Power Law Performance
What do you do when business wins keep turning into losses?
If your business is hitting its KPIs but missing its revenue targets, the issue isn’t doing more of the same. It’s finding the levers that drive revenue and increase margins. When power law dynamics are in effect, it takes a different approach to drive above-baseline results.
Learn how the power law is impacting your team’s performance, and how to make the changes that get you above baseline.
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Is your business a power law business?
Most KPIs are built for a bell curve, where the typical account sits near the average. What happens when your revenue doesn’t follow a bell curve? For many businesses, revenue follows a power law dynamic, where a minority of accounts are responsible for a majority of the revenue. If this describes your business, then KPIs based on volume, like cost of acquisition or conversion rates, are biased against the results you’re aiming for.
Get the newsletter. Every week, what scaling value instead of volume looks like inside a revenue team.
Why hitting your volume KPIs drags the average down
In 1970 the economist George Akerlof described the mechanism in “The Market for ‘Lemons’”: when buyers can’t tell quality apart at the point of sale, the market prices everything at the average, and the above-average sellers quietly exit.1 His example was used cars. Later work found the same adverse selection in insurance, where buyers know their own risk better than the insurer,2 and in lending, where banks can’t tell safe borrowers from risky ones.3 Michael Spence showed how the better side gets noticed: by sending a signal that is costly to fake.4 Akerlof, Spence and Joseph Stiglitz shared the 2001 Nobel prize in economics for this work.5
That research is about consumer markets and the information buyers and sellers have about each other, but the same thing happens in customer acquisition. If your acquisition system is judged on volume, it can’t see value, so it doesn’t buy any.
Volume-based optimizations are naturally biased against value. Improved performance numbers compound negatively: an expanding market with shrinking margins.
- George A. Akerlof, “The Market for ‘Lemons’: Quality Uncertainty and the Market Mechanism,” Quarterly Journal of Economics 84, no. 3 (1970): 488–500. Journal, Wikipedia.
- Michael Rothschild and Joseph Stiglitz, “Equilibrium in Competitive Insurance Markets: An Essay on the Economics of Imperfect Information,” Quarterly Journal of Economics 90, no. 4 (1976): 629–649. Journal, Wikipedia.
- Joseph E. Stiglitz and Andrew Weiss, “Credit Rationing in Markets with Imperfect Information,” American Economic Review 71, no. 3 (1981): 393–410. JSTOR, Wikipedia.
- Michael Spence, “Job Market Signaling,” Quarterly Journal of Economics 87, no. 3 (1973): 355–374. Journal, Wikipedia.
- The Nobel Prize in Economic Sciences 2001, awarded to George A. Akerlof, A. Michael Spence and Joseph E. Stiglitz “for their analyses of markets with asymmetric information.” nobelprize.org.
The research library has more than 100 works on adverse selection, signals, power laws and the metrics teams manage to.
Optimizing for Power Law
Optimize for the signal, not the thing
Once your book is in four tiers, trace each tier back through the funnel and find the earliest signal that predicts it. That signal is what you optimize for.
- 1
Identify Above Avg.
Tier every account from the statements it produces, on the same rule every month, and mark the ones running above the average.
- 2
Apply Attribution
Attribute each tier back to the sources, campaigns, pages and reps that produced it, to find the early traits that lean toward the top tiers.
- 3
Implement Signals
Put those traits to work as early in the funnel as they show up: in targeting, in lead scoring and in routing to sales.
- 4
Optimize
Move spend toward what produces above-baseline accounts, read R2m, the net revenue each $1 invested returns by month m, as it comes in, and repeat every statement cycle.
The earlier in the funnel you can identify and anchor a signal, the bigger its impact on value.
How do you beat a revenue target you keep missing?
It sounds backwards, but chasing the revenue number harder won’t get you there. Find the early signal, aim marketing at it, route the accounts that can carry the book to sales, and let each team do its job on the right metrics. Your results beat the baseline the plan assumed, your margins go up, and you reach the target from underneath.
ABPRO_ is built to do exactly that, reading your investment through to revenue and back every statement cycle, and flagging what’s running above and below baseline while there’s still time to move the money.
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