The time to repurchase measures how many days it takes a customer to make another purchase after their last one. You can view this data by customer, by product category, or for the entire store.

Every business has its own rhythm: pet food is restocked every few weeks, while running shoes may take months.

Why does it matter?

If you understand the natural repurchase cycle, you'll know when to reach out to each customer. Reaching out too soon can be annoying; reaching out too late leaves the sale to another store.

Furthermore, it's a warning sign: when a customer goes well beyond their usual time without making a purchase, they're likely losing interest, and it's best to take action before losing them.

How is it calculated?

Formula: sum of the days between consecutive purchases ÷ number of intervals between purchases.

For example, if a customer made purchases on March 1, March 31, and April 30, they have two 30-day intervals. Their reorder time is (30 + 30) ÷ 2 = 30 days.

Story mode

Lucia buys protein from an online sports store about every 30 days. The store knows this, and 25 days after her last purchase, it sends her a WhatsApp message with a reminder and a direct link to her usual product.

Lucia replies, makes a purchase in two clicks, and doesn't have to look anywhere else.

How to Use It with Data4Sales

At Data4Sales, each customer has more than 90 attributes that are updated daily, including their unified cross-channel purchase history. With that:

• The predictive model for days until the next purchase estimates when each customer is likely to return.
• You create a buyback flow that kicks in at just the right moment for each person.
• You identify those who have deviated from their usual pace and add them to a list of at-risk customers.

Related terms

• Repurchase Cycle
• Days until the next purchase
• Buyback
• Customer at risk