Revenue Performance Management and B2B Demand Generation: Connecting the Dots
Around 2010 the marketing automation vendors changed their vocabulary. Instead of "automating marketing" they began to talk about managing revenue performance. Eloqua called it Revenue Performance Management; Marketo talked about Revenue Cycle Analytics. Revenue is good, so the shift sounded positive. But many marketers wondered whether it described new technology or just new marketing. The honest answer was: both, and neither.
Why automation projects failed
Spending on marketing automation was growing quickly, yet many adopters were disappointed. Projects failed when marketers could not connect two dots. First, they needed a clear picture of how to build a modern demand generation programme at the process level. Second, they needed to tune that programme against revenue, not against the number of leads delivered to sales.
Most teams had focused on the mechanics: sending email, managing contacts, running campaigns, and measuring success as leads handed over. Revenue performance management asked a harder question: which activities actually drive revenue, and which levers should we pull to grow it?
ROMI in one line
The formula is simple; the attribution is not. A B2B deal may involve a dozen people and dozens of touches over a year. Which touch gets the credit?
| Attribution model | How credit is assigned | Best used for |
|---|---|---|
| First touch | All credit to the first recorded interaction | Understanding which channels create new demand |
| Last touch | All credit to the final interaction before conversion | Short cycles; quick optimisation of offers |
| Linear | Equal credit to every touch | A neutral starting point |
| Position-based (U-shaped) | Most credit to first and lead-creation touches, rest shared | B2B nurturing programmes |
| Data-driven / incrementality | Credit based on measured lift versus a control group | Mature teams with enough volume |
No model is "true". Use one consistently, compare it with a second, and test the big decisions with holdout groups where you can: withhold a programme from a random slice of the audience and measure the difference.
Casinos have been measuring marketing return for decades
Casino operators were doing revenue performance management long before software vendors named it. Land-based casinos calculate each loyalty member's theoretical win, the amount the house expects to win from their play given the games, stakes and time played, and then decide how much of that to reinvest in free rooms, meals and offers. Marketing spend is judged against incremental theoretical win, not against how many offers were mailed.
Online operators go further, comparing each promotion against a control group that did not receive it, so the bonus cost can be set against the extra net gaming revenue it truly produced. It is one of the clearest real-world examples of incrementality-based ROMI. We work through a full example, with numbers, in attribution and ROMI: the casino loyalty programme case study.
Connecting the dots in practice
- Agree stage definitions and track every lead to an opportunity and a closed deal. See the waterfall stages.
- Store campaign and content touches against contacts and accounts in the CRM, not only in the automation platform.
- Report pipeline and revenue influenced alongside lead volume, every month.
- Keep a few holdout tests running so you can tell correlation from contribution.
- Present results to executives in their language. See communicating with execs.
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