AI tools for e-commerce: which ones to compare

There are three families of tools, and they don't answer the same problem. The first, support and tickets, covers solutions like Gorgias and Zendesk: they centralise after-sales requests (returns, service, order tracking) and close them fast. The second, general-purpose chat, covers tools like Crisp and Tidio: a simple, accessible chat widget so you're reachable without heavy configuration. The third, advice that sells, covers solutions like iAdvize, Dialog and Ryma: the aim is not to close a request, but to help a visitor choose a product before they buy.

The difference fits in one sentence: one closes the request, the other leads to the cart. It is not a question of quality, it is a question of purpose. A well-tuned ticketing tool will close your after-sales requests efficiently. It will not recommend one serum over another to a hesitating visitor, because that is not its job.

Some tools straddle two families depending on how they're configured — Intercom, for instance, was born for SaaS support and has widened its use. The test to keep in mind: ask yourself « was this tool designed to classify requests, or to argue a product choice? » The answer decides the family.

The right tool is chosen from your main problem, not from a feature list. Here are the most common cases.

• Your problem is a volume of after-sales tickets (returns, order tracking, invoices) → look at the support family: Gorgias or Zendesk, built for commerce at volume (our line-by-line comparisons: Gorgias alternative, Zendesk alternative).
• Your problem is a SaaS product with technical questions → look at Intercom, more oriented to product support and software onboarding.
• Your problem is simply being reachable, on a small budget with little configuration → look at Crisp or Tidio, accessible general-purpose chats.
• Your problem is that visitors hesitate before buying and leave without advice → look at the advice-that-sells family: iAdvize (a French conversational-commerce player) or Dialog (a French general-purpose AI shopping agent).
• Your problem is specific to beauty and skincare (skin type, allergies, routines) → look at a sector-specialised solution such as Ryma, built for that sector precisely.

Nothing stops you combining two tools — one for after-sales, one for pre-purchase advice. That is often the right reflex, rather than asking a single tool to do everything.

Beyond the families, four concrete criteria let you compare two tools seriously.

Proof, not promise. A statistic attributed to a named, checkable study is worth infinitely more than a floating percentage with no source on a marketing site. For example, the bareMinerals case study published by Gorgias reports 8.8 times return on investment in the first month, and the Topicals one (skincare) measures sales driven by customer advice growing 78%. Those are figures you can find and check. Be wary of any figure a vendor cannot source.

Sector specialisation. A general-purpose tool can answer more or less anything, superficially. A tool specialised in your sector knows the questions that come back, the vocabulary of the trade, and the traps to avoid. In beauty, for instance, McKinsey (State of Beauty 2025) notes that people repurchase a product that kept its promise, well ahead of price: a tool that doesn't understand that misses the real buying criterion.

Bounded reliability. A good advice-that-sells tool must never recommend outside your catalogue, and must know when to hand over to a human on sensitive cases. That is a point to verify explicitly, not to assume.

Channels, and the real quality of the language. WhatsApp has become a central channel for many customer bases. Check too that the language the tool actually writes in is natural, not rough machine translation: it is often the first sign of a tool's real quality.

One reminder that should weigh on the decision: badly calibrated general-purpose chatbots rank, in France, as the least-liked channel of all, according to Ipsos BVA (5,000 people, 2025). And according to PwC (15,000 consumers), 32% of customers walk away from a brand they love after a single bad experience. A badly chosen tool is not neutral: it can cost you loyal customers.

For products that touch health or skin, health validation becomes criterion number one — ahead even of conversion. Bad advice on an allergy or an interaction is not a detail: it is a real risk for the customer, and for the brand.

Which is why a solution built for this sector has to rest on three verifiable pillars: being fed the official documentation of the major brands; working from a register of guidance reviewed and approved by health professionals (a dermatologist, a paediatrician, a pharmacist); and applying a fixed rule on sensitive cases (pregnancy, allergy, a complaint) — hand over to the retailer's team rather than answer in its place.

A concrete example of what that looks like in production: Beautymarket, the number one beauty and skincare store in Morocco (1,000,000 visitors a month, traffic measured by SimilarWeb), runs the Ryma advisor on a dermo-cosmetic catalogue including L'Oréal, La Roche-Posay, Vichy, Avène, Bioderma and CeraVe. In testing, 100,000 conversations were handled before going into production, with 70% of requests handled end to end with no human involvement. Those are measured figures, not estimates.

Worth noting too: the major brands (L'Oréal, La Roche-Posay, Vichy) have each built their own AI skin-assessment tool for their site. A specialised advice tool for your store doesn't replace those brand tools — it plays a different part, at the scale of your catalogue and your customer relationship. See the detail on the online skin assessment.

The best way to compare two tools is still to test them with the same trick questions, rather than trusting a prepared demonstration. Here is a list of questions to put to each vendor, or to test yourself on their public demo.

• « What happens if a visitor asks about an allergy, or during a pregnancy? » (check there is a real escalation to a human, not an answer generated on the fly)
• « Can you recommend me a product that isn't in my catalogue? » (a good tool must refuse)
• « What documentation are you drawing on to talk about this brand? » (a vague answer is a warning sign)
• « How long to go live: do you have an app to install on my store, or do I have to export my catalogue to you? »
• « Do I keep control of the conversations, and can I take any of them over at any moment? »
• « That performance figure you quote — which study or which customer does it rest on, and can I check it? »

A serious tool answers these simply and precisely. One that dodges, or promises an answer to everything with no limit, deserves your suspicion. To go further on reliability and the regulatory frame, see our page on reliability, GDPR and responsibility. And if you are on Shopify, installing an AI on Shopify sets out the concrete steps.