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Scoring My 2025 Predictions via @sejournal, @Kevin_Indig

Boost your skills with Growth Memo’s weekly expert insights. Subscribe for free!Every year, I hold myself accountable for my previous predictions by scoring them.
This year, I got three misses, two mixed results, and five hits:
1. Agentic LLM Models Reach +100 Million Users
Score: Miss
Thought Process: When I made this prediction, I assumed that once models improved at reasoning, usage would shift from chat to action, and agents would become the obvious next step.
Reality: While general LLM usage (like Gemini and ChatGPT) cleared +800 million weekly users, true autonomous agent adoption, where the AI performs complex actions like “buying a product” without oversight, remained a niche power-user feature with very wonky performance.

Google’s “Project Mariner” and OpenAI’s agent features only entered broad public beta in mid-2025.
Most consumers still use AI for information (chat) rather than action (agents).

I over-weighted the speed of productization and user trust, and under-weighted how slow people are to let software spend their money or act without supervision.
2. More AI Victims
Score: Hit
Thought Process: Here, I zoomed out from early signals like Chegg and Stack Overflow and treated them as the first visible cracks in a broader margin collapse. My bet was that whenever AI sits between buyers and a labor-intensive industry, the middle layer will feel the pain first.
Reality: By Q3 2025, major call center outsourcing firms faced a crisis as enterprise clients switched to “AI Voice First” support layers. Translation services continued to shrink as browser-based, real-time AI translation became native to OS updates.

In RWS Holdings’ (translation services) 2025 half-year report, Adjusted EBITDA plummeted 41%, and profit before tax fell nearly 60%.
Chegg continues to fall apart.
In September 2025, Concentrix shares dropped ~9% in a single day after missing earnings expectations and cutting its full-year guidance. Enterprise clients aggressively switched to “AI Voice First” layers. Instead of hiring 100 agents for a support queue, a client might hire 10 agents for complex issues and use an AI voice agent for the rest. This destroyed the traditional “per-seat” billing model that BPOs rely on.

3. AI Automation Becomes The Default For Marketing Teams
Score: Hit
Thought Process: This call came from watching clients quietly stitch together AirOps, Make, Zapier, and custom scripts while headcount stayed flat or shrank. I expected economic pressure plus better tooling to push marketing toward “systems thinking,” where workflows matter more than channels.
Reality: “System building” became the primary skill on marketing job descriptions in 2025.

Recruitment data from Ashdown Group (2025 Marketing Job Market Report) showed that roles involving campaign automation and AI tool integration commanded a 7-9% salary premium over generalist marketing roles.
A 2025 HubSpot State of Marketing report found that 78% of B2B organizations had shifted to relying on marketing automation as their primary infrastructure.

With marketing budgets remaining tight, the reliance on “Team of One” structures powered by automation chains (Make, Zapier, custom AI workflows) became the industry standard.
4. AI Overviews Evolve
Score: Hit
Thought Process: I read AI Overviews as an experiment, not a finished product, and assumed Google would iterate toward more personalized, richer SERP formats once multimodal models matured. The underlying belief was that Google had to change the page itself to defend its moat against standalone LLMs.
Reality: Google tested its Web Guide SERP layout extensively as of November. For me (opted into SGE, Search Generative Experience), it’s still the default. Instead of a standard list of blue links or a single AI answer at the top, “Web Guide” breaks the entire search result page into AI-generated “buckets” or headlines.

In June 2025, Google began embedding YouTube Shorts and timestamped video clips directly into AI Overviews.
In December, Google started integrating AI Mode deeper into AI Overviews.

5. Reddit Becomes Part Of The Default Channel Mix
Score: Hit
Thought Process: I assumed that once Reddit showed up for everything from product searches to troubleshooting, marketers would have no choice but to treat it like a core performance channel, not a side project. When you compare ad revenue from Meta and Alphabet platforms with how visible they are in Search, Reddit’s upside becomes clear.
Reality: Reddit had a banner year in 2025. Ad revenue grew 61% YoY Q1 2025 – and then another +68% in Q3 (to $585M). With Google Search continuing to prioritize forum discussions, Reddit became an unavoidable placement for advertisers seeking high-intent traffic.

Daily Active Users (DAUs): Reached 108.1 million in Q1 and climbed to 116 million by Q3 2025.
Reddit is the second largest site on Google by visibility (only Wikipedia is larger).
Reddit finally launched true ecommerce catalog ads (Dynamic Product Ads → DPA). Early beta tests in Q1 2025 showed these ads delivered a 2x higher return on ad spend (ROAS) compared to previous formats, making Reddit viable for “performance” marketers, not just “brand awareness” teams.
Of course, Reddit remains the most cited platform for most LLMs.

6. More Sites Cloak For LLMs
Score: Miss
Thought Process: I expected especially B2B sites to move tactically and fast by feeding bots a cleaner, more structured version of their sites once it became clear LLMs rewarded that pattern. Underneath sat the assumption that people would quietly bend the rules if there was upside and no obvious penalty.
Reality: The “Bot-Only Web” did not emerge via cloaking; it emerged via APIs and paywalls. Instead of creating optimized versions for bots (cloaking), most major publishers aggressively blocked bots via robots.txt and lawsuits (e.g., The New York Times vs. OpenAI continuing saga).
7. The Current Google Shopping Tab Will Become The Default
Score: Miss
Thought Process: I treated the Shopping tab as Google’s sandbox for a future Amazon competitor, similar to how past tab experiments leaked into the main SERP. The core belief was that Google would push harder on shoppable, personalized results in the face of AI pressure and ecommerce growth needs.
Reality: Google kept the main search tab distinct. While the Shopping experience became more personalized and AI-driven (often resembling a feed), Google did not replace the default search experience with the Shopping tab interface for commercial queries.
8. AI-Generated Audio And Video Hits Mass Adoption
Score: Hit
Thought Process: Here, I connected the dots between rapidly improving generative tools and the constant pressure on creators to ship more content with the same or less budget. I assumed that once tools like Sora, Veo, and ElevenLabs crossed a basic quality bar, they would seep into production pipelines even if audiences could still tell something was synthetic.
Reality: 2025 was the year of the “Synthetic Creator.” YouTube had to update its partner program policies in July 2025 specifically to manage the flood of AI-generated content. Despite the crackdown on “AI slop,” high-quality AI-generated B-roll and voiceovers became standard for millions of creators.

On July 15, 2025, YouTube officially updated its Partner Program (YPP) eligibility terms to include a specific clause against “Mass-Produced & Repetitious Synthetic Content.”
The policy explicitly demonetized channels that used “templated, programmatic generation” (slop) but protected creators who used AI tools for “production assistance” (B-roll, voiceovers, scripting) as long as there was “clear editorial oversight.”
87% of creators now use AI in their workflows.

9. Google And Apple Divorce
Score: Mixed
Thought Process: I read the DOJ case as a structural threat to Google’s distribution deals and assumed judges would eventually push on the default search arrangements. My framing was that even a partial unwind of exclusivity could shift how search power is negotiated, without instantly changing who “wins” search. Judge Mehta’s first conclusion sounded a lot like he would take a hard stance on remedies.
Reality: The DOJ remedy ruling in September 2025 was disappointing. A toothless tiger. The court prohibited Google from paying for default exclusivity on browsers (Chrome/Safari) and devices, but:

Google can still pay Apple to be the default, but the contract cannot say “Apple must not use anyone else.”
The judge did not enforce a “choice screen” like the European Union, which leaves the door open for Apple to voluntarily implement choice screens or offer alternatives (like ChatGPT or Perplexity) without losing Google’s payments entirely.
Also, Apple is licensing Gemini for Siri.

So, was it really a divorce or a forced transition to an open marriage?
10. Apple Or OpenAI Announces Smart Glasses
Score: Mixed
Thought Process: This prediction came from treating smart glasses as the logical next hardware surface for AI assistants, especially with Meta gaining traction. I assumed that OpenAI plus Jony Ive, or Apple’s need for a new device story, would pull a prototype into the public eye even if real adoption stayed years out.
Reality: On November 24, 2025, OpenAI CEO Sam Altman and designer Jony Ive officially confirmed that their joint hardware venture (under the startup “LoveFrom”) had a finished prototype during an interview hosted by Laurene Powell Jobs. The device was described as “screen-free” and “less intrusive than a phone,” aligning with the “smart glasses” or “AI Pin” form factor predictions.
However, it’s not yet proven that OpenAI will publish glasses. It might also be some sort of necklace device. Meanwhile, Apple did not announce a new product and is dealing with leadership issues instead. And then, just before I hit publish on this Memo, Google announced new smart glasses for 2026.
My Conclusion: This Is The Year “AI Deployment” Began
For those of us in tech and digital marketing, we’re going to remember 2025 as the year the AI-driven “pilot programs” ended and official “deployment” began.
Not only internally across our teams, workflows, and tech stacks, but we also watched classic search habits (informed by decades of human + search engine behavior) transform right in front of us.
We didn’t get the sci-fi future of agents buying our groceries (Pred No. 1) or widespread smart glasses (Pred No. 10) just yet.
Instead, we got something more pragmatically disruptive: A world where marketing teams are half the size but twice as technical, where BPO industries (business process outsourcing) are collapsing, and where “Googling it” increasingly means “Reading a Reddit thread summarized by an AI.”

Featured Image: Paulo Bobita/Search Engine Journal

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digital marketing

Addressing The B2B Trust Deficit: How To Win Buyers In 2026 via @sejournal, @alexanderkesler

We have entered a new buyer era, one defined not by hesitation, but by a fundamental trust deficit in vendor promises.Buyers are almost twice as likely to do business with vendors they trust; yet many have not established that trust before the crucial moment when shortlists are formed. 85% of buyers choose from their day one shortlist, with 90% having prior experience with at least one of the vendors they considered.
In short, if trust is not established early, you become invisible.
This shift demands a buyer-led approach that prioritizes enablement over lead generation and emphasizes consultative selling and outreach to demonstrate a genuine responsiveness to buyer needs.
In this article, I share a practical blueprint for embedding trust into your go-to-market (GTM) strategy using a layered trust framework as well as actionable tactics to build buyer confidence across every stage of the journey.
Buyer Behavior Has Shifted From Due Diligence To Instant Validation
What we recognize as traditional buyer behavior is centered on extended validation cycles and comprehensive reference checks. While still complex, buying journeys begin invisibly in the dark funnel, and are guided by AI to enable faster decisions.
B2B buyers spend nearly three-quarters of their buying journey researching anonymously before ever contacting a vendor, consuming up to 15 pieces of content before making a purchase decision, much of which resides outside an organization’s direct control.
This is due, in part, to buyers no longer tolerating generic, sales-led conversations. They seek experiences that address their specific challenges and provide personalized guidance through their research process.
The pressure intensifies when evaluating AI-driven solutions. Buyers must distinguish between genuine capability and marketing hype while navigating rapid technological evolution.
This may account for why 78% of buyers select products they had heard of before starting their research; for enterprise buyers, this rises to 86%. Brand awareness and preference carry a premium.
Recognition translates to consideration, consideration to evaluation, evaluation to selection.
Vendor Promises Face A Crisis Of Confidence
A significant trust gap has emerged between vendor promises and buyer confidence. Buyers express deep skepticism about return on investment (ROI) projections, business case assumptions, and sales engagement authenticity.
Only 45% of sellers claim they have fully mastered their client’s pain points and challenges. When salespeople lack confidence in their own value propositions, buyers notice.
This gap manifests in extended decision cycles and increased scrutiny of vendor claims. Buyers seek validation through multiple channels before committing to expensive, high-stakes purchases that affect their professional trajectory.
Where Buyers Place Their Trust
In North America, B2B business buyers rank competence (30%), dependability (19%), and consistency (17%), as the most important trust levers across industries, purchase contexts, and buyer roles.
Data on where buyers place their trust vary, yet all have one point of commonality; they do not include vendors as trusted sources of information:

59% trust consultants and subject matter experts.
68% trust referrals.
71% trust third-party opinions.
82% trust coworkers and internal management.

Vendors cannot control all these channels directly, but they can create strategies to influence their brand presence and reputation, and tailor how they appear in the invisible, AI-driven buying journey.
What This Means For B2B Marketers
Placement on the day one shortlist requires systematic signaling of credibility.
The opportunity lies in closing the trust gap early through content, clarity, and demonstrated value before buyers raise their hand or appear in your client relationship management (CRM) platform. This requires leaning into risk management and brand awareness strategies to establish presence in this invisible discovery process.
Organizations that enable discovery and build confidence outpace competitors who wait for inbound interest.
Building Trust Through Comprehensive Trust Architecture
Effective trust architecture addresses buyer needs across three essential layers:

Technical trust.
Peer trust.
Continuous value.

Technical Trust: Integration Compatibility And Compliance
Technical trust addresses fundamental questions about implementation feasibility, security standards, and operational compatibility.
Buyers need confidence that solutions integrate with existing systems without creating technical debt or security vulnerabilities.
Embed technical trust into your trust architecture by:

Deploying comprehensive documentation, implementation guides, and self-service tools that allow technical evaluators to assess compatibility independently.
Providing clear information about security certifications, compliance frameworks, and data governance.

Technical stakeholders prioritize clarity, accuracy, and proven results over promotional language.
Peer Trust: Validated Success From Similar Organizations
Peer trust emerges from evidence that similar organizations have achieved measurable outcomes using your solution.
Embed peer trust into your trust architecture by:

Facilitating access to case studies, benchmark data, and social proof that speaks to specific use cases and vertical nuances.
Aggregating data that demonstrates typical implementation timelines, adoption curves, and outcome ranges, providing buyers with realistic expectations.
Enabling direct conversations between prospects and existing clients when appropriate.

Peer validation carries more weight than vendor claims.
Continuous Value: Ongoing Innovation And Client Success Engagement
Continuous value demonstrates commitment beyond the initial sale.
Buyers evaluate whether vendors invest in product evolution, maintain responsive support structures, and enable ongoing optimization.
Embed continuous value into your trust architecture by:

Establishing proactive communication cadences that surface relevant product updates, industry insights, and optimization opportunities.
Demonstrating commitment through transparent product roadmaps, user communities, and accessible client success resources (e.g., success stories, implementation guides, templates).

Trust Enablers Across The Buying Journey
Your trust architecture requires consistent deployment of these enablers:

Show up before the search begins: Brand awareness campaigns, thought leadership content, and industry participation establish recognition before buyers enter active evaluation.
Deliver context-aware content that reflects specific use cases and vertical nuances: Generic positioning undermines credibility with buyers who need solutions tailored to their unique challenges.
Shift GTM strategy from generating leads to creating confidence: Prioritize buyer enablement over lead generation metrics. Success is measured by influence on buyer decisions, not form completions.
Create brand memory links that make your organization unforgettable before the first sales conversation: Distinctive points of view, valuable frameworks, and consistent presence build lasting recall.

How To Create A Systematic Trust Blueprint
A trust architecture defines the layers of buyer confidence.
A trust blueprint puts this into action, providing a scalable system to embed trust across the entire buying journey.
Together, they form a unified strategy: the architecture sets the vision, and the blueprint makes it real, enabling trust where it matters most.
Below is a structured approach to establishing credibility at scale:
1. Create A Unified Trust Document
A centralized trust summary consolidates critical information buyers need to evaluate your solution. This document should address:

Security architecture and compliance certifications: Provide clear explanations of data handling practices, encryption standards, and regulatory adherence. Include industry-specific compliance (e.g., SOC 2, ISO, GDPR).
Implementation framework and integration approach: Detail typical implementation timelines, resource requirements, and technical prerequisites. Address common integration scenarios with specificity.
Proof of outcomes with quantified results: Present aggregate performance data across your client base. Include distribution curves showing typical, strong, and exceptional results rather than highlighting only best-case scenarios.
Support structure and escalation paths: Explain how clients access assistance, typical response times, and how critical issues are prioritized and resolved.

Make this document easily accessible and ungated. When buyers can open, read, and share it freely, they circulate it across teams to build internal consensus. Every barrier to access slows that process and reduces momentum toward a deal.
2. Build An Enablement Resources Hub
Each individual member of a buying group evaluates solutions through their functional lens. Develop enablement resources tailored to common stakeholder roles:

For technical evaluators: Provide API documentation, integration specifications, security architecture diagrams, and performance benchmarks.
For financial stakeholders: Create Total Cost of Ownership (TCO) models, ROI frameworks, and payback period calculators grounded in realistic assumptions. Finance leaders scrutinize economic models.
For operational leaders: Demonstrate implementation approaches, change management frameworks, and adoption acceleration strategies.
For executive stakeholders: Synthesize strategic alignment, risk mitigation, and competitive positioning.

3. Design Consensus-Building Tools
Facilitate internal consensus rather than requiring target buying group champions to build it independently.

Provide comparison frameworks that help buying groups evaluate alternatives systematically. These frameworks should acknowledge strengths and limitations across solution categories, not just promote your offering.
Create decision criteria worksheets that guide stakeholders through solution requirements. When buyers use your frameworks to structure their evaluation, you shape the decision criteria.
Develop internal presentation templates that champions can customize for stakeholder conversations. Reduce the effort required to socialize solutions internally.

4. Provide Progressive Validation Mechanisms
Enable buyers to validate claims incrementally throughout the evaluation process.

Offer technical proof of concepts (POCs) with clear success criteria defined collaboratively. POCs that demonstrate specific capabilities under realistic conditions build confidence more effectively than broad demonstrations.
Provide access to existing client references who match the prospect’s profile. Facilitated peer conversations accelerate trust development.
Share transparent product roadmaps that acknowledge current limitations alongside planned enhancements. Honesty about product gaps builds trust more than overstating current capabilities.

5. Ensure Explainable AI And Decision Transparency
For AI-driven solutions, explainability is not optional. In the E.U., the AI Act already establishes requirements for explainability mechanisms that make decision criteria transparent, with implementation phases beginning in September 2026.

Document how AI models make decisions, what data they use, and how accuracy is validated. Provide transparency about training data principles, model limitations, and ongoing performance monitoring.
Build dedicated trust centers that consolidate information about AI systems, security practices, and compliance adherence. Make these resources accessible to all stakeholders without requiring sales engagement.

Organizations leading in the AI buying era recognize that trust is increasingly a transparent product feature, not just a sales promise.
Fast-Tracking Trust Across The Buying Journey
Embedding trust across your GTM strategy requires deliberate architectural decisions at each stage of the buying journey.
Dark Funnel Phase: Build Recognition
70% of the B2B buying journey happens in the dark funnel, long before brands are ever contacted or sales conversations begin. Deals are won or lost before providers know they even exist.
Visibility in hidden channels establishes initial awareness and shapes early perceptions. Below are ways to build recognition:

Deploy thought leadership content that educates buyers about category dynamics, evaluation criteria, and implementation considerations. Content that helps buyers think more clearly about their challenges builds credibility and recall.
Participate actively in industry communities, forums, and review sites where buyers conduct research. Third-party validation carries more weight than owned content.
Invest in SEO, GEO/AEO (Generative/Answer Engine Optimization), and content discoverability so buyers encounter your perspective during organic and AI-led research. Being present when buyers search for solutions to their challenges creates initial touchpoints.

Awareness Stage: Confirm Rather Than Convince
When buyers initiate contact at the awareness stage, they have typically completed the dark funnel phase of their research independently and are now seeking confirmation for their initial assumptions.
The goal at this stage is to reinforce, not sell. Buyers are looking for validation that their research aligns with reality and that your solution fits the conclusions they’ve already drawn.

Replace calls to action focused on convincing with approaches focused on confirming (e.g., “validate,” “confirm fit” over “schedule a demo,” “contact us”).
Provide additional detail, clarify specific questions, and connect buyers with descriptive resources (e.g., guides, roadmaps, FAQs) rather than launching into standard pitches.

Listen more than present. Understanding where buyers are in their thinking allows for targeted responses that address genuine questions rather than generic positioning.
Consideration Stage: Enable Comparative Evaluation
During consideration, buyers evaluate multiple vendors systematically. They need resources that facilitate comparison across options.

Provide objective comparison frameworks that help buyers assess alternatives across relevant criteria.
Acknowledge category tradeoffs honestly. Buyers appreciate transparency about where different solutions excel and where they face limitations.
Facilitate technical validation through POCs, technical deep dives, and architecture reviews.
Remove friction from the evaluation process rather than adding sales-imposed hurdles.

Decision Stage: Accelerate Consensus
At the decision stage, buyers must achieve internal consensus across diverse stakeholders. This is where deals most often stall.

Equip champions with resources they can use to build internal agreement. Provide stakeholder-specific materials, objection-handling frameworks, and implementation guides.
Offer to facilitate stakeholder conversations when helpful. Executive briefings, technical workshops, and finance discussions that address specific concerns accelerate decisions.
Address product risks proactively. Deployment risk and concerns about ROI and performance often stall decisions more than functional gaps.

Revenue And Beyond: Demonstrate Continuous Value
Trust does not end at contract signature. 80% of buyers are dissatisfied with the provider they choose at the end of the purchase process. Post-sale, client success-led experience determines renewal, expansion, and referenceability.

Establish clear success metrics collaboratively during onboarding. Define what success looks like and track progress against those metrics systematically (e.g., product usage rate, NPS score).
Provide proactive communication about product enhancements, industry developments, and optimization opportunities. Demonstrate ongoing investment in client success.
Create opportunities for clients to share experiences with prospects. Peer advocacy is the most powerful trust accelerator.

Key Takeaways

The risk-averse buyer did not disappear, but their trust has been eroded in an environment saturated with unsubstantiated or exaggerated claims.
Build instant credibility to power your growth engine. Vendors that establish trust systemically earn earlier engagement, faster sales cycles, and stronger margins.
Demonstrate competence through transparent frameworks, validate claims through peer proof, and maintain trust through continuous value delivery.
Brand recall, demonstrated proof, and organizational maturity have become the new sales pitch. Enablement outweighs lead generation when buyers control most of their journey before vendor contact.
Create repeatable trust frameworks that scale with speed and scrutiny. Make trust a GTM feature embedded across every buyer touchpoint, not a post-sale promise delivered inconsistently.

More Resources:

Featured Image: eamesBot/Shutterstock

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digital marketing

Negativity Bias: Why Customers Don’t Want Anything To Do With You (And What To Do About It) via @sejournal, @SequinsNsearch

Picture this: You’re sitting on a train to see a friend of yours you haven’t seen in a long time, sipping your favorite coffee order, and looking at a beautiful landscape outside the window. Everything is going great. Right up until someone sits right next to you, chatting loudly on the phone and ruining that peaceful journey of yours. Even though the train gets to its destination on time and without a hiccup, do you think you are most likely to mention the coffee, the landscape, and the quiet of the first part of the journey, or that annoying seatmate, when you friend asks how the journey’s been?If you chose the latter, it’s not because you are a particularly pessimistic person. It’s all very normal, part of a common phenomenon known as negativity bias.
What Is The Negativity Bias?
The negativity bias is defined as an overattention to the negative aspects of an experience as compared to positive ones that carry the same emotional load. It affects the way we process and remember information, but also the way we interpret the world around us and make decisions. In short, it makes us value and remember the “bad” much more than the “good.”
The origins of the negativity bias are still under debate, and different theories have been raised, but one thing seems clear: It’s so ingrained in our biological profile that it even shows up as a functional asymmetry in our brain. That means that certain regions involved in emotional processing (like the amygdala and the pregenual anterior cingulate cortex) tend to process negative stimuli faster, or respond to them in a stronger way, showing that a greater weight is assigned to averse stimuli and situations as compared to neutral and positive ones. This has been corroborated by electroencephalography (EEG) studies isolating larger late positive potential amplitudes, which are a measure of stimulus significance, for negative rather than positive stimuli.
These neurobiological markers translate in a negative overattention that can be seen at the behavioral level from a very early age, which tends to rule out the possibility of the bias as a learned behavior. According to evolutionary theories, the bias might be tied to an early and adaptive response to threat, which hardwired us to be wary of negative or ambiguous stimuli in order to safeguard our species’ survival.
The Negativity Bias In Marketing
Given the power of negativity in shaping the perception of the world and, most importantly, our impressions and judgements, it is only natural that our industry has learned to leverage this bias as a way to get more content traction online. Think about those TikTok videos that start with a deceptive hook along the lines of “Why I’ll never buy [brand]” to then list only positive aspects of the experience. Or the way clickbait headlines still work, despite the fact we know exactly what the media are doing.
Several marketing studies have shown that CTRs are higher across different channels (including SEO) when we use negative superlatives as compared to neutral or positive ones, something that has been confirmed in a large Nature study on the consumption of negative news.
So, it is a known fact that, from the first touchpoints until the very last, negativity is a way to capture and retain the most precious commodity of today’s age, attention. However, what a lot of brands fail to acknowledge is that it can be a double-edged sword as well.
Because if it is true that our curiosity is piqued when we see something negative, it is also true that we are very quick at abandoning the journey when we realize we’ve been tricked into a click that wasn’t worth our time. And once people drop a journey, they are not likely to give it a second chance, particularly if they’re not already invested in the brand.
This doesn’t only have to do when brands are not delivering on their early promises (such a discount claimed on a title that ends up only being available under certain caveats, or an outdated pricing), but also includes the later stages of the experience, too.
An annual study by Baymard analyzing reasons for cart abandonment (when users have already put energy and time into evaluating offers and deciding to convert) found that a large portion of these blockers have to do with UX issues such as no guest check-out, insufficient information, and too long processes, rather than a misalignment of expectations:
Screenshot by author, November 2025
And most times, these “bad portions” of the journey are the ones that tend to be remembered, rather than all the positives that users have encountered before the blockers. One bad experience can taint a website’s reputation in the prospects’ eyes, and represent a threat to the brand as a whole (see, for example, what happened with Coca-Cola and its AI ad recently).
How Can Brands Avoid Losing Customers To The Negativity Bias?
Even when a decision is made on the basis of rational arguments, it’s often the way someone feels about a product or brand that seals the deal. That’s the reason why you want to account for negative experiences (and how to fix them) in your customer acquisition and retention strategy.
Here are my top three tips to put in the agenda for a negativity-free 2026:
1. Removing Ambiguity
First of all, brands need to commit to transparency. The balance between negative and positive is skewed unfavorably when there is insufficient information.
Anytime someone needs to validate a brand’s legitimacy online, or the reliability of their processes and services, it’s an indicator of something that needs to be made clearer or more prominent earlier on in the journey. Isolating brand queries from internal analytics or social listening tools is a good starting point to really figure out what might be the ambiguity that becomes a blocker in the path from awareness to transaction.
2. Minimizing Unnecessary Frustrations
We have seen how the journey can be cut short even when the user is very motivated to complete an action, and how this can be tied to very specific negative experiences that outweigh all the positive aspects of an online journey. Sometimes, the mishaps we come across a website can be the equivalent of that annoying seat mate in our journey from intention to action. It can even drive us to change carriage.
So, in order to prevent dropouts, we don’t only need to fix the reported issues – we need to proactively remove the barriers our users have yet to encounter: cognitive load that produces decision paralysis, distractors that affect purchase intention, intrusive pop-ups that block a natural navigation, and much more.
Ultimately, your job has to help make the journey as smooth as possible and provide the path of least resistance to the action your users want to take.
If you’re looking for ways to get started on this, you can start by isolating behavioral data and potential friction points via surveys, CX logs, heatmapping tools, and ngram analysis from platforms that collect first-hand experiences belonging to both the awareness and the post-purchase stages.
3. Turning Flaws Into Ways To Connect With Customers
You know what’s a perfect example of this? 404 pages.
No one cares about them, especially when they’re a fraction of the millions of URLs a user can land on, but for some, they will be their first impression of a business. This is a particularly likely scenario when we know that AI assistants make up URLs and send users to broken pages more often than it would occur with a traditional search engine.
While we know that first impressions tend to last, particularly if they’re negative, the very last stages are equally important and should be given just as much attention.
If a user lands on a 404 page after evaluating all the offers that are relevant to them, that one annoyance has the potential to be pervasive of the entire experience, affecting the perception of the brand or service as a whole.
But here’s the thing: If you take that opportunity to turn that one frustration into a chance for connecting with your user, you might still come out on the winning end of that interaction. Negative is memorable because it makes us feel a certain way  – so we need to find ways to produce another emotion that can compete with it.
You can do so by acknowledging users’ frustration in a way that makes them smile, and providing them with an alternative path to reach the same goal, like on this page by Tripadvisor:
Screenshot of Tripadvisor, November 2025
Or switching it up completely, and turning the experience into a positive one by leveraging surprise, delight, excitement.

Chrome Dino Game. Source: Shutterstock (Image from author, November 2025)
It might seem almost too simple, but we need to remember that humans are much less complicated than we make them out to be. Deep down, most people just want to be understood and have reason to trust whoever they are placing their bets and time on – face to face, but mostly online.
Don’t make things harder for them, make them feel good, and most of all, do not trick them, as it will most likely backfire.
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Featured Image: Vitalii Vodolazskyi/Shutterstock

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Generative AI

AI Overviews Changed Everything: How To Choose Link Building Services For 2026 via @sejournal, @EditorialLink

This post was sponsored by Editorial.Link. The opinions expressed in this article are the sponsor’s own.“How do you find link-building services? You don’t, they find you,” goes the industry joke. It’s enough to think about backlinks and dozens of pitches that hit your inbox.
However, most of them offer spammy links with little long-term value. Link farms, PBNs, the lot.
This type of saturated market makes it hard to find a reputable link building agency that can navigate the current AI-influenced search landscape.
That’s why we’ve put together this guide.
In This Guide1. Understand How AI-Driven Search Changes Link Building2. Verify Their Expertise and AI-Search Readiness3. Scrutinize Their Track Record Via Reviews, Case Studies & Link Samples4. Evaluate Their Process, Pricing & Guarantees5. Choosing A Link Building Partner For The AI Search Era
We’ll share a set of steps that will help you vet link providers so you can find a reliable partner that will set you up for success in organic and AI search.
1. Understand How AI-Driven Search Changes Link Building
Before you can vet an agency, you must understand how the “AI-influenced” landscape is different. Many agencies are still stuck in the old playbook, which includes chasing guest posts, Domain Rating (DR), and raw link volume.
Traditional Backlinks Remain Fundamental
A recent Ahrefs study found that 76.10% of pages cited in AI Overviews also rank in Google’s top 10 results, and 73% of participants in Editorial.Link survey believes they affect visibility in AI search.
However, the signals of authority are evolving:

When vetting a service for AI-driven search, your criteria must shift from “How many links can you get?” to “Can you build discoverable authority that earns citations?”
This means looking for agencies that build your niche authority through tactics like original data studies, digital PR, and expert quotes, not just paid posts.
2. Verify Their Expertise and AI-Search Readiness
The first test is simple: do they practice what they preach?
Check Their Own AI & Search Visibility
Check the agency’s rankings in organic and AI search for major keywords in their sector.
Let’s say you want to vet Editorial.Link. If you search for “best link building services,” you will find it is one of the link providers listed in the AI Overviews.
Screenshot of Google’s AI Overviews, November 2025

It doesn’t mean an agency isn’t worth your time just because it doesn’t rank high, as some services thrive on referrals and don’t focus on their own SEO.
However, if they do rank, that’s a major green flag. SEO is a highly competitive niche; ranking their own website demonstrates the expertise to deliver similar results for you.
Ensure Their Tactics Build Citation-Worthy Authority
A modern agency’s strategy should focus on earning citations.
Ask them these questions to see whether they’ve adapted:

Do they talk about AI visibility, citation tracking, or brand mentions?
Do they build links through original data studies, digital PR, and expert quotes?
Can they show examples of clients featured in AI Overviews, Chat GPT, or Perplexity answers?
Can they help you get a link from top listicles in your niche? Ahrefs’ data shows “Best X” list posts dominated the field. They made up 43,8% of all pages referenced in the responses, and the gap between them and every other format looked huge. You can find relevant listicles in your niche using free services, like listicle.com.

Screenshot of Listicle, November 2025

3. Scrutinize Their Track Record Via Reviews, Case Studies & Link Samples
Past performance is a strong indicator of future results.
Analyze Third-Party Reviews
Reviews on independent platforms like Clutch, Trustpilot, or G2 reveal genuine clients’ sentiment better than hand-picked testimonials on a website.
When studying reviews, look for:

Mentions of real campaigns or outcomes.
Verified client names or company profiles.
Recent activity, such as new reviews, shows a steady flow of new business.
The total number of reviews (the more, the more representative).
Patterns in negative reviews and how the agency responds to them.

Screenshot of Editorial.Link’s profile on Clutch, November 2025

Dig Into Their Case Studies
Case studies and customer stories offer proof of concept and provide insights into their processes, strategies, and industry fit.
While case studies with named clients are ideal, some top-tier agencies are bound by client NDAs for competitive reasons. Be wary if all their examples are anonymous and vague, but don’t dismiss a vendor just for protecting client confidentiality.
If the clients’ names are provided, don’t take any figures at face value.
Use an SEO tool to examine their link profiles. If you know the campaign’s timeframe, zero in on that period to see how many links they acquired, their quality, and their relevance.

Screenshot of Thrive Internet Marketing, November 2025

Audit Their Link Quality
Inspecting link quality is the ultimate litmus test.
An agency’s theoretical strategy doesn’t matter if its final product is spam. Ask for 3 – 5 examples of links they have built for recent clients.
Once you have the samples, don’t just look at the linking site’s DR. Audit them with this checklist:

Editorial relevance: Is the linking page topically relevant to the target page?
Site authority & traffic: Does the linking website have real, organic traffic?
Placement & context: Is the link placed editorially within the body of an article?
AI-citation worthiness: Is this an authoritative site Google AI Overview, ChatGPT, or Perplexity would cite (e.g., a reputable industry publication or a data-driven report)?

4. Evaluate Their Process, Pricing & Guarantees
A reliable link-building service is fully transparent about its process and what you’re paying for.
Look For A Transparent Process
Can you see what you’re paying for? A reliable service will outline its process or share a list of potential prospects before starting outreach.
Ask them for a sample report. Does it include anchor texts, website GEO, URLs, target pages, and publication dates? A vague “built 20 links” report doesn’t cut it.
Finally, check if they offer consulting services.
For example, can they help you choose target pages that will benefit from a link boost most?
Or are they just a link-placing service, as this signals a lack of expertise?
Analyze Their Pricing Model
Price is a direct indicator of quality.
When someone offers links for $100 – $200 a pop, they are typically from PBNs or bulk guest posts, and frequently disappear within months.
Valuable backlinks from trusted sites cost significantly more on average, $508.95, according to the Editorial.Link report.
Prospecting, outreach, content creation, and communication require substantial time and effort.
Reputable agencies work on one of two models:

Retainer model: A fixed monthly fee for a consistent flow of links.
Custom outreach: Tailored campaigns with flexible volume and pricing.

Scrutinize Their “Guarantees” For Red Flags
This is where unrealistic promises expose low-quality vendors.
A reputable digital PR agency, for example, won’t guarantee the number of earned links. The final result depends on how well a story resonates with journalists.
The same applies to “guaranteed DR or DA.” These metrics don’t directly affect rankings, and it’s impossible to guarantee which websites will pick up a story.
Choosing A Link Building Partner For The AI Search Era
Not all link-building services have the necessary expertise to help you build visibility in the age of AI search.
When choosing your link-building partner, look for a proven track record, transparency, and adaptability.
A service with a strong search presence, demonstrable results, and a focus on AI visibility is a safer bet than one making unsubstantiated claims.

See Real Examples Of Link Building Best Practices

Image Credits
Featured Image: Image by Editorial.Link. Used & modified with permission.
In-Post Images: Image by Editorial.Link. Used with permission.

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Generative AI

Google Hit By EU Probe Into Unfair Use Of Online Content via @sejournal, @martinibuster

The European Commission has launched an antitrust inquiry into Google to determine whether the company has violated EU competition rules, partly focusing on whether Google has used creator and publisher content in ways that leave publishers unable to refuse such use without risking their search traffic. It is also looking into whether Google is granting itself privileged access to YouTube content for AI in a way that leaves competitors at a disadvantage.How Google’s Terms May Pressure Publishers and Creators
The Commission is focusing on publisher content is used by AI Overviews and AI Mode to generate answers but without a way to compensate the publishers or for them to opt out of having their content used to generate summaries.
They write:
“The Commission will investigate to what extent the generation of AI Overviews and AI Mode by Google is based on web publishers’ content without appropriate compensation for that, and without the possibility for publishers to refuse without losing access to Google Search. Indeed, many publishers depend on Google Search for user traffic, and they do not want to risk losing access to it.”
This raises concerns that Google may be using publisher content in its AI products without offering a workable opt-out, leaving publishers who rely on Search traffic with little choice but to accept this use.
Use of YouTube Content to Train Google’s AI Models
The Commission is also examining Google’s use of YouTube videos and other creator content for training its generative AI models. According to the announcement, creators “have an obligation to grant Google permission to use their data for different purposes, including for training generative AI models,” and cannot upload content while withholding that permission. Google provides no payment for this use while blocking rival AI developers from training on YouTube content under YouTube’s policies.
This mix of mandatory access for Google, limits on competitors, and no payment for creators underpins the Commission’s concern that Google may be giving itself preferred access to YouTube content in a way that may harm the wider AI market.
The Commission has notified Google that it has opened an investigation into whether they have breached EU competition rules prohibiting the abuse of a dominant position.
Featured Image by Shutterstock/Mo Arbid

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SEO

Long-Tail SEO in an AI World

In 2006, Wired magazine editor Chris Anderson famously described the availability of niche products online as the “long tail.” Search optimizers adopted the term, calling queries of three words or more “long-tail keywords.”
Optimizing for long-tail searches has multiple benefits. Consumers searching on extended keywords tend to know what they want, and longer queries typically have less keyword competition. Yet the biggest benefit could now be AI visibility: Generative AI platforms such as ChatGPT fan out using multiword queries to answer user prompts.
Long-Tail Queries
A seed term plus modifiers
Any long-tail query consists of a seed term and one or more modifiers. For example, “shoes” is a seed term, and potential modifiers are:

“for women,”
“red,”
“near me,”
“on-sale.”

Combining the seed term and modifiers — “red shoes for women,” “on sale near me” — yields narrow queries that describe searchers’ needs, such as gender, color, location, and price.
Modifiers reflect the searcher’s intent and stage in a buying journey, from exploration to purchase. Thus, keyword research is the process of extending a core term with modifiers to optimize a site for buying journeys.
The more modifiers, the more specific the intent and, typically, the lesser the volume and clicks. Conversely, more modifiers improve the likelihood of conversions, provided the content of the landing page follows closely from that phrase. A query of “red shoes for women” should link to a page with women wearing red shoes.
Types of modifiers
A core term can have many modifiers, such as:

Location,
Description (“red”),
Price (typically from searchers eager to buy),
Brand,
Age and gender,
Questions (“how to clean shoes”).

Long-Tail Opportunities
Keyword research tools
Grouping keywords by modifier type can reveal your audience’s search patterns. Keyword research tools such as Semrush and others can filter lists by modifiers to reveal the most popular.
Semrush’s Keyword Magic Tool reveals the most popular modifiers for “shoes.”
Adjust Semrush’s “Advanced filters” to see queries that contain more words.
“Advanced filters” reveal queries that contain more words.
Search Console
Regular expressions (regex) in Search Console can identify longer queries, such as fan-out searches from ChatGPT and other genAI platforms. In Search Console, go to “Performance,” click “Add filter,” choose “Query,” and “Custom (regex).”
Then type:
([^” “]*s){10,}?
This regex filters queries to those with more than 10 words. Change “10” to “5” or “25” to find queries longer than 5 or 25 words, respectively.
Regex in Search Console can identify longer queries, such as fan-out searches from ChatGPT and other genAI platforms.
Keyword Dos and Don’ts
Search engines no longer match queries to exact word strings on web pages, focusing instead on the searcher’s intent or meaning. Hence a query for “red shoes for women” could produce an organic listing for “maroon slippers for busy moms.”
Keyword optimization circa 2025 reflects this evolution.

Avoid stuffing a page with keywords. Instead, enrich content with synonyms and related phrases.

Don’t create a page with variations of a single keyword. Group pages by modifiers and optimize for the entire group.

Include the main keyword in the page title and the H1 heading. Google could use either of those to create the all-important search snippet.

Assign products to only one category. Don’t confuse Google (and genAI platforms) by creating multiple categories for the same item to target different keywords.

Search Google (and genAI platforms) for your target query and study the results. Are there other opportunities, such as images and videos?

Don’t force an exact match keyword if it’s awkward or grammatically incorrect. Ask yourself, “How would I search for this item?” In other words, write for people, not search engines.

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News

Google Confirms Smaller Core Updates Happen Continuously via @sejournal, @MattGSouthern

Google updated its core updates documentation to say smaller core updates happen on an ongoing basis, so sites can improve without waiting for named updates.

Google explicitly confirms it makes “smaller core updates” beyond the named updates announced several times per year.

Sites that improve their content can see ranking gains without waiting for the next major core update to roll out.

The documentation change addresses whether recovery between named updates is possible.

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