Orange: Retention Case Study
€200,000 Annual Savings by Identifying Churning Customers
CUSTOMER BASE
2 mil.
RETAIL STORES
100+
CALL CENTRE AGENTS
100+
DURATION
04/2017 →
Goal
To identify customers who think about leaving for competition and retain them.
Problem
Random recalling could not identify all unhappy customers and other feedback solutions were low-performing. Orange needed a quality satisfaction check on as many retail and call centre interactions as possible.
Methodology
After every visit or call, we request customer feedback via SMS/email. Besides measuring the CSAT metric, we provide the opportunity to leave spontaneous insights. The automated semantic analysis then identifies customers thinking about leaving the brand.
Top Solutions Used
Staffino Standard Feedback
Staffino Semantic Engine
Staffino CSAT
Results
|
Contact volume surveyed in transaction survey |
562 358 |
|
Conversion Rate
|
7 % |
|
Feedback volume |
38 365 |
|
Negative feedback % |
12 % |
|
Negative feedback volume |
4 724 |
|
Reactive retention cases % (based on our benchmark) |
15 % |
|
Reactive retention case volume |
708,57 |
|
Success rate of reactive retention |
70 % |
|
Average life-cycle of subscription |
21 |
|
ARPU |
18,00 € |
|
Value of 1 saved customer |
378,00 € |
Total saved value
187 487,91 €
Per one month subscription8 928,00 €
Per one month subscription8 928,00 €
“Thanks to the simplicity of the Staffino platform and the ability to internally discuss each case directly within the app, we’ve been able to retain 70% of customers who were likely to leave.”
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