Cross-Post: 4 Use Cases for Internet Messaging Applications in Development Programs

Nearly half of the world’s population uses one or more messaging applications and increasingly, development organizations are seeing the value of using mobile messaging applications to reach both urban and rural populations across the globe.

The Digital Impact Alliance (DIAL) worked with Echo Mobile to examine how international development organizations are using messaging apps and capture lessons for development and technology practitioners in DIAL’s Messaging Apps for Development White Paper.

In addition to the White Paper, DIAL published two useful resources:

  • 14 Project Summaries to show the broad landscape of how messaging applications have been used in development.
  • 6 Case Studies that incorporate messaging applications across sectors and regions, and with varying success.

Overall, the findings are fascinating for technology providers and development practitioners who seek to better connect with staff and constituents using tools like WhatsAppFacebook MessengerViber, and all manner of chatbots. The report identified four common use cases where messaging apps have been effective for international development organizations:

One-to-One Matching of People With Resources

One of the most common messaging app use cases is the use of messaging apps to efficiently connect individuals to services and information to help people identify opportunities and make decisions related to their livelihoods and well-being. For example:

  • The Amigo Anônimo Facebook Messenger chatbot establishes matches between individual users and nearby offline resources provided by AA, as well as relevant online information.
  • Farm.ink’s chatbot mines large volumes of farming information shared on its Facebook group and consolidates it into daily Facebook Messenger digests, which it then matches and delivers to individual users based on their expressed crop preference and location.
  • mVAM’s SMS, USSD, IVR, and eventually its messaging app chatbot channels establish and facilitate matches between WFP beneficiaries and locally relevant services and food security information.
  • MomConnect uses messaging apps and other channels to collect information from pregnant women and mothers and then match them with health information based on their health records, clinics based on their locations and online clinicians based on their expressed needs.
  • DZCareer matches unemployed youth with relevant job listings based on their expressed interests and qualifications and delivers that information over WhatsApp.

Group Peer-to-Peer Learning and Behavior Change

Messaging applications can be effective for facilitating group engagements with the goal of changing knowledge, attitudes, and behaviors among the group or building technical skills. Three scenarios combined direct training—pushing technical content to the group—with facilitated peer-to-peer dialog and information sharing as techniques for driving learning and behavior change:

  • ECAP, focused these goals on internal program staff.
  • WTS and AVC, focused on external program beneficiaries

These methodologies are useful when critical information is distributed among beneficiaries or staff rather than held centrally by the development organization. In these cases, development organizations can deploy messaging apps to bring people together to share their knowledge and learn from one another.

This is in contrast to matching use cases, where organizations are able to identify and compile information and resources that users need, such as AA meeting locations or translators, before deploying a messaging app service to connect them.

The peer-to-peer learning use case is especially valuable when information is constantly evolving, as it was during the ECAP project, when the Ebola outbreak scenario was unprecedented and the decentralized community mobilizer approach was untested.

Information Broadcast

While matching and group learning both rely on two-way information exchange, organizations have also used messaging apps for the one-way broadcast of information to beneficiaries or staff. This fulfills many organizations’ basic need to efficiently provide critical, actionable information to large groups on an ad hoc basis.

This use case thus differs from the scheduled, automated and personalized matching of information facilitated by platforms like MomConnect and DZCareer, and by chatbots like Farm.ink. Broadcasting also differs from group learning, in that one-way broadcasts are applied when information is considered essential and actionable enough to prevent group replies that might cause others to miss it.

Crowdsourced Reporting and Feedback

While information broadcasts and matching via messaging apps are intended to provide information to individual users, and groups are used to facilitate information exchange between users, organizations have also used messaging apps to collect information from users. Information gathering by development organizations takes many forms:

  • SMS surveys
  • In-person data collection using paper or electronic forms
  • Focus group discussions
  • Telephone hotlines

As messaging apps become increasingly ubiquitous in emerging markets, development organizations have seen an opportunity to improve on these methods by making mobile data collection more efficient and reliable. Messaging apps allow the submission of large amounts of text as well as photos, videos, and audio recordings, all of which represent an improvement over SMS for mobile data collection. At the same time, messaging apps, like SMS, do not require the personnel necessary for conducting field-based data collection or managing call centers.

This post is adapted from the DIAL’s Messaging Apps for Development White Paper.

The original post can be found on ICT Works