This post is the second in a two-part series exploring the role of behavior mapping in the pharma industry, click the following link to read The Value of Behavior Mapping for Pharma (Part 1) | Challenges & Benefits.
In Part 1, I explained why behavior mapping matters so much for pharma teams, helping them move beyond assumptions and design smarter, patient-centered solutions.
Now let’s get into the “how.” In this post, I’ll walk through the behavior mapping process step by step, showing how this approach can de-risk decisions and lead to better outcomes.
The power of behavior mapping
Most pharma teams are pretty familiar with patient experience
Behavior mapping has become a powerful tool in pharma. Some companies have applied it systematically for years, across multiple therapeutic areas and global markets, not just as a one-off exercise, but as an enduring resource.
In practice, we often find that around 70–80% of behavioral frictions are universal across different countries. They show up consistently across conditions like Alzheimer’s, obesity, diabetes, and breast cancer. But how those frictions play out, and what solutions will work, depends heavily on context.
Take obesity as an example: a common friction is patients discontinuing treatment after hitting their weight loss goal, only to regain weight soon after. That behavior appears globally, but its implications vary depending on things like healthcare policy and medication costs, especially when you compare the US and Europe.
What makes behavior mapping durable is that it focuses on human behavior itself, which tends to remain stable over time. A behavior map created years ago often remains useful today, while many patient experience maps become outdated fast because they chase changing digital touchpoints rather than underlying actions.
That said, assumptions can’t replace evidence. When expanding into a new market or therapeutic area, it’s important to validate, using surveys anchored around known friction points, followed by interviews that dig deeper into real-world behaviors without biasing participants.
De-risking decisions with a systematic approach
At S3 Connected Health, we use a seven-stage process to uncover friction points and behavioral drivers in a systematic, evidence-based way.
The goal is simple: de-risk decisions by identifying what truly influences behavior, before investing in solutions that might not stick.
Rather than starting from scratch every time, this approach helps teams map real behaviors, understand why they happen, and prioritize where to intervene.
The key stages:
So what does this look like in practice? Here’s how we break it down:
Stage 1: Define the desired outcomes
Every behavior map starts by defining what success looks like. What’s the business goal? What specific behavior needs to happen to achieve that goal?
Outcomes like “adherence” aren’t behaviors themselves, they’re the result of many smaller actions. For someone to be adherent, they need to:
- Visit the doctor
- Get a prescription
- Pick up the medication
- Remember to take it
- Actually take it (consistently)
When you break it down this way, something that sounds simple quickly reveals unexpected complexity and valuable insight.
Stage 2: Gather existing knowledge
Before jumping into new research, we take stock of what’s already known: client insights, secondary research, academic studies, and stakeholder input. The goal here is to avoid reinventing the wheel and build on existing knowledge before talking to patients.
Stage 3: Map every action (or inaction)
Next, we map out what people are actually doing, or failing to do, in the real world.
Steps that get described as “just one” often turn out to involve 20+ micro-decisions. This stage helps build a complete picture, including where and why people fall off track.
Stage 4: Diagnose behavioral barriers
Through interviews and observation, we systematically diagnose why people aren’t doing what’s needed.
We categorize these barriers into behavioral themes, cognitive overload, lack of motivation, environmental friction, social influence, and so on.
This diagnosis is key for designing interventions that actually work, rather than surface-level fixes.
Stage 5: Build and validate the behavior map
At this point, we construct a validated behavior map that shows:
- Every step (or dropout point)
- The reasons behind actions or inactions
- The context around them (e.g., distractions in a busy clinic)
We validate this map by speaking to both adherent and non-adherent individuals, revealing where and why their behaviors diverge.
Stage 6: Segment by barriers, not personas
Instead of grouping people by high-level demographics or personas, we segment them based on shared barriers.
For example, two very different patients on paper may both struggle with remembering to take their medication.
This segmentation gives teams a clearer, more actionable picture: how many people face each barrier, and how barriers often overlap in real life.
Stage 7: Prioritize what’s significant and can be realistically impacted
Not every barrier can or should be tackled. Some, like the cost of medication, may sit outside a team’s ability to change.
That’s why this final step is about focus: identifying the barriers that are both meaningful and addressable, where the need is clear and the solution space is realistic.
The goal: solve the right problem, in the right way, for the right group.
Wrapping up
Behavior mapping is a durable, practical way to reduce wasted effort and ensure solutions match the reality of how people actually behave. Part 1 of this series covers the benefits and challenges of behavior mapping.
Next steps: See behavioral science in action
Want to see how behavioral science transforms digital health solutions? Watch this video where some of our consultants explain how understanding people — and the many factors influencing their behavior — makes interventions more effective and engaging.
