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Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
Mobile user analytics tool case study   mobile agriculture
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Mobile user analytics tool case study mobile agriculture

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In the last few years, we have seen a significant number of products and services around the world aiming to serve underserved populations (1,600 as of May 2014 in our own product and service tracker). Because these are delivered through a mobile platform, many of these services are generating valuable data that could be used to identify areas for service improvement.

GSMA’s Mobile for Development Impact team are in a unique position to explore this topic, acting as a trusted partner for service providers to help responsibly unlock the value of potentially sensitive data. We wanted to understand the viability and utility of supporting services in this area, and the role we might be able to play in providing best practice and tools on this relatively nascent topic for a wide range of players offering mobile solutions to underserved customers across all sectors.

To begin, we considered a method to identify bottlenecks in customers’ journeys toward regular use of a service – already successfully applied in the case of a mobile money deployment.

Published in: Technology, Business
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Transcript of "Mobile user analytics tool case study mobile agriculture"

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  5. 5. 59%
  6. 6. Date # users added
  7. 7. Date # users added
  8. 8. High score Low score LR% RU% IU% NRU% RT% RT% RNU%
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