Guide
How to Identify At-Risk Customers Before They Become Inactive
Most customers give signals before they go quiet. This guide explains which signals to watch in your purchase data and how to decide who deserves attention first.
At-Risk vs. Inactive
An at-risk customer has gone longer than usual without buying but has not crossed your inactivity threshold. An inactive customer already has. At-risk customers are usually easier to keep, because the relationship is still recent.
For reference, Revenow currently applies one fixed rule set (Generic 1.0) to every customer, counted from the analysis reference date: under 60 days since the last purchase is active, 60–89 days is at risk, and 90 days or more is inactive. These are Revenow's product settings, not an industry standard. The right windows for your own manual analysis depend on how often your customers normally buy.
Recency and Frequency
Recency is days since the last purchase. Frequency is how often the customer buys. A customer who normally orders every two weeks and has been silent for six weeks is a stronger warning sign than a twice-a-year buyer silent for the same time.
Historical Customer Value
Not every warning sign deserves the same response. Add each customer's total historical spend and average order value so you can see what is at stake.
Practical Warning Signs
- A gap since the last order noticeably longer than the customer's usual gap
- Smaller orders than before
- Fewer products per order, or a regular product no longer ordered
Segment and Prioritize
| Segment | Example | Suggested attention |
|---|---|---|
| High value, recently overdue | Big regular account, slightly late | Personal check-in |
| Medium value | Steady small buyer | Timely reminder |
| Low value, rarely bought | Occasional one-off buyer | General newsletter |
Illustrative segmentation; adapt it to your business.
Turning Signals Into Action
Review the at-risk list on a regular schedule rather than once. To see how Revenow flags and ranks this group, read about at-risk customer detection. For the money side, see how to calculate revenue at risk.
Frequently Asked Questions
How often should I check for at-risk customers?
Monthly works for most repeat-purchase businesses; weekly if customers order very frequently.
Is an at-risk customer going to leave?
Not necessarily. It is a warning sign worth reviewing, not a prediction.
Should I offer discounts to at-risk customers?
Start with a relevant, helpful message. Discounts can train customers to wait for offers.