ONBOARDING REVIEW

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

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

Fixed price · Two-week sprint

We fix the steps where new users get stuck.

We map your signup process, find where people drop off, and give you a clear plan to fix the biggest problems.

USER SIGNUP

“Why do so many people quit after entering their email?”

We show you the exact screen or question that makes people leave. You get a simple fix, like removing a confusing field, so more people complete signup.

PRODUCT TOUR

“New users open the app but don't do the main task.”

We track where users get lost in your tutorial. You learn which step to simplify, so users quickly see your product's core value.

CUSTOMER SUPPORT

“Our team gets the same 'how do I...' questions every day.”

We identify the onboarding step causing the confusion. You can add a tooltip or reword an instruction, which reduces support tickets.

WEEKLY REPORTING

“Our activation rate is low, but we don't know why.”

We pinpoint the biggest drop-off point in your funnel. You get a prioritized list of changes, so you know exactly what to fix first.

DELIVERY
Two-week sprint

From kickoff to scoped fixes and a mapped onboarding funnel. Read-only access — no engineering time required from your team.

GUARANTEE
3 fixes

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

FIXED PRICE
Fixed price

One price. Everything included. Event audit, funnel map, friction log, fix scoping, email audit, and 60-minute readout.

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.

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.

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.

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.

Your team ships the fix that recovers the most lost users from onboarding.

WHAT YOU GET

20 deliverables that turn onboarding drop-off into three buildable fixes.

Week 1 · Instrumentation
Activation Funnel Map with Completion Percentages

A complete picture of onboarding from first login to the moment users get real value, with exact completion percentages at every step. You see precisely where users are leaving, not just that activation is low.

  • Step-by-step drop-off analysis from cleaned event data
  • Shareable funnel visualisation for PM, CEO, and engineers
  • Activation definition agreement documented company-wide
  • Live drop-off dashboard built in your analytics tool
Week 1 · Mapping
Replay, Heatmap, and Cohort Evidence

We watch real users struggle through onboarding and combine that qualitative evidence with heatmaps and cohort splits. The result is visual, behavioural proof of why users are stuck, not a spreadsheet of unexplained percentages.

  • 30–80 session replays reviewed, scaled to drop-off concentration
  • Heatmap analysis of critical onboarding screens
  • Cohort breakdown by plan, channel, and device
  • 8–15 timestamped replay highlights for stakeholder buy-in
Week 2 · Diagnosis
Instrumentation Gaps + Revenue Impact

Specific tracking gaps are documented with the insight they block and the business cost of staying blind. Each drop-off point is also sized in revenue terms, so engineering resources can be justified with numbers instead of complaints.

  • 4–12 specific missing events identified with priority
  • Revenue impact calculated per drop-off point
  • Root cause analysis per step, not just a funnel number
  • Effort versus impact matrix for every friction point
Week 2 · Prioritisation
Top 3 Engineering-Ready Fix Recommendations

The output is not “improve onboarding.” You get three specific changes with acceptance criteria your developers can act on immediately, plus experiment designs for validating the fixes before a full build.

  • Specific fix recommendation per drop-off point
  • 3 experiment designs with hypothesis, metric, sample size, and duration
  • Quick wins separated from structural product changes
  • Prioritised by what your team should build this sprint versus next quarter
Week 2 · Email + Readout
Full Report, 90-Minute Readout, and Support

Every finding, recommendation, and piece of evidence is documented in a written report your board, investors, or future VP of Product can understand. The recorded readout aligns the team, and 30 days of implementation support keeps the fixes faithful to the diagnosis.

  • Every finding and recommendation documented with supporting evidence
  • 90-minute recorded readout with prioritisation support
  • Fix prioritisation follow-up once implementation has started
  • Everything above for $3,997, with no hourly billing or scope creep

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. The review finds the step that loses 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

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.

  • 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

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.

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

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

Gainify
Guardio
monday.com
Payoneer
thirdweb
Canary Mail

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.

Know exactly where onboarding loses users, why, and which three fixes recover the most of them.

Your onboarding funnel mapped from the data. The drop-off confirmed — not debated. Three fixes your team can ship this quarter, scoped for engineering and ranked by impact.