Personalization tool
Nosto
AI commerce platform combining personalized search, recommendations, merchandising, and content/A-B testing under one data layer.
Recommendations and search
E-commerce, Marketplace
The vendor’s claim
AI-powered ecommerce personalization, search, and merchandising. Content, banners, and merchandising adapt to each individual's affinities, from site to app to email.Source
Where it’s strong
- Search, category merchandising, and recommendations run off the same shopper-affinity data, so results, banners, and content stay consistent
- Built-in A/B testing (part of Conversion Optimization) means lift can in principle be measured, not just asserted
- A named central AI agent ("Huginn") plus sub-agents run continuously to surface opportunities. A specific product mechanism, not generic AI marketing
Where it runs out
- G2 reviewers flag significant price increases over time and describe pricing as opaque: custom quotes, sales-gated access, and commission-style billing
- Analytics depth is a recurring reviewer complaint
- A recs/merchandising engine without an active holdout still can't be priced for lift. The built-in A/B tooling only helps if it's actually configured that way
Best for
Retailers who want search, recs, and content personalization managed as one connected system rather than stitched from point tools.
Questions before you buy more of it
- Is our contract commission-based, and if so how does that change as personalized AOV grows?
- Where specifically is the recs/ranking holdout configured, and is it always-on or something we have to build ourselves?
Connected applications
Session-first recommendations
This visit's job outranks last year's purchase.
They're ready to buy something new. You keep selling last time.
Intent-weighted search ranking
Results respect the query, then history. Not the other way around.
They searched for something specific. You showed bestsellers.
Inline job complement
One missing piece, named, in the cart.
Compare it in the hub
Put up to three tools side by side, or start from the customer situation you want to personalize.
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