TF Trust-First Retention

Consumer growth · Trust · Retention

Portfolio simulation: Fictionalized company context and synthetic scenario data.

Make leaving easy.
Make returning believable.

A product case study for the moment most retention teams optimize backwards: cancellation. Explore the experience, inspect the friction, and test the launch decision.

Try the flow Read the PRD

01 · Product experience

One relevant alternative. Zero obstruction.

The response changes with the customer's reason; the route back to cancellation never does.

Account · Membership

Step 1 of 2

What changed?

Choose the closest reason. This helps us show one relevant option—and improves the product whether you stay or go.

Cancellation reason

02 · Friction map

Diagnose the decision, not the click path.

Open the full evidence map ↗
01

Find

“Where is cancellation?”

Navigation debt
02

Understand

“What happens to my data?”

Consequence ambiguity
03

Decide

“Is there a better-fit option?”

Choice overload
04

Confirm

“Did it actually cancel?”

Status uncertainty
05

Recover

“Can I come back later?”

Re-entry anxiety

Evidence discipline: the full map labels each friction as observed, inferred, or unknown. Unknowns become research questions—not facts.

03 · Decision lab

Would you ship this outcome?

Choose a synthetic scenario. The recommendation follows pre-registered thresholds, not the prettiest lift.

Recommendation

Ship to 25%

All gates pass

The base case clears the value threshold and every trust guardrail. Ramp gradually and review reason-level heterogeneity before 100%.

30-day retained value

+5.8 ppShip: ≥ +3.0 pp

Cancellation completion

92.6%Guardrail: ≥ 90.0%

Support contacts

−22%Guardrail: ≤ 0% change

Post-flow trust

+0.1Guardrail: ≥ −0.1 / 5

Decision rule Ship only if retained value clears the threshold and every guardrail passes. A dark-pattern win is counted as a product loss.

Audit metric definitions ↗

All values in this lab are synthetic scenario data for portfolio demonstration.