The problem

A hire price has more parts than a retail price. There is a minimum hire period, a price for that first period and a charge for each extra day. On a recent client's Shopify store, those figures were held in three places. The price on product tiles came from the booking platform, the extra-day pricing table came from a Shopify metafield, and the price shown in search results came from whatever had been typed into the meta description.

None of the three were linked. When a price changed in one place, the other two stayed as they were, and on a lot of products they no longer matched. Duplicating a product to list a new one made it worse, because the copy kept the original's meta description, price included.

What we did

We started by mapping every field the product page needed: where its data came from, which system owned it, how long it could be and what it should show when empty. That map became the basis for a new product template built from structured fields, with the first-period price and extra-day rate shown together, and specifications and reviews alongside.

The second half was process. Most pricing errors were introduced when products were listed, so we designed a new listing process and trained the client's in-house team to use it. Each new product is set up with its booking price, pricing table, meta title and meta description written from the same figures, and the copied meta description is cleared when a product is duplicated.

Give price data one source

Pricing drift is rarely a code problem. It comes from the same figure living in several places, with nothing keeping them in step. Mapping each field to one source, and giving the team a listing process that follows that map, keeps new products consistent from the day they go live and makes older ones easier to find and correct.

If your prices differ between search results, product pages and checkout, tell us about your project