More repeat orders and bigger baskets from the customers you already have.
The agent picks products for each person, on every page and in every email. After the first order, it follows up with their likely next buy.
- Runs next to your email tool
- Live the same day on Shopify and plug-ins
- Proven in your own orders
Most stores go quiet after the first order.
They show everyone the same products, send a receipt and wait. The agent treats each customer as one person, everywhere.
| Most stores today | With the agent | |
|---|---|---|
| Product, cart and thank-you pages | The same bestsellers for everyone | The next item for this visitor |
| One static product block per send | Products chosen per recipient, per send | |
| After the first order | A receipt, then silence | Post-purchase, price drop, back in stock and winback flows |
| A shopper with a question | A search box and an FAQ page | A chat agent that builds the basket |
| Rewards and feedback | Separate tools, separate data | Points, vouchers and forms on one profile |
Six ways to bring customers back and fill the basket
Everything she does with your brand shapes what she sees next. One memory runs all six.
The right next item on every page
Blocks on every page show what this visitor is likely to add. The agent picks the approach and tests placements on its own.
See the sales agent →Each email built for its recipient
In a controlled A/B test, these emails earned 96% more revenue per recipient than a replica of Klaviyo's logic (Singapore womenswear brand, week one).
See Retention →Flows that follow the first order
Post-purchase, price drop, back in stock and winback flows run on email, push, SMS, Viber or WhatsApp. Frequency caps keep customers from hearing too much.
A chat agent that builds the whole basket
At a Bulgarian DIY retailer, orders after its advice were nearly 4× the store's average order (30 days, shoppers who chose to chat).
Points and vouchers that pay customers back
Customers earn points for spend and actions, and swap them for vouchers from your coupon codes. A personal loyalty page shows their balance.
Feedback that shapes the next message
Build Typeform-style forms and ask for NPS after key moments. Scores and answers land on the profile and shape the next message.
Measured in the brands' own orders
Store data, with the comparison and period stated for each.
the 60-day reorder rate of first-time buyers who clicked a recommendation, against those who did not. Monthly cohorts, April to June 2026.
Read the case study →Same brand · year on year+56%repeat-customer revenue, while new customers fell 49%. Total revenue held within 1.4%. 1 April to 14 August 2026 vs 2025.
How we measure →Bedding and sleepwear brand · WooCommerce, Europe−10.2%items per order in the two weeks after the brand began switching Releva off in stages for a test, June to July 2026. That explained 93% of the drop in average order value.
Read the case study →Used-motorbike marketplace · Malaysia35%of weekly revenue came from repeat customers after five weeks, up from 28% (July to August 2026, Releva dashboard). Buyers here get a bike every few years.
Read the case study →Keep your email tool. Start with one flow.
Klaviyo is your CRM. Releva is your sales agent.
Start with site recommendations and one flow, such as winback. It is live the same day on Shopify and plug-ins, and other platforms take 3 to 5 business days. Nothing migrates: your lists, campaigns and newsletters stay where they are. Move more when the numbers say so, as Ivet did: it started with one flow and later chose to consolidate onto Releva.
For retention marketers →From install to a readout in 30 days
Connect your store
Install the Shopify app or add one tag. On Shopify, the agent loads two years of orders.
Turn on pages and one flow
Recommendations go live on product, cart and thank-you pages, plus one flow, such as winback.
Hold a group back
Part of your visitors don't get the agent, so the lift is measured, not claimed.
Read it in your orders
At day 30, compare items per order and revenue per visitor in your store data. The 60-day repeat rate follows.
In development: alerts when items per order or the repeat rate slip.
Where this has run
eBag: three in ten orders include a recommended item
An online grocery that uses only website recommendations. The cart page reminds each shopper of their usual items.
Read the case study →Case studyT-Market: 23% of online revenue from email and recommendations
A supermarket chain's online shop in its first full year with Releva. Triggered emails out-earned newsletters many times over per send.
Read the case study →Questions about repeat orders and bigger baskets
How does Releva increase repeat orders and basket size?
It picks the next product for each person, on the site and in every message, and times the follow-up: back in stock, price drop, replenishment and winback. You choose the goal, bigger baskets or long-term customer value, and it decides per shopper.
How is this different from upsell apps like Rebuy or LimeSpot?
Rebuy and LimeSpot sell upsell and recommendation apps for Shopify stores. Releva chooses bundles and upsells from the same profile as its messages and loyalty program. The product in the cart, the next email and the next voucher all work toward the same goal.
Do I have to replace Klaviyo or my current email tool?
No. Releva runs next to it. Start with one flow and compare both in your own dashboards.
Does this work if customers buy rarely?
There are early signs. At a Bulgarian tyre retailer, Releva-engaged buyers reordered within 60 days at 11.9%, against 6.1% for other buyers (September 2025 to August 2026). That figure is not from a holdout.
How do you know the recommendations caused the repeat orders?
A comparison of buyers who clicked a recommendation with those who didn't shows a link, not the cause. For the cause, the agent holds back part of your visitors and compares revenue per visitor in your store data.
Can I run the loyalty program in Releva, or keep my current one?
Either. Points, vouchers and a personal loyalty page run in Releva, or Releva runs alongside your current loyalty tool.
See which customers are ready for a second order
Thirty minutes with your store data. We look at your repeat rate, items per order and where the agent would start.
Book 30 minutes
You'll talk to one of us.