which shows cursors pointing toward God’s outstretched hand, as in Michelangelo’s “The Creation of Adam,” and another for Dawn, an AI mental-health app, that says “Racing Thoughts Don’t Do Waiting Rooms.”

[Photo: courtesy Harris Alterman and Dave Ross]

They call the lack of distinctiveness around AI advertising in its design, voice, and fonts “slop voice,” and note that while these ads sound like they’re speaking to you, they’re really talking to someone else: a high tech, SaaS-speaking in-group. And it’s ok if the copy alienates everyone else.

[Photo: courtesy Harris Alterman and Dave Ross]

“People are confused by tech advertising,” they tell Fast Company in an email. “99% of the people reading these ads have no idea what they’re talking about. It feels like 20 people in tech, advertising to 20 other people in tech. Do you really need to put up ads? Can’t you guys just get in a group chat together?”

[Photo: courtesy Harris Alterman and Dave Ross]

That’s how Alterman and Ross made their ads, after all. The comedians wrote them together. Ross then designed the ads in Photoshop and made websites for them using HTML/CSS and Javascript. While their fake ads aren’t for real tech companies, they are selling something. The comedians put up a merch shop under their brand called Goofstump.

Alterman says they plan to make more fake ads, and they’d like to partner with the MTA to make an official art installation. Though they’ve set up websites for some of the parody brands, he says they didn’t pay for all the URLs they’re advertising. The URL for sellyourposessions, for example—”Are You Poor? Sell Your Possessions,” is the tagline—costs about $700, or “a little too much for a joke,” he says. Especially in times like these.

Feature image credit: courtesy Harris Alderman and Dave Ross

By Hunter Schwarz

Hunter Schwarz is a Fast Company contributor who covers the intersection of design and advertising, branding, business, civics, fashion, fonts, packaging, politics, sports, and technology.. Hunter is the author of Yello, a newsletter about political persuasion More

Sourced from FastCompany

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Don’t let your brand name hold you back

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The dos and don’ts of naming a brand.

Mountain Valley vs. Liquid Death. They both sell water. One sounds refreshing. The other sounds like a rock band or a media company. One tells you where it’s from. The other makes you double-take.

Same product, wildly different runways.

A brand’s name isn’t just its first impression; it’s often its longest-lasting asset.

Positioning may shift. Even the best logos and visuals may evolve. Packaging gets refreshed. Product mixes expand and contract. But a name often outlasts these, meaning a decision made at a company’s inception must survive a future the business can’t fully see yet.

And to make matters more consequential, the rules of that future are being rewritten in real time.

As categories blur and technology helps them move at warp speed, brands that stay relevant can’t afford to stay singular, static, or in their respective lanes. The ones that win are built to move and adapt. They’re building responsive businesses and offerings and becoming cultural lightning rods that cut across generations, moments, and need states.

It’s why an online bookstore is now the infrastructure of modern commerce. Fitness brands are opening hotels. Beauty brands are becoming merch machines. And as it turns out, media companies like Unwell are launching water brands.

These days, the category a brand starts in is rarely the one it stays in.

Which means we’re selecting our most permanent asset in a market defined by constant reinvention. And some brands are naming themselves into corners without realising it.

The great naming trap

Selection of Oatly packaging

Oatly’s name shows what it does clearly (Image credit: Oatly)

Brand names tend to exist on a spectrum from how clearly you describe what you offer (think: Whole Foods) to names with no literal connection to the offering (think: Erewhon).

Beyond clarity and convention, there’s another question that doesn’t get asked enough: how narrow or broad should the name be? It’s a deliberate balance: clarity drives early adoption, but breadth leaves room for growth. This needs to be an intentional, thoughtful step. But when brands skip it, they often pay for it later.

Clear, descriptive names work hard. Dave’s Killer Bread tells you exactly what world it lives in. Oatly leaves little ambiguity about what’s inside the carton. But they’re also making a bet. The more specific the name, the more specific the future you may be locking yourself into.

What if Oatly wants to move into other alt-milks and compete with the likes of Califia Farms and Malk? Or consumers suddenly decide oats are cancelled?

And there’s the trap. The same name that once clearly defined the business is now confining it.

ClassPass logo

ClassPass began as a fitness brand and has moved into food and beverage (Image credit: ClassPass)

We’re seeing this play out with ClassPass. For years, the name worked beautifully – until the business evolved beyond it. Recently, it expanded into food and beverage, reframing themselves around broader wellness access versus just fitness class access. Strategically, it makes sense. Nominally, they’re stuck.

The issue of whether the expansion is credible aside. Will people think to use the ClassPass app to order a smoothie? The name frames behaviour, and in this case, it’s framing the wrong one.

SoulCycle is a different version of the same trap – except they’re not trying to expand, they’re trying to survive. When boutique spin was hot, the name was an asset. But the category’s been cooling for years, and there’s very narrow territory they can slip into without fighting assumptions baked into their name.

To be clear, a name can’t save a broken business model. But a limiting one can make it harder to grow, evolve and pivot. And in a world where categories and markets shapeshift overnight, flexibility is everything.

For both, the choice is the same: change the name or change perception. Neither is free. Neither is easy. And neither is guaranteed.

Some of the world’s biggest brands have faced this tension:

Dunkin' rebrand

Dunkin’ dropped the ‘donuts’ (Image credit: Dunkin’)

Dunkin’ dropped the Donuts to signify breadth and modernity.

Weight Watchers became WW amid diet-culture baggage, then moved back to Weight Watchers amid the GLP-1 craze.

Athletic Greens became AG1 to expand their audience and usage occasions.

Facebook became Meta to untether themselves from social media.

These weren’t cosmetic updates. They were attempts to manufacture flexibility after the fact. And they cost time, money, and in some cases, enterprise value.

Which brings us to HBO. Remember when I said “longest-lasting asset?” HBO spent years trying to shed theirs. It rebranded to Max, only to quietly add HBO back when audiences refused to follow. Unfortunately, a name change isn’t always a simple escape hatch.

Name of the long game

HBO Max

HBO has had several name changes (Image credit: HBO Max)

So, what if we built that flexibility in from the start? Where businesses ask themselves how far the brand name could take them, not just how well it tells the story of who they are today? It’s the difference between naming the thing you sell and the world you envision.

A brand can start narrow – it’s often the right strategic move. But the name doesn’t have to cement that bet.

That’s not an argument for vagueness or abstraction. It’s an argument for a more durable anchor.

Uber get together

Promo for Uber (Image credit: Uber)

Consider Uber. The name means above, beyond, superior. It’s anchored in a sense of service, not a mode of transport. Which is exactly why it could proliferate into Uber Eats, Uber Freight, and Uber Direct. Their name was never the ceiling; it was the foundation.

In a world where brands become platforms, names need legs. Impossible Foods is named after a mission with no limit – impossibly delicious, impossibly sustainable, impossibly whatever comes next. Vacation sells sunscreen. The name doesn’t, which means a hotel, a clothing line, a podcast – it all fits. And then there’s the goddess of victory. An anchor so durable, Nike could own basketball, skateboarding, golf, and a multi-billion-dollar DTC business naturally.

As categories continue blurring and markets reinvent themselves, one of the riskiest things a brand can do is define itself too narrowly, too early.

That’s why the smartest names aren’t just telling a story about the business, product, or service – they’re making room for the one that doesn’t exist yet.

The Brand Impact Awards 2026 are now open for entries! If you have a standout branding project from the last year that you think deserves recognition, you need to enter the BIAs. You have until July 9 to enter and you can do so on the Brand Impact Awards website.

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As a Senior Strategist at CBX, Claire blends insight with instinct, using culture and consumer behaviour as her compass to help brands close the gap between what they say, what they mean, and what they do. Her strategic approach has shaped everything from startups to global brands like Snapchat, Anheuser-Busch, and Kimberly-Clark across food and beverage, wellness, e-commerce, tech, and beyond – helping them build distinctive voices, sharper stories, and stronger connections.

Sourced from CREATIVE BLOQ

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AI Search Cites Random YouTubers More Than Your Brand. Here’s How to Build a Strategy For the AI Search Era

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BY ASHLEY COUTO

New data shows AI assistants cite independent YouTube creators more than brand-owned content. Founders who adjust their creator briefs now will get pulled into the answers that drive buying decisions.

YouTube creator content now appears in more than 25 percent of prompts answered by AI assistants, according to new research from Jellyfish shared exclusively with Adweek. In high-intent categories like consumer electronics and financial services, nearly one in two references come from Youtube.

The Jellyfish team analysed 27 million responses across seven AI search assistants and found that independent, niche creators consistently outrank brand-owned content and celebrity influencers in AI-generated answers.

For founders, that means the customer journey is being rerouted through creators they may have never considered partnering with. While Reddit used to be the belle of the AI search ball, YouTube has overtaken it. Here are five things founders can change about their creator strategy to get pulled into AI search results.

Look beyond celebrity influencers

Jellyfish analysed responses across Claude, ChatGPT, Gemini, DeepSeek, Meta AI and Perplexity. Smaller creators consistently came out on top, especially those with high niche authority as opposed to more generalized creators.

An OtterlyAI study of more than 100 million citations found that roughly 41 percent of cited YouTube videos had fewer than 1,000 views and 36 percent had fewer than 15 likes. The median cited channel had posted fewer than 41 total videos.

That means a micro-creator with 2,000 subscribers and a well-structured tutorial can earn more AI citations than a high-profile partnership. AI systems prioritize reference value over popularity metrics, according to OtterlyAI’s analysis.

Prioritize long-form video over short-form

Jellyfish’s data favoured videos longer than 10 minutes. OtterlyAI found AI platforms barely cited YouTube Shorts at all outside Google’s own surfaces, with 94 percent of cited YouTube videos qualifying as long-form.

That contradicts the standard creator brief at most startups, which still asks for 30-second cuts optimized for TikTok and Reels. To surface your brand in AI search assistants, fund a structured 12-minute walkthrough rather than a punchy clip.

Insist on chapters and timestamps

Only 31 percent of cited YouTube videos have chapter structure, according to OtterlyAI’s research. That gap represents an opportunity competitors haven’t closed.

Chapters turn one video into multiple citable units. When a creator adds timestamps for “unboxing,” “setup,” “first impressions” and “comparison,” each section becomes its own potential AI citation.

Make this a line item in your creator brief. Pay for the editing time required to get the structure right.

Prioritize topical authority over follower count

A detailed YouTube review from a recognized creator now carries more citation weight than a Reddit thread with mixed opinions, according to a Superlines analysis. AI systems read subscriber counts, channel history and stated credentials as authority signals.

The right questions to ask when vetting creators are whether they consistently cover the category and whether their channel has a clear topical focus. A creator who posts consistently about makeup for olive skintones is a better bet than a generalist with five times the audience for AI search.

Track AI citations as an influencer success metric

AI search traffic converts at 14.2 percent, compared with 2.8 percent for traditional Google search, according to data cited in PikaSEO’s analysis. That conversion gap is too significant to leave unmeasured.

Adding creator-sourced AI citations as a tracked metric, alongside backlinks and branded search volume, gives founders a clearer picture of which partnerships are working. Most creators aren’t well versed in the intricacies of SEO, let alone answer engine optimization (AEO) and generative engine optimization (GEO), so you’ll likely need to coach on keywords and structure to maximize generative search capabilities.

AI assistants are sending searchers to video creators, and the brands those creators reference will end up with the sale. Founders who adjust their creator strategy now will get cited while their category competitors catch up.

Feature image credit: Getty Images

BY ASHLEY COUTO

Sourced from Inc.

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Smart Glasses Are Here. Can You Identify Their Hidden Cameras?

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By Jason Chun

Ready or not, the smart glasses future is upon us.

Even if you’ve never seen a pair of smart glasses before, you’ve probably heard about the wearable tech. Upcoming devices like Snap Specs and XReal Aura aren’t much thicker than a normal pair of glasses, but they can perform many of the same functions as a computer. This week, Meta announced new, cheaper glasses, including a frame designed in collaboration with Kylie Jenner.

But is society ready for the repercussions of everyone walking around with cameras on their faces?

Last month, a woman in London was approached by a man wearing smart glasses, who recorded their interaction without her knowledge. The video was uploaded to social media without her consent — it got 40,000 views, and the man refused to take it down unless she paid him.

This is just one of many events that highlight the privacy concerns of smart glasses.

I told a friend about Meta Ray-Bans, which look like a chunkier pair of normal black Ray-Ban Wayfarers. The average person probably wouldn’t suspect that their frames contain a hidden camera. My friend found the concept repulsive.

“Ew,” she said. “Why do those exist?”

I’ve never owned a pair of smart glasses, but I’ve seen them in the wild on two occasions. Once was when I was riding the New York subway and noticed a person sitting across from me wearing the frames.

The other time was when I struck up a conversation with a guy at a bar. It took a minute in the dimly lit room, but then I recognized the tell tale signs of his smart glasses.

I was unsettled. For a moment, I felt as if I were encountering an urban creature, like a rat or raccoon, and I didn’t know how to behave.

“Act natural,” I told myself. He wasn’t recording me (I’m pretty certain). But I knew that he could be.

Smart glasses and privacy problems

Much of the general public still doesn’t know anything about smart glasses, and that’s a major problem.

Some smart glasses wearers are exploiting the ignorance by harassing strangers and filming their reactions. Many of their victims are homeless people, service workers and women.

These glasses aren’t a niche product, either. Meta sold 7 million pairs of smart glasses in 2025. For a relatively low price (they start at $300), “manfluencers” and other content creators can buy a pair of Meta Ray-Bans and use them to record unwitting subjects.

Smart glasses can be used to survey people participating in protests or secretly record people in restrooms and other public places. The privacy problem will only get worse if companies add facial recognition features to their smart glasses — and Meta is reportedly planning to do just that.

It may not always be possible to stop someone from filming you in public without your consent. But you can make it harder for this new generation of “glassholes” to film you in secret. The first step is knowing how to identify the technology.

What do smart glasses look like?

A pair of eyeglasses with a heavy black frame, sitting on a translucent pedestal
Snap’s Specs on display at Augmented World Expo 2026 in Long Beach, California. Scott Stein/CNET

Not all smart glasses look alike, and not all models have cameras. The Even Realities G2 glasses contain only microphones and screens, while plug-in display glasses like Xreal‘s and TCL‘s connect to other devices and function as wearable monitors. The Viture Beast contains a camera, but it’s meant for limited augmented reality experiences.

Google’s Intelligent Eyewear is coming later this year, as are the $2,200 Snap Specs. Apple is rumoured to be debuting a pair of smart glasses next year. For now, the vast majority of camera glasses currently available are produced by Meta.

The easiest way to identify a pair is by locating the indicator light — a small LED bulb that turns on when the wearer is taking a picture or video.

According to CNET editor and wearable tech expert Scott Stein, “Each pair of smart glasses has its own type of indicator. And many smart glasses do different things. We don’t have a clear mental map of what to look for. That’s a big part of the problem.”

CNET's Scott Stein smiling while wearing Ray-Ban Meta Gen 2 glasses.
CNET’s Scott Stein sporting the second-gen Meta Ray-Bans. Relative to the wearer, the camera is in the upper left corner of the frames, while the indicator LED is in the upper right. Joanna Desmond-Stein/CNET

Meta Ray-Bans have been around since 2021. (They launched under the name Ray-Ban Stories.) A slimmer second-generation model was introduced in 2023.

The latest iteration includes a small screen built into one of the lenses, though from most angles, this feature is only visible to the wearer.

All Meta Ray-Ban models have relatively thick plastic frames with a camera lens in the upper left corner (or the upper right if you’re facing the wearer). On the opposite corner is the LED light, which automatically turns on when the wearer is filming. It lights up when a photo is taken and pulses during video recording.

To take a photo or record a video, the user presses the capture button on the right arm of the glasses (near the LED light). The user can also use voice commands: “Hey Meta, take a photo” or “Hey Meta, take a video.”

Meta also produces glasses in partnership with Oakley. The HSTN model looks like a rounded version of the Ray-Ban frames, with the camera and LED in the same location. But the Vanguard model looks more like wraparound goggles than glasses, and its camera and LED are found in the centre of the nose bridge.

A woman in a bright pink jacket stands outside wearing the Oakley Meta Vanguard AI sunglasses.
CNET’s Vanessa Hand Orellana wearing the Oakley Meta Vanguard glasses. The camera sits above her nose, and the LED light is just above the camera.  Vanessa Hand Orellana/CNET

In addition to the indicator LED, you might get an audio cue: a shutter snap sound when a picture is taken. However, both of these cues are relatively subtle.

Even if you’re aware of smart glasses indicators, you might not know for sure if you’re being filmed. Outside in direct sunlight, it’s virtually impossible to detect when the recording light is on.

Feature image credit: Bloomberg/Getty Images

By Jason Chun

Jason Chun is a CNET writer covering a range of topics in tech, home, wellness, finance and streaming services. He is passionate about language and technology, and has been an avid writer/reader of science fiction for most of his life. He holds a BA from UC Santa Barbara and an MFA from The New School. 

Sourced from CNET

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Zero Coding Skills Needed to Build Powerful AI Workflows : Complete Guide 2026

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Claude Code offers a unique way for non-coders to automate tasks and manage workflows without needing programming expertise. Simon Scrapes explains how this system goes beyond simple chat interactions by acting as an execution layer for complex processes. One standout feature is the use of a `claude.md` file, which allows users to define rules, preferences and contextual details to improve accuracy and consistency. For example, when automating overview generation, specifying date ranges, formatting and data sources in the file ensures reliable outputs. This structured approach makes Claude Code accessible and effective for both personal and professional tasks.

In this explainer, you’ll gain insight into practical applications of Claude Code, from creating reusable “skill systems” to integrating external platforms using the Multi-Connection Protocol (MCP). Discover how features like Auto Mode and advanced commands such as `/goal` and `/loop` streamline repetitive processes while maintaining user control. Additionally, learn strategies for managing memory effectively and addressing limitations like context degradation. Whether you’re looking to automate simple tasks or design scalable workflows, this guide provides actionable steps to help you make the most of Claude Code.

Features of Claude Code

TL;DR Key Takeaways :

  • Claude Code is a user-friendly automation tool that enables non-technical users to streamline workflows, integrate tools and execute commands efficiently through a terminal or desktop app.
  • Its functionality relies on precise prompts and a customizable `claude.md` file, which acts as a blueprint for consistent and accurate task execution.
  • Key features include “skills” and “skill systems” for modular task automation, Multi-Connection Protocol (MCP) for seamless tool integration and advanced commands like /effort and /goal for handling complex workflows.
  • Automation tools such as /loop and “hooks” reduce manual effort, while memory management practices help maintain performance and prevent context degradation.
  • To maximize efficiency, users should adopt a scalable mindset, focus on reusable workflows and use external tools to address limitations like memory recall and context accuracy.

Claude Code simplifies automation and tool integration, allowing you to perform tasks such as creating files, managing spreadsheets and connecting to CRMs. Unlike traditional chatbots, it operates through a terminal or a user-friendly desktop app, offering a robust platform for executing commands. Its ability to integrate with external tools and execute actions directly from a chat-like interface distinguishes it from other automation tools.

By using its intuitive design, you can streamline workflows and reduce manual effort. For example, you can automate repetitive tasks like data entry or overview generation, saving time and minimizing errors. This makes Claude Code a practical solution for both personal and professional use.

How Prompts and Context Work

The effectiveness of Claude Code relies heavily on crafting precise and detailed prompts. Context plays a crucial role in making sure accurate outputs and the tool allows you to define rules, preferences and business-specific information in a `claude.md` file. This file acts as a blueprint, making sure consistent performance and reducing the likelihood of errors.

For instance, if you’re automating a overview generation process, including specific parameters such as date ranges, formatting preferences and data sources in your prompt will yield more accurate results. By maintaining a well-organized `claude.md` file, you can enhance the tool’s reliability and efficiency.

 

Advance your skills in Claude Code by reading more of our detailed content.

Permissions and Automation Control

Claude Code prioritizes user control and safety by requiring approval before executing actions. This default setting ensures that you remain in charge of the automation process. For repetitive tasks, you can enable Auto Mode, which minimizes the need for constant approvals while still flagging potentially risky actions.

This balance between automation and oversight makes Claude Code suitable for a wide range of workflows, from simple task automation to complex, multi-step processes. The ability to toggle between manual and automated modes allows you to adapt the tool to your specific needs, making sure both efficiency and security.

Understanding Skills and Skill Systems

Claude Code introduces the concept of “skills,” which are pre-written instructions designed to perform specific tasks. These skills can be combined into “skill systems,” allowing you to chain multiple skills together to create end-to-end automated workflows.

For example, you can design a skill system that extracts data from emails, updates a CRM and generates a summary overview, all in one seamless process. This modular approach enables you to build scalable and reusable workflows, making it easier to manage complex tasks.

Tool Integration with Multi-Connection Protocol (MCP)

The Multi-Connection Protocol (MCP) is a standout feature of Claude Code, allowing seamless integration with external platforms such as Google Drive, Notion and CRMs. These connections remain active during sessions, allowing for real-time data exchange and streamlined operations.

However, it’s important to monitor memory usage when working with multiple integrations, as active connections can impact performance. By managing these integrations effectively, you can maximize the tool’s capabilities without compromising efficiency.

Managing Memory Effectively

Claude Code uses auto memory to store user preferences and project details, enhancing usability and personalization. However, managing large data sets can be challenging. To optimize memory recall and ensure smooth operations:

  • Keep your `claude.md` file concise and focused on essential details.
  • Use external memory tools for storing extensive information.

These practices help reduce the risk of context degradation, often referred to as “context rot,” and ensure that the tool performs consistently across different workflows.

Advanced Functionalities

Claude Code offers advanced commands and features designed to handle complex tasks with precision:

  • /effort: Adjusts reasoning levels to tackle intricate workflows effectively.
  • Ultra Code: Breaks tasks into sub-agents, each responsible for specific aspects of a process. Sub-agents operate independently, improving task accuracy and preventing context pollution.

These advanced functionalities make Claude Code a robust solution for dynamic and multi-layered workflows, allowing you to address complex challenges with ease.

Automation Features

Several automation tools enhance the efficiency of Claude Code, allowing you to focus on higher-value activities:

  • /goal: Ensures tasks meet predefined completion criteria, improving accuracy and consistency.
  • /loop: Automates recurring tasks on a schedule, reducing manual intervention.
  • Hooks: Scripts designed for repetitive tasks, minimizing reliance on AI tokens and improving efficiency.

These features simplify repetitive processes, freeing up your time for more strategic tasks.

Tips for Maximizing Efficiency

To make the most of Claude Code, consider these practical tips:

  • Use screenshots for visual problem-solving when text descriptions are insufficient.
  • Avoid correcting broken outputs; instead, restart tasks with clearer instructions to achieve better results.
  • Keep setups portable to avoid vendor lock-in and maintain flexibility in your workflows.

By following these strategies, you can enhance the tool’s effectiveness and adaptability, making sure consistent performance across various use cases.

Addressing Limitations

While Claude Code is a powerful tool, it does have limitations. Memory recall and context degradation can pose challenges, particularly for extensive projects. To mitigate these issues:

  • Use semantic recall to improve memory functionality and maintain context accuracy.
  • Incorporate open source tools to enhance long-term memory reliability and scalability.

These improvements can make Claude Code more dependable, especially when managing complex or long-term workflows.

Adopting a Scalable Mindset

Using Claude Code effectively requires a shift in mindset. Treat the tool as a modular system, focusing on creating reusable configurations and workflows. Instead of correcting errors, restart tasks with improved setups to ensure consistent results. This approach enhances scalability and allows you to adapt to growing workflow complexities with ease.

By adopting this mindset, you can maximize the potential of Claude Code, transforming it into a reliable and versatile tool for automation and task execution.

Media Credit: Simon Scrapes

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