
Digital health platforms lose most members within the first 90 days, and a loyalty program borrowed from retail – badges, points, a rewards catalog – rarely shifts that curve because it isn't designed around the behavior that truly predicts retention. We create incentive programs linked to the specific health behaviors your product relies on, developed within the compliance boundaries healthcare requires, and integrated with your actual product data rather than operated as a marketing side project.
Member engagement surges in week one and collapses by day 90, while the loyalty program gets added after the drop-off pattern is already established
Most digital health platforms see a predictable curve: strong onboarding engagement, a steep decline around week three or four, and a long tail of members who never come back. By the time a loyalty program gets built, it's usually bolted onto a product that already has this churn pattern baked into its onboarding. Fixing retention after the fact costs more than designing the incentive structure into the first 90 days from the start.
Points systems adapted from retail loyalty don't align with health behavior change, and members notice
A points-and-badges system works for a coffee shop because the desired behavior is simple – buy more coffee. Health behavior change is different: medication adherence, consistent biometric logging, and completing a care plan each require a different kind of reinforcement than a generic point balance. Members managing a real health condition see through a gamification layer that treats their care like a punch card, and it erodes trust rather than building loyalty.
Most marketing teams don't know how to identify the boundary between a useful incentive and an inappropriate inducement
Rewarding a member for completing an educational module is different from rewarding them for using a specific clinical service, and that difference carries real regulatory weight depending on payer relationships and state law. Marketing teams without healthcare-specific experience default to whatever incentive drives the most engagement, without checking whether the design creates compliance exposure. Getting this wrong can trigger legal review that kills a program after it's already launched.
Loyalty programs operate separately from the product, meaning rewards don't reflect what members actually do in the app
When the loyalty program lives in a marketing tool with no connection to product analytics or the EHR, rewards get triggered by email opens instead of the behaviors that predict whether a member sticks around. This produces a program that looks active on a dashboard – points issued, redemptions tracked – while doing nothing to change the underlying retention curve, because it's optimizing engagement with the marketing layer instead of the product itself.
We begin with a retention diagnostic, not a brainstorming session about rewards. We segment your member base into cohorts and pinpoint where drop-off occurs – day 7, day 30, day 90 – along with the behaviors associated with members who remain engaged beyond that point. This shows us what the incentive program must reinforce before we create a single mechanic, because designing without this diagnosis means guessing at what makes people stay.
We then shape the incentive architecture around the behaviors your retention data identifies – consistent logging, care plan milestones, program completion, or whatever the diagnostic reveals as the genuine predictor. That may mean a tiered model that unlocks meaningful benefits at meaningful milestones, or a streak mechanic connected to a habit your product needs members to develop. The design question is never 'what reward sounds fun' – it's which behavior, reinforced consistently, actually helps this member remain engaged and healthier.
Before launch, we put the design through a compliance review tailored to your regulatory position – whether you work with payer relationships, fall under state-specific incentive rules, or operate in consumer wellness with greater design flexibility. Compliance is part of the architecture from day one, so you aren't rebuilding the program after a flag appears six weeks after launch.
Execution involves connecting the mechanics to your real product data – your app, the EHR when applicable, or the analytics stack – so rewards are triggered by actual usage rather than proxy measures such as email opens. We also create the member communications surrounding the program, from incentive onboarding through milestone notifications, making it feel like an integrated product experience instead of a marketing layer tacked on afterward.
To measure performance, we compare cohort retention and reactivation with baseline, segment program participation by the behaviors that matter, and monitor downstream signals such as referral behavior among engaged members. We don't evaluate points issued or redemption rates on their own – a program may issue many points without changing churn at all.
Unlike a standard loyalty vendor, we begin with your real retention data and compliance position, design the incentive mechanic afterward, and connect it to your actual product rather than running a standalone campaign. A digital health loyalty program must meet a higher standard than a retail rewards app – it must be transparent about what it incentivizes and genuinely improve the retention number.
A loyalty program can issue thousands of points each month and still do nothing for your day-90 retention curve. That doesn't mean it's underperforming – it means you're measuring the wrong outcome. The only number that counts is whether program participants stay longer than members who don't participate.
We deliver loyalty and rewards design through a 90-day sprint that results in a live, integrated program, not a strategy deck. The opening 30 days focus on diagnosis: we divide your member base into cohorts and chart the retention curve to identify which behaviors correlate with members who remain beyond the drop-off point. Days 30 through 60 cover design and compliance: we develop the incentive architecture, take it through compliance review, and create the integration plan for your product stack. Days 60 through 90 focus on launch: the program goes live, communications are deployed, and cohort-level measurement against baseline is instrumented.
Our approach differs from a loyalty platform vendor in two respects. First, the incentive is designed around what your retention data shows genuinely predicts engagement, rather than a generic retail points-and-tiers template. Second, compliance review is embedded in the design process instead of handled as legal approval after the build, which is where many digital health loyalty programs are delayed or stopped.
The initial 30 days focus on diagnosis. We gather your member cohort data, chart retention curves by signup month, and determine which behaviors distinguish members who remain beyond day 90 from those who churn. Before an incentive is designed, you receive a clear view of where the program must intervene.
Days 30 through 60 cover design and build. We develop the incentive architecture, take it through compliance review, and create the technical integration plan. We require product analytics access, a compliance contact, and engineering time from your team to connect the integration.
Days 60 through 90 focus on launch. The program launches for an initial cohort, communications are rolled out, and cohort-level tracking is instrumented against the phase-one baseline. Most engagements continue beyond 90 days as the program rolls out to the entire member base – ongoing work typically lasts three to six months, and longer for multi-month care plans.
Our cadence includes a biweekly review of cohort retention and participation data, along with a monthly written report. We remain involved for the first complete retention cycle – usually 90 to 180 days after launch – to determine whether the program truly shifted the churn curve it was built to address.
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Pricing depends on the incentive architecture's complexity, the level of compliance review required by your regulatory position, and the integration necessary for your product or EHR data. A consumer wellness app offering greater design flexibility is scoped differently than a program connected to a payer relationship.
The diagnostic and design phases cover the first 60 days, and the program launches for an initial cohort by day 90. Measuring retention impact honestly requires a complete cycle – generally 90 to 180 days after launch – because sufficient time is needed to determine whether engaged members stayed longer than a comparable cohort that did not engage.
We require access to product analytics or usage data to create the retention diagnostic, as well as a compliance contact who can review the incentive design ahead of launch. Engineering time is also needed to connect the loyalty mechanics with your product data.
A loyalty platform vendor provides a points-and-tiers template for you to configure. We use your real retention data to identify the behavior the program should reinforce, embed compliance review in the design rather than handling it as a legal check after launch, and connect rewards to actual product data instead of proxy measures such as email opens.
We measure cohort-level retention and reactivation against baseline, participation linked to the exact behaviors the program aims to reinforce, and referral activity among members who engage compared with those who don't. Issued points and redemption totals measure activity, not outcomes, so they aren't the scorecard – what matters is whether engaged members stayed longer and used the product more.
This service suits companies with 5M to 100M ARR and a subscription or ongoing-engagement model – including chronic condition management, fitness or wellness platforms, and care programs where retaining members beyond 90 days directly affects revenue. It is not a good fit for one-time transactional products without an ongoing relationship around which to build loyalty.
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