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In a May 2023 test, AI shopping assistants could hold a conversation and understand requests, but reviewers often disliked the products they recommended. The central problem was not whether the bots could chat; it was whether they could find something worth buying.
What the test found
Business of Fashion staffers gave assistants the same prompts and asked follow-up questions to gauge how they handled different shopping requests. The examples included outfits for a boat party in Europe, a graduation ceremony in Chicago and a cricket match near London. The assistants generally understood the requests and responded coherently, yet reviewers were often underwhelmed by the actual product suggestions. Marc Bain’s May 10, 2023 report is a qualitative snapshot, not a current review of these services.
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That distinction matters: a fluent answer can make an assistant feel capable even when its recommendations miss the occasion, style or other constraints. As one reviewer put it, “Can’t say I’m convinced.” Business of Fashion did not identify that reviewer by name.
Where recommendations worked—or missed
Boat-party outfits
For a summer boat-party request, one tester found Shopify’s suggestions somewhat more curated and sent a white button-front maxi dress to a friend. KNXT’s assistant, Madeline, did less well for another reviewer: it suggested Balenciaga looks the reviewer considered unsuitable for a summer boat party. In a separate search for Bottega Veneta menswear, Madeline still returned Balenciaga suggestions.
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Graduation clothes
Reviewers did not agree on a clear winner for a graduation-dress prompt. One preferred Madeline’s style suggestions but found its interface clunky; the same reviewer found Shopify quick and easy to use but disliked several of its suggestions. ShopWith AI’s graduation-dress options also failed to impress one tester.
A cricket match near London
Two testers said Shopify appeared to factor in weather. For the London-area cricket-match request, it suggested a raincoat—a useful example of local context influencing a recommendation, but not evidence that the assistant handled every location or event well.
Rank #2
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Personalization and persona prompts
Mercari’s assistant, Merchat, drew complaints that its recommendations were not sufficiently curated. One reviewer appreciated that it tried to account for a shopper who was 6 feet 3 inches tall; another found the number of questions frustrating. ShopWith AI’s Lenny Kravitz persona, meanwhile, performed better for a concert-outfit prompt than its graduation-dress suggestions did. A result that suits one persona or occasion does not establish broad recommendation quality.
Why a shopping chatbot can miss the mark
The catalogue may not fit the request
An assistant can only recommend from the products it can access. If a retailer’s catalogue has few suitable items, the results may be poor even when the prompt is clear. That leaves shoppers unsure whether the request was misunderstood or the available selection was the limiting factor.
Rank #3
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Context helps only when it improves the result
Asking about height, weather or the occasion can make suggestions more personal. But each extra question adds effort, and the Merchat reviewers’ mixed reactions show the trade-off: context gathering can be useful to one shopper and feel like friction to another.
Conversation is not the same as relevance
Some replies in the test sounded like marketing copy. Chat can help people ask for suggestions in ordinary language rather than search through filters, but persuasive or polished wording cannot make an unsuitable product relevant.
Rank #4
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How to judge an AI shopping assistant
The reported examples suggest practical questions to ask when trying any such tool. They are useful checks, not a formal scoring system used in the 2023 article.
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- Personalization: Does information such as fit or height meaningfully change the recommendations?
- Catalogue fit: Does the retailer carry enough suitable options for your request?
- Useful follow-ups: Does each question improve the results enough to justify the extra effort?
- Local context: Does the assistant account for details such as weather or location when they matter?
- Next steps: Can you easily inspect and act on a suggestion, rather than just receive a well-written reply?
What this 2023 test can—and cannot—tell shoppers
The test shows that conversational understanding and product relevance are separate challenges. Shopify appeared more convenient to one graduation-dress reviewer, while that reviewer preferred Madeline’s style suggestions; Shopify’s weather-aware cricket suggestion and ShopWith AI’s stronger concert-persona result were specific successes, not proof of consistent performance.
These observations are tied to the assistants and prompts reported in May 2023. The article does not establish whether Shop.ai, Madeline, Merchat or ShopWith AI remain available, or what their capabilities are now. It also reports qualitative reactions rather than a sample size, success rate or performance percentage, so its findings should not be read as a measured ranking.
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