Why set up an automatic customer feedback semantic analysis solution at Groupama?
When we decided to implement satisfaction surveys following customer contact, our three main objectives were to:
- Provide the results to operational managers so that they could lead their teams on a daily basis
- Encourage our advisors to call back customers following surveys as well as to raise awareness on the importance of their role when it comes to customer satisfaction
- Ensure that customer surveys follow an upward trend and thus match our strategic goal regarding customer satisfaction
Semantic analysis is used for about 12,000 surveys per month, providing us a thorough and much more efficient analysis of customer feedback. Concretely, managers use word clouds to show results to their teams. Analyses allow detecting “at-risk” customers, either because waiting for a reply or because a churn risk has been identified.
Can you provide some concrete examples of insights, key figures or ROIs gained with the help of the Groupama customer feedback analyses?
Assessing customer satisfaction allows us to highlight some insights we couldn’t have identified otherwise. For example, we’ve found out that the bonuses granted to promoters were 25% higher than the ones granted to detractors. The churn rate of detractors was 45% higher than the churn rate of promoters.
Our “at-risk customers” calling system has also allowed us to retain 1,500 customers.
Furthermore, twice a year, we make use of customer feedback for our customer experience improvement plans.
Verbatim also prove a great team managing tool. Customer feedback bears witness to the importance of each employee’s role in customer satisfaction.