Catch the customers about to churn while you can still keep them
Omniconvert Commander spots customers who are slowing down, by segment, so you win them back before they go quiet.
Placeholder values below. Replace them with yours.
customers × share lost × orders × order value
See how Omniconvert Commander finds the recoverable part of this number ↓
Simple arithmetic on the numbers you enter, assuming lost customers would have kept buying at the same rate. It is a scenario, not a benchmark or a forecast.
Built on data from 2,500+ eCommerce brands
In shortReduce customer churn with RFM-based risk scoring. See which segments are about to lapse, feed NPS and survey signals into the model, and trigger targeted win-back instead of blanket campaigns.
How early would you actually see a customer slipping?
Tick what is true today. Be honest, nobody is watching.
"90 days since last order" fits some customers and misses others
It fires late for a brand people buy from every month and early for one they buy from twice a year. Omniconvert Commander scores each customer against their own history instead.
Same rule, two customers
60 days too late.
90 days too early. A healthy customer is flagged long before their usual reorder.
Illustrative example, not a benchmark.
Each gap has a specific fix, and your team keeps the final say
Omniconvert Commander connects to your store and ad accounts, then does the watching, scoring and syncing, with a person approving each push.
Omniconvert Commander scores churn risk by segment, against each customer's own rhythm
- Recency, frequency and spend are compared with that customer's history, not a calendar rule
- A slowing high-value customer surfaces before they go quiet
- Every segment reads healthy, at risk or act now
Your team still: decides which segment to act on first.
Omniconvert Commander pushes the at-risk segment to Klaviyo, Meta and Google
- One segment, three channels, no CSV exported and re-uploaded
- Healthy long-cycle buyers are left out of the offer
- Every push waits for a human sign-off
Your team still: approves each push. Omniconvert Commander never triggers a campaign or moves budget without a human sign-off.
Nothing goes live without a person's yes.
Omniconvert Commander folds NPS and survey answers into the risk model
- Low NPS and post-purchase answers sit next to order behavior
- The reason a segment is leaving informs how you try to keep it
- That is the difference between a discount and a real fix
Your team still: reads the reason and chooses between a fix and an offer.
Your retention work, with and without Omniconvert Commander
| Task | Without | With Omniconvert Commander |
|---|---|---|
| Spotting churn | A flat rule, like 90 days since last order | Each customer scored against their own rhythm |
| Who gets the win-back | Everyone inactive | The segment that is genuinely slipping |
| Reaching them | Manual export and upload to each tool | Pushed to Klaviyo, Meta and Google |
| Knowing why | Survey data kept apart from order data | NPS and survey signals feed the risk model |
| Control | Left to each campaign owner | A person approves every push |
Two things worth knowing upfront
Why not just send a win-back offer to everyone inactive?
A blanket offer goes to loyal customers who buy slowly and to one-time shoppers who were never coming back. The first group did not need a discount, and the second group will not respond to one. Omniconvert Commander scores each customer against their own buying rhythm, so the win-back goes only to the segment that is really slipping. That protects margin and stops healthy customers from learning to wait for an offer.
The most common churn mistake is one inactivity rule for every customer
A rule like "no order in 90 days" fires late for customers who buy every month and early for customers who buy twice a year. By the time it flags a high-value customer, they have often gone quiet already. Compare each customer with their own history instead, and the slowdown shows while you can still act on it.
Common questions
What is customer churn and how is churn rate calculated?
Customer churn is the rate at which customers stop buying from a brand over a given period. It is calculated by dividing the number of customers lost during a period by the number you had at the start of it, expressed as a percentage. For eCommerce, churn is usually defined by a lapse in repurchase rather than a cancelled subscription, so the definition of lost depends on your natural repurchase cycle. Retention matters because increasing customer retention by 5% has been shown to increase profits by 25% to 95% [Bain & Company, 2000].
What is a good churn rate for eCommerce?
There is no single benchmark, because churn depends heavily on category and repurchase cycle: a consumable brand and a furniture brand will have very different healthy ranges. The more useful comparison is your own trend over time and how churn differs between your high-value and low-value segments.
What is the difference between churn and retention rate?
They are two sides of the same measure. Retention rate is the percentage of customers you keep over a period; churn rate is the percentage you lose. If retention is 80%, churn is 20% over the same window.
How is reducing churn different from growing customer lifetime value?
Reducing churn is the defensive move: spotting who is about to leave and keeping them. Growing lifetime value is the proactive one: deciding who is worth investing more in before anyone goes quiet. Reducing churn is about catching customers at risk, while growing CLV is about where to invest for upside.
What is RFM-based churn risk scoring?
RFM scores each customer on recency, frequency, and monetary value. Applied to churn, it flags customers whose buying pattern is slowing relative to their own history, which surfaces a lapsing high-value customer earlier than a flat days-since-last-order rule would.
How do you win back at-risk customers without discounting everyone?
By targeting the win-back at the specific segment that is genuinely slipping, using the survey and behavioral signal for why they slowed, rather than sending a blanket discount to every inactive account. That protects margin and avoids training healthy customers to wait for an offer.
How does Omniconvert Commander reduce churn?
Omniconvert Commander scores churn risk by segment using RFM and survey signals, pushes at-risk segments to email and ad channels for targeted win-back, and folds NPS and post-purchase feedback into the model so the reason a segment is leaving informs how you keep it. Every push needs a human sign-off.
See which customers are about to slip away
30 minutes. We walk through your own customer data, not a demo store.