Most features ship to silence. This sprint fixes that before a line of code ships.

Engineering is wrapping. Launch is imminent. Nobody has defined “adopted,” no one has instrumented the signals, and nobody knows which users to target first. This 5-week sprint changes that. $6,500–$9,500.

Book a Call → See what’s included ↓

30 minutes. You’ll leave knowing whether the sprint fits your launch timeline.

AUDIT → TARGETING → ROLLOUT → COMMS

Readiness Audit Baseline analytics and historical adoption patterns reviewed

Target Segment Map The 20% of users with highest adoption probability, ranked

Feature Scorecard Primary metric, 30/60/90-day targets, definition of “adopted”

Instrumentation Spec Every event engineering needs — tiered and developer-ready

Rollout Plan Phased release with defined gate conditions between phases

5 weeks · fixed scope · $6,500–$9,500

Five weeks from now

Targeted

The feature launches to the 20% of users most likely to adopt. Early numbers come back strong. Internal confidence builds. The feature gets real usage from the right people before it’s opened to everyone.

Instrumented

Every critical user action is tracked from day one. No retrofitting at week four. Your developer got a document, not a conversation. The data is there when you need to make the call on phase 2.

Measured

At 30 days, you’re reading a dashboard instead of arguing about whether the numbers are right. The whole team agreed on what winning looks like before launch day — so there’s one shared answer.

THE SCOPE SYSTEM

Eight deliverables. Everything you need before launch day — not after week four.

Survey

Readiness Audit — what's missing before launch

Cluster

Target Segment Map + Feature Scorecard

Observe

Instrumentation Spec — what to measure

Price

WTP research + gating decision

Execute

Phased rollout + comms + 30-day diagnostic

Audit · Week 1

Pre-Launch Adoption Readiness Audit

Baseline review of current analytics data, instrumentation gaps, and historical adoption patterns for previous features.

What current users actually do — not what was assumed
Which segments are most likely to adopt the new feature
Realistic adoption ceiling based on product history
Launch strategy built on real signal, not enthusiasm

Targeting · Week 1

Target Segment Map

Behavioural data analysis of which existing users are most likely to adopt, ranked by fit against the JTBD the feature solves.

Launch to the 20% with highest adoption probability
Early adoption numbers return strong instead of flat
Internal confidence builds before broad release
Phase 2 gets real usage data, not hypotheses

Scorecard · Week 2

Feature Success Scorecard

A one-page definition — primary metric, secondary metrics, 30/60/90-day targets, and the exact behavioural definition of “adopted.”

Whole team agrees on what winning looks like before launch
“Is this working?” has one shared answer at week four
Engineering and product stop having the same argument
Post-mortem uses data, not competing interpretations

Instrumentation · Week 2

Instrumentation Specification

Every event, property, and naming convention engineering needs — tier 1 critical before launch, tier 2 in week one, tier 3 nice to have.

No retrofitting analytics at week four
Data is there from day one
Developer gets a document, not a conversation
Implementation takes a day, not a month of back-and-forth

Pricing · Week 3

WTP & Gating Recommendation

A bundle-vs.-gate decision with pricing rationale, grounded in Van Westendorp or Gabor-Granger research where scope warrants it.

Two-week Slack debate resolved with data, not a vote
What users are willing to pay — from real research
Whether gating increases perceived value or adds noise
One clear recommendation: bundle, gate, or test

Rollout · Week 4

Phased Rollout Plan

A controlled release sequence with defined gate conditions between phases — not a calendar-based “we flip it on for everyone on the 15th.”

Problems found in phase 1 before phase 2 launches
UX issues exposed to 10% of users, not 100%
Rollout has decision points, not just a date
Adoption stall diagnosed before it becomes a post-mortem

Comms · Week 4

Adoption Communication Playbook

Channel-by-channel, segment-by-segment communication sequence for 30 days post-launch — email, in-app, and CS touchpoints.

Users who benefit find out at the right time, in the right way
No single email blast wondering why adoption is flat two weeks later
CS team knows which users to prioritise for outreach
Communication sequenced by trust and adoption stage

Diagnostics · Week 5

30-Day Post-Launch Diagnostic Framework

A decision tree covering the three most common feature adoption failure modes — with specific diagnostic steps for each.

When adoption is lower than expected, you know exactly where to look
No post-mortem that ends with “we need more marketing”
Team has a plan for the most likely failure scenarios before launch
Root cause identified, not argued about

THE TIMELINE

Five weeks. Everything delivered before the feature ships.

WEEK 1

Pre-Launch Audit + Segment Analysis

Baseline analytics reviewed. Historical adoption patterns examined. Target segment map built from behavioural data — ranked by adoption probability against the JTBD the feature solves.

WEEK 2

Success Scorecard + Instrumentation Spec

Feature Success Scorecard produced — primary metric, secondary metrics, 30/60/90-day targets, and the definition of “adopted.” Instrumentation specification handed to engineering — tiered and production-ready.

WEEK 3

WTP Research + Gating Recommendation

Willingness-to-pay research conducted. Bundle-vs.-gate decision produced with evidence. Pricing rationale documented — the internal debate resolved before engineering ships.

WEEK 4

Rollout Plan + Communication Playbook

Phased rollout plan with gate conditions built. Adoption communication playbook produced — channel, segment, and timing defined for the first 30 days post-launch.

WEEK 5

Final Delivery + 30-Day Diagnostic Handover

All 8 deliverables delivered. Full team walkthrough. 30-day diagnostic framework handed over. Everything owned by you permanently — no ongoing dependency.

The difference between launching to silence and launching to adoption.

	Without the sprint	With the sprint
Target users	Everyone. Announced to the whole base on day one.	The 20% most likely to adopt first. Broad release backed by data.
“Adopted”	Not defined. The team watches usage counts.	One behavioural definition. The whole team agreed before launch.
Analytics	Set up by whoever is free in the week before launch.	Instrumentation spec with engineering. Tier 1 events live from day one.
At week 4	15% adoption. Nobody knows why. Post-mortem begins.	Dashboard read against Scorecard. Diagnostic framework runs if below threshold.
Pricing/gating	Debated in Slack for two weeks. Compromise reached.	WTP research completed. Data-backed recommendation. One clear decision.
Rollout	Everyone gets it on the launch date.	Phased with gate conditions. Problems found in phase 1, not phase 3.

IS THIS YOU?

Built for product teams shipping significant features at Series A–B.

VP Product / CPO

Feature shipping in 4–8 weeks. No adoption plan.

$5M–$30M ARR · Series A–B

Why this fits

The engineering sprint is wrapping. Launch is imminent. You realise there’s no targeting strategy, no definition of “adopted,” and no way to measure whether it works at 30 days. This sprint produces everything you need before the feature ships.

What you leave with

Target segment map with ranked adoption probability
Feature Success Scorecard the whole team agrees on
Instrumentation spec handed to engineering before launch

You launch to the right users, with data from day one, and a shared answer when someone asks “is it working?”

Head of Growth

Feature shipped. 15% adoption. No diagnosis.

Post-Launch · $5M–$30M ARR

Why this fits

The feature shipped six weeks ago. Adoption is lower than expected. Nobody can agree on whether it’s a targeting problem, a UX problem, a messaging problem, or all three. The 30-day diagnostic framework was built for exactly this situation.

What you leave with

Root cause identified from the three most common failure modes
Specific diagnostic steps for what’s actually broken
Targeted fix — not a broad “more marketing” recommendation

You know what’s actually broken — and you have a plan that addresses that specific thing.

Recurring Buyer

This problem repeats every major release.

Series A–B · 2–4 major features per year

Why this fits

Significant feature launches happen 2–4 times per year at Series A–B. Each one is a potential re-engagement — the same sprint applied to a different feature, with the team getting faster each time because the methodology is already established.

What you leave with

Consistent adoption methodology across every major feature
Instrumentation naming convention established once, reused every time
Each launch informed by the last one’s data

Feature adoption becomes a repeatable process — not a one-off scramble before each launch.

THE PROCESS

What happens after you click.

30-minute call

We assess the feature, your existing analytics quality, and your launch timeline. You leave knowing whether the sprint fits — and what the biggest gaps in your current launch plan are. No pitch. No deck.

2-page proposal

Specific scope, deliverables, timeline, price. If WTP research requires external recruitment, that’s scoped clearly. Nothing ambiguous. If the sprint doesn’t fit, we’ll say so before you sign.

The 5-week sprint

Audit + targeting → scorecard + instrumentation → WTP + gating → rollout + comms → final delivery with team walkthrough. Checkpoint at each phase before moving forward.

Full handover

All 8 deliverables delivered in a full team walkthrough. Instrumentation spec handed to engineering. 30-day diagnostic framework in your hands before launch day. Everything yours permanently.

What this costs — and what it would cost to source it separately.

What’s included	Standalone market rate
Pre-launch adoption readiness audit	~$1,500
Target segment map (behavioural analysis)	~$2,000
Feature Success Scorecard	~$1,000
Instrumentation specification (tiered, dev-ready)	~$2,500
WTP & gating recommendation	~$2,500
Phased rollout plan	~$1,500
Adoption communication playbook	~$1,500
30-day diagnostic framework	~$1,000
Sourced separately	~$13,500
This sprint — one-time, 5 weeks	$6,500–$9,500

$6,500–$9,500

One-time · 5 weeks · fixed scope

Pre-launch adoption readiness audit
Target segment map — ranked by adoption probability
Feature Success Scorecard — primary metric + targets
Instrumentation specification — tiered, dev-ready
WTP & gating recommendation
Phased rollout plan with gate conditions
Adoption communication playbook (30 days)
30-day post-launch diagnostic framework

Fixed scope — no surprise invoices All deliverables yours permanently No ongoing dependency

Book a Call →

ProductQuant runs 2–3 active engagements at a time. Book a call to check current availability.

The cost of skipping this: One engineering sprint wasted on a feature that ships to 15% adoption and no diagnosis costs more than this engagement in engineering time alone. The instrumentation gaps that take a day to fix now take weeks to retrofit after launch — with data gaps that can’t be recovered.

Questions.

Or book a call →

What if the feature has already shipped?+

The sprint can run post-launch — the readiness audit becomes a retrospective diagnosis, the instrumentation spec gets retrofitted, and the focus shifts to the rollout plan and diagnostic framework. The most valuable deliverable post-launch is often the 30-day diagnostic framework, which identifies exactly where to look when adoption is lower than expected.

Does WTP research require external user recruiting?+

Not necessarily. If you have a large enough user base and can facilitate email outreach, we run WTP research with your existing users. For smaller user bases or where independent validation is preferred, external recruitment is scoped and priced separately. We confirm the approach on the initial call.

What does “instrumentation specification” mean in practice?+

A document your developer can implement from directly — event names, properties, data types, naming conventions, and implementation priority tiers. Implementation is not included in the sprint, but the document is designed so a competent developer can implement tier 1 events in a day or two without additional guidance.

How much of our team’s time does this require?+

1–2 hours per week from the PM or product lead — one checkpoint per phase and turnaround on approvals within 24 hours. For WTP research: you facilitate user contact or provide email lists. The developer needs one session at handover to walk through the instrumentation spec.

How quickly can we start?+

Kickoff within 2 weeks of signing. If your launch date is tight, we can front-load the instrumentation spec and scorecard so engineering can start implementing before weeks 3–5 complete.

WHO’S DOING THE WORK

Jake McMahon · Founder, ProductQuant

Jake McMahon

8+ years building growth systems inside B2B SaaS · Bachelor’s in Behavioural Psychology · Master’s in Big Data

Eight years as a product leader inside B2B SaaS companies — product manager, growth lead, head of product, from seed-stage to $80M ARR. He kept watching smart teams make the same mistake: good tools, real talent, no system connecting any of it.

ProductQuant is what he’d hire if he were still an operator — rebuilt as a service. There’s no team of junior analysts. Jake runs the targeting analysis, builds the instrumentation spec, and delivers every document himself.

What he won’t do:

Promise revenue numbers he can’t verify
Hand you a strategy deck and disappear
Recommend work you don’t need
Build something that only works if you keep paying him

“Could our VP Product run this analysis themselves?”

They could run one layer — either the readiness audit, or the segment targeting, or the instrumentation spec. Running all eight in five weeks while also managing the roadmap and the launch timeline isn’t realistic. The SCOPE System is designed for dedicated focus: each deliverable informs the next, the targeting shapes the instrumentation, and the 30-day diagnostic starts from a clean baseline. That sequencing is what makes it work.

Teams Jake has worked with

Most features ship to silence. This sprint fixes that before a line of code ships.

Eight deliverables. Everything you need before launch day — not after week four.

Five weeks. Everything delivered before the feature ships.

The difference between launching to silence and launching to adoption.

Built for product teams shipping significant features at Series A–B.

What happens after you click.

What this costs — and what it would cost to source it separately.

Questions.

Know before you ship whether it’ll be used.