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No feature workshops
What a customer uses comes out of their data, including what they forgot to mention.
01Benefits
Why teams love it
What you get out of the box. No premium tier.
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Priority by revenue
Every gap carries the onboardings it blocks and the MRR behind them. The build order argues itself.
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Still right after the next delay
Dates slip, usage findings change. The plan re-sorts instead of going stale in a spreadsheet.
02Mechanics
How it works
From signal to outcome in four explicit steps, with no hidden hand-offs.
Connect your roadmap tool
Planned features, dates and status flow in from Jira, ProductBoard or Linear. Your product team keeps planning where it already plans.
Define the detection once
Per source system: which data pattern means which feature. Set up once, used by every customer after that.
Load customer data
Each migration dataset is evaluated against the rules. Blocked and ready customers separate themselves.
Work the list
Per feature: affected onboardings and blocked MRR. Per customer: blocked or ready to start. On the timeline: where a delay collides with a planned start.
03Capabilities
What's inside
Every headline backed by a concrete workflow. Screenshots show what your team will actually use.
Capability 01
Usage comes out of the data, not out of a workshop
Define once per source system which data pattern means which feature. Every customer dataset you load is then evaluated against it, including the features nobody mentioned in the kick-off.
Capability 02
Your roadmap, attached to real customers
Planned features, dates and status flow in from whichever tool your product team runs: Jira, ProductBoard or Linear. Each one carries the onboardings it holds up and the revenue behind them — in the same record your product team already works in.
Capability 03
A build order you can defend
One list, sorted by what each gap costs. Which feature unlocks the most customers, which one can wait, which one nobody actually uses. The argument between product and delivery settles itself.
Capability 04
A plan that survives the next delay
A release date moves, or a new dataset shows a customer uses something else. Affected onboardings and start dates move with it, and the timeline flags the collisions instead of hiding them.
Capability 05
The overview the board asks for
Feature status at a glance, the features holding up the most revenue, and how migrated MRR develops over time. Financial forecasting and capacity planning off the same data the delivery team works in — not off a slide someone assembled the night before.
04Use cases
Situations we keep seeing
Anonymised from our customer base. See whether one of them is yours.
M&A project lead
Scenario
Platform acquired, dozens of customers to move, and no defensible answer to 'who can we start with?'
Outcome
Blocked and ready customers separated by their own data. The first wave started without waiting for the full feature set.
Head of Product
Scenario
Build order argued from opinion; every slipped release date meant reshuffling the plan by hand.
Outcome
One list sorted by blocked revenue that re-sorts itself whenever a date moves or a dataset lands.
COO or CEO
Scenario
The transformation has to pay off, and the picture of it comes from status calls rather than from data.
Outcome
One overview of what is blocked, what it costs, and where the next engineering euro unlocks the most migrated revenue.
05What we replace
Replacing what?
The three most common alternatives our customers come from.
The feature matrix in ExcelCorrect on the day it is written. One moved release date later it quietly is not, and nobody notices until go-live.
Gap pages in ConfluenceDocumentation, not live state. Nobody goes back to edit it when a customer turns out to use something else.
Workshops with the acquired teamAsks people what they believe their customers use. The data says something different often enough to hurt.
06Across the platform
Pairs well with
Other parts of the platform you'll use alongside this.
Frequently asked
A feature a customer uses in the source system that the target does not have yet: missing entirely, only partly equivalent, or the same name with a different meaning. It is detected from that customer's data, not from a list someone typed up.
From the migration data. Once per source system you define which data pattern indicates which feature. After that every dataset you load is evaluated automatically — the effort is spent once, not per customer.
No, it reads from it. Your product team keeps planning where it plans. The platform adds what your roadmap tool cannot know: which customers and how much revenue hang on each item.
You need access to source data. As soon as an export exists, detection runs against it. The earlier that happens, the more the scope of work rests on evidence instead of estimates.
Ready to see it on your data?
20-minute call. Show us your source, we show you the mapping. No deck required.