Every visitor gets a personal shopper.
Search, product pages, banners and a chat that answers from your catalog, picked for each visitor, logged in or not.
- Search, recommendations, chat and banners
- Works before anyone logs in
- Shopify app, live in hours
Search results ranked for the person typing.
Results follow your live catalog, what this shopper returns to, and what similar shoppers bought. It works as you type, on the web and in the app, and ranks per shopper rather than by keyword alone. Every search joins their profile, so pages, chat and the next email know what they looked for.
What personalized search means →The right products on every page, chosen for each visitor.
Product blocks on the home, category, product, cart and thank-you pages, with the approach picked per visitor and page. It tests choices and placements against each other and moves traffic to what sells. Your merchandising rules stay on top: boost, bury or exclude whatever you choose.
What next-basket prediction means →
A chat that answers from your catalog and builds the basket.
It answers product questions and recommends from the live catalog, in the languages you sell in, from your size guides, FAQs and policies for each market. Signed-in customers can check their orders. When a person should reply, it hands the conversation to your team in Gorgias, Zendesk or Freshdesk. Every language is signed off before launch.
The chat in every market →Pop-ups, flyouts and bars that carry the right products.
A pop-up in the middle of the page, a flyout in a corner or a bar across the page, carrying the products that shopper was looking at. You choose who sees it, when it shows and how often, for shoppers who have signed in and for those who have not.
Where the revenue came from, in clients' own data
One client each; the first three compare feature users with other shoppers.
of revenue from the 4.9% of visitors who used search, over 35 days.
Read the case study →Womenswear brand · Shopify, Singapore29%of revenue from the 3.8% of visitors who used recommendations, first 25 days.
Read the case study →DIY and home retailer · Bulgaria3.9×the average order when the chat agent recommended products, over 30 days.
Read the case study →“Thanks to Releva we manage to offer our customers much more personalized and relevant content. We engage them, encourage them to buy and increase the average basket.”
Questions about the sales agent
What does Releva's sales agent do?
It gives every visitor a personal shopper. It ranks your site search, picks the products on every page, chooses banners and pop-ups, and answers questions in chat from your live catalog and documents, in your store's languages. It works for shoppers who never log in, and toward the goal you set.
Is this a chatbot?
It includes one. The chat knows what the shopper searched and viewed, and answers from your live catalog. The same agent also ranks your search, picks the products on every page and chooses the pop-ups, for every visitor, not only the few who type.
How is Releva different from Zipchat, Rep AI or Tidio?
Zipchat calls itself an AI chatbot for ecommerce sales and support, Rep AI an AI shopping and sales assistant, and Tidio's Lyro an AI customer service agent. Releva's chat is one part of a sales agent that also ranks search, picks products and writes messages from one profile per shopper.
How is it different from Nosto, Rebuy or LimeSpot?
Nosto calls itself AI-powered ecommerce personalization, Rebuy a personalization platform for Shopify, and LimeSpot AI product recommendations for Shopify and BigCommerce. Releva's recommendations come from the same profile as its search, chat and messages, so what a shopper asked in chat or opened in an email changes what they see next.
See where your store could sell more
One call with your store open. If the gaps are not there, we will say so.
See it on your store
You'll talk to one of us.