Reorganising high friction clients into a six segment psychographic model that realigns how the service is delivered. The program is a chronic care service for 7,000+ clients.
At Amura, a client complaint becomes an escalation the moment a manager gets tagged in a message or called into the group chat directly. Escalations matter because they burn expensive backstage resources. They emotionally exhaust the care team and their managers and quietly degrade the experience of every other client under that same care team.
“Clients drop off because they are not serious. The protocol works, so the failure sits with the client.”
A belief awaiting evidenceThe record of what clients actually did, sitting in their chats, calls and escalations.
The reason underneath, held by the people who watch these clients daily.
Reconstructs what happened, from 80 clients worth of chats, recorded calls and escalation logs.
Surfaces the why, sitting with and questioning coaches, doctors and escalation managers.
Now the belief can be tested against real behaviour.
The real question: who are the clients unaware of the effort required on their end to succeed in this program and can that be seen coming?
Before the findings, the shape of the work. About 44 days, front loaded onto reading the raw signal, because the answers were already sitting in what clients had said and done. Synthesis and modelling were fast once the signal was clean.
The founder read the drop offs as a client commitment problem. I treated that as a claim to verify and went to the record for the evidence.
What clients actually did was already recorded in their own chats, calls and escalations, so I started there. With 7,000+ clients I needed a defensible cut. The protocol and the systems had held steady for eight months, so behaviour was comparable across that window. I took the clients who had breached the escalation benchmark of three in a six month journey. That gave 120. I read 80 of them closely, the number I could do justice to in the time.
confusions, friction points, resistance to protocol, fears, lifestyle issues, adherence gaps and reasons for deviation.
the final tipping point, plus how much each client could tolerate before breaking.
The remaining gap. The records explained most of the behaviour. To reach the why behind the rest, I turned to contextual inquiry.
The records tell you what a client did. The why lives with the coaches, doctors and escalation managers who sit with these clients week after week, so I ran more than 20 sessions, part observation of the real work and part structured conversation, to reach the why behind the behaviour.
the daily texture: what clients say between sessions and where they quietly bend the plan.
the clinical read: which deviations are medical and which are behavioural.
the breaking point: what a client sounds like just before asking for a refund.
Eighty clients across two methods is a wall of observations. Affinity mapping clustered that wall by what the notes had in common. Thematic analysis then named the patterns that kept recurring. Those patterns are what became the segments and the failure stages.
clustered a wall of observations into groups by what they shared.
named the patterns that recurred and turned them into the segments and the failure stages.
The boards themselves are not shown. They hold real client data, so the outputs stand in for the working.
Why not personas, or demographics? During the audit, a 20 year old student in the US and a 64 year old retiree in Kerala turned out to show identical adherence patterns. That was the proof: in chronic care, demographics like age, gender and geography are poor predictors of behavior.
Adherence is driven by internal mental models and a lifetime of health related stimuli, not anything trackable in a straight line. Psychographic segmentation made it possible to design for the belief system rather than the biography, surfacing 6 distinct segments that predicted how a client would respond to the program long before they dropped off.
“This reversal should slot seamlessly into my existing schedule.”
“My environment and schedule must be intentionally redesigned until this behavior becomes a habit.”
Time based restriction lapses. Program follow through. Meal planning consistency. Supplement adherence.
Health management is filed away as a background task. Business and family responsibilities stay the core priorities, leaving limited mental and physical bandwidth for execution. Program effort reads as a productivity tax.
“If the program is truly effective, it should be manageable alongside my current lifestyle without requiring significant sacrifice.”
“The intensity of my desire to change equals my capacity to execute.”
“Sustainable change requires environment design, not just sheer willpower.”
Lapses in consistency, especially during social eating. High emotional fatigue. Regression to old habits when motivation dips.
The client significantly overestimates individual discipline and underestimates social and cultural friction. Relying purely on willpower creates a cycle of high initial effort followed by inevitable burnout.
“Failure is personal weakness. If I truly want this outcome, I will force myself to make it work, regardless of the environment.”
The first real realization here: it is not entirely anyone's fault when a client arrives with the wrong mindset. Even so, it becomes the service's job to recognize that mindset early and subtly correct course before it hardens into disengagement.
Mapping each segment against the actual protocol made the failure visible, not as a vague non compliance label, but as a specific stage in the journey where a designed intervention was missing and where a policy reminder was never going to fix it.
“This is a bit more complicated than I thought.”
“I didn't expect it to be this strict.”
“Why are there so many things to follow daily?”
“I missed it today, but I'll do it properly tomorrow.”
“I'm mostly following, just adjusting a little.”
“I couldn't manage it with my schedule today.”
“I'm doing everything, but I don't see any change.”
“Is this supposed to feel like this?”
“I'm not sure if this is working for me.”
“This is getting hard to manage every day.”
“I have too much going on to keep up with this.”
“I'm trying, but it's not sustainable like this.”
“This is not working for my lifestyle.”
“I need something more practical.”
“I can't continue like this.”
Once approved, the model became a living parameter on every client. The coach reads each client against the six mindsets and revisits it as they move through the program. When a client matches a high risk mindset the matching interventions switch on. Coaches and doctors then tailor coaching and medical advice to that specific mindset.
every client, revisited as a living parameter through the program.
when a client matches a high risk mindset.
coaches and doctors adapt to the specific mindset.
What those interventions are is the subject of case study 02.
This audit gave the team the ground truth to move from a one size fits all service to a targeted, mindset aware model. The shift was tracked across three teams whose clients made up the 80 audited, comparing a cohort before the behaviour failure model with a comparable cohort after it.
| Before the model | After the model | |||||||
|---|---|---|---|---|---|---|---|---|
| Team | Cohort | Escalations | Refunds | Flags acted | Cohort | Escalations | Refunds | Flags acted |
| Team 32 | 67 | 18 (27%) | 12 (18%) | 0 | 36 | 7 (19%) | 0 (0%) | 23 |
| Team 16 | 58 | 16 (28%) | 9 (16%) | 0 | 43 | 8 (19%) | 3 (7%) | 19 |
| Team 21 | 72 | 20 (28%) | 11 (15%) | 0 | 48 | 8 (17%) | 3 (6%) | 25 |
| Pooled | 197 | 54 (27%) | 32 (16%) | 0 | 127 | 23 (18%) | 6 (5%) | 67 |
The before and after groups are comparable cohorts measured at the same stage of the program. The lever is the early risk flag: the model gave coaches a way to catch and act on risk early, 67 times across the after cohorts.
Research as a business metric: user friction is effectively an operational tax. Translating user pain into wasted clinical bandwidth made the research land with stakeholders in their own language. Demographics, in this case, turned out to be noise. Mental models were the real signal.
Empathy has to extend beyond the client to the clinical staff delivering the service. If a service design burns out the doctors and coaches behind it, the client experience fails no matter how good the client facing design looks.