ONBOARDING REVIEW — $3,997 · 2-WEEK SPRINT

Jake McMahon — ProductQuant

8+ years B2B SaaS · Behavioural Psychology + Big Data (Masters)

More new users reach the core value moment because you fixed the onboarding steps that were losing them.

A 2-week sprint that maps your onboarding funnel from signup to activation — confirms where users abandon, and scopes the top 3 fixes by impact.

Start the Onboarding Review → See what’s included ↓

3 scoped fixes with data behind them — or full refund · 2-week delivery

WHAT YOU HAVE AT THE END

Onboarding funnel mapped Signup to first core action, every step with completion rates from data

Drop-off confirmed With event data and session replays — not assumptions

Top 3 fixes scoped Engineering-ready scope, effort estimate, and expected impact per fix

Email sequence audit Timing and messaging reviewed against where users actually drop

60-min readout Walk-through with your team, questions answered

$3,997 · fixed price · 2-week sprint

YOU ALREADY KNOW SOMETHING IS WRONG

Users complete setup but never come back

“We’re getting signups. They complete the setup flow. Then they just… don’t come back. Support sees some of them but most we never hear from again. Nobody’s figured out what’s happening in those first 14 days.”

VP Product — B2B SaaS

Onboarding emails aren’t moving activation — root cause unclear

“We send a welcome email, a feature tip, and a check-in. Open rates are fine. Click rates are fine. But it’s not moving activation at all. We keep tweaking the subject lines. I’m not sure the email is even the problem.”

Head of Growth — Series A

Time to value unmeasured — no definition, no baseline

“Someone asked how long it takes users to reach their first success in the product. Nobody knew. We guessed ‘a few days.’ I pulled the data and nobody could agree on what event counted. Time to value is a phrase we use but can’t measure.”

Product Manager — B2B SaaS

Team deadlocked — product vs. onboarding vs. messaging

“Product thinks the onboarding flow is fine and the problem is the product itself. Marketing thinks it’s a messaging mismatch. CS thinks users need more hand-holding. We’ve been having this conversation for three months.”

CEO — Seed stage

WHAT THIS TYPICALLY UNCOVERS

The onboarding step losing the most users is almost never the one your team is debating.

The biggest onboarding drop is rarely where the team thinks it is.

Teams usually focus on the step that feels most complex. But the data typically points to an earlier step that looks simple — a step nobody flagged because it seemed obvious. Users leave before they reach the part everyone is debating.

Onboarding emails often fire at the wrong step in the user’s actual journey.

Email sequences are usually timed to the intended onboarding path. But when users abandon at step 2, the email that fires at step 4 never reaches them. The timing problem hides behind decent open rates.

Users who reach the value moment in the first 48 hours typically retain far longer.

Time-to-value is usually a stronger predictor of retention than which features users try during onboarding. The sprint identifies the steps that slow users down inside that critical window.

“Completed onboarding” may not predict who stays.

Teams often define success as finishing the setup flow. But when you check against retention data, a different action — often one that happens after the guided sequence ends — predicts who becomes a paying customer.

WHY THIS IS DIFFERENT

Most onboarding reviews end with a list of observations. This one ends with ranked fixes your engineer can build next sprint.

UX reviews tell you what looks broken. Session recordings give you a bag of observations. Neither tells you which drop-off point matters most or what to build first. Teams end up with a long list of possible improvements and the same debate about priority they started with.

This sprint works from the quantitative funnel down. Step-level completion rates establish where users actually abandon — not where the recording looks uncomfortable. The root cause at each drop-off is confirmed from event sequences and session replays together, not inferred from one signal. And every fix comes out scoped: what to change, how much engineering it takes, and what activation rate movement to expect.

The email sequence audit happens in the same sprint because onboarding emails rarely fail in isolation — they usually fail because they’re timed to a step the user already abandoned. The audit reviews timing and messaging against the actual funnel map, not the intended one.

TIMELINE

From raw event data to knowing which onboarding fix recovers the most lost users — in 14 days.

WEEK 1

Audit + Map

Read-only access to your analytics tool. Event coverage audited across every onboarding step. Instrumentation gaps identified. Full funnel mapped with step-level completion rates. Session replays reviewed at the top exit points.

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WEEK 2

Scope + Review

Top 3 fixes scoped with engineering effort and expected impact. Email sequence reviewed against the actual funnel map. Each fix classified by type — copy, UI, or engineering — with dependencies documented.

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DAY 14

Readout + Handover

60-minute session with your product and growth leads. Funnel walked through step by step. Fixes ranked and scoped. Everything handed over — nothing withheld.

Day 15: your team ships the fix that recovers the most lost users from onboarding.

WHAT YOU GET

Three fixes your engineer builds next sprint — not twenty observations your PM files away.

Week 1 · Instrumentation

Event Audit — Trust the Data First

Before the funnel can be mapped, the instrumentation needs to be trusted. Missing and misfiring events identified across every onboarding step — so the drop-off data reflects reality, not gaps in tracking.

Event coverage mapped across every onboarding step
Missing and misfiring events identified and flagged
Quick instrumentation fixes scoped if critical gaps exist
Confidence rating per step before analysis begins

Week 1 · Mapping

Full Onboarding Funnel Map with Drop-Off Data

Every step from signup to first core action, with measured completion rates at each transition. Not a wireframe — a data-backed map of where users actually go and where they stop.

Step-by-step funnel with completion rates at each stage
Time-to-completion analysis across the sequence
Cohort splits: free vs. paid, channel, plan type
The expected path vs. what users actually do

Week 2 · Diagnosis

Friction Log from Session Replays

The 3 steps where the most users leave, with root causes confirmed from session replays reviewed against the quantitative drop-off map. Observation triangulated with data — not a bag of recordings.

Drop-off ranked by volume and downstream activation impact
Root cause per step: friction, confusion, missing value signal, or wrong expectation
Session replay highlights for each confirmed drop-off point
What users do in the two minutes before they abandon

Week 2 · Prioritisation

Top 3 Fix Recommendations with Engineering Scope

For each drop-off point: one recommended fix, scoped for your engineering team, with effort and expected impact estimated. The debate about what to build first ends with this document.

Specific fix recommendation per drop-off — not directional guidance
Engineering effort estimated in days, classified by type
Expected activation impact ranked by return-on-effort
Quick wins clearly separated from structural changes

Week 2 · Email + Readout

Email Sequence Audit + 60-Minute Readout Session

Your onboarding email sequence reviewed against the actual funnel map — timing, messaging, and step alignment. Followed by a live session with your product and growth leads walking through every deliverable.

Email timing reviewed against when users actually drop
Messaging gaps identified where copy creates wrong expectations
Full funnel walkthrough with data at each step
Fix prioritisation reviewed and confirmed with your team

On cost of delay: every signup that completes onboarding but never reaches the value moment is revenue your product already earned the right to collect. If 100 signups come in per month and 40% never become active, that’s 40 users who wanted to pay but got lost in the onboarding. The review finds the step that lost them — and turns existing signups into active users without touching acquisition spend.

FIT CHECK

Users sign up. Most never reach the moment that makes them stay. Sound familiar?

GOOD FIT

B2B SaaS where users complete signup but don’t become active within 14 days

Onboarding exists · activation gap confirmed

The situation

You have an onboarding flow — some combination of in-product steps, email sequences, and possibly guided setup. Users are completing the initial signup. But within 14 days, a meaningful share has gone quiet: not converting, not using the product regularly, not becoming paying customers. You have some analytics but haven’t structured it into a step-level funnel that reveals where the abandonment happens.

What you leave with

Step-level drop-off rates that end the guessing about where users exit
Root causes confirmed from data — not inferred from surveys or hypotheses
Top 3 fixes scoped and ready for your next sprint

More new users reach the value moment — new revenue from traffic you already have.

NOT A FIT

Pre-launch, no onboarding instrumentation, or onboarding isn’t the constraint

Wrong stage or wrong problem

When this sprint doesn’t apply

If you haven’t launched yet, there’s no funnel to map. If your product has no onboarding instrumentation at all — no events firing across the signup and setup flow — the event audit in Week 1 will reveal that quickly, but there won’t be enough data for a reliable funnel map. And if users are onboarding fine but churning at 90 days — then this sprint is pointed at the wrong problem.

Better starting points

Instrumentation Setup

Get your event tracking in place before running any analysis sprint.

Focused Sprint

Answer “where does churn concentrate?” when retention is the bottleneck.

The Foundation

Covers onboarding alongside retention, competitive, and go-to-market.

What this sprint doesn’t cover

The Onboarding Review delivers the analysis and scoped recommendations. Your team does the building. If you need the full picture — including implementation — that’s a different engagement.

Implementing the fixes — your engineering team ships the changes
Redesigning the onboarding UX — the sprint identifies where, not how to redesign
Ongoing experimentation — the sprint delivers scoped fixes, your team runs the experiments

For full implementation → Growth LAB

Jake McMahon — ProductQuant

Jake McMahon

8+ years building retention, activation, and growth programs inside B2B SaaS · Behavioural Psychology + Big Data (Masters)

I run this sprint myself — the instrumentation audit, the funnel mapping, the session replay review, the fix scoping. Not a team, not a template. Onboarding problems are specific to your product, your user type, and the gap between what users expect when they sign up and what they actually encounter. Generic audits produce generic recommendations.

The output is built for your product team to act on directly. The funnel map tells your PM which steps to prioritise. The engineering scope tells your dev lead what to build. The email audit tells your growth lead what to change. No interpretation required — everything is formatted for the person who needs to use it.

I won’t do this:

Deliver drop-off findings without root causes — “users exit at step 3” is not actionable on its own
Recommend fixes without scoping them for engineering
Conflate a UX observation report with a data-backed funnel analysis — they produce different answers
Audit onboarding emails without referencing the actual drop-off data to judge their timing

What if we barely have analytics?

Most onboarding sprints start with incomplete instrumentation. The audit in Week 1 identifies exactly what’s missing and what can be trusted. If gaps are significant, we scope the minimum fixes needed and work with what exists for the funnel map. You leave with both the onboarding findings and an instrumentation roadmap — so the next engagement has better data to work with.

Teams Jake has worked with

PRICING

One price. Everything your team needs to fix onboarding.

$3,997

one-time · fixed price

2-week sprint

Event audit — instrumentation gaps identified and flagged
Full onboarding funnel map with step-level completion rates
Friction log from session replay review at each drop-off
Top 3 fix recommendations with engineering scope and effort estimates
Email sequence audit reviewed against the actual drop-off data
60-minute readout session with your team
All assets formatted for your PM, engineer, and growth lead
Everything stays with your team permanently

3 scoped fixes with data behind them — or full refund. No conditions.

Book a 30-minute call →

3 scoped fixes that recover the most lost users from onboarding — backed by your data — or full refund. If the data can’t support a scoped fix list, we tell you in week 1 and scope what’s possible. The deliverable either exists or it doesn’t.

Questions.

Or book a call →

What if we barely have analytics? +

The sprint starts with an instrumentation audit precisely because most products have gaps. We work with what exists and scope the minimum fixes needed to make the funnel map reliable. If instrumentation is too sparse for quantitative analysis, we shift to a mixed-methods approach using session recordings and support data — and document the exact events to add for a cleaner analysis next time. You leave with both the onboarding findings and an instrumentation roadmap.

How is this different from a UX audit? +

A UX audit surfaces friction based on observation and heuristics. This sprint surfaces drop-off based on data — actual completion rates at each step, confirmed by session recordings and event sequences. The distinction matters because friction that looks bad in a recording may not be where the drop-off actually happens. We go where the data points, not where the recording looks uncomfortable.

Do you run the fixes or just recommend them? +

The sprint delivers the diagnosis and the scoped fixes — your engineering team builds them. Each fix recommendation includes an effort estimate and a clear outcome to measure, so your team knows what to build and how to confirm it worked. If you want full implementation — the onboarding redesigned and the experiment run to confirm the improvement — that’s a Growth LAB engagement.

What if activation is fine but retention isn’t? +

The sprint will surface this. If completion rates are reasonable across the funnel but 14-day retention is still low, the analysis shifts toward whether users are reaching genuine value or just completing steps mechanically. In that case the deliverable becomes a value-gap analysis rather than a friction-reduction plan — and you get a clear recommendation on where to look next.

What’s the guarantee? +

If the sprint doesn’t produce 3 scoped fixes with data behind them, you get a full refund. The guarantee is straightforward: the deliverable either contains a data-backed diagnosis or it doesn’t. If the data genuinely can’t support a definitive answer — which is rare — we tell you that before day 14 and refund in full.

What do we own at the end? +

Everything: the event audit, the funnel map, the friction log, the fix recommendations, the email sequence audit, and all supporting analysis. Formatted for the people who need to use them — the funnel map for your PM, the engineering scope for your dev lead, the email audit for your growth team. No dependency on ProductQuant after the sprint ends.