As AI agents grow in popularity, retailers are reportedly spending to attract their attention.
“We’ve seen brands that previously were putting out three or four new blog posts or articles a month, are now trying to do 100 or 200,” Brian Stempeck, chief executive at generative engine optimization platform Evertune.ai, told Reuters Wednesday (Nov. 26).
That company, the report says, works with companies to make their websites more discoverable by artificial intelligence (AI) large language models (LLMs), charging roughly $3,000 a month to customers that include shoe and apparel sellers.
As Reuters notes, retailers had traditionally based their ad placements with Meta and Google on phrases that users searched or links they had clicked. But without the ability to advertise in the largest generative AI tools, these businesses have turned to new methods, like posting more often on branded blogs or writing about their products on Reddit.
Meanwhile, larger retailers are creating websites that can’t be seen by shoppers but are designed solely to be read by AI scrapers that feed information to platforms like ChatGPT and Gemini, which then suggest gift ideas.
The report also points out that while traffic from AI platforms to retail websites remains miniscule, retailers nonetheless see an opportunity. For example, bed linen company Brooklinen has begun to pay social media influencers to talk about its bath towels and comforters on platforms like Facebook, YouTube and TikTok, Chief Operating Officer Rachel Levy told Reuters, hoping to get the attention of AI scrapers.
She added that traffic from agentic AI sources is “super small,” as Gen Z, the biggest adopter of tools such as ChatGPT, has less buying power than its older counterparts.
PYMNTS explored the way agentic AI is changing the eCommerce space earlier this year in a conversation with Kumar Senthil and Scott Hendrickson, founders of agentic AI merchant network firmly.
As that report noted, the role of the AI agent is not simply to fetch information but to carry out actions on behalf of the customer, from adding an item to cart to completing payment. The technology combines an LLM’s knack for understanding natural-language requests with direct connections with merchant catalogs and payment rails.
“What consumers really want is for commerce to happen immediately,” Hendrickson said in an interview with PYMNTS CEO Karen Webster. “People’s time has never been more valuable, and they expect things to be frictionless.”
Source: https://www.pymnts.com/
