Outcome-Based Customer Diagnostic
Study successful customers, find shared behaviors, and design around them.
- Difficulty
- Moderate
- Time to result
- ~weeks to results
- Steps
- 6
- Confidence
- 95%
The Outcome-Based Customer Diagnostic starts with customers who already achieve the best results rather than with assumptions about what the product should provide. Select the strongest users, examine their repeated behaviors, and identify the touchpoints they share. In Star's case, successful members participated in community, attended live training and coaching, learned from guest speakers, networked, and helped one another. Those patterns then informed both the offer's messaging and its customer experience. The mechanism is outcomes to behavioral patterns to product emphasis to broader adoption. Because the analysis is observational, teams should treat common behaviors as hypotheses and verify that encouraging them improves results for a wider customer population.
Origin
Extracted from The Jasmine Star Show, where the Social Curator team diagnosed what its most successful members did differently and shifted the launch toward community-led participation.
Core principles
- 01Access to tools does not guarantee use.
- 02Motivation alone often produces temporary engagement.
- 03Successful customers reveal which behaviors support outcomes.
- 04Products should make high-value behaviors easier and more visible.
How to run it
- 1
Define customer success
Choose clear outcomes that distinguish customers receiving exceptional value. Use behavioral and business results where possible.
Pro tip Combine quantitative outcomes with evidence of sustained use.
Watch out Do not equate frequent logins automatically with meaningful success.
- 2
Select the strongest cohort
Identify customers consistently achieving those outcomes. Use a cohort large enough to reduce the influence of unusual individuals.
Pro tip Include customers from different backgrounds or acquisition periods.
Watch out A tiny handpicked group can produce misleading patterns.
- 3
Map shared behaviors
List the features, events, relationships, and routines the successful cohort repeatedly uses. Note frequency and sequence where the data permits.
Pro tip Interview customers to capture behaviors not visible in analytics.
Watch out Do not rely solely on what customers say they do.
- 4
Prioritize plausible drivers
Separate behaviors that merely accompany success from those likely to help create it. Form explicit hypotheses about the strongest candidates.
Pro tip Look for behaviors that expose customers to feedback, accountability, or collaboration.
Watch out Shared behavior is evidence of association, not proof of causation.
- 5
Design for adoption
Adjust onboarding, programming, messaging, and product flows so more customers encounter and repeat the high-value behaviors.
Pro tip Make the first beneficial behavior easy during the customer's first week.
Watch out Do not force every customer into one rigid participation style.
- 6
Verify improved outcomes
Measure whether customers adopting the emphasized behaviors achieve better results over time. Refine the product based on that evidence.
Pro tip Compare cohorts before and after the experience change.
Watch out Engagement gains without outcome gains may indicate activity rather than value.
In the wild
Star's team examined the members getting the most use and strongest results from Social Curator. The common behaviors were participation in community, live training, guest classes, coaching, networking, and peer support. The team consequently made community a central value proposition and built Welcome Week activities around participation.
→ Observed customer-success patterns shaped both launch messaging and the redesigned member experience.
Common mistakes
Assuming tools create outcomes
Customers may receive useful resources without putting them into practice. Study the behaviors that convert access into application.
Overinvesting in motivation
Repeated motivational pushes can create short-lived activity while consuming substantial effort. Build routines, relationships, and structures that sustain behavior.
Treating association as causation
Successful customers may share behaviors that do not cause their success. Test whether encouraging those behaviors improves outcomes for other cohorts.
Is it for you?
Best for
It is best for memberships, courses, software, and service programs with uneven engagement and enough customer history for comparison.
Not ideal for
It is not ideal when outcomes are undefined or too few customers have completed the experience to reveal credible patterns.
From the transcript
“What was the common theme between them? Biggest thing. They were a part of the community.”
“And so then I thought, okay, well, if you give people the tools to use them and you provide some motivation or momentum, then then…”
“You have to give disproportionate amounts of motivation to actually get people to use the tools.”
From the episode
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