Future-Proofing E-Commerce SEO for 2026 and Beyond with Ross Hudgens & Will Critchlow

In this session, Will Critchlow (CEO, SearchPilot) sat down with Ross Hudgens (Founder & CEO, Siege Media) to explore how e-commerce brands must adapt their SEO strategies in an AI-driven world. From high-fidelity content and digital PR to advanced measurement techniques, they covered the tactics and mindset shifts needed to thrive through 2026 and beyond.

Going from Generic Blog Posts to High-Fidelity Content Experiences

In the past, simple listicles and templated articles could attract links and rankings with minimal effort. Today, AI-powered tools generate that same boilerplate content instantly, making it harder for generic content to stand out. 

What attracts both human visitors and ultimately impresses automated agents is bespoke, high-fidelity content that integrates custom visuals, interactive tools, and subject-matter expertise. Ross Hudgens explains that interactive product charts and on-page calculators require precise data integration and design finesse. These are qualities that generic AI output cannot replicate. 

These assets not only perform better in traditional search results but also earn links and unlinked brand mentions, which feed AI models and improve brand authority over time.

Elevating Brand Authority with Digital PR and Co-Citation Signals

Digital PR has grown rapidly as Google’s systems place increasing weight on unlinked brand mentions and co-citation patterns when assessing authority. Yet many teams rush into outreach campaigns without first ensuring their own content is compelling. 

Ross notes that publishing original data studies or multimedia storytelling pieces generates more sustainable coverage than scattershot link requests. When those publications mention your core products alongside authoritative brands or influencers, they produce co-citation signals that elevate your brand in search summaries and AI knowledge graphs. This approach multiplies the impact of each content investment, generating both direct referral traffic and indirect AI-driven recommendations.

Rethinking Analytics to Capture Dark Traffic and AI Referrals

Traditional analytics methods are challenged by visits that carry no referrer string and by AI-driven overviews that mask source information. To adapt, teams should:

• Break down traffic by channel: separate Google organic, product search formats such as Google Shopping, and visits driven by AI summaries.
• Aggregate those streams into an “all-source” view to capture every click, even when it appears as direct or dark traffic.
• Invest in dedicated analytics expertise to build attribution models with statistical confidence rather than relying on gut instinct alone.
• Continue monitoring the evolution of measurement options as more data becomes available (e.g. in Search Console).

This comprehensive approach uncovers the true impact of both classic SEO work and AI-powered recommendations.

Capturing Homepage and Brand Search Gains from AI Overviews

Siege Media’s internal research showed that B2B brands saw homepage traffic increase by up to ten percent after launch of AI summaries, with e-commerce sites experiencing lifts of around eight percent. These gains result from AI assistants surfacing the homepage as a brand entry point. 

Specialized tool-style pages such as converters and calculators remain largely unaffected, since AI summaries have not replaced those niche functions. Investing in genuinely useful on-site tools therefore yields both organic ranking improvements and new AI-driven referral volume.

Embedding SEO into Product and UX Development

The most durable source of SEO advantage comes from direct collaboration with product and UX teams. When every SKU or feature is treated as a mini content asset - complete with rich schema, clear naming conventions, and user-centric filters - the entire catalogue becomes discoverable to shoppers and AI agents alike. Embedding SEO specialists in product roadmap planning accelerates enhancements in:

• Treat each SKU as a content asset by embedding price, stock and review schema directly into your product CMS instead of bolting it on afterward
• Bake SEO into faceted navigation so category and filter combinations render clean HTML URLs that both shoppers and AI crawlers can index, avoiding messy query-string parameter.
• Collaborate on site performance by co-owning image compression, lazy-loading patterns and CDN configuration with the product team to ensure every PDP update ships at peak speed

By weaving SEO into your site’s architecture, you make discoverability a built-in feature rather than an afterthought.

Leveraging User Reviews for Long-Tail Visibility

Even the most advanced AI models rely on real-world user feedback to answer hyper-specific queries.LLMs can’t try the product out for themselves! Brands that scale post-purchase review collection boost long-tail visibility and supply raw data for AI summaries. Strategies include:

• Partnering with affiliate sites to generate in-depth reviews
• Adding review-gathering widgets to every product page
• Encouraging customers to submit photos and detailed feedback
• Ensuring that reviews and ratings are available in the served HTML without relying on JavaScript

A robust review repository supports dynamic pages tailored to micro-segments, yielding additional SEO wins and reinforcing AI agent recommendations.

Maintaining Agility Through Continuous Optimization

In an environment where AI capabilities evolve weekly, continuous optimization becomes essential. Will and Ross stressed the importance of disciplined goal setting that blends:

• Process-oriented targets, such as publishing two data studies each quarter or running 5 tests a month
• Achieve an 8–10 percent lift in homepage impressions driven by AI overviews by the end of Q3

Time-blocking strategic work in a “perfect calendar” and holding regular progress reviews help teams stay on track without burning out. Cross-functional squads combining expertise in SEO, analytics, design, and product ensure rapid adaptation to algorithm changes, AI feature rollouts, and shifting consumer preferences.

Stay Ahead of AI-driven search with SearchPilot’s SEO A/B Testing

Preparing your e-commerce site for an AI-driven future requires integrating SEO across every aspect of your brand, from custom content creation and digital PR to product catalog optimization and advanced analytics. 

It’s key, as you evolve your site for this new future, that you ensure that you’re not harming your traditional search performance, and that you are making changes that actually help your AI search visibility. It’s a complex and opaque system, and it’s not really possible to figure out from the outside how it works. This is where testing comes in!

Interested in preparing your organization for this next generation of search? Schedule a free SEO session with SearchPilot’s expert team. Learn how data-driven SEO testing can empower your business to adapt confidently and succeed in the evolving search landscape.