Fix the flows that decide whether you get paid.
Onboarding, activation, upgrade, and renewal — the journeys where users decide to stay, to pay, and to come back. We redesign them using data on where people drop off and why, not from intuition, and hand you a plan to prove the new flow actually moved the number.
Your funnel leaks, and nobody's sure exactly where.
People sign up and never come back. Trials end without a card. Each step in the journey quietly sheds a fraction of the people who started it, and the running theory about why is usually a guess dressed up as a fact. The flow looks fine when you click through it yourself — but you already know where the next button is. We find the leaks the way they actually show up: in the funnel, in session replays, in the steps where real users hesitate and quit. Then we redesign those steps and prove the fix in the numbers. Less polishing screens that already work; more closing the gaps that cost you customers.
A pretty flow that still loses people.
Each symptom points to a specific step in the journey — and to the number it's costing you.
- 01
Onboarding drop-off is a top metric
A redesigned onboarding flow built around the exact step where people leave.
- 02
Trial-to-paid conversion is below target
A path that gets users to the value moment before the upgrade prompt ever appears.
- 03
You don't know where users get stuck
Funnel data and session replays that show the real stuck spot, not the guessed one.
- 04
The flow 'feels clunky' but nobody can say why
A friction inventory: each hesitation point named, measured, and ranked.
- 05
You shipped a fix and can't tell if it worked
A hypothesis and a before-after metric attached to every flow we change.
Flows fixed where the data points.
Not a prettier version of the same leak — the specific steps where people quit, redesigned and measured.
Current-state flow analysis
How onboarding, activation, upgrade, and renewal really work today — drop-off and all.
Friction inventory
Every hesitation point, ranked — tied to the evidence and the metric it hurts.
Redesigned flows
New onboarding, activation, upgrade, and renewal paths, built where the data points.
Hypothesis & measurement plan
A metric per change, a baseline, and a way to prove the redesign worked.
From a leaky funnel to a flow that converts.
- 1Map current
- 2Find friction
- 3Redesign
- 4Hypothesize
- 5Measure
Each step earns the next: mapping the current flow shows where the funnel leaks, the friction pass explains why, the redesign closes the gap, and a written hypothesis plus a baseline make “did it work?” answerable once it ships.
Where users drop off — measured.
We instrument the journey and look at it three ways: the funnel shows which step falls off a cliff, session replays show what people were doing right before they left, and a heuristic pass flags where a flow breaks what users expect. The stuck spot is almost never where the team assumed — and the data settles the argument before anyone redesigns a thing.
- Funnel data, step by step
- Session replays at the drop-off points
- Heuristic walkthrough of the journey
- The real stuck spot, not the guessed one
Every hesitation, on one list.
We map the current state in full — every screen, branch, and edge path, including the empty states and dead ends users actually hit — then turn it into a ranked friction inventory. Each point is tied to evidence and to the metric it costs you, so 'the onboarding feels clunky' becomes 'this step loses 12% of sign-ups.' Not every friction point is worth fixing; the inventory tells you which ones are.
- Full current-state flow map
- Edge paths and moments of doubt included
- Each friction point tied to a metric
- Ranked by cost, not by gut feel
New flows, with a way to prove them.
We redesign the flows the data pointed at — onboarding, activation, upgrade, renewal — and attach a hypothesis and a metric to each change before it ships. We capture the baseline up front and plan the A/B test or before-after read, so the new flow doesn't just look better: you can show it moved trial-to-paid, lifted activation, or cut the drop-off it was meant to fix.
- Onboarding, activation, upgrade, renewal redesigned
- A hypothesis written for each change
- Baseline captured before launch
- A/B or before-after plan to prove it
From the data, to the flow, to the proof.
Instrument the journey
We pull the funnel data and session replays for the flow you're worried about — and find where the numbers fall off.
Map the current state
Every screen, branch, and edge path laid out end to end, annotated with where users actually drop.
Inventory the friction
Each hesitation point named, tied to evidence and to the metric it costs, then ranked.
Redesign & hypothesize
New flows where the data pointed, each with a written hypothesis and the metric it should move.
Measure & iterate
A baseline, an A/B or before-after plan, and a read on whether the change actually worked.
The funnel is leaking and the theories are guesses.
Onboarding drop-off is your top metric
People sign up and never make it to the value — and the step where they leave is the one you watch most.
Trial-to-paid is below target
Plenty of trials, not enough cards. The upgrade prompt lands before users ever feel why they'd pay.
You can't say where users get stuck
Something in the journey is leaking, the theories are guesses, and nobody has looked at the replays.
Methods chosen to find the leak, not to fill a deck.
The things teams ask first.
Stop the leak where it happens.
Tell us which flow is costing you — onboarding, trial-to-paid, renewal — and what the metric looks like today. We'll find where users actually drop off, redesign the steps that matter, and hand you a plan to prove the fix moved the number.