Diagnostic for product and growth leaders Typical diagnostic: $3,500-$7,500

The $500K Question

Your team is about to bet next quarter on something. Maybe a feature push. Maybe a lifecycle workflow. Maybe a new growth program. This diagnostic is built to answer the uncomfortable question first: is this actually the right thing to bet on before you burn the quarter proving it the hard way?

Book This Diagnostic Fixed fee. Usually delivered in 2-3 weeks. Built for teams that need clarity before they commit roadmap, engineering time, or activation budget.

See what actually moves revenue before you burn a quarter

  • A ranked view of which behaviors, features, segments, or workflows correlate most with revenue
  • A stop-doing list for sacred cows that look important but do not move the metric
  • A sharper MVP-first roadmap for the next experiment or activation workflow
  • A clean handoff into activation or product analytics implementation

This is for you if...

  • Your roadmap is full of plausible ideas but weak proof
  • You need to know where product, marketing, and revenue data agree before you place the next bet
  • You want an MVP-first approach, not a six-month analytics program
  • You need evidence strong enough to change the planning conversation

This isn't the right fit if...

  • You want a perfect model of every customer behavior before acting
  • You need a large experimentation platform implementation
  • You are unwilling to stop doing things the data does not support

What you get

Leverage map

A ranked view of the growth bets, features, segments, or workflows most tied to real outcomes.

Stop-doing list

The initiatives that look important but are not earning their place in the plan.

MVP recommendation

A practical first workflow or analytics implementation to prove value fast.

Implementation path

A direct next step into Data Activation or a narrower analytics engagement.

How It Works

1

Frame

We identify the upcoming bets, the target metric, and the systems holding the relevant product, growth, and revenue data.

2

Connect

We line up usage, acquisition, lifecycle, and outcome data well enough to compare signal against noise.

3

Rank

We produce a leverage map showing what appears correlated with revenue, retention, or expansion — and what does not.

4

Decide

You leave with a sharper next bet, a clearer stop-doing list, and a pragmatic path to implementation.

Get the framework we use to pressure-test growth bets

Not ready to book yet?

Get the framework we use to pressure-test growth bets

Most roadmap debates are opinion fights dressed up as strategy. This framework shows how we separate real growth signals from executive intuition so your next big bet is grounded in what actually correlates with revenue and retention.

  • How we distinguish high-signal growth indicators from vanity metrics that look good in a deck
  • The questions we ask before recommending a product analytics build versus a quick experiment
  • A practical way to frame the investment conversation for leadership without stalling momentum
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Where this usually leads

PLG SaaS Product Team

Reverse ETL workflow shipped in 3 weeks and reduced churn 18%

The data showed which accounts were at risk — the missing piece was acting on it. We shipped a reverse ETL churn workflow in three weeks and cut churn 18% that same quarter.

Read case study

Mid-Market Ecommerce SaaS

Warehouse-as-CDP approach replaced an expensive vendor and improved activation flexibility

They were paying $120K/year for a CDP they’d outgrown. We replaced it with warehouse-native segmentation and reverse ETL — more flexibility, fraction of the cost.

Read case study

Ready for the full engagement?

Need to instrument the growth model, not just test the bet?

If this diagnostic confirms the growth bet is worth pursuing, Revenue Analytics builds the tracking, attribution, and reporting infrastructure to prove it at scale.

Explore Revenue Analytics

Go Deeper

If the answer is not another dashboard but a workflow that changes behavior, this is the next layer down.

See Data Activation

Related Reading

Common questions before booking this diagnostic

Do you need perfect experimentation data for this to be useful?

No. The point is to make a better next bet with the data you actually have, not to hold the roadmap hostage until the instrumentation is perfect. We will call out where confidence is strong versus directional.

What kinds of bets does this help evaluate?

Typical examples include feature priorities, onboarding changes, lifecycle workflows, segmentation ideas, scoring models, and activation programs where the team needs to know what is most likely to move revenue or retention.

Is this for product teams or growth teams?

Usually both. The best outcomes happen when product, analytics, and growth are all looking at the same leverage map instead of protecting separate theories about what matters.

What usually comes next if the signal is real?

The common next step is a scoped Data Activation or implementation engagement that turns the highest-leverage signal into an operational workflow, score, or decision-support layer.

If the next roadmap bet feels expensive, test it first

This diagnostic exists to keep a plausible-looking initiative from quietly becoming an expensive quarter.

Book a Discovery Call
Book a Discovery Call