Tag: AI

Exploring the Agentic Web: Are We Prepared?

The rapid emergence of the agentic web has left many of us pondering: Are we genuinely ready for this new frontier?

To get to the bottom of this, let’s start by addressing some foundational questions:

What’s the agentic web? How can it be utilized? What benefits and drawbacks does it present?

This piece is not aimed at pressuring AI skeptics to dismiss their valid queries regarding the agentic web.

Additionally, it doesn’t pass judgment on how you, as an individual or professional, engage with this digital landscape.

With diverse opinions swirling around the agentic web, I hope to offer some clarity, devoid of any marketing varnish.

Disclosure: While I am employed by Microsoft and have faith in their direction with the agentic web, my aim is to maintain a platform-neutral perspective.

Now let’s delve deeper into what exactly the agentic web entails.

The agentic web consists of advanced tools or agents, tailored to our preferences, that perform time-consuming tasks with our permission.

For instance, using one-click checkout allows me to transmit my payment details to a merchant seamlessly.

Neither the merchant nor I need to manage the minutiae; instead, I just consent to the transaction.

Curious about how AI defines the agentic web, I posed this question to four AI models, discovering intriguing variations in their answers.

Copilot describes it as a layer of the internet where AI agents turn human intentions into outcomes, keeping user choice intact. Gemini, Perplexity, and Claude offer similar but varyingly nuanced definitions.

Understanding these varying views helps underscore the fact that AI models are trained on differing data, resulting in diverse responses.

The clear sentiment divide arises from whether we view the agentic web as a user-friendly layer or an overwhelming digital entity.

Gemini mentions APIs, crucial for communicating within this space, emphasizing how saved preferences will increasingly play a role.

To truly grasp the agentic web, we must explore two protocols, ACP and UCP, that underpin its operations.

Dig deeper: AI agents in SEO: What you need to know

The Agentic Commerce Protocol (ACP) focuses on actions initiated by express user intent, streamlining transactions via standardized AI interactions.

Meanwhile, the Universal Commerce Protocol (UCP) encompasses the whole shopping experience, facilitating interactions across platforms and payment systems.

ACP and UCP are not competitors; rather, they enhance different stages of the user journey, supporting precise or exploratory shopping needs.

So, what is the agentic web? Truthfully, it’s still evolving alongside user behavior, placing us in a position to shape its destiny.

Next, let’s explore how we can harness the agentic web, along with its potential benefits and pitfalls.

Dig deeper: The Great Decoupling of search and the birth of the agentic web

Based on the unified theme of autonomous actions in its definitions, here are practical applications of the agentic web.

Consider delving into Elmer Boutin’s technical exploration of how schema will affect agentic web compatibility. Benjamin Wenner offers insights into PPC management in a full agentic ecosystem.

Let’s now focus on some consumer-centric applications, presented through tasks you’re already familiar with.

Five consumer applications of the agentic web are currently operational or in development.

1. Intent-driven Commerce

For example, stating “Find me the best running shoes under $150” allows an agent to handle the entire commerce process, optimizing around user intent.

By processing user intent, these agents provide a streamlined shopping experience, balancing guidance and user control.

Consumers enjoy reduced decision fatigue, while brands benefit from enhanced engagement and more direct consumer interactions.

2. Brand-owned AI Assistants

Brands can deploy their own AI agents, maintaining control over their customer interactions and providing consistently reliable support.

By utilizing first-party data, these assistants deliver faster responses while upholding the brand’s voice and accountability.

They enable global participation without sacrificing brand identity to larger platforms.

3. Autonomous Task Completion

Users can assign outcomes like “Prepare a weekly performance summary,” with agents autonomously executing the necessary tasks.

As agents mature, they evolve from task managers to independent analysts, optimizing results based on initial input.

This shift enables professionals to focus on strategic insights rather than logistics.

4. Agent-to-Agent Coordination

Agents can negotiate and coordinate with each other, streamlining processes like procurement or media buying.

This could revolutionize consumer and professional interactions, making them quicker and more efficient.

5. Continuous Optimization

Agents continuously learn from every action they take, improving their performance over time.

As they learn, interactions become increasingly personalized, and systems naturally enhance their effectiveness.

Understanding the pros and cons of the agentic web helps us make informed decisions about its integration into our lives.

Pros of Embracing the Agentic Web

We’ve already been conditioned to appreciate convenience. The agentic web proposes a future that embraces this concept fully.

Simplified interactions, characterized by interpreted user intent, represent the epitome of this streamlined process.

Cons of Embracing the Agentic Web

Brands may face challenges in adapting their content to align with AI systems while preserving human accessibility.

There’s the hazard of designing primarily for machines at the risk of losing the human touch.

Pros of Resisting the Agentic Web

Some users value human-centric experiences, suspicious of automated systems—leaning away can help build trust with this audience.

Cons of Resisting the Agentic Web

A complete detachment could impact visibility and limit access to emerging opportunities as the digital landscape evolves.

Many existing systems are built to integrate, preserving fundamental infrastructure rather than replacing it completely.

The agentic web is still evolving based on how we engage with it. Our understanding of it will guide us in determining its role in our lives.

Inspired by this post on Search Engine Land.

February 3, 2026
Unlocking Digital PR: 7 Secrets to Boost Your SEO Success
I’ve noticed a shift as informational searches decline. Digital PR is now fueling authority, relevance, and high-intent outcomes in SEO. Here’s what I’ve discovered about its impact.

Digital PR is becoming more crucial than ever—not just a trend or a rebranded link-building tactic. The dynamics of search and discovery are evolving, and here’s why that’s important to me.

Brand mentions, earned media, and the broader PR ecosystem are redefining how search engines and large language models perceive brands. This shift influences how I approach visibility, authority, and revenue in SEO.

Informational search traffic is dwindling. Fewer people are clicking on expansive blog posts for top-of-funnel keywords.

Now, the commercial value is centered around high-intent queries, like product and category pages. Digital PR perfectly aligns with these changes.

Here are seven practical, experience-driven secrets showcasing how effective digital PR is transforming SEO in my view.

Secret 1: Digital PR can be a direct sales activation channel

While digital PR is often seen as a link-building or branding strategy—or recently, a way to influence AI and generative search outputs—its direct impact on revenue is sometimes overlooked.

Being featured in the right media puts your brand before buyers, not during passive awareness but in a critical moment of consideration.

Platforms like Google excel at understanding user intent. Digital PR leverages this by positioning you where your audience is already searching.

Executed well, two outcomes arise:
- Your brand gains recognition even if your site already ranks well. Familiarity grows as your name associates with credible insights.
- Exposure boosts brand searches and direct clicks. Some readers click through immediately, while others search your brand later, entering your funnel with trust that generic searches lack.
This effect, rooted in recency and familiarity, is hard to single out in analytics but significantly impacts commerce.

I’ve observed this mostly within direct-to-consumer, finance, and health markets, where purchasing is highly active and intent-driven.

In the right environment, digital PR is not just aiding sales—it’s part of the sales engine.

Discoverability in 2026: How Digital PR and Social Search Work Together

Secret 2: The mere exposure effect is one of digital PR’s biggest advantages

Repeated exposure in relevant media helps build familiarity, turning it into trust and then preference. This is the mere exposure effect—vital for brand growth.

This often happens through syndicated coverage, where a powerful story in regional or sector-specific media results in widespread mentions.

Historically, some SEOs undervalue such coverage due to non-unique links, missing the point.

Repetition builds a network of associations, positioning your brand alongside relevant subjects, influencing public and machine perception alike.

An ongoing digital PR strategy, rather than sporadic major hits, accelerates familiarity growth in both human and algorithmic terms.

Secret 3: Big campaigns come with big risk, so diversification matters

Large digital PR campaigns are tempting, generating excitement and industry approval. However, they also consolidate risk.

Giant campaigns might succeed tremendously or flounder silently, often failing to yield the desired links or mentions.

The reason is simple: what marketers enjoy may not meet journalists’ needs.

Journalists need prompt, engaging stories. If a campaign doesn’t translate well, it will flounder. Overinvestment in one idea leaves no backup.

A diversified digital PR approach spreads resources across smaller efforts and reactive opportunities, ensuring consistent coverage.

In the realm of digital PR, consistent reliability often trumps one-off brilliance.

How to Build Search Visibility Before Demand Exists

Secret 4: The journalist’s the customer

It’s easy to forget the gatekeeper in digital PR: the journalist.

From a brand’s angle, goals include links and authority. For journalists, it’s about stories that capture reader interest.

They determine if your pitch succeeds, so they are, quite literally, the customer.

Effective digital PR should first simplify journalists’ tasks by offering clear angles, credible data, timely insights, and quick responses.

Helping journalists enriches your exposure, affecting search engines and AI systems favorably.

Treat journalists as partners instead of mere distribution channels.

Secret 5: Product and category page links are where SEO value is created

Not every link is created equal in SEO. Links to product, category, and core service pages are usually more valuable than those to blogs. Yet, securing these links via traditional outreach can be challenging.

Digital PR shines here. It places links naturally within product or service contexts, steering authority to revenue-driving pages.

As informational content’s traffic-generating role diminishes, ranking high-intent pages grows in economic significance.

Sometimes, a few high-quality, relevant links are more valuable than numerous superficial ones directed at top-of-funnel content.

Digital PR planning should prioritize these target pages from the start.

How to Make Ecommerce Product Pages Work in an AI-First World

Secret 6: Entity lifting is now a core outcome of digital PR

Search engines have long emphasized context, underscoring the importance of surrounding text and brand descriptions for defining brand identity.

This has escalated with large language models, which interpret data chunks, drawing meaning from context rather than isolating links.

Repeatedly mentioning your brand with specific topics enhances your standing in those arenas, a process known as entity lifting.

This approach extends beyond individual pages, enhancing term and category rankings by bolstering overall authority.

AI systems also increasingly reference consistently relevant brands.

Digital PR offers a scalable method to spread this contextual insight.

Secret 7: Authority comes from relevant sources and relevant sections

Ex-Google engineer Jun Wu explains in “The Beauty of Mathematics in Computer Science” that authority stems from recognition within specific knowledge clusters.

In simpler terms, where you’re mentioned and the context matters as much as the site’s size.

A relevant mention within a prestigious publication’s specific section often surpasses a home-page mention in terms of value.

Effective digital PR should focus on publications and sections aligned closely with your industry and target topics.

That’s how authority is constructed for both search engines and AI systems.

The New SEO Imperative: Building Your Brand

Where Digital PR fits in SEO

Digital PR is emerging not just as a support tool for SEO but central to how brands are discovered, understood, and trusted.

As informational traffic wanes and high-intent competition surges, successful brands will blend relevance, repetition, and authority across earned media.

When done right, digital PR offers all three.

Inspired by this post on Search Engine Land.
February 3, 2026
Discover Bing’s New Multi-Turn Search Feature Now Live Worldwide

I’m excited to share that Microsoft has introduced a game-changing update to Bing with the global rollout of multi-turn search. As I scroll through Bing’s search results, I now see a Copilot search box conveniently positioned at the bottom, waiting to assist with follow-up queries.

What is multi-turn search? In essence, this feature enables me to continue my search seamlessly. Imagine typing a follow-up question in the Copilot search box right at the bottom of the results page without any need to scroll back up. It feels so intuitive and user-friendly!

Here’s a vivid screenshot that perfectly captures this experience:

And here’s a video that brings it to life, showcasing the seamless functionality:

Here’s what Microsoft had to say. Jordi Ribas, the CVP and Head of Search at Microsoft, took to X to share this exciting update, revealing that “After shipping in the US last year, multi-turn search in Bing is now available worldwide.”

Ribas went on to explain that “Bing users don’t need to scroll up to do the next query, and the next turn will keep context when appropriate,” indicating a significant enhancement in user experience.

He further noted, “We’ve seen gains in engagement and sessions per user in our online metrics, highlighting the positive user value of this approach.”

Why it’s important for us. With many search engines, including giants like Google, trying to push for more AI integration, Bing’s new feature is a step in that direction. Google’s AI Overviews, although not entirely without controversy, are pushing users deeper into AI interfaces. Meanwhile, Bing’s Copilot box, after rigorous testing over several months, is now fully available, underscoring Microsoft’s commitment to user-centered innovation.

Inspired by this post on Search Engine Land.

February 3, 2026
Understanding ChatGPT Ads: Behavior Over Targeting
Ads in ChatGPT signify a major transition from focusing on keyword intent to understanding user behavior. This evolution changes how we approach relevance, creativity, and performance measurement.

Currently, ads are being tested in ChatGPT in the U.S., appearing to various users across different account types. For the first time, we see advertising stepping into an AI environment designed for answering queries, which fundamentally changes the game for marketers like me.

AI has been an integral part of ad creation and planning across platforms like Google and LinkedIn for years. However, placing advertisements inside an AI that people trust to assist with thinking, decision-making, and actions is a completely new challenge. It’s not just another channel in our existing media strategy.

The primary concern for us isn’t targeting, but understanding psychology. Replicating strategies successful in search or social may lead to disappointing performance or even damage trust.

To thrive, brands must comprehend why users engage with ChatGPT, and what implications that has for capturing attention and enhancing the customer journey.

ChatGPT is a Task Environment, Not a Feed

When people use ChatGPT, they have a purpose. Whether it’s:
- Solving a specific problem.
- Refining a shortlist.
- Planning a trip.
- Writing something.
- Making sense of a complex decision.
Unlike feed-based platforms, where users passively scroll and consume content, ChatGPT users are goal-oriented.

In such a task-centered environment, behavior shifts:
- Goal shielding: Users focus narrowly on finishing tasks, filtering out distractions that don’t contribute.
- Interruption aversion: When focusing, unexpected distractions feel more annoying.
- Tunnel focus: Clarity and speed take priority over exploration.
This means gaining clicks will be more challenging than some advertisers might anticipate. If ads don’t assist users in progressing their tasks, they’ll seem irrelevant, no matter how topically aligned they might be.

Considering trust in AI is still being established, tolerance for distracting ads is particularly low.

Dig deeper: OpenAI moves on ChatGPT ads with impression-based launch

Behavior Over Search Volume: Designing a Strategy for ChatGPT

Traditionally, search volume has directed our planning.

Keywords informed us about what users sought, how often, and the level of demand competition. This framework informed both SEO and paid media strategies.

However, ChatGPT changes this model. Instead of searching for keywords, users describe situations, ask detailed questions, and pursue outcomes beyond mere information.

Without query data to optimize, our success depends on understanding:
- The task the user aims to complete.
- The journey stages they’re outsourcing to AI.
- The specific help they need at that moment.
This is where behavioral insights replace keyword demand as the foundational strategy.

Transitioning from Keyword Intent to Behavioral Targeting

Instead of centering our plans around queries, we should focus on behavior modes, representing the mindset of users when they turn to ChatGPT.

We can consider these modes as follows:
- Explore mode: Users seek inspiration or shape a perspective.
- Ads here should ignite ideas, offer options, or reframe the problem.
- Reduce mode: Users aim to narrow choices effectively.
- Ads should clarify differences, simplifying decisions.
- Confirm mode: When users want reassurance, trust trials such as reviews or guarantees matter most.
- Act mode: Users aim to complete the task, so ads that eliminate friction, like clear pricing, will succeed.
These modes correspond with recognized human drivers in search behavior: forming perspectives, informing, reassuring, and simplifying. ChatGPT condenses these moments into one interface.

Dig deeper: What AI means for paid media, user behavior, and brand visibility

In ChatGPT, Relevance is About Utility

The key shift is that relevance in ChatGPT is not merely about a match but about functionality.

An ad can align with a category but still fall short if it doesn’t help users with their tasks. Anything creating extra work or that distracts from goals feels frustrating in a task environment.

High-performing ads are likely to act less like traditional ads, and more like:
- Tools.
- Templates.
- Guides.
- Checklists.
- Shortcuts.
- Decision aids.
Such ads integrate seamlessly into user workflows.

Generic brand ads, mere awareness messages, and content serving as detours are likely to underperform.

Dig deeper: Your ads are dying: How to spot and stop creative fatigue before it tanks performance

Helpful Content Bridges Channels

The assets that create compelling ChatGPT ads—guides, frameworks, and reassurance-focused content—do more than boost paid performance. They enhance authority for SEO, earn media coverage for digital PR, and strengthen brand trust across social and owned channels.

Here, silos can break performance.

Paid media teams cannot create “helpful ads” in isolation while SEO focuses on authority, PR works on trust signals, and brand teams shape voice independently. AI-driven discovery blends these signals.

The best-performing ads may rely on:
- Brand voice for consistency.
- Trusted voice from reviews, experts, or validation.
- Amplified voice through media coverage and authority.
The line between advertising, content, and credibility is increasingly blurred.

Rethinking Measurement

Evaluating ChatGPT ads purely on click-through rates risks missing their broader influence. These ads might sway decisions without triggering immediate clicks, aiding in brand recall or re-entry through different channels.

More significant indicators might include:
- Shortlist inclusions.
- Brand recall.
- Assisted conversions.
- Branded search increases.
- Direct traffic improvements.
- Conversion boosts further down the line.
This underscores the need for cross-department collaboration. If performance spans the customer journey, so too must measurement and accountability.

Dig deeper: AI tools for PPC, AI search, and social campaigns: What’s worth using now

Winning Brands Master Behavior

This is not just a new ad format; it’s a shift in behavior. Brands that succeed will deeply understand:
- What people use ChatGPT for.
- Journey stages being shifted to AI.
- How to support these moments without losing trust.
We should revisit jobs-to-be-done thinking, mapping actions leading up to a purchase, inquiry, or commitment, and identify where AI reduces effort, uncertainty, or complexity.

This approach empowers us to ask, not simply, “how do we advertise here?” but “how can we be genuinely helpful when it counts most?”

Adopting this mindset will not only shape performance in ChatGPT but influence the broader future of AI-led discovery, where understanding behavioral intent will surpass the old focus on keywords.

Inspired by this post on Search Engine Land.
February 2, 2026
2 Million LLM Sessions: AI Discovery Insights Revealed
Analyzing nearly two million LLM sessions across nine industries throughout 2025 was a fascinating journey for me. I began with the assumption that ChatGPT would dominate and that AI usage patterns would be relatively uniform with minimal impact.

The findings, however, were surprising.

While ChatGPT does indeed control 84.1% of the trackable AI discovery traffic, it’s primarily serving as a broad-market tool. This discovery significantly impacts strategic approaches.

In today’s landscape, relying solely on a single discovery strategy is not viable. A multi-platform approach that aligns with how and where users find productivity is essential.

Brands must now discern which platforms are empowering productivity rather than merely supporting initial discovery phases.

Various LLMs are excelling in different sectors, often with stark differences. The key takeaway for 2026 is more complex than simply focusing on ChatGPT.

Here’s what I’ve discovered from the data.

The Growth Rate Divergence: ChatGPT vs. Competitors

Throughout 2025, major LLM platforms exhibited significant growth discrepancies:
- ChatGPT: 3x growth
- Copilot: 25x growth
- Claude: 13x growth
- Perplexity: 1x growth
- Gemini: 1x growth
Although ChatGPT grew, Copilot and Claude experienced much more rapid growth. Platforms like Perplexity and Gemini remained steady, reinforcing specific workflows.

These numbers highlight strategic priorities:
- Satya Nadella celebrated Copilot reaching 100 million monthly users.
- Dario Amodei revealed that Anthropic’s revenue grew from $100 million to $8–10 billion in under two years.
- Aravind Srinivas noted significant interest in Perplexity Finance.
The focus on growth is crucial because it signals true user value:
- Copilot excels in the Microsoft ecosystem.
- Claude appeals to developers.
- Perplexity thrives among finance professionals.
Different LLMs are thriving in various industries at markedly different rates.

Pattern 1: Copilot’s Striking Growth

Copilot’s remarkable 25x growth is indicative of its premier position in B2B environments reliant on Microsoft tools.

SaaS
- ChatGPT: 2x growth
- Copilot: 21x growth
- The rapid adoption mirrors modern SaaS practices, embedding LLMs directly into workflows.
Education
- ChatGPT: 6x growth
- Copilot: 27x growth
- Copilot benefits from educational settings fostering knowledge sharing and synthesis.
Finance
- ChatGPT: 4.2x growth
- Copilot: 23x growth
- Finance aligns with Copilot due to automation needs and context dependency.
Copilot’s growth is most pronounced in industries where professionals are deeply integrated with Microsoft tools.

Instruments like Excel transform into data interpretation powerhouses with Copilot, eliminating the need for external searches.

Implications

For work-centric audiences like SaaS, finance, and education specialists, AI discovery is shifting into LLMs embedded in workflows.

Pattern 2: Perplexity Shines in Finance

While Perplexity has flat growth overall, it stands strong in finance with a 24% market share, unlike in other sectors where it has diminished.
- SaaS: down to 7.3%
- E-commerce: down to 3.4%
- Education: down to 5.2%
- Publishers: down to 3.6%
Finance demands accuracy; thus, traceable sources make Perplexity vital in this sector.

Partnering with Benzinga, FactSet, and others, Perplexity offers in-depth data vital for financial decisions.

Trust and verifiability are crucial in finance, and that’s where Perplexity excels.

Implications

In finance, selection of platforms that integrate with licensed data and credible sources is critical. Success hinges on being part of these authoritative ecosystems.

Pattern 3: Claude’s Dominance in Analysis

With just a 0.6% share, Claude might appear to be an underdog, but it thrives in specialist sectors like publishing and finance.
- Publishers: 49x growth
- Education: 25x growth
- Finance: 38x growth
- SaaS: 10.3x growth
Claude’s strength lies in standalone, strategic thinking rather than integrated tools like Copilot.
- Publishing professionals and financial analysts use Claude for its substantial context window, enabling complex and strategic queries.
Implications

Target audiences that require in-depth analysis should focus on creating structured and detailed content. Claude’s user base is smaller but highly influential.

Pattern 4: Challenges in Tracking Gemini

The data concerning Gemini is puzzling, showing both growth and declines. This could be attributed to issues with attribution rather than an actual decline in users.
- Education: −67% tracked traffic
- SaaS: +1.4x growth
- Finance: +1.3x growth
- E-commerce: +2.7x growth
Gemini’s interaction model keeps users within its ecosystem, making measurement challenging.

The reality is that usage might still be robust, but the tracking systems need to catch up with user behaviors.

Implications

As AI-assisted conversions increasingly occur, traditional last-click attribution models need reconsideration.

Monitor brand search performance and invest in broader visibility strategies.

Strategizing Your LLM Approach

AI discovery is diversifying rather than converging. Tailoring strategies based on your audience’s preferences and behaviors is crucial.
- Enterprise Audiences: Focus on Copilot integration for SaaS and B2B environments.
- High-Stakes Decisions: Consider Perplexity’s reliability in providing traceable data.
- Technical Evaluations: Claude’s detailed analysis capabilities require rich, structured content.
- Emerging Sectors: Initiate with ChatGPT, monitor for evolving platform preferences.
- Measurement Challenges: Adjust strategies to accommodate for gaps in tracking.
Success in AI discovery is rooted in understanding your audience’s platform preferences and their specific needs.

Read the full study: 2025 State of AI Discovery Report: What 1.96 Million LLM Sessions Tell Us About the Future of Search

Inspired by this post on Search Engine Land.
January 30, 2026
Boost Your Google Ads in 2026 with v23 API Insights

As I delve into Google Ads API v23, I’m excited to share this update marks the beginning of a faster-paced release cycle in 2026. With this update, I’m now able to access improved Performance Max reporting, sophisticated AI-driven audience tools, and more detailed campaign controls.

What’s new:

Performance Max Transparency: I’ve discovered that PMax campaigns now offer ad network type breakdowns, making it easier for me to analyze performance.

More Detailed Invoices: Through InvoiceService, I can retrieve campaign-specific costs, regulatory fees, and adjustments, allowing for more precise financial tracking.

More Precise Scheduling: It’s a game-changer for me to now schedule campaigns using precise start and end date-times instead of limiting to date-only fields.

Local Data Access: I’m now able to access store location details via PerStoreView, which matches the data in the Stores report accurately.

New Audience Dimension: With life-event-based audience building through LIFE_EVENT_USER_INTEREST, my Insights tools are more powerful than ever.

Smarter Demand Gen Planning: The conversion rate forecasts I rely on now vary by surfaces such as Gmail and Shorts, enhancing my strategy planning.

Generative AI Audiences: I can efficiently translate free-text audience descriptions into structured attributes, simplifying audience target creation.

Expanded Shopping Metrics: The inclusion of new competitive and conversion metrics by conversion date helps me improve my shopping ads performance.

Why I care: A quicker update cycle means I can leverage new features faster. With Google’s shift towards automation and AI-driven insights, staying on top of these updates helps me optimize campaigns effectively.

Between the lines: These updates require my team to upgrade client libraries and code, so scheduling development time is crucial to benefit fully from v23.

Bottom line: The Google Ads API v23 is setting the stage for 2026. I’m ready to embrace these improvements that introduce faster releases coupled with enhanced AI insights, refined reporting, and better campaign control for large-scale advertisers.

Inspired by this post on Search Engine Land.

January 29, 2026
How AI Highlights the Vital Role of Human Connections in Agencies

Working as an office manager in my early 20s, I discovered Dale Carnegie’s “How to Win Friends and Influence People.”

The timeless principles in that book have been my guiding compass through various career shifts. I’ve realized that success in most professions hinges on how we interact with others—be they clients or colleagues.

For many years, combining human touch with technical skills has been a winning formula for digital marketers. It was this ability to demystify complex machines coupled with strong relationship-building that allowed agencies to retain clients.

But now, this model is under scrutiny as AI becomes integral to PPC platforms, raising a pertinent question: why shouldn’t clients dive into an entirely AI-driven approach?

What agencies have an edge on is their relational strength—their ability to communicate effectively and understand what business owners genuinely need.

1. Ask questions

I’ve learned that one of the most effective ways to understand people and what makes them tick is by asking questions. Though it seems straightforward, communication often becomes lost in translation or obscured by assumptions.

Whenever I walk into a sales call, I arm myself with a list of questions. How much can I uncover about this potential client in a brief half-hour conversation?

Similarly, during strategy discussions, I prepare a comprehensive set of queries—some for myself, and some for the client. What are they aiming to achieve? What aspects of their current strategy need refinement? How can we enhance it?

To this day, AI can’t fulfill this role—not yet, at least. Our exchanges with AI remain predominantly one-sided.

AI doesn’t actively seek to understand us as individuals or identify our unique challenges. These discoveries only come from asking questions and actively listening, which leads to the next point.

Dig deeper: 6 tips to build PPC client relationships

2. Talk less, listen more

How often do I find myself in conversations, impatiently waiting for a pause to insert my thoughts? I’m guilty of this, but I’ve found that clients crave the opportunity to be heard.

Allow them to express themselves fully, encourage them with more clarifying questions, and just keep listening. It’s remarkable what you can learn about someone when you enter a conversation with no other agenda but to understand the other person.

Fill the silences only if they become awkward, and if you have valuable agenda points to address based on what you’ve learned. This approach fosters collaboration and generates ideas more swiftly than dominating the conversation could. It solidifies agreement, which is foundational in building relationships.

Dig deeper: 8 questions to ask your new PPC clients

3. Find common ground

Whenever possible, I aim to discover commonalities between myself and new acquaintances. By doing so, I build rapport, enriching both personal and professional relationships.

Being personal and specific, whether dealing with a friend or a client, is key. I love recalling little details about people and bringing them up in future conversations. People appreciate being remembered and valued.

Though AI is beginning to develop memory, finding shared experiences with others is a uniquely human skill that, fortunately, remains beyond AI’s reach.

Dig deeper: When and how to fire PPC clients

4. Smile, be less serious (when it’s appropriate)

In the fast-paced marketing realm, it’s easy to succumb to the all-consuming cycle of data analysis and testing. Remember, though, not to take ourselves too seriously.

After all, this profession is relatively new, and its evolution is unpredictable. Let’s not forget why we ventured into marketing—to help and connect with people. Let’s embrace opportunities to be less serious and inject humor when it fits.

We’re human, and it’s vital for those we work for to recognize this humanity as an integral part of any relationship.

Dig deeper: How to set and manage PPC expectations for teams and stakeholders

What differentiates a partner from an algorithm

In a world increasingly dominated by AI, the focus is shifting from technical prowess to personal connection. AI excels at data and analysis, available at a moment’s notice, but knowledge alone isn’t sufficient anymore.

Empathy, shared experiences, and true rapport are beyond AI’s capability to replicate. These human principles, combined with expertise, are what enabled agencies to decode machines for clients and nurture enduring relationships.

By returning to relational basics—posing insightful questions, practicing active listening, and establishing common ground—agencies can affirm their indispensable value.

These relational skills are vital in distinguishing a partner from an algorithm, ensuring that the work of agencies remains not just relevant but essential.

Inspired by this post on Search Engine Land.

January 29, 2026
Maximizing AI Visibility: Why It’s 30x Tougher Than Google SEO

When it comes to AI assistants like ChatGPT, Gemini, and Perplexity, my experience shows that many brands excelling in local Google searches struggle to be visible. SOCi’s 2026 local visibility index highlights this gap, revealing that AI recommends a meager 1% to 11% of locations.

Interestingly, business profile accuracy varies significantly across platforms. While Gemini maintains 100% accuracy, ChatGPT and Perplexity lag behind at 68%.

AI limits local visibility. Examining data from almost 350,000 locations tied to 2,751 multi-location brands, it’s clear that AI platforms are incredibly selective compared to Google’s local outcomes:

Only 1.2% of locations get the nod from ChatGPT, 11% from Gemini, and 7.4% from Perplexity. In contrast, Google’s local 3-pack features brands 35.9% of the time, indicating that securing AI visibility is three to 30 times more challenging.

AI and Google visibility differ. Across different sectors, less than half of brands topping Google’s local visibility are also among the elite in AI search outcomes.

For instance, in retail, only 45% of the top 20 brands in local search visibility made it to the top in AI recommendations.

Why I care. Just because my brand does well on Google doesn’t mean it will shine in AI-driven results. It’s crucial to ensure that my brand’s information is consistent across all platforms AI systems draw from, such as Google Maps, Yelp, and Facebook. Strong, accurate data and a clear, positive presence are now fundamental.

AI favors higher-rated businesses. AI consistently promotes businesses with high customer sentiment, treating reviews more like a filter than a ranking tool.

For instance, ChatGPT recommends locations averaging 4.3 stars, whereas ratings on Gemini and Perplexity are slightly lower. Unlike traditional methods that prioritize proximity, AI platforms look for confidence.

Impact varies by industry. Different sectors experience varying levels of AI visibility:

Retail: A limited number of retail giants like Sam’s Club lead, while others like Target fall short. This gap illustrates AI’s focus on reliable signals across platforms.

Restaurants: Culver’s excels with up to 45.8% recommendation rates, driven by strong ratings and accurate profiles, highlighting how essential these elements have become.

Financial services: Liberty Tax improved its AI visibility by boosting data accuracy and ratings, achieving impressive figures compared to competitors lacking in these areas.

Failing to maintain top-notch fundamentals now means disappearing from AI recommendations altogether. SOCi observes this as a critical shift.

The report. For more detailed insights, I can check out the 2026 Local Visibility Index (registration required).

Inspired by this post on Search Engine Land.

January 28, 2026
Meta’s New Paid Subscriptions: A Game-Changer for Social Media?

Recently, I’ve noticed that Meta is testing paid subscriptions on Instagram, Facebook, and WhatsApp. Their goal is to unlock premium features and incorporate AI more prominently across these platforms, which could significantly shift how we create and interact with content.

What’s unfolding? Meta’s new subscription trials aim to bring exclusive features to each app, tailored to productivity, creativity, and enhanced AI capacities, while the core experiences remain free. It’s interesting to see how Meta plans to develop unique subscription offerings instead of just a single bundle, especially as they explore which combinations of features might work best.

Subscriptions will provide premium controls and tools that can benefit everyday users, creators, and businesses, distinct from Meta Verified. For instance, on Instagram, initial testing might include features like unlimited audience lists, insights into non-followers, and stealth story viewing.

Meta also aims to launch paid AI features, notably increasing access to its Vibes AI video generation tool through a freemium model. I’m curious about how this might change our interaction with content creation tools.

Why this matters to us. These paid subscriptions could transform user engagement on Meta’s platforms, potentially altering privacy settings and audience reach. Additionally, new AI-driven creation tools could shift the landscape of user-generated content that advertisers either compete against or harness for campaigns. Over time, these subscription tiers might redefine targeting strategies and the value of organic versus paid engagement on these platforms.

Reading between the lines: AI is central to this strategy. Meta plans to scale Manus, an AI agent they acquired for $2 billion, by embedding it within their apps and offering standalone subscriptions to businesses. Reports suggest that we’ll soon see Manus shortcuts directly in Instagram, creating tighter integration between social media engagement and AI-enhanced content creation.

Why the timing is right. While advertising is still at the core of Meta’s revenue model, diversifying into subscriptions can provide a new income stream. With users more open to paying for unique social features, as seen with Snapchat+ boasting over 16 million subscribers, Meta is betting on replicating that success without adding to the subscription overload many of us feel.

The takeaway. Meta’s experiment with premium social and AI enhancements could potentially open a significant new revenue stream beyond advertising. The real test will be whether these features provide enough value to justify another subscription in our already crowded monthly commitments.

Explore further. For more details, check out TechCrunch’s full article on Meta’s subscription test.

Inspired by this post on Search Engine Land.

January 28, 2026
Streamline Ad Reviews with Google’s Instant PMax Previews

I’ve noticed something pretty exciting in Google’s recent update to Performance Max. They have introduced one-click ad previews, making it incredibly easy to review creatives directly from the asset group table. This update feels like a breath of fresh air to anyone who’s ever been bogged down by the previous clunky process.

What’s new? Now, with just a click on any image or video within the Asset Groups table, I can instantly see how my ads will look across different Performance Max placements, without needing to navigate away from the page.

Why we care. Before this, checking ad previews meant jumping through various hoops into different views or settings. Now, everything is streamlined, keeping my workflow smooth and efficient, which makes creative quality assurance and iteration a lot less of a hassle.

Between the lines. There has been consistent feedback about the transparency limitations of Performance Max. So, even these small UI changes that bring creatives to the forefront are a big deal for me and many others in the field.

The bottom line. While one-click previews aren’t a game-changer in terms of strategy, they are a real time-saver. This especially helps when I’m handling large asset libraries or frequent creative updates.

First seen. This handy update was first spotted by Paid Search marketer Bia Camargo, adding another reason to appreciate these nuanced yet impactful changes.

Inspired by this post on Search Engine Land.

January 28, 2026