Earlier this week, we presented some insights from the customer transactions records of an active mobile money deployment. By looking at the data, we found that the customer journey to regular usage was longer than expected – 10.5 months from registration to regular usage. This raises an obvious question: Are there places that operators can intervene to accelerate the adoption of mobile money and shorten the journey to regular usage?
The findings came out of a bigger piece of business intelligence done to segment customers for one specific, successful mobile money deployment. Operators have struggled to bring more users active on their mobile money service, and a more nuanced fact-based customer segmentation framework is helpful to address that. A segmentation framework we found useful for this deployment is presented above. Some high-level findings from this deployment:
- The customer journey was longer than first thought: it took 10.5 months from registration to monthly active usage for the average user. There is a need to help customers along the journey and shorten this timeframe.
- 30% of registered users never did a transaction in the first place, becoming dormant registered users.
- P2P was a ’gateway product’ that brought customers onto the platform. Users readily embrace new products over time, but P2P is the initial use case for most.
- ARPU contribution increased steadily for active users, with the operator seeing their contribution double over the first two years.
- Revenue contribution from the most active user segment, ‘Power Users’, was greater than expected: the 4% of Power users contributed to 46% of the revenue for the deployment. This segment should be identified and their needs fully understood to further grow it.
To get deeper insights of the findings that the data analysis uncovered, we found it necessary to follow up with qualitative interviews with users of the segments identified. The findings in the presentation below include data-based user segmentation with the profiles created from interacting with real users in these segments.
We encourage operators to look at their data and do similar analysis. Please email us for a technical guide how to replicate this in your deployment, as we want to share and get feedback on the methodology and the considerations we made.