Introduction
The retention dashboard highlights the impact of the loyalty program on the life cycle of your customers.
Global statistics
Indicators
In this section, five key indicators are displayed to give you an overview of performance :
Customers: total number of unique customers who have placed an order
Revenue per customer: revenue per customer over a one-year period
Average basket: average order value including VAT
Average orders: average number of orders per customer
Repurchase time: average time between 2 purchases
Graphics
Next, two visual representations allow you to explore the distribution of revenue and customers according to whether it's their first, second or third purchase or more.
Left pie chart: analyzes retention data by customer profile (one-off, recurring, frequent)
Right pie chart: shows the breakdown of revenue according to the above-mentioned customer profile.
Bar chart: details the daily breakdown of revenue generated by unique, recurring and frequent customers. This gives an overview of daily activity, and enables you to identify peaks or specific variations over time according to customer profile
Distribution
Indicators
This section analyzes retention data according to your customers' profiles and purchasing habits.
For each customer profile (guests, customers, repeat customers), this table provides you with key information:
Number of customers: how many customers belong to each category.
Average basket: the average value of purchases made by these customers.
Average number of orders: the average purchase frequency per customer in each profile.
Revenue per customer: the average sales generated per customer over a one-year period.
Retention
The number defined on the cohort corresponds to the number of customers for the month. Then month 1 corresponds to the month of arrival +1 month.
Filter indicator 1: Retention rate
In this section, you have access to an analysis of the conversion of purchase stages, according to customer profile.
💡 Utility :
Identify the periods when customers are most likely to return, to better target marketing actions.
Each line corresponds to a cohort (customers who made their first purchase during a given period).
Filter indicator 3: Average basket
This table shows the evolution of the average basket for each customer cohort (group having made their first purchase at a given period) over the months.
💡 Utility:
Track changes in customer buying habits for each cohort.
Identify months when average baskets fall to adapt marketing strategies (targeted offers, loyalty campaigns).
Identify the best-performing cohorts in terms of average basket over time.
Filter indicator 4: Customers
This table tracks the number of active customers for each cohort (groups of customers who made their first purchase at a given time) over the months.
💡 Utility
Identify cohorts with above-average loyalty to adjust engagement strategies (e-mail campaigns, targeted promotions, etc.).
Identify the months with the greatest customer loss and take action to reduce this loss (exclusive offers, relaunches).
Time to repurchase
This table enables you to measure customer repurchase times and their behavior over time. A filter system in the top right-hand corner lets you select a time frame, such as the results between the :
First and second purchase.
Second and third purchase
Third and fourth purchase
💡 Benefits
Analyze customer loyalty: understand when your customers return to make a new purchase. The higher the 30- or 90-day rate, the more effective your loyalty efforts.
Optimize your marketing campaigns: promote reward or loyalty programs to accelerate repurchase.
Measure the impact of actions: use this data to compare your results after specific campaigns and see if your repurchase rates are improving.
Purchasing behavior
This table analyzes re-purchase factors over several consecutive purchases, distinguishing between non-rewarded, rewarded and sponsorship-related purchases.
💡 Utility
Measure the impact of loyalty programs: the chart shows that reward purchases increase with repurchases, proving the effectiveness of loyalty programs over the long term.
Recommended action: strengthen incentives after the 2nd purchase to accelerate loyalty and encourage repeat purchases by your customers.