AI Shopping Assistant
Problem it solves
High intent shoppers still leave because product questions, compatibility issues, and bundle opportunities are not handled well in session.
How it works
We train a shopping assistant on catalog data, reviews, policies, support history, and your merchandising priorities, then deploy it where buying friction is highest.
Expected results
Brands typically see stronger conversion on assisted sessions, better bundle attachment, and fewer pre purchase support tickets.
Who it is for
Best for brands with complex assortments, premium price points, or a high volume of product questions.
Mini case study: a fashion brand lifted assisted session conversion by 14 percent in 10 weeks.
Smart Product Search
Problem it solves
Native search often misses shopper intent, hides high value items, and forces operators to patch the experience with manual rules.
How it works
We pair semantic retrieval with merchandising logic, inventory awareness, and product economics so search results are relevant and commercially useful.
Expected results
The expected payoff is cleaner discovery, more revenue from search led sessions, and clearer visibility into the products customers want most.
Who it is for
Best for brands with wide catalogs, naming complexity, or accessory and compatibility logic.
Mini case study: a beauty catalog recovered 11 percent more revenue from onsite search traffic after a six week rebuild.
Growth Automation
Problem it solves
Lifecycle teams lose speed when segmentation, timing, and creative logic are rebuilt manually for every campaign.
How it works
We connect browsing behavior, purchase history, margin profile, and channel preference into automated flows across email, SMS, and retargeting support.
Expected results
Teams usually gain faster deployment, stronger replenishment timing, and better retention efficiency with less weekly manual work.
Who it is for
Best for repeat purchase businesses, subscriptions, and brands running coordinated lifecycle plus paid retargeting programs.
Mini case study: a nutrition brand reduced manual campaign prep by 60 percent while improving repeat order timing.