How do I measure expansion revenue by play?
Attribute every expansion deal to the play that started it, so you know what actually works.
Measure expansion revenue by play by giving each play its own campaign and attributing every expansion deal to the campaign of the play that started it, so you can compare plays against each other, prove which ones drive revenue, and invest in the winners. A play you cannot measure is a play you cannot improve.
What you attribute back to each play is real revenue, tracked over time against each account's plan from your own internal data, so the comparison rests on what customers actually bought and used rather than external guesswork.
This guide closes the loop on the plays built in building a cross-sell play and coordinated in avoiding two offers at once. It applies the same attribution discipline used for new-business scoring in measuring lead scoring.
How does attribution work?
Each play has its own campaign. When an account enters the play, its contact joins that campaign, and any meeting or opportunity that follows inherits the campaign. Expansion revenue then rolls up by play in the campaign reports you already use, with no manual tagging to maintain.
What should I compare across plays?
Four numbers tell you which plays deserve more effort.
| Metric | What it answers |
|---|---|
| Enrollment volume | How many accounts the play reaches |
| Sequence-to-meeting rate | How well the play opens conversations |
| Win rate | How often those conversations close |
| Revenue per play | The bottom line each play produces |
Comparing those lets you set the day-30 cross-sell against the usage upsell against the whitespace play, and shift effort to the strongest. In healthcare you can also cut these numbers by specialty from the NPPES taxonomy and by care setting from CCN-keyed CMS data, so you learn not just which play wins but which play wins in ambulatory surgery, behavioral health, or senior living. Because SignalRx keeps those account attributes complete, filling thin records from public sources, the cuts hold up rather than collapsing on missing fields.
Illustrative example
Illustrative, based on how SignalRx customers work. Over a quarter, a vendor sees the usage-upgrade play enroll fewer accounts than the day-30 cross-sell play but produce more revenue per enrolled account, because its deals are larger. The team keeps both running but moves an AE's time toward the upgrade play, a decision they could only make because every deal was attributed to the play that started it.
Why is this hard without a system?
Manual tagging drifts and gets skipped, so revenue cannot be traced back to the motion that produced it. Automatic campaign membership on enrollment keeps attribution clean by default, the same approach used in the day-30 cross-sell play.
Key takeaways
- Give each play its own campaign so deals attribute automatically.
- Compare plays on enrollment volume, meeting rate, win rate, and revenue.
- Automatic attribution beats manual tagging that drifts.
See it in action: Increase Customer Revenue with SignalRx.
Related: How do I measure lead scoring? and How do I build a cross-sell play?
Want any of these running on your data?
Frequently Asked Questions
.svg)
.avif)