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SearchGPT Is Coming. What Brand Visibility in AI Chat Tells Us About the Evolution of SEO

SearchGPT Is Coming. What Brand Visibility in AI Chat Tells Us About the Evolution of SEO

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How could SHEIN optimize for generative AI, given that its brand is barely mentioned when AI chatbots are asked for affordable fashion recommendations?

The rise of Generative AI (GenAI) chatbots like ChatGPT is reshaping online search and shopping experiences – a trend likely to accelerate with OpenAI’s announcement of a SearchGPT prototype search engine that it plans to eventually fold into ChatGPT.

These chatbots are increasingly being used by consumers to research brands and products, as shown by an analysis of affordable fashion options, as demonstrated by Similarweb data. And while both search and GenAI chat are ways that consumers can discover information, the way they function is different.

We were particularly interested to find a significant gap between consumer awareness of brands like SHEIN – which has been in the news because of an impending IPO – and how little they were mentioned when consumers asked for a recommendation. Although AI chatbots represent a new mode of searching for information, they will inevitably demand a new generation of SEO techniques from brands wanting to get noticed.

In custom research for clients, Similarweb has begun sampling queries entered into ChatGPT and similar services and the answers they produce.

Understanding the Data

The charts included below illustrate two aspects of GenAI questions and answers:

  1. Share of Branded Prompts within Affordable Fashion Queries on GenAI Chatbots
  2. Share of Brand Mentions in Answers to Affordable Fashion Questions

Share of Branded Prompts within Affordable Fashion Queries

Our first chart looks at how often brands are mentioned by name in a sampling of prompts entered into GenAI platforms.

share of branded prompts with affordable fashion chatbots

From this chart, it’s evident that certain brands dominate consumer searches for affordable fashion on GenAI platforms. Here’s the breakdown:

  • SHEIN leads with 37.04% of the total GPT searches.
  • TEMU follows closely with 31.11%.
  • H&M and ASOS hold 12.59% and 9.63% respectively.
  • ZARAFashion Nova, and Cider capture smaller shares, indicating less frequent mentions in user queries.

This data signifies the popularity and consumer trust towards these brands when seeking affordable fashion solutions. What’s also clear is that nearly two-thirds of consumers did not ask for any brand by name and were truly looking for a recommendation.

Share of Brand Mentions in Answers to Affordable Fashion Questions

When consumers ask GenAI chatbots to recommend an affordable clothing brand, what brand do they recommend? That’s what this next chart shows.

chart: share of brand mentions in affordable fashion answers

In summary:

  • H&M dominates the answers with an 88.89% share.
  • ASOS and ZARA are also prominent with 48.89% and 45.93%, respectively.
  • Interestingly, SHEIN, despite its high search volume, only appears in 9.63% of the answers.
  • TEMU is absent from these results, with a 0% answer share, despite being the brand consumers are second most likely to mention in branded queries.

Search and sentiment

Share of neutral vs negative searches

Lastly, this slighting of certain brands really it is a chatbot thing. The lack of recommendations does not come from previously input negative branded queries. In fact, as per the above chart, despite frequent backlash of the Chinese platform by the public opinion, recent analysis conducted on Shein branded queries highlighted that only 2% of them were negative (for example: “shein prices increase”, “as i add items”, “how to return orders from shein”, or “how shein is bad”).

Key Insights and Implications

The disparity between search queries and responses highlights a crucial gap. While consumers more frequently search for brands like SHEIN and TEMU, the GenAI chatbot responses favor H&M, ASOS, and ZARA. This discrepancy suggests an opportunity for brands to optimize their presence in GenAI responses.

Why Optimizing for GenAI Matters

  1. Consumer Trust and Engagement: Being referenced in chatbot responses builds consumer trust and increases brand engagement. When consumers see their queries consistently met with answers from certain brands, it reinforces their perception of these brands as reliable sources for affordable fashion.
  2. Visibility and Conversion: Higher visibility in GenAI answers can lead to increased website traffic and higher conversion rates. Brands that dominate chatbot responses are more likely to drive consumers to their websites and convert queries into sales.
  3. Competitive Advantage: Brands that optimize for GenAI can gain a competitive edge. By ensuring that their products and brand information are easily accessible and favored by GenAI algorithms, they can capture a larger market share.

Strategies for Brands

To bridge the gap between search queries and chatbot answers, brands need to implement the following strategies:

  1. Content Optimization: Ensure that content is well-optimized for GenAI algorithms. This includes using relevant keywords, providing detailed product information, and maintaining updated inventory data. In other words, brands should keep doing many of the same things they do for SEO, but with a parallel cycle of testing the impact of those efforts on GenAI as opposed to search and iterating to improve results.
  2. Partnerships with AI Platforms: Collaborate with GenAI platforms to understand how their algorithms prioritize responses. This can involve direct partnerships or leveraging AI-specific SEO practices.
  3. Customer Feedback and Adaptation: Regularly gather and analyze customer feedback to adapt and refine strategies. Understanding why consumers search for certain brands and what they expect in responses can help tailor content to meet these needs.

“The emergence of GenAI channels has dramatically increased the fluidity of consumer behavior, creating numerous new touchpoints for brand discovery and decision-making. While traditional search engine optimization tactics—such as content creation, review management, technical SEO, and semantic relationships — have long been effective, they may not directly translate to GenAI platforms. This shift presents both opportunities and challenges for brands. To succeed in this evolving landscape, companies must develop innovative strategies specific to GenAI while ensuring a cohesive brand message across all mediums, both traditional and emerging. This integrated approach is crucial for maintaining brand consistency”

– Baruch Toledano, VP and General Manager of Digital Marketing Solutions, Similarweb

Conclusion

Similarweb data underscores the importance of optimizing for GenAI in the affordable fashion sector and in all industries. Brands that can effectively align their search presence with chatbot responses will not only enhance their visibility but also drive consumer trust and engagement. Finding the right formula will require experimentation, but brands cannot afford to ignore the need to ensure they will be not only found but recommended when consumers look for answers from GenAI chatbots.

Image by Alexandra Koch from Pixabay

author-photo

by Inès Durand

Inès provides market research insights in Retail, CPG, and Financial Services. Her work has appeared in Retail Today, CNBC, and AFP.

This post is subject to Similarweb legal notices and disclaimers.

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