Designing Products Around Behaviors
TLDR: After you select or invent the right behavior(s), design the product or service explicitly to make that behavior obvious, easy, and rewarding in the user’s real context. Validate Solution Market Fit first; then iterate toward Product Market Fit.
Purpose
This phase translates your validated behavior(s) into product and service decisions. The goal is not to ship features. It is to enable the target behavior under realistic conditions with minimal friction and clear value.
Inputs
- Validated Problem Market Fit (the problem exists and matters)
- Validated Behavior Market Fit (users can and will perform the behavior in context)
- Prioritized behavior(s) with known barriers/enablers
Outcomes
- A solution that measurably enables the target behavior (Solution Market Fit)
- Evidence that the behavior sustains in the market with viable economics (Product Market Fit)
Principles
- Behavior-led scope: Start with the behavior and work backward to the smallest solution that enables it.
- Friction removal first: Resolve limiting BSM components (ability, motivation, environment) before adding depth.
- Fast value loop: Deliver immediate benefit on first successful behavior; expose reinforcement for repetition.
- Debug before pivot: If outcomes lag, debug UX and friction thoroughly before swapping target behaviors.
Practical Checklist
1) Behavior-to-UX Mapping
- Express the target behavior as a one-line job: “User schedules a bill payment in the banking app at night to avoid late fees.”
- Map each step the user must perform; mark friction (cognitive, physical, social, environmental).
- Create a “first successful instance” path that minimizes steps, choices, and form fields.
2) Enablement Tactics
- Defaults only when the “behavior” is a one-time configuration decision (and after fit is validated)
- Progressive disclosure to keep the path simple
- Templates/wizards for hard steps
- Immediate, specific feedback on completion
- Credible peer benchmarks or accountability only when they reflect real behavior (treat as marginal optimization)
3) Pilot and Measure (Solution Market Fit)
- Define completion criteria for the behavior
- Instrument Time-To-First-Behavior (TTFB)
- Track completion rate and failure points
- Run small field pilots; iterate to clear friction until ≥ target thresholds
4) Scale and Sustain (toward Product Market Fit)
- Define bPMF for the cohort window (e.g., 30 days)
- Track behavior retention curves (D30/D180)
- Tie behavior change to outcome metrics (revenue, clinical, etc.)
- Verify unit economics and operational readiness
When to Revisit Behavior Selection
If repeated UX debugging and pilot iterations fail to meet Solution Market Fit thresholds (e.g., completion rate, TTFB), return to behavior selection. Pick the next highest‑ranked behavior and repeat.
Alignment with the Overview Article
This phase corresponds to “Product or Service Development” in the overview. The intent is identical: build around the chosen behavior and iterate. The Four‑Fit model makes the interim gate explicit: first achieve Solution Market Fit, then Product Market Fit.
Frequently asked questions
What is Solution Market Fit in Behavioral Strategy?
Solution Market Fit is the gate where the solution reliably enables the validated target behavior in the real environment. If the behavior does not occur, you do not have Solution Market Fit regardless of feature completeness.
When should I revisit behavior selection?
After repeated enablement iterations fail. If you cannot hit feasibility thresholds without heroic effort, you likely chose the wrong behavior (or the wrong population/context constraints). Re-rank candidates and validate the next best behavior.
Are defaults, prompts, and other “nudges” part of product design?
Sometimes, but late. Defaults are configuration and prompts are last-mile. Use them only after the behavior is feasible and validated; treat them as marginal optimization, not a substitute for correct behavior selection.
What is the role of Time-to-First-Benefit (TTFB)?
TTFB is how quickly a user experiences real value after attempting the behavior. Shortening TTFB makes repetition rational; long delays break the loop and increase dropout.
How do I prevent feature creep?
Use behavior-led scope: map every feature to a step in the behavior chain and cut anything that does not reduce friction, increase feasibility, or deliver value at the moment it matters.