Our Strategy for Growth and Impact

Introduction

In February, we launched v1.0 of the HealthLearn platform, which is tailored to the learning needs of the primary health center (PHC)-based health workers we serve. The platform currently hosts two courses:

• Newborn Care Foundations: an updated version of a course we previously piloted that’s designed to improve birth attendants’ adherence to life-saving basic newborn care practices.

• IDSR Foundations: a course developed by Resolve to Save Lives that teaches health workers how to detect, report, and respond to suspicious cases that could develop into infectious disease outbreaks.

We already have thousands of health workers enrolled in these courses. To address our greatest uncertainties about the intervention, we’re also in the early stages of conducting an evaluation of how the newborn care course impacts clinical practice.

We assume that the impact per health worker trained may be relatively small, so we need to scale up to reach tens of thousands of health workers to maximize our impact and cost-effectiveness. To accomplish this, we’re working to rapidly and iteratively improve both our Product (the learning platform and the courses on it), and our Program (the ways in which we reach health workers, enroll them in our courses, and encourage them to enact the behaviors they learn).

Growth strategies

Improving conversions and retention

With much greater usage of our platform, we’ve gained a lot of insight into where learners get stuck and drop out. We’re currently very focused on platform features that are designed to improve conversion (the fraction of site visitors who become learners by registering and enrolling in a course) and retention (the fraction of learners who complete a course). Priority features include notifications to remind users to come back and complete their work and user experience updates to increase learners’ persistence. Over time, we aim to use split testing to compare feature updates while also integrating more and more behavioral insights into our product development and improvement. To guide these product optimizations, we’re developing a handful of North star metrics, with the goal of observing how different product updates impact key metrics related to retention, growth, and learning. We’re also using qualitative methods (including user testing and stakeholder interviews) to better understand user needs and prioritize the features that are most likely to have an impact.

Incentives

We know that motivation to learn is complex and influenced by many factors, including incentives. We’re particularly interested in testing out non-financial incentives. Health workers in Nigeria are required to maintain their license by completing continuing professional development (CPD) training. We’re currently in discussions with the relevant governing bodies in Nigeria to secure accreditation for the courses hosted on our platform. We expect CPD will increase motivation and persistence, but we’re also exploring other incentives. We may provide participants with a small amount of mobile data to ensure they were able to access the course (we used this incentive in our pilot). Finally, when we need to target the course to specific facilities or groups of health workers, we’ll also consider financial incentives (such as small cash transfers), or even lottery-based prizes for participants.

Tapping into network effects

Many health workers who finish our courses ask about training in other topics, and a meaningful percentage of users who complete one course on our platform will go on to take another course, so we think that growing the number of highly relevant, high-impact courses on the HealthLearn platform can also increase user retention and referrals. That’s why we are keen to partner with organizations to offer more high-impact courses for PHC-based health workers. This activates a virtuous cycle: more courses bring in more health workers, and a larger user community can increase the platform's appeal to organizations that aim to reach a large audience of health workers. Finally, we’re exploring ways to amplify our reach through referrals, shares, and social media advertising. 

Challenges

We anticipate a few different challenges as we grow:

• Preventing misuse: this is a particular concern if we offer incentives, which will need to be carefully designed and implemented to avoid exploitation.

• Maintaining targeting for impact: even in the absence of outright misuse, there may be a balance between how easy it is to recruit and retain a user and how much they stand to gain from our courses. For example, it’s possible that health workers with more advanced training find it easier to take our courses. 

• Keeping user acquisition costs low: we anticipate there will be a lot of room in optimizing our campaign targeting, and our calls to action, to ensure cost-effective distribution of courses.

• Improving our monitoring and evaluation: as we scale up, we’ll need to find better ways to monitor our program and connect North star metrics directly to program impacts (such as lives saved). Better monitoring can also help us protect against some of the other challenges listed above.

• Evaluating performance of growth initiatives: to some degree, our efforts to promote growth on multiple fronts could make it difficult to connect cause and effect. We will need to implement a/b testing (or find suitable proxies) to help us compare different approaches to growing our user base.

• Platform scalability: our platform is still quite new and it hasn’t been exposed to high traffic volumes. As we make efforts to expand our user base, we’ll likely uncover areas that need further optimization to support high levels of concurrent users.

What’s next

As we explore different growth strategies, we’ll generate more evidence to test our hypothesis that these improvements synergize – for example, a better user experience leads to higher retention and more referrals, driving organic growth. We’ll also be looking for opportunities to add features to our platform that simplify our program operations – for example, if we find that health workers’ supervisors have an outsize impact on their likelihood of enrolling and completing courses, we can build features that encourage that behavior. By the end of 2024, we aim to have strong evidence that we can scale up to reach tens of thousands of health workers.

How you can help

We’re looking for experts who can advise us on our growth. If you have experience growing tech products' user bases through diverse approaches (such as referrals, product-led tactics, and social media engagement), please reach out to us!