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Author: shivamcrushpressai

The Future of SEO Leadership: Navigating the Complexity
The job posting from Anthropic that everyone seems to be discussing is becoming the new standard. Companies who get this right are poised to quietly dominate the next decade.
The latest Anthropic job listing is causing a stir in the SEO community. They may as well have called it the Search Gawd position. To be honest, this is a reality across the board.
I’ve penned this kind of job description multiple times and even interviewed for it myself. I’ll admit, I haven’t seen many of these roles actually filled, but I’ll touch more on that shortly.
Titles vary—from Head of SEO to Director of AI Search, and even VP of Search or Agentic Commerce GEO Consultant. Lots of titles, same core responsibilities: manage technical SEO, grasp paid search, direct content, collaborate with engineering, build metrics, prepare for AI discovery, and translate it all into growth.
It’s predictable that people think this sounds like several jobs rolled into one—a single employee carrying the weight of an entire agency. This might be a fair observation, but it misses the critical point.
Businesses have been on the lookout for such talent for years. The rise of generative search is now compelling action.
This Isn’t Just an Anthropic Issue
While browsing job boards today, I noticed:
- Victoria’s Secret: Director, AI & Organic Search (AEO, GEO, SEO), $152K–$216K.
- Publicis / Starcom: VP, SEO (Performance Content).
- Accenture: Agentic Commerce GEO Consultant.
- SailPoint: AEO/GEO Manager.
- AirOps: Senior SEO Manager spanning SGE, Perplexity, ChatGPT, Gemini.
- Responsive: Senior Manager, Web Strategy — SEO, GEO, plus Next.js, React, Vercel, DNS.
- Danaher, Experian Health, Amazon News: variations of SEO + AEO + GEO.
- Anthropic: SEO Lead, $255K–$320K.
Diverse industries, varying salaries, yet they’re all unconsciously seeking the same elusive candidate.
Misalignment Between Titles and Responsibilities
Consider Agency X looking for a “Director, SEO/SEM,” whose job includes no SEO—just paid platforms, vendor management, and leading a team of seven.
Then there’s Consulting firm Y, seeking a “Director, SEO/AIO,” without clarifying what AIO entails. A smaller agency’s “VP/Director, SEO” asks for paid search, social, and pharma marketing as preferred skills.
A research firm is hiring a “Director, SEO & AEO,” which accurately reflects SEO and AEO duties—an unusual alignment worth highlighting.
If the company can’t settle on pre-defining the role, a candidate standing a chance seems improbable. The taxonomy says one thing, the JD another, the recruiter screens for something else, and the manager interviews for yet another role. Meanwhile, the applicant tracking system (ATS) disregards viable candidates.
In Search of the Missing Link
You’re searching for someone who can bridge technical search, content, PR, product, engineering, analytics, performance media, and brand—someone who knows these interactions are more intertwined than they appear on organizational charts.
Search highlights these intersections. Technical issues may seem like content issues, and content problems could stem from product issues. Visibility issues might be about authority, not just optimization. Paid search often uncovers messaging issues quicker than brand research does.
In the era of generative discovery, these connections can’t be ignored. When results provide answers, SEO shifts from being purely traffic-driven.
To sidestep into Yoda-speak to avoid AI jargon: information exists only if the infrastructure supports it. Content helps understanding, brand garners trust, and product transforms discovery into utility—or it doesn’t.
You’re not expecting one individual to tackle every task; rather, you want someone who understands the cohesion of these parts. That candidate exists, but traditional systems make it difficult to find them.
The Résumé Might Surprise You
The candidate you need won’t be evidently showcased by years with an SEO title or specific software lists. It’s about their judgment:
- Identifying crucial technical issues versus distractions.
- recognizing when content struggles require external resolution.
- Knowing when to invest, automate, or pause, and when to advise leadership against certain actions.
This kind of discernment doesn’t easily translate onto a résumé. The right candidate might have navigated through various roles in agencies, publishing, product, consulting, and operations. Their career might not appear streamlined like a specialist’s, yet that very diversity equips them for this role.
Unfortunately, your ATS will likely disqualify them, while your recruiter labels them as “non-linear.” Your hiring panel might note they’ve never held the precise title before. But remember, this role didn’t exist before, and there’s no consensus on its name.
Clearly, this selection process is heading off-course.
The Alsotative Possibility
Some processes may be more about absorbing insights from interviewing candidates than actually filling the position.
Senior candidates often diagnose: detailing function structure, identifying organizational weaknesses, outlining first-90-day plans, recommending tools, and highlighting tasks to abandon. By inviting numerous candidates, companies might inadvertently gather varied organizational strategies and priorities without making any hires.
Perhaps that wasn’t the original intent. But if roles remain unfilled for months, resurface repeatedly, alter their titles and scope, and produce interview-like advisory sessions, candidates are right to question what the company truly seeks: talent acquisition or strategic input?
Addressing the Real Issue
Narrowing the job description won’t eradicate the work needed. Focus on deciding the core requirement. Is it:
- A specialist to execute tasks?
- A leader to assemble a team?
- An executive to integrate search, content, product, brand, and performance?
- A consultant to advise on necessity?
These are distinct roles, and expecting them to merge into one is unrealistic.
A Final Thought
I’d excel at such a role, along with a few others who’d be filtered out for the same reasons.
Concerning the Anthropic opportunity, it isn’t materializing for me.
Five years under a nonexistent title from five years ago? My resume doesn’t show that. It matches the job spec — perfectly tailored for ATS rejection. It’s a straightforward system to manipulate, especially for those seasoned in the field.
The elusive talent is indeed genuine. Generative search only spotlighted the gap. Before your company finds someone to bridge these systems, ensure the capability to recognize, hire, and support them.
The companies that master the art of identifying the right candidate—and not just crafting an ideal job description—will take the lead in the coming decade. Meanwhile, others will continue LinkedIn debates about whether GEO is truly a word.

Inspired by this post on Search Engine Land.
June 23, 2026
Amazon Revolutionizes Shopping with Alexa+ Conversational Ads

I’ve always been fascinated by how technology can change the way we interact with advertisements, and Amazon’s latest innovation, Alexa+ Agentic Ads, is a game-changer.

This incredible new format allows us to browse, inquire, and purchase products within the comforting interface of an Alexa conversation, dramatically simplifying the buying process.

Introducing Alexa+ Agentic Ads. Today, Amazon unveiled this forward-thinking advertising solution that seamlessly transitions users from viewing an ad to making a purchase, all without leaving the Alexa environment.

They’ve partnered with key players like Papa Johns for food orders and artists like Beck, Jill Scott, and Omar Courtz for concert ticket sales, making this experience accessible on Echo Show devices.

The Impact. By eliminating the typical handoff between an ad and a checkout page, Alexa+ Agentic Ads aim to enhance conversion rates and reduce drop-off. This could be especially beneficial for early adopters looking to engage high-intent customers right at their moment of decision.

How It Operates. Unlike traditional ads that redirect you to another platform, Alexa+ Agentic Ads maintain the entire purchasing journey within a dialogue.

With interactive capabilities, it enables us to ask questions, compare options, check availability, and finalize purchases through natural conversations with Alexa, minimizing friction between desire and acquisition.

Concerts and Culinary Delight. The format is initially being utilized for live events and dining experiences.

Imagine seeing an ad for a concert; you can inquire about show specifics, compare seat options, and buy tickets—all directly through Alexa. Tickets are then seamlessly added to your Ticketmaster account, bypassing the need for additional apps or sites.

Similarly, when pondering dinner plans, a Papa Johns ad may spark immediate ordering as Alexa+ employs past interactions and preferences to suggest your favorite toppings before completing the order—all within the same conversation.

Looking Ahead. As we witness the evolution of digital advertising through Alexa+ Agentic Ads, we’re glimpsing a future where AI assistants are pivotal commerce platforms, offering brands a revolutionary way to engage consumers right at the point of action.

Inspired by this post on Search Engine Land.

June 23, 2026
Channel Strategies: Broad Approaches vs. Focused Commitment

When I first started looking at budget allocation, I was tempted to believe that every marketing channel followed the same path: spend a little, get a lot, but with diminishing returns.

Visually, it’s easy to assume all channels mimic this pattern.

The typical log-shaped curve illustrates that the first dollar you spend is often the most productive. With this mindset, spreading the budget across numerous channels seems like the go-to strategy.

However, I quickly learned not all channels conform to this model. Some require much more than just a sprinkle of funds to be effective. These channels start with a less efficient spend but eventually pay off if given time to warm up. This condition shifts away from the usual ‘test small, scale the winners’ strategy many marketers follow.

At the core of this difference lies a fundamental question: Is the response curve C-shaped or S-shaped?

Understanding the shape of the response curve can drastically change how I conduct channel testing and measurement, especially with Google’s increasing inclination towards S-shaped campaigns.

Let’s delve into what these two curves signify and why they are crucial.

Response curves plot conversions or revenue against spend. Typically, we encounter two main types in marketing.

A C-shaped curve means diminishing returns kick in from the first dollar spent. Meanwhile, an S-shaped curve starts slow, becomes steep at the inflection point, and finally leads to saturation.

This insight is crucial for allocation because the marginal curve—the derivative—guides budget decisions. Here, shapes diverge with significant implications.

For a C-shaped curve, the highest marginal return is from the first dollar, decreasing thereafter. Conversely, for an S-shaped curve, the initial return is low, increases up to a peak, and then declines.

This aspect of increasing marginal returns is pivotal. It’s what differentiates channels with productive small budgets from those that seem inefficient but could perform better when scaled correctly.

Mainstream marketing campaigns exhibit this principle clearly. For instance, if your CPA goal is $50, the way the S-shaped channel behaves under scaling tells a critical story.

A preliminary $10,000 test may misleadingly suggest failure, but at $20,000-$25,000, the channel might be your most cost-effective choice. Small trials in the warm-up phase mislead the eventual conclusion.

This common misconception arises as many automatically rely on ‘test small, scale what works’. Yet, without sufficient testing past the warm-up phase of an S-curve, we risk dismissing channels that could have been game-changers.

For allocation logic, in C-shaped channels, going wide is beneficial. One global optimum dictates that spreading your budget thinly across many channels generally works.

But with S-shaped channels, a small budget is inadequate. Either commit enough budget to surpass the inflection point or don’t invest at all. There is a true minimum budget to ensure viability.

In marketing, determining whether a channel requires breadth or depth is critical. Channels historically leaned towards a concave shape, although modern platform dynamics have blurred these lines.

The differences are increasingly relevant with AI-driven campaigns. For example, ‘AI Max’ necessitates sufficient conversion data to learn effectively, affirming the concave-to-sigmoid shift. Campaigns like PMax blend both response types, initially concealing inefficiencies through promising headline numbers.

The key is recognizing the harvest versus create dichotomy. Harvest channels, like branded searches, display fast saturation and diminishing returns. Still, creating new demand—especially through platforms like Meta or YouTube—demands investment beyond superficial trials for truly incremental growth.

In conclusion, understanding whether to expand broadly or concentrate deeply in a specific channel can transform the efficiency of a marketing strategy.

Inspired by this post on Search Engine Land.

June 23, 2026
Discover Google’s New AI Performance Reports: Expanded Access Unveiled

I’ve noticed something exciting happening with Google Search Console lately. The AI performance reports are becoming accessible to a wider audience, and it’s a game-changer for those of us eager to see how our content performs in Google’s AI environments.

John Mueller from Google recently shared on Bluesky, “We’re just rolling these out incrementally to sites, and reviewing the feedback along the way. I know everyone wants the new shiny thing immediately… but first, patience.” It’s like waiting for a gift you’ve been longing for!

AI performance report. These reports offer insights into how well our content and websites are featured in AI-driven searches, showcasing metrics such as impressions, pages, countries, devices, and dates. Although it doesn’t yet track click data, it’s still a significant step forward.

Expanding access. Earlier today, I spotted several SEOs sharing that these reports are now available beyond the UK! They’re able to access reports for sites in the US, India, Switzerland, and more.

As John mentioned, Google is gradually rolling these updates out to more sites, listening to feedback, and hopefully moving towards a global release.

What it looks like. Here’s a snapshot of the report:

Why we care. As someone deeply invested in how content is presented, I find this development thrilling. Publishers and site owners like me have long wanted more control over Google’s AI features. The speed at which Google has rolled this out is impressive—just within 20 days of its initial release!

Inspired by this post on Search Engine Land.

June 23, 2026
Deciding to Build or Buy Your Next SEO Tool with AI Insights
Before I consider requesting a new SEO tool, I always ensure that I understand the trade-offs between custom solutions, SaaS platforms, and hybrid approaches that utilize both.

AI has empowered SEO teams, including mine, to become more ambitious about automation. Tasks that once required engineering support are now tackled easily with tools like Claude or ChatGPT.

This is thrilling, yet it brings a new challenge: the assumption that everything can be automated. In today’s language, it boils down to a single question: Do we build or buy the tool?

The build-versus-buy dilemma is intricate, made even more so by AI advancements. It isn’t merely about cost; it’s about security, maintenance, data access, internal capabilities, workflow fit, and whether a custom solution can stay reliable and useful as time progresses.

How AI Lowers the Barrier to Building

AI has drastically lowered the barrier to experimentation. Even those of us without technical know-how can now create custom GPTs, build workflows, connect data sources, or craft an internal AI assistant.

However, maintaining a tool over the years remains a challenge, even if I managed to build it initially with AI support.

AI significantly aids SEO teams in data analysis, pattern recognition, summarizing information, and recommending actions, saving us a lot of time. Ignoring AI would surely leave us trailing behind.

It’s essential to acknowledge that AI still hasn’t reached the level of human creativity. It excels at working from established patterns and predicting outputs. This could evolve in the coming years.

AI tools also come with unseen costs. Internally developed tools may appear free since their invoices typically bypass our SEO teams, but expenses from token usage, API calls, infrastructure, engineering time, security reviews, and maintenance do exist.

Many organizations, as noted by Reuters, are experiencing “AI sticker shock,” finding themselves unable to forecast usage-based AI costs accurately. Companies like Uber, reported by TechCrunch, have even established AI spending caps after exceeding their annual budget in only a few months.

Currently, marketing teams, including mine, aren’t the largest AI consumers compared to engineering teams. Yet, this could shift rapidly.

When this happens, our expenditures will undoubtedly rise, prompting organizations to evaluate which AI tools and processes genuinely add value as opposed to simply consuming our budget.

Start by Defining What You Need

Before choosing whether to build or buy, SEO teams must define their true needs.

Different Ways to Use AI and Automation

I’ve noticed that many teams, including ours, lump various solutions together, yet they differ in cost, complexity, and maintenance.
- A custom tool: Generally a complex internal system necessitating engineering support, often focusing on automation and potentially incorporating AI aspects.
- A custom workflow: A repeatable process built with numerous tools like a custom GPT, spreadsheets, and automation, usually with an AI layer.
- A custom layer on SaaS: Leveraging data from existing tools to shape personalized reporting, prioritization, or recommendation processes.
- A true AI agent: A system capable of taking more autonomous actions, such as scanning Slack and following up on pending communications.
Though similar, these are often misidentified. Overgeneralizing terms like “AI agent” can lead to cost and complexity misjudgments.

Look for Repetitive, Context-Rich Tasks

Our team is still exploring AI capabilities. So far, we have concentrated on daily tasks involving substantial manual work.

For instance, we developed a custom GPT to assess whether our content aligns with our personas and addresses their pain points. The aim is not to replace our copywriters or reviewers, but to ensure that content isn’t generic and suggest pertinent enhancements.

We’ve also leveraged AI for translations, monthly reporting, and creating a weekly summary that integrates meeting notes, Slack, and Jira to identify outstanding tasks or follow-ups.

One of our newest workflows converts internal meeting recordings into structured landing page briefs.

Such tasks are ideal candidates for AI-powered custom workflows, given their dependence on internal context, repeatability, and specific company knowledge.

Not Everything Should Be Built

A case from our team involved a colleague who vibe-coded a prompt tracking tool. Although a good start, data presentation required manual steps for trend graphing, soon becoming a maintenance hassle due to changes in LLM tools.

The core issue was reliability. For AI visibility and prompt tracking, we needed stable data presentation, leading us to switch to a specialized platform like Peec AI, rather than maintain our own version.

This experience was insightful, enhancing our understanding of the problem, complexities, and necessary features when considering external solutions.

Here’s my advice: whether opting to build or purchase a tool, always explore existing market solutions. It helps to narrow down the essential features, preventing reliance on non-essential ones.

Especially for business-critical tools like rank tracking and website crawling, smaller SEO teams without technical support should be cautious of building from scratch. Reliability should be prioritized when data is crucial for decision-making.

Use AI Where Your Data Already Lives

Consider buying a crawler, rank tracker, or AI visibility platform and focus on linking these with custom data like GA or GSC accounts, or CRM data. This integration allows comprehensive analysis in a single view.

MCP connections also warrant consideration. The Model Context Protocol is a standard for linking AI applications with external systems, enhancing current workflows.

Though not necessary to learn coding, understanding enough to ask the right questions is beneficial.

If sensitive data is involved, like proprietary research or customer details, it’s crucial to assess security risks. It may be safer to allocate engineer support to avoid compromising sensitive information.

Deciding on a custom tool requires acknowledging the full cost, including engineering time, security reviews, and API usage, despite invoices not being SEO-related.

Before requesting any tool, SEO teams should articulate the problem, expected value, cost comparison between building and buying, and potential consequences of taking no action.

Effective requests should not start with tool needs, but with the problem, its significance, tested solutions, and the proposed optimal solution.

How to Prioritize What to Build First

No one-size-fits-all matrix exists for prioritizing builds.

Tools vary; from website crawlers to content evaluation systems, each can’t be judged by identical criteria.

In doubt, start by mapping current workflows versus the ideal ones. Patterns often emerge, highlighting primary priorities.

The first group involves tools that aid revenue generation, like identifying content opportunities or improving conversion. Marketing, including SEO, seeks visibility and leads, thus revenue-centric tools can be higher priorities.

The second category concerns tools minimizing repetitive tasks. While they may not directly create revenue, they free up valuable team time for strategic work.

Quick wins should not be ignored. Stakeholders value timely results, thus a small project with potential returns within weeks can build trust and support larger initiatives.

Also, consider cross-team value in your decision. SEO problems often extend beyond one team. Collaborating with other teams can strengthen the business case for shared solutions.

Often, the best tool isn’t the most complex. Starting small could be the strategy for smarter progress.

Remember, effective scoping leads to good decisions. Even with AI easing the build process, proper scoping of what to build remains essential.
- Define the problem, expected value, user base, and post-launch maintenance.
- Engage with your team and other departments, identifying whether it’s solely an SEO issue or a broader business challenge.
- Avoid building for AI’s sake, or being swayed by impressive demos.
Neglecting scoping risks acquiring costly tools that don’t integrate with workflows or building internal tools beyond maintenance capabilities.

Thoughtful consideration of scope is crucial before opting to build, buy, or customize a solution.

Inspired by this post on Search Engine Land.
June 23, 2026
Mastering PMax to Capture Net New Customers Effectively

As I explore the potential of Performance Max for acquiring new customers, I realize that without proper setup, it’s easy to see inflated dashboard metrics that obscure the reality of your profitability.

One major pitfall is recycling traffic from Meta. Paid search and social traffic often overlap, leading to the dreaded scenario where platforms each claim credit for conversions they didn’t fully drive.

Many direct-to-consumer (DTC) brands I talk to boast about their growing numbers. But upon deeper inspection, it’s clear that those ‘new’ customers frequently originate from existing brand efforts, shared between different ad platforms.

These overlapping sales, while still revenue, can be deceiving. Their true cost is higher than often reported, eroding actual profit without proper intervention.

Rather than limiting yourself to one ad channel, utilizing an effective system to measure genuine customer acquisition is key.

Using brand and audience exclusions along with Customer Match data, I have developed a four-step framework to target genuine new customers through Performance Max, minimizing overlap across platforms.

Steps like excluding specific audiences and leveraging first-party data can help Performance Max focus on new customers instead of warm leads.

By refining these strategies, we’re optimizing how our ad spend contributes to true customer acquisition and enhancing overall profitability.

Inspired by this post on Search Engine Land.

June 23, 2026
Discover YouTube’s New AI Tools for Enhanced Insights

Google has just unveiled some exciting AI-powered tools on YouTube. These tools are designed to reveal creator trends, enhance understanding of audience behaviors, and optimize marketing campaigns.

YouTube’s expansion of its toolset for creator marketing and campaign intelligence now includes features powered by Gemini. With these updates, I’m able to delve deep into identifying trends, understanding the creator audiences, and boosting the performance of my campaigns.

What’s happening: Google has introduced several insights and optimization tools across YouTube and Google Ads. As a marketer, these tools give me crucial visibility into trends, creator performance, and audience behavior.

The opportunity to make smarter creative and media planning decisions is more important than ever, especially in an AI-driven marketing world. That’s exactly what these new tools are designed to support.

Why I care: With deeper insights into YouTube trends, I can see which creators are resonating most with audiences and assess how my brand is performing in terms of both paid and organic content. This empowers me to make smarter choices about creator partnerships and campaign strategies.

What’s new:

More detailed trend insights: Google Ads’ Insights Finder now provides even more detailed trends in the U.S., giving advertisers like me a better view of what’s capturing attention on YouTube.

Brand Pulse data in Insights Finder: With the integration of select Brand Pulse metrics, I can now evaluate both my paid and organic efforts from a single location.

New creator insights API: The fresh Content & Creator Insights API offers agencies and partners more detailed information about YouTube creators and their audiences, enhancing my media planning and creator selection process.

Gemini-powered creative recommendations: Soon, Gemini will offer creative optimization suggestions for Demand Gen campaigns, including tips on visuals and creative elements that could boost performance.

The bigger picture: As content created by influencers plays a growing role in purchasing decisions and brand discovery, advertisers like me are keen to spot trends early and gauge creator impact effectively.

Google is banking on AI to help marketers like myself uncover insights quickly and plan more efficient campaigns.

Bottom line: YouTube is providing brands and agencies more data on trends, creators, and campaign performance. Using Gemini, these insights can be transformed into more robust creative and media decisions.

Inspired by this post on Search Engine Land.

June 23, 2026
Master Google Ads: New Bid Strategy Updates Revealed

I’ve come across important news about Google Ads that could significantly impact how we manage our campaigns. Google is on the verge of altering its target-based bidding strategies, particularly for campaigns running on limited budgets.

Mark your calendar for August 17th when these changes will take full effect. But don’t worry, a Bid Target Adjustment Tool will be available as of July 6 to help us prepare and adjust our goals accordingly.

What’s going on? Google’s update aims to closely align target-based bidding strategies such as Target CPA with our set goals, even when budget constraints come into play.

They’re introducing a new tool that allows us to tweak our targets before the updates hit, which is crucial for maintaining our campaign performance.

Why should we care? If your campaigns are currently exceeding their target CPA or ROAS goals, they might not continue to do so post-update without adjustment. This update is meant to ensure budget-constrained campaigns stay true to their targets.

For example, if my campaign is achieving a $5 CPA against a $10 target, the performance might shift towards $10 unless I make some changes.

Thankfully, the new tool is there to help us proactively update our bidding goals before the changes roll out. If we don’t take advantage of this, we might end up paying more per conversion or see our performance realign with Google’s targets instead of our historical results.

Why is Google doing this? Google wants to reduce fluctuations and provide more predictable results when we tweak or adjust our budgets.

The tool is designed to help us synchronize our bidding targets more closely with actual business outcomes before the automatic implementation begins.

What should we do? It’s a good time for us to reevaluate campaigns using target-based strategies and verify if our current targets still align with desired results.

Notifications will be sent through Google Ads accounts before the update, and the Bid Target Adjustment Tool can highlight which campaigns might be affected.

Key takeaway: For those of us with campaigns that consistently outperform their targets, maintaining current performance might require tweaking target settings instead of leaving them unchanged.

Bottom line: Google is tightening the link between target-based goals and campaign performance. It’s now more essential than ever for us as advertisers to keep bidding targets updated consistent with our business objectives.

Inspired by this post on Search Engine Land.

June 22, 2026
Teaching AI Who You Are: The New Frontier for SEO

Recently, I dove deep into a 2023 Google patent that outlines how AI systems could evolve to grasp a deeper understanding of businesses, brands, products, and other entities by drawing from websites and public data.

This patent details a method for AI to extract information, recognize relationships, and eventually create what Google refers to as a ‘deep, holistic characterization’ of an entity.

As AI systems hold more sway in search results, it seems our SEO strategies might need to pivot. We may need to ensure that Google comprehends not just what we say, but who we truly are.

Historically, Google has been helping users discover information published on webpages for more than two decades now. But with their search products becoming more conversational and driven by recommendations, just understanding individual documents doesn’t seem to cut it anymore.

For AI to efficiently suggest a business, compare products, or detail a brand, it first needs to understand the entity standing behind the content.

This is where Google’s intriguing ‘Data extraction using LLMs’ patent comes into the picture. On the surface, it might seem like your everyday content extraction tool, yet Google speaks of a larger ambition here.

The patent posits that AI should help build and enrich a comprehensive, nuanced profile of a specific entity. Google’s definition of an entity stretches across people, businesses, places, objects, and concepts.

Rather than merely skimming facts or indexing content, the system aims to interpret data, connect relationships, produce summaries, and ultimately grasp the entity those details represent.

To illustrate this, the patent includes diagrams showcasing how AI processes various information sources and forms an understanding of an entity’s identity, attributes, and relationships.

This AI-driven model of entity understanding transforms traditional SEO strategies by focusing not just on page content but on the holistic representation of a business or product across multiple platforms and data points.

The patent’s strategy involves capturing and interpreting information across diverse media and formats, underscoring the need for brand consistency across all public communications.

If you’re anything like me, tapping into this new perspective in SEO involves analyzing your own digital footprint, ensuring your brand’s story, values, and attributes are consistently communicated across all channels, including your website, social media, and third-party platforms.

Both local businesses and large enterprises could benefit substantially from this approach by presenting a coherent digital identity. When Google’s AI can accurately piece together who you are, you’re more likely to be the name that AI recommends.

Ultimately, this shift in SEO from focusing on isolated webpage optimization to fostering comprehensive entity understanding presents a new challenge—creating an intertwined digital narrative of who you are and what you offer.

Inspired by this post on Search Engine Land.

June 22, 2026
Unlocking Reddit’s AI-Driven Ads: A New Era in Digital Marketing

I’ve always been fascinated by how social platforms can transform advertising, and Reddit has just taken a giant leap in that direction. They’ve unveiled cutting-edge AI-powered tools, crafted from the heartbeat of community discussions, to revolutionize how advertisers engage with audiences.

Reddit’s introduction of these tools is a bold move, leveraging insights from an astounding database of over 25 billion posts and comments. These tools aren’t just about targeting; they’re about understanding the pulse of their community to craft campaigns that truly resonate.

What excites me is how Reddit is helping brands create campaigns that not only capture attention but also quicken consumer purchase decisions. This is achieved by tapping into the genuine stories and sentiments shared on Reddit every day.

For those of us focused on authentic engagement, these new tools turn community conversations into compelling ad narratives and dynamic shopping experiences. Imagine your brand messaging reflecting real user sentiment, appealing directly to a high-intent audience.

The creative tools they’ve released are nothing short of groundbreaking. The free-form ad generator in beta brilliantly combines your website data with Reddit’s rich conversations, crafting ads that feel perfectly at home on the platform.

Moreover, the tailored creative assets—also in beta—use AI to identify specific communities, generating headlines and visuals that strike a chord with every view. It’s personalized advertising on a whole new level.

Now generally available, the Redditor Highlights feature lets brands include authentic Reddit discussions directly in their ads. Seeing community sentiment front-and-center adds a layer of trust and credibility that users crave.

In the arena of shopping ads, Reddit is testing a new ad format that showcases products in carousel style—matching them to ongoing user discussions and creating a seamless shopping experience.

On the technical side, Reddit is pushing boundaries with enhanced ad performance through innovative machine learning applications, highlighted by a 130% boost in view-through rates and a 71% increase in video completion rates during early tests.

For me, the power of merging machine learning with Community Intelligence seems to unlock endless possibilities for strategic ad targeting and execution.

The bottom line is clear: Reddit doesn’t just want to be a part of the consumer journey—they want to redefine it. By turning everyday conversations into valuable advertising content, they’re empowering brands like never before.

Inspired by this post on Search Engine Land.

June 22, 2026

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