Back in stock email conversion rate: what counts, and how to measure yours

Every conversion rate is one count divided by another. For a back-in-stock email, the top is usually purchases of the item that came back. The bottom is where definitions split.

The smaller the bottom count, the bigger the rate. A rate per click can be several times a rate per signup for the same restock, with nothing else different.

The window is how long after the email a purchase still counts. A shopper who buys within an hour almost certainly bought because of it. One who buys three weeks later may have seen an ad, a post or the product in a shop window. A longer window counts more sales and gives a higher rate.

Choose the window from how fast the item sells. If a restock usually sells out in two days, a 30-day window adds little. For an expensive item people think about, a week or more is fair.

Then decide what a sale is. Count a refunded or cancelled order and the rate looks better than the money you kept. Count the item’s price, not the whole order, if you want the figure to mean what the alert sold rather than what the shopper added to the cart.

Rates published by email and app companies for back-in-stock messages range widely. The ones we checked come from each publisher’s own customers, and rarely say which count they divide by, how long the window is, or whether refunds were taken off.

That’s why we don’t quote one here. A figure measured per click against a 30-day window can’t tell you whether your rate per delivered email over 7 days is good. Your own first restock, measured carefully, is the baseline that matters.

If you send restock emails yourself, from a list you collected with a form, you can measure each send in two ways.

With tagged links and Shopify’s reports

1. Tag every link in the email. Add UTM parameters to the product link: a source such as restock, the medium email, and a campaign name that is new for each restock, such as overshirt-oct.
2. Read Shopify’s marketing reports. Shopify’s marketing reports include Sales attributed to marketing and Performance by marketing campaign, which list sales by UTM campaign.
3. Know which model you’re reading. Shopify credits a sale by an attribution model. The default is last non-direct click, which gives the sale to the last channel the customer came from, not counting direct visits. A shopper who read the email but came back through a search is credited to the search.

With your list and your orders

1. Keep the list you emailed and the time you sent it.
2. Export the orders for that product from the send time to the end of your window.
3. Match the two on email address in a spreadsheet. Keep only lines for the item that came back, and take refunded orders off.
4. Divide the matched buyers by the number of emails delivered, and write down the window you used.

The second way catches shoppers who didn’t click, but misses anyone who checks out with a different address. Both take time for each restock, which is the work an app does for you.