Our problem isn't traffic. It's helping shoppers find the right product, fast.
Shoppers search by age, size or occasion, not product name. The agent helps them in search, on every page and in chat.
- Search from the first keystroke
- Recommendations on every page
- A chat that builds the basket
Keyword search fails when shoppers describe a need.
A DIY shopper asks what they need to tile a bathroom. Keyword search looks for product names and finds nothing.
Every visitor sees the same bestsellers. Shoppers dig through categories, or leave.
Three ways the agent helps a shopper choose
What a shopper searches for shapes what she sees next.
Answers from the first keystroke
Results appear as she types, ranked by the live catalog, what she did (sizes, categories) and what similar shoppers bought.
How search works →The right products on every page
The strategy is picked per visitor and page: next basket, color and size match, or bought together.
How recommendations work →A shop assistant that builds the basket
It answers questions from your live catalog, size guides and FAQs, and adds products to the basket.
How the chat works →Search · Pages · Chat: one memory of every shopper
Shoppers ask in their own words. The agent answers from your catalog.
It handles questions keyword search can't, and puts everything the job needs in the basket. It answers in the shopper's language, with your policy applied per market, shows order status to signed-in customers only, and hands over to people in Gorgias, Zendesk or Freshdesk, in the same chat.
See the sales agent →What happened when shoppers could find it
The first three show where revenue concentrates among shoppers who chose a feature, not a controlled lift.
of revenue came from the 4.9% of visitors who used search, over 35 days.
Read the case study →Womenswear · Shopify29%of site revenue came from the 3.8% of visitors who engaged with recommendations, in the first 25 days after launch (June to July 2026).
Read the case study →DIY and home · Bulgaria3.9×the store's average order, for orders placed after an agent recommendation, over 30 days.
Read the case study →Motorbike marketplace · Malaysia+40%test-ride bookings per visitor once the agent started optimizing, in equal 22-day windows, while traffic fell about 20%.
Read the case study →The agent tests what to show. You check your orders.
You set the goal, such as conversion or basket size. The agent decides what each visitor sees. It tests on its own: each placement tries several strategies and shifts traffic to what sells. And a holdout proves it: part of your visitors do not get the agent, so the lift is measured, not claimed.
How it decides →Where this has run
A chat that answers in every market you sell in
Answers from the live catalog and the customer's own orders, under each market's policy, with a handover to your team in the same chat.
Read the use case →Use caseYour team sets the theme. The agent picks the products.
Weekly themed rows on the home page, with the products inside each row picked for each shopper.
Read the use case →Questions about finding the right product
How does Releva help shoppers find the right product?
Three ways, from one memory. Search is ranked for each shopper as they type, and products on every page are chosen for them. A chat answers questions about size, age or occasion from your live catalog and documents. Shoppers can also send a photo in chat.
How is this different from Doofinder, Luigi's Box or Algolia?
Doofinder, Luigi's Box and Algolia are site-search specialists. Releva's search is ranked per shopper from the same profile that drives its recommendations, chat and messages, so a search today can change tomorrow's email. You choose the goal, and a holdout group shows the lift.
How is it different from Aqurate or Clerk.io?
Aqurate sells recommendations and site search; its search FAQ lists Gomag and Romanian only (28 September 2026). Clerk.io sells search, recommendations, email and chat. Releva's search, recommendations and chat work from one profile per shopper, toward your goal.
Does it work for visitors who are not logged in?
Yes. Search and recommendations are ranked from what each visitor did on this and earlier visits. When they log in or buy, that history joins their profile.
Can we still control what gets shown?
Yes. You set the goal, and the agent decides per visitor within your merchandising rules, boosts and filters.
Does the chat replace our customer service team?
No. It answers product questions and sells, and order status for signed-in customers. When a question needs a person, it hands over to your team in Gorgias, Zendesk or Freshdesk, in the same chat.
See where your shoppers get stuck
Thirty minutes with your store open. If the gaps aren't there, we'll say so.
Book 30 minutes
You'll talk to one of us.