Machine Learning

BrightonSEO San Diego has been an amazing personal experience and a treasure trove of insights into the evolving world of SEO and search technologies. From brand-entity optimization to leveraging LLMs for content strategies, the conversations at the event underscored how marketers need to adapt to shifting paradigms in search behavior and technology. Here’s what I learned and how it will shape our approach at WordLift.

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Key Takeaways

1. The Importance of Brand-Entity Optimization

In today’s omnichannel world, optimizing for brand entities is no longer optional—it’s essential. As Marcus Tober highlighted, platforms like Reddit are pivotal for brands like Cloudflare, helping them not only answer user queries but also secure top spots on search engines for those questions. This integration of brand presence across forums, structured data, and search results is a perfect example of brand-entity optimization at work.

The challenge lies in converting entities in a knowledge graph into features or entities recognized by language models. Achieving this requires monosemanticity, a term I’ll explore further in an upcoming article. Simply put, monosemanticity ensures that entities are uniquely identifiable, both for humans and machines—a cornerstone for successful brand-entity optimization. The brilliant Crystal Carter in a recent blog (SEO for brand visibility in LLMs) post wrote:

“Entities form a core component of LLM training and that brands with robust entities will have high visibility within LLMs” — Crystal Carter

Fabrice Canel’s presentation on the Bing ecosystem highlighted also quite interestingly that not all clicks are created equal. AI-driven clicks, while fewer in number, lead to much higher engagement and conversion rates compared to traditional search. This shift requires a deeper focus on building meaningful connections between entities, as those connections are what truly drive value in AI-optimized search experiences.

Here’s an example of how brand-entity optimization can help your brand be discovered on Google for key search intents, such as “AI-powered SEO tools” for a solution like WordLift.

2. Creating LLM-Friendly Content

The era of “write-for-humans-first” is evolving into “write-for-humans-and-algorithms-equally.” Large Language Models (LLMs) thrive on structured, precise, and rich content (see Marcus’ example on why brands shall invest on Reddit). Discussions with the always insightful Mike King, Jordan Koene, and Martha van Berkel reaffirmed that creating content tailored for algorithmic audiences—whether through structured data or topic clusters—is no longer optional; it’s a tactical necessity. Mike argued that Google remains well-positioned to lead the pack, though this could change if government efforts to break up the company succeed.

This is where llms.txt comes into play—a proposal to help LLMs better understand websites. Much like robots.txt helps search engine crawlers, llms.txt is a markdown file that provides brief, structured background information and guidance specifically for language models. WordLift has already adopted this standard, as we recognize its potential to bridge the gap between our content and LLMs. Think of it as a way to create an AI-friendly “map” for your brand’s identity and offerings.

Marcus Tober’s projection that ChatGPT could rival Google’s dominance in four years—driven by a 13% month-over-month growth rate—further underscores the urgency of creating content that resonates with LLMs. Structured content isn’t just an advantage; it’s becoming a necessity.

It was incredibly exciting to finally meet Fabrice Canel in person and discuss Bing’s data ingestion pipeline, the significance of IndexNow, and how to leverage it to optimize traffic for news content.

Thanks Fabrice for the insightful conversation we had.

3. KPIs Need a Revamp: Follow the Money, Not the Clicks

With generative AI driving an estimated 50% reduction in organic search traffic by 2028 (as per Gartner), the SEO community faces a critical question: Are we still optimizing for 2023’s metrics in 2024? The short answer is that we shouldn’t be.

Will Reynolds’ session drove home the importance of rethinking metrics. Love this slide by the way 😉. 

Traditional KPIs like rank and CTR are becoming less effective measures of success in an environment increasingly influenced by AI and generative search experiences. Instead, marketers must shift their focus to insights that capture visibility and impact within AI-assisted search. Some of Will’s proposed metrics include:

• Query word count trends: Analyzing paid search query data to understand shifts in user behavior, particularly as users adopt more conversational and detailed queries in generative search.
• Chat visibility tracking: Using tools like Google Sheets and ChatGPT to measure a brand’s presence in AI-generated answers and conversational interfaces.
• Market share in chat search: Gauging competitor visibility in AI-assisted search environments to identify opportunities and threats.

We cannot wait for search engines to provide data on these metrics; instead, we must innovate and experiment with proxies and tools to stay ahead. For example, tracking changes in query length or using automated workflows to scale visibility tracking in chat search are immediate steps we can take.

That said, Google is not going away. Rand Fishkin’s closing remarks emphasized this point: while the landscape is shifting, traditional search engines still dominate the scene. As Datos’s latest data shows, Google continues to drive the lion’s share of clicks, and generative AI has not yet changed the overall landscape in any dramatic way. However, this balance could eventually tilt, especially if external pressures—like the DOJ’s efforts to break up Google and address its unfair distributional advantage—gain traction.

The challenge for SEOs lies in navigating this transitional period. While Google remains dominant, the shift toward AI-driven search behavior is inevitable. This means search marketers must optimize for both current realities and future possibilities. By aligning with new metrics and preparing for a post-Google-dominated world, we can ensure continued relevance and success.

Looking Ahead and Personal Notes

BrightonSEO reinforced my belief that SEO is at a crossroads. With the rise of LLMs and generative AI, the tactics of yesterday will not suffice. At WordLift, we’re doubling down on:

• Data Modeling: Ensuring our knowledge graphs enable monosemanticity for seamless integration with LLMs. 
• Content Modeling: Focusing on the right meaningful concepts also referred to as features to be associated with our brand-entity. This is meant to both evaluate and facilitate the understanding of our entities by LLMs.
• Dynamic Content Creation: Crafting content that satisfies both human readers and algorithmic audiences across the customer journey.
• Forward-Thinking Metrics: Developing new ways to measure visibility and impact in a generative AI-driven world. SEO is about driving business impact, not traffic.

In the words of Mike King: “Visibility is just the start. Impact is the end game.” The SEO community’s ability to adapt will define its relevance in this new era. 

A heartfelt thank-you goes out to all the amazing friends I had the pleasure of meeting during the hectic two days of the conference. In no particular order: Steve Wiidman, Michael King, Martha van Berkel, Chris Shin & Jeff Preston (special thanks to both for the time we spent together), William Sears, Tom LeBaron, Michele Robbins, Cindy Krum, Eric Wu, Jackie Chu, George Nguyen, Noah Learner, Ray Grieselhuber, Michael Bonfils (whom I first met in San Diego after hearing so much about), Kristine Schachinger, Cameron Taylor and the many others that I might have forget to mention. 

I am also incredibly grateful to our fantastic team. Bravissima Silvia Fratini for putting up with both David Riccitelli and myself! It was, of course, great fun working with David last minute to finalize Agent WordLift’s upcoming Chrome extension and seeing how it helps optimize for Google’s AIO. That was truly a blast! It was equally refreshing to hear so many people stopping by our booth and saying, “This is exactly what I need!“. 

A special thank-you goes to our US team and Armando Biondi, whom we had the pleasure of meeting in New York. His support is inspiring us to dream big as we venture into this incredible new market.

As Black Friday approaches, retailers focus on optimizing strategies for the year’s biggest shopping event. Yet, many fail to leverage Shopping Loyalty Programs on Google Merchant Center, a powerful tool to enhance visibility, boost sales, and strengthen customer relationships. Available to merchants in the US, Australia, and Japan, loyalty programs integrate seamlessly into Google’s ecosystem, offering a technical yet impactful solution to drive performance.

Are You an SEO Professional? WordLift offers powerful tools to help you improve rankings, optimize websites, and deliver results for your clients. Book a demo today to discover the difference.

How Shopping Loyalty Programs Work

Shopping Loyalty Programs operate across three core pillars:

1. Comprehensive Benefit Coverage
   Loyalty benefits are gathered from Merchant Center, third-party integrations, and website crawling, ensuring all program perks are accurately reflected.
2. Google Ecosystem Integration
   Benefits are displayed across platforms like Search, Shopping Tab, Ads, and even GPay and YouTube, giving broad exposure to loyalty perks.
3. Personalized Member Experiences
   User data from merchants, Gmail, and Wallet powers tailored shopping experiences, creating stronger engagement and repeat purchases.

Together, these pillars enable retailers to craft wide-reaching, personalized programs that resonate with users.

A Strategic Advantage for All

Loyalty programs benefit all stakeholders in the shopping ecosystem:

• For Shoppers: Exclusive pricing, free shipping, and loyalty points improve the buying experience and incentivize engagement.
• For Retailers: Increased conversions, high-value customer retention, and compliance with data privacy standards.
• For Google: Enhanced user experience, greater platform loyalty, and opportunities to drive incremental ad revenue.

This synergy strengthens trust and ensures consistent engagement across Google’s platforms.

Boost Black Friday Sales with Loyalty Programs

Loyalty programs effectively attract more shoppers by prominently displaying perks like member discounts and free shipping directly on product listings. For example:

• Retail Stores: Highlight exclusive discounts available only to loyalty members.
• Brands: Offer free delivery and special pricing for enrolled customers.

By showcasing these benefits, your offers become more competitive, driving increased clicks and sales during Black Friday.

Boost Engagement with Loyalty Annotations

Loyalty annotations in shopping units improve engagement by clearly highlighting member benefits. These perks—such as discounts, loyalty points, and personalized offers—encourage customers to sign up and increase conversions.
Displaying loyalty annotations directly in product listings helps attract more shoppers and strengthens customer relationships, making them an essential tool for Black Friday campaigns.

Google Integrates Loyalty Benefits into Search Results

Google has expanded its integration of loyalty programs by showcasing loyalty benefits directly in search results, transforming how shoppers interact with listings.

Why This Integration Matters

• Increased Visibility: Exclusive pricing and free shipping perks are now visible at critical decision-making points.
• Enhanced Engagement: Shoppers are more likely to click on listings with clearly displayed loyalty benefits, driving higher-quality traffic.
• Competitive Advantage: Retailers that display loyalty perks in search results gain an edge, particularly during Black Friday’s competitive landscape.

This integration positions loyalty programs as a key driver of visibility and customer acquisition.

Are You an SEO Professional? WordLift offers powerful tools to help you improve rankings, optimize websites, and deliver results for your clients. Book a demo today to discover the difference.

Boost Visibility with Member Pricing in Search

Member pricing displayed directly in search results improves visibility and encourages customers to join loyalty programs for access to exclusive deals. For example, a retailer offering special member-only prices motivates shoppers to sign up and unlock savings.

During Black Friday, showcasing member pricing can drive more clicks, boost conversions, and foster long-term customer loyalty, making it a critical strategy for maximizing sales.

Drive Sales with Shipping Benefits for Loyalty Members

Shipping perks are one of the most effective loyalty features during high-traffic events like Black Friday. Offering free or fast shipping can attract new members and retain existing customers.

Key Shipping Benefits

• Free Standard Shipping: Simplifies purchasing decisions and reduces cart abandonment.
• Express Shipping: Enhances customer experience by providing faster delivery options.

Why It Works

Displaying these perks in search results or product listings creates a strong value proposition, encouraging sign-ups and purchases. For Black Friday, this strategy helps brands stand out by offering added convenience and value.

How to Set Up a Loyalty Program in Google Merchant Center: Step-by-Step

Creating a loyalty program in Google Merchant Center is a straightforward process. Here’s how to set it up:

Step 1: Access the Loyalty Program Setup

• Log in to your Merchant Center account.
• Go to Growth > Manage Programs and select the Loyalty Program option.

Step 2: Enter Basic Program Details

• Add a program name, ensuring it’s customer-friendly and concise.
• Create a program label for use in your feeds.
• Write a short description of member benefits (e.g., “Earn 2 points per $1 spent”).
• Provide a sign-up URL where users can enroll.

Step 3: Add Program Levels

Define membership tiers, such as:

• Basic Level: Free to join with standard benefits.
• Premium Level: Requires specific criteria, such as a spend threshold, offering enhanced perks.

Include details like:

• Level Name: Visible to shoppers.
• Level Label: Used in product feeds.
• Level Requirements: Conditions to qualify for the tier.

Step 4: Add Benefits to Each Level

For each membership tier, add specific perks:

• Loyalty Points: Define points earned per purchase (e.g., 5 points per $1).
• Free Shipping: Offer benefits like free standard or express delivery.
• Other Custom Benefits: Tailor additional perks to enhance the value of your program.

Step 5: Submit for Approval

• Review all program details and submit them for approval.
• Google reviews the program for compliance, with approval typically taking 48 hours.

This process ensures your loyalty program is ready to drive engagement in time for Black Friday.

How to Enable Loyalty Benefits Using Product Data

To display loyalty benefits effectively, retailers can assign details through supplemental feeds. This ensures accurate representation of benefits in search results and product listings.

For a Single Loyalty Program

Assign a loyalty program name, level, and relevant perks (e.g., member price, loyalty points).

For Multiple Loyalty Levels

Add multiple tiers with unique benefits for each level. For example:

• Basic Level: Offers a discounted price with 10 loyalty points.
• Premium Level: Includes a deeper discount and 20 points per purchase.

Key Considerations

• Ensure program names and levels match those set in Google Merchant Center.
• Accurately link benefits like pricing, shipping, or points to each product.

This structured approach makes loyalty perks more attractive and ensures they are displayed seamlessly in shopping results.

Conclusion

Shopping Loyalty Programs in Google Merchant Center are a powerful yet underutilized tool for retailers. By integrating loyalty benefits such as member pricing, shipping perks, and loyalty annotations into search results and product listings, retailers can significantly enhance visibility and engagement during Black Friday.

These programs provide a valuable opportunity to streamline data integration, enhance click-through rates, and deliver tailored shopping experiences. With simple implementation processes and the ability to showcase benefits effectively, loyalty programs are a powerful tool for driving success during Black Friday.

The media landscape has been greatly influenced by the introduction of AI tools that produce content at scale, so staying visible and relevant has never been more important. The growing influence of AI is changing how audiences discover and trust content. 

Recent insights reveal a fascinating trend: 16.5% of Google search users now use AI platforms to access information and news. For many, these platforms offer a level of relevance and trustworthiness that traditional search engines struggle to match.

In fact, 37% of users engaging with AI-generated results report finding them more reliable or relevant than conventional sources. This perception of AI as a trusted guide extends even further, with 55% of users believing these platforms make it easier to uncover high-quality, trustworthy content.

This shift is rewriting the rules for publishers. AI discovery is no longer a side trend; it’s becoming a primary way people connect with the stories and information they value most. This is both a challenge and an opportunity for publishers and editorial teams: a chance to adapt to new ways of building trust, engaging readers, and standing out in a crowded digital space.

Let’s explore how publishers can embrace these changes and succeed in this new environment.

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Understanding the New Reality of AI in Publishing

AI has transformed the way people interact with information. Tools like AI assistants and chat platforms are increasingly handling tasks that were once the domain of traditional search engines, reshaping how content is accessed. But with this transformation comes challenges:

• Eroding Trust: AI-generated content sometimes prioritizes consensus over accuracy, which can mislead audiences and decrease confidence in digital information.
• Audience Fragmentation: Readers now navigate a complex landscape that includes AI platforms, search engines, and aggregators.
• AI Disintermediation: Content served directly through AI bypasses publisher platforms, reducing site traffic and making it harder to connect with audiences directly.

To navigate this environment, publishers must re-establish their authority by focusing on trust, relevance, and visibility.

Rebuilding Trust Through Verifiable Content

Trust is the cornerstone of successful publishing, and AI’s limitations in fact-checking make this an area where human publishers excel. Readers value credible, accurate information—and search engines and AI platforms reward it too.

To rebuild and maintain trust:

• Emphasize Fact-Checking: Verified content isn’t just good journalism; it’s also good SEO. Fact-checked articles are more likely to be featured in snippets and highlighted by AI-driven tools. Read more about fact-checking and AI.
• Highlight Expertise: Use structured data to connect articles with their authors. By showcasing the credentials and expertise of your writers, you strengthen your content’s credibility. Learn about structured data for publishers.

This focus on accuracy doesn’t just build reader confidence; it also helps publishers stand out in a crowded digital ecosystem.

Why Structured Data Is Essential

Structured data may sound technical, but its purpose is simple: it helps search engines and AI tools understand your content better. By incorporating structured data into your articles, you make it easier for platforms to feature your content prominently in search results and AI-generated summaries.

For editorial teams, this means:

• Ensuring articles include author bios that highlight expertise, linking back to their profiles and past work.
• Using schema markup to clearly tell search engines what your content is about, making it easier for users to find!

Structured data not only boosts your visibility but also reinforces your authority, making your content a preferred choice for readers and platforms alike.

Adapting to the Zero-Click Future

As AI platforms provide answers directly, fewer readers click through to publisher websites. This shift can feel discouraging, but it also creates opportunities to adapt. Publishers can:

• Focus on High-Impact Content: Create articles designed to shine in featured snippets or AI summaries. Explore high-impact content strategies.
• Optimize for User Intent: Craft content that directly answers the questions your audience is asking, ensuring value even when users don’t visit your site.

By meeting readers where they are, you can remain a vital source of information in an AI-driven world.

Actionable Strategies for Editorial Teams

Here’s how publishers can start succeeding today:

1. Fact-Check Smarter: Use fact-checking tools and ensure all claims are supported by evidence. Verified content earns both trust and visibility. Learn about detecting AI-generated content.
2. Showcase Expertise: Make sure every article connects to an author with visible credentials. This simple step strengthens your brand’s reputation for reliability.
3. Leverage Data: Use tools that integrate structured data into your workflow, ensuring search engines and AI platforms can easily understand and recommend your content. Understand the role of knowledge graphs.
4. Analyze Reader Behavior: Study how audiences are finding and engaging with your content. Use this insight to adapt your strategy for AI discovery.

Looking Ahead: The Power of Adaptation

AI isn’t replacing publishers—it’s redefining the way audiences find and engage with content. By embracing these shifts and focusing on trust, personalization, and technical adaptability, publishers can not only survive but succeed in the age of AI.

The key lies in recognizing this moment as an opportunity to lead. Build credibility, optimize for new discovery methods, and position your brand as a trusted source of information. The future of publishing is here, and it’s yours to shape.