How Nurtra. works

Four steps from your order history to a change worth making.

Import

Export orders and products from your platform and upload them. Shopify, WooCommerce, BigCommerce or anything that exports CSV.

Analyse

Nurtra. tests every product pair in your catalogue for a real, statistically significant buying relationship.

Review

Work through the ranked opportunities, the evidence behind each, and the pairings that were set aside.

Change

Make the recommended change in your store. Nurtra. has no write access and does nothing on your behalf.

From data to a decision

Re-import whenever you want a fresh read on newer orders.

Find

Find the opportunity

Nurtra. examines every pair of products in your catalogue and identifies where buyers of one go on to buy another far more often than chance would explain.

Prove

Prove it is not chance

Each candidate is significance-tested and corrected for the number of pairs examined. Test enough pairs and some will look meaningful by luck alone; that correction is what stops those reaching you.

Size

Size it in pounds

Nurtra. counts the customers who own one product and not the other, applies a stated conversion assumption and your realised price, and gives a range rather than a single misleading figure.

What Nurtra. needs from your store

Order history, product data and customer purchasing behaviour. Nothing about how you sell has to change.

An order history export

Order id, customer, date, product, quantity and price. A CSV from any platform will do.

Enough scale to be worth it

Below roughly 3,000 customers the figures Nurtra. finds are unlikely to cover its own cost. Thin data produces an honest empty result rather than a padded one.

Someone who can make the change

An opportunity only becomes revenue when the recommendation goes live on your product page. Nurtra. tells you what to change; you change it.