ANALYTICS AUDIT — 10-DAY SPRINT

Jake McMahon — ProductQuant

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

Know exactly which data to trust, which gaps to fix, and in what order.

An audit that reviews your entire analytics stack and tells you exactly what’s broken, what it’s costing you, and what to fix first.

Book the Audit → See what’s included ↓

5 actionable improvements worth more than the fee — or full refund.

WHAT GETS AUDITED

Stack assessment Tool config, event taxonomy, data quality, dashboard setup

Event audit Every event reviewed — status, issues, recommendations

Gap analysis 5–10 biggest measurement gaps sized by revenue impact

Fix roadmap Dev-ready specs, prioritised by impact vs. effort

60-min walkthrough Walk through every finding and prioritise what to fix first

Fixed price · 10-day sprint

We build a clear action plan for your data.

You get a prioritized list of fixes for your analytics, so you can trust your numbers and make better decisions.

MARKETING REPORT

"Why do our campaign numbers look different in every tool?"

We find where your tracking is broken or duplicated. You get a single source of truth, so your marketing team can finally trust their reports.

SALES DASHBOARD

The sales pipeline dashboard is always wrong.

We trace the incorrect numbers back to a missing data point in your CRM setup. Your sales director gets accurate forecasts they can rely on.

EXECUTIVE MEETING

"Which of these five reports should we actually use?"

We audit all your reports and dashboards. We tell you which ones are reliable and which to turn off, saving your team hours of confusion.

PRODUCT TEAM

Engineers can't see how a new feature is being used.

We find the gap in your event tracking. Your product managers get the data they need to improve the user experience.

YOU ALREADY KNOW THE DATA IS WRONG

Three people, three answers to the same question

“Someone asked how many users activated last month and three people gave three different numbers. Events fire inconsistently. Properties are missing. We stopped looking at dashboards because the data doesn’t match reality.”

VP Product — B2B SaaS, $8M ARR

Instrumented what was easy, not what matters

“We tracked button clicks, page views, generic events. But the questions that actually drive decisions — which features correlate with retention? Where do users drop off? — can’t be answered with what we have.”

Head of Product — Series B

“Fix analytics” has been on the backlog for two quarters

“Every retrospective ends the same way: we should fix our tracking. But nobody knows where to start. Engineers don’t know what to instrument. Product doesn’t know what to ask for. The gap between the data we have and the data we need keeps growing.”

Product Manager — B2B SaaS

Dashboards exist but nobody opens them

“We built 12 dashboards last year. I checked the view count — most haven’t been opened in weeks. The numbers don’t match what CS sees. Nobody trusts them, so nobody uses them.”

CEO — $5M ARR

WHAT THE AUDIT TYPICALLY FINDS

Most analytics stacks have more broken events than useful ones.

Most events are either broken, duplicated, or tracking actions nobody uses for decisions.

In a typical audit, a minority of tracked events answer a question anyone cares about. The rest are noise that makes your dashboards less trustworthy, not more.

The highest-value features often have no instrumentation at all.

The features driving expansion revenue, retention, or activation rarely have the event coverage to prove it. You can’t tell who uses them, when, or how often — so you can’t double down on what works.

Activation and retention metrics that don’t actually predict anything.

Teams define activation around a feature milestone — “completed onboarding” or “created first project” — and discover most churned users also “activated.” The metric is meaningless, and the real predictor is buried deeper in the funnel.

Revenue impact of each gap is unknown — so the fix never gets prioritised.

Your team knows analytics is broken but can’t justify the engineering time because nobody has sized the cost of each gap. The audit sizes every gap by the revenue it obscures — so the business case writes itself.

WHY AN EXTERNAL AUDIT

Your team built the analytics stack. They can’t audit their own assumptions.

The people who instrumented your product made reasonable decisions at the time. But those decisions accumulated into an event taxonomy that reflects engineering convenience, not product questions. An internal fix starts from the same assumptions that created the gaps. An external audit starts from the questions your team actually needs answered — and works backward to the events required to answer them.

Your PM gets a gap analysis sized by revenue impact. Your engineer gets exact event names, properties, and implementation specs. Your team gets a ranked roadmap they can execute without a meeting to explain it. Everyone works from the same document, pointed at the same priorities.

TIMELINE

A ranked fix roadmap your team can act on immediately.

DAYS 1–2

Stack Assessment

Read-only access to your analytics platform. Tool configuration, event taxonomy, data quality, dashboard setup, and integration health reviewed. No write access, no code changes.

→

DAYS 3–5

Event Audit

Every event reviewed by hand. Which ones are useful, which have broken properties, which critical user actions have no tracking at all. Full inventory with status and recommendations.

→

DAYS 6–7

Gap Analysis

The 5–10 biggest questions your analytics can’t answer today. Each gap sized by revenue impact. This is what the fix roadmap is built on.

→

DAYS 8–10

Roadmap + Walkthrough

Dev-ready specs for each gap. Prioritised by impact vs. effort. 60-minute walkthrough call. Recording included so your team can reference it during implementation.

Day 11: your team ships the fix that recovers the most blind spots.

WHAT YOU GET

19 deliverables that turn unreliable analytics into a ranked fix roadmap.

Days 1–2 · Assessment

Stack Assessment Across 5 Dimensions

Tool configuration, event taxonomy, data quality, dashboard reliability, and integration health scored in one assessment. You see not just what is broken, but how broken it is and what each gap costs the business.

Scored matrix your leadership can use as the baseline for improvement
Integration health checked before bad joins affect major decisions
10+ key reports receive reliability scoring
5–10 specific data quality problems surfaced with fixes

Days 3–5 · Audit

Event-by-Event Audit of 100+ Tracking Events

Every event is reviewed for firing accuracy, naming consistency, property quality, and actual usage. The output is a spreadsheet with status, issues, and recommendations your engineering team can turn into tickets directly.

Every event: status, issues, and specific recommendations
Typically 20–40 decision-affecting event problems identified
Event naming convention standards documented for future tracking
Duplicate, redundant, and unused events marked for cleanup

Days 6–7 · Analysis

Revenue-Sized Gap Analysis

The measurement gaps blocking revenue decisions are ranked by business impact. Abstract data quality concerns become a fix list with a business case behind each item, so the right analytics work gets prioritised.

5–10 significant measurement gaps sized by revenue impact
Questions your data cannot answer today made explicit
Dashboard rebuild priority list ranked by usage and reliability
Data quality fix checklist your team can rerun after the audit

Days 8–9 · Roadmap

Implementation Roadmap with Developer-Ready Specs

Each fix is documented with enough technical detail that a developer can scope and implement it without a follow-up call. The roadmap compresses the gap between audit finding and production fix from weeks to days.

Exact event names and properties your engineers add next
Dashboard charts to build, with the queries behind them
Prioritised by revenue impact vs. implementation effort
Complete audit report sized for leadership and implementation use

Day 10 · Walkthrough

60-Minute Walkthrough + 30-Day Clarification Support

Every major finding is walked through live, decisions about implementation priority are documented, and the recording is structured as a reference for engineers and analysts during the fix phase. For the next 30 days, clarification is included.

Full findings walkthrough with data at each point
Implementation priority discussion notes captured in writing
Follow-up roadmap prioritisation session after capacity is mapped
Everything above for $3,497, with no hourly billing or scope creep

On the cost of bad data: every product decision made without trustworthy analytics is a coin flip dressed up as strategy. If your team ships features based on unreliable data, you risk wasting engineering effort on the wrong priorities. The audit pays for itself the first time your team ships the right fix instead of the loudest opinion.

FIT CHECK

Your dashboards exist. Your team doesn’t trust them. Here’s how to tell if this audit is the right move.

GOOD FIT

B2B SaaS with established revenue and analytics that nobody trusts

PostHog, Amplitude, Mixpanel, or similar running

The situation

You set up analytics months ago and have been adding events since. Dashboards exist but nobody opens them for decisions. Three people give three different answers to the same question. Your team knows the data is unreliable but can’t justify the engineering time to fix it because nobody has sized the cost of each gap.

What you leave with

Every event reviewed — what to keep, what to fix, what to add
The 5–10 biggest gaps sized by revenue impact — the business case for the fix
A dev-ready roadmap your engineering team executes without debate

Decisions backed by data your team actually trusts — starting the week after the audit.

NOT A FIT

Pre-product, no analytics tool, or data isn’t the bottleneck

Wrong stage or wrong problem

When this audit doesn’t apply

If you haven’t set up an analytics tool yet, there’s nothing to audit. If you have very low monthly active users, the data volume may be too low to draw reliable conclusions. And if your analytics are solid but your team doesn’t know what to do with the data, the problem is upstream of instrumentation.

Better starting points

Activation Deep Dive

If activation is the specific problem and you need the funnel mapped end-to-end.

Focused Sprint

Answer a single product question when analytics is solid but insight is missing.

The Foundation

Full growth diagnostic across all six layers — analytics is one piece of that.

What this audit doesn’t cover

The Analytics Audit delivers the diagnosis and the ranked fix roadmap. Your team does the implementation. If you need the full picture — analytics plus retention, activation, competitive, and go-to-market — that’s a different engagement.

Implementing the fixes — your engineering team ships the instrumentation changes
Building dashboards from scratch — the audit specifies what to build, your team builds it
Ongoing analytics management — the audit delivers the roadmap, your team executes it

For the full growth diagnostic → The Foundation

Jake McMahon — ProductQuant

Jake McMahon

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

I run the audit myself. Not a team of analysts. Not an automated report generator. Every event reviewed by hand, every gap sized by me based on what I know about B2B SaaS activation, retention, and expansion revenue. The difference between a useful audit and a checkbox exercise is whether the person doing it knows what a good analytics setup actually looks like — and why most don’t.

Most audits hand you a list of things that are broken. This one hands you a ranked roadmap with revenue sizing and implementation specs. Your PM sees the business case. Your engineer sees the exact event names and properties. Nobody needs a meeting to translate the findings into action.

I won’t do this:

Deliver a generic best-practices checklist without reviewing your actual events
Flag gaps without sizing the revenue impact of each one
Recommend instrumentation changes without providing exact event specs
Treat every analytics platform the same — each has platform-specific issues to look for

What analytics platforms do you audit?

Amplitude, Mixpanel, PostHog, Segment, GA4, Heap, and custom-built stacks. Read-only access is all that’s needed. The audit process is the same regardless of platform — what changes is which platform-specific issues to look for. Custom stacks often have more gaps than managed platforms.

Teams Jake has worked with

PRICING

One price. A prioritised fix list your team acts on the following week.

$3,497

one-time · fixed price

10-day sprint

Stack assessment — tool config, data quality, integration health
Event audit spreadsheet — every event reviewed with recommendations
Gap analysis — 5–10 biggest gaps sized by revenue impact
Implementation roadmap — dev-ready specs, prioritised by impact
60-minute walkthrough call + recording
All assets formatted for your PM, designer, and engineer
Everything stays with your team permanently

At least 5 actionable improvements worth more than the fee — or full refund.

Book a 30-minute call →

If we don't find at least 5 actionable improvements worth more than the audit fee, full refund. If the data can't support meaningful findings, we tell you early and scope what's possible.

Questions.

Or book a call →

What analytics tools do you audit? +

Amplitude, Mixpanel, PostHog, Segment, GA4, Heap, and custom-built stacks. Read-only access is all we need. The audit process is the same regardless of platform — what changes is which platform-specific issues to look for.

Do we need to give you admin access? +

No. Read-only access is sufficient for the entire audit. We’ll specify exactly what we need at kickoff — typically a guest login or read-only API key. No write access, no code changes. The data stays in your systems throughout. Access can be revoked at any time after the audit.

What if we’re on a custom-built analytics stack? +

We audit the architecture regardless of tooling. Custom stacks often have more gaps than managed platforms — which means the audit typically surfaces more value, not less. The same process applies: event review, gap analysis, and dev-ready specs.

What do we own at the end? +

Everything. The stack assessment, the event audit spreadsheet, the gap analysis, the implementation roadmap, and the walkthrough recording. All formatted for your team to use directly. There’s no dependency on ProductQuant after the audit ends.

What happens after the audit? +

You get a prioritised roadmap. If your team has engineering capacity, you implement it yourself. If you want the full diagnostic across all six growth layers — analytics plus retention, activation, competitive, and go-to-market — the audit feeds directly into The Foundation. The audit work carries over and the cost is credited toward The Foundation.

What’s the guarantee? +

If we can't find at least 5 actionable improvements worth more than the audit fee, full refund. No questions. If the data genuinely can't support meaningful findings, we tell you early and scope what's possible.