Repeat Purchase Rate

What repeat purchase rate is and why it matters

Repeat purchase rate is the share of buyers who came back for a second or later purchase within a
defined period. It shows how well a store converts a single transaction into a relationship.

RPR = (buyers with 2+ orders / all buyers in the period) × 100%

If a store acquired 10,000 buyers in a quarter and 2,800 placed a second order, RPR is 28%.

Why RPR matters more than it looks

Acquiring a new customer costs several times more than keeping an existing one. A five point gain in
RPR on a base of 100,000 buyers means 5,000 additional buyers with no performance spend at all. That
raises lifetime value directly and relieves pressure on unit economics.

Important: RPR is not self-sufficient. Read it alongside purchase frequency and average order
value — otherwise it can be lifted with cheap discounting while margin falls.

Benchmarks by vertical

Sitting more than ten points below the vertical average is a diagnostic signal: the cause may be
assortment relevance, the post-purchase experience or weak communications.

Measuring it correctly

The analysis period depends on purchase frequency in the vertical. Twelve months is sensible for
electronics; a quarter is enough for grocery. What matters is measuring consistently over time so
cohort comparisons hold.

A cohort view is more precise than an aggregate: the RPR of the January cohort shows how return
behaviour evolves at 1, 3, 6 and 12 months — the basis of a retention curve.

Instruments for raising RPR

The second visit is the pivotal moment. Most buyers who do not return within 30–60 days of a first
purchase never do. The factors that move it:

• Relevance of recommendations on the return visit — the shopper should see products matched to
  their profile, not a generic bestseller
• Triggered scenarios: thirty days have passed, time to reorder X, for consumables; or something
  matched to the previous purchase
• Homepage personalization — a familiar and current selection lowers cognitive load and speeds
  the decision
• The post-purchase experience: fast delivery, simple returns and clear order status build the
  willingness to come back before the next need even appears

Common mistakes

• Mixing cohorts of different ages. First-quarter buyers have had more time to repeat than
  December ones; the comparison needs normalising by cohort age.
• Ignoring the quality of repeat purchases. RPR lifted by permanent discounting creates a
  price-sensitive audience with poor margin — read RPR together with order value.
• Not separating organic returns from induced ones. An A/B test isolates the effect of
  personalization from the background rate; without one you do not know how many of those repeats
  would have happened anyway.