Product Exercise
Today, CardSwitcher presents merchants in a generic list. Users have no signal about which merchants matter most to them. By sorting merchants by spend, billing urgency, and reward multiplier, we can surface the highest-value switches first.
Generic onboarding, no confidence signal
Choose which merchants to update with your new American Express card.
Personalized recommendations build confidence
Your merchants, ranked by spend, urgency, and reward potential.
Outcome
Personalized ordering guides users to high-value merchants first. Contextual urgency drives immediate action and builds momentum to complete the full list.
How it works
Issuers already share transaction data with Knot. We use that to score each merchant by when they'll bill next, how much the user spends there, and what reward multiplier applies.
Personalized reordering consistently lifts conversion in similar fintech and e-commerce flows. We modeled a conservative lift on CardSwitcher's baseline — the exact number is less important than the signal from a 30-day A/B test.
A scoring algorithm and a sort parameter on the existing API. No SDK changes for issuers. A/B test with one partner, measure completion rate over 30 days.