ROI models without probabilities are fantasies, not forecasts.
Many ROI models assume static conditions and perfect execution. This never happens. So why would you tell a client they can achieve it?
In our value consulting practice, we help clients quantify and articulate the real value of their digital marketing investment.
Not just in theory, but in measurable financial impact.
And one way we ensure it's reliability is through 'expected value' (EV), a method that accounts for probabilities and potential outcomes, not just best-case scenarios
This might be a better breakdown:
👉 Good: ROI model assumes everything will go as planned.
👉 Better: ROI model factors in failure rates, market shifts, execution risks.
👉 Best: ROI model that uses expected value - weighing all possible outcomes by their probabilities to get a more realistic, data-driven forecast.
Now for the EV calculation:
👉 If a campaign has a 60% probability of generating $1M but a 40% chance of only adding $200K, the EV is: (60% × $1M) + (40% × $200K) = $640K EV
Of course, this is just the simple formula. You'd likely have multiple other factors unique to your product's value that need to be considered (or different models entirely).
If you're working in value consulting or a value-selling rep, consider leveraging the "expected value" concept to build better ROI analyses that account for uncertainty.
One final note that can't be overlooked - this is a team effort. It's a result of deep collaboration with our partners. We work relentlessly to give our partners the tools, data, and confidence they need to drive change inside their own organization.
Despite my preference for solo sports 😅, what we do as a team to support our partners fires me up!
If you're looking to measure and maximize the value of your digital marketing efforts, let's connect. Drop a comment or DM me.
#digitalmarketing#valueselling#consulting