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The Post-Traffic SEO Shift – Practical Ecommerce

Solega Team by Solega Team
June 2, 2025
in E-commerce
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Google’s new AI Mode highlights the dramatic changes in organic search. AI answers often eliminate the need to click, though users wanting more details must search unlinked brand names separately.

The result is massive shifts in optimizing for search engines:

  • Traffic is no longer a key ecommerce performance indicator, as many shoppers will make purchase decisions without clicking.
  • Optimizing for brand-name search is increasingly important because consumers often query a brand or product name, as AI answers don’t usually link to them.

Business owners are understandably concerned and unsure how to adjust SEO.

Here’s my overview.

Position Products

Generative AI platforms use external sources to recommend products and brands. Unless they encounter the benefits of a product or company, the platforms are unlikely to include or recommend them.

Thus an AI-driven SEO strategy includes creating and marketing “brand knowledge content,” which explains:

  • The brand’s unique value proposition.
  • Differences from competitors (e.g., price, quality, service, etcetera).
  • Targeted audience, including geographic focus.

The goal is to supply info to large language models about your business to increase its chances of being surfaced in AI answers for related consumer questions.

The example below is a chart from Google’s AI Mode comparing Zoho and HubSpot, two popular customer management platforms, in response to a query.

Comparison table from AI Mode summarizing key differences between Zoho CRM and HubSpot CRM, including customization, integration, user interface, AI capabilities, and pricing. HubSpot is noted for ease of use and advanced features, while Zoho is highlighted for customization and affordability.

Table from AI Mode comparing Zoho CRM to HubSpot. Click image to enlarge.

Brand Mentions, Backlinks

Brand mentions are as important as backlinks for genAI algorithms. ChatGPT, Gemini, and others rely on “similarity” and co-occurrence, i.e., where a brand name appears in a relevant context of a query.

Yet backlinks remain important for traditional organic search rankings, and genAI platforms also rely on those engines: Google, Bing, others.

Hence optimizing for AI search should include link building and brand marketing. The following tactics will help with both:

  • Co-citation link building, such as appearing or being linked in listicles alongside competitors.
  • Media outreach for generating links and mentions from reputable outlets.
  • Reddit community building: Participating in relevant subreddits or managing your own. Reddit can raise visibility with journalists, Google, and ChatGPT.

Solve Problems, not Keywords

Generative AI search engines use a so-called “query fan-out” technique. Google introduced the term, but other LLMs use similar methods.

This technique goes beyond direct answers. It includes related and follow-up concepts to provide a more detailed explanation and solve users’ problems more efficiently.

Keyword research remains essential for understanding shoppers’ journeys, but optimizing for those terms is more than including them in titles, headings, and body text. Think about the problems driving each keyword and address them with additional info on your page.

My GPT, “SEO: Search Query Analyzer,” can assist, as can ChatGPT and Gemini via this prompt:

My target keyword is [KEYWORD]. What follow-up questions and additional information would help my target audience searching on this query?



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