Let’s face it: Most businesses are complex. Because of the daunting scope, when business managers are called upon to analyze data in search of the next pricing and discounting targets, they often rely on aggregated data.
Therein lies the rub. The problem with aggregated data is that, once the numbers are all neatly rolled up, they often hide opportunities that exist at the micro-market level. That’s because aggregation is based on averages, and averages can be misleading.
We call it the “Flaw of Averages.” In the real world, it can play out this way:
A major auto manufacturer was giving customers cash back at $2,000 per vehicle. On average, this was appropriate, but when Revenue Analytics was tasked with taking a deeper analytical look at the micro market, we found something alarming.
In San Jose, a discount of at least $3,000 was required to get customers into the showroom. In Tulsa, $1,000 was sufficient incentive, and anything more was an unnecessary rebate. In Orlando, it was $1,500 and, in Hartford, $2,500.
The flaw of averages was at work. We helped turn around the situation by creating a system by which the auto manufacturer could target discounts with greater precision. As a result, the manufacturer generated hundreds of millions of dollars more in incremental sales in certain markets, and saved hundreds of millions in cash incentives in other markets.
The power of precision defeats the flaw of averages. All companies – no matter how complex – need to remember is that:
- Customer demand data must be at the micro-market level.
- Overly aggregated data glosses over hidden opportunities.
- The “average” customer does not exist.