The importance of data driven decisions explained with hamburgers
In the 1980’s, A&W tried to compete with the McDonald’s Quarter Pounder by selling a 1/3 pound burger at a lower cost.
The product failed, because most customers thought 1/4 pound was bigger.
The Third Pounder burger was priced the same as the Quarter Pounder but had more meat, and outperformed McDonald’s in blind taste tests, with customers preferring the flavour of A&W’s burger.
When you are developing a product, you feel that there are 2 or 3 entities to please:
- 1) Stakeholders
- 2) The design team
- 3) The development team
All of these people will have opinions that they will believe are the right ones, but you cannot know which ones are right without hard data proving it.
Designing for consensus of internal people who do not use or buy the products just creates terrible products.
As said by Melissa Perri, here.
The true entity that needs to be pleased is the customer, and the customer can be a very finicky and unpredictable creature.
A&W had a better product, and better priced, what could go wrong? The guys that made the decisions had lots of previous experience, no doubt, but the product still flopped due to something they could not control.
Alfred Taubman, owner of A&W at the time, wrote about the confusion in his book Threshold Resistance:
More than half of the participants in the Yankelovich focus groups questioned the price of our burger. “Why,” they asked, “should we pay the same amount for a third of a pound of meat as we do for a quarter-pound of meat at McDonald’s? You’re overcharging us.” Honestly. People thought a third of a pound was less than a quarter of a pound. After all, three is less than four!
In this case, they assumed the customer was able to tell that 1/3 was bigger than 1/4, which proved wrong.
“The customer, regardless of his or her proficiency with fractions, is always right.”
This doesn’t mean the customer’s facts are right, it just means that if you are selling something nobody understands, you will not sell. Let’s replace customer with market, the market is always right.
Always assume you are wrong and collect data to show you where.
The previous example was something as simple as fractions, when customers are faced with a complex UI you can imagine how hard it can be to get it done right.
Spend less time behind closed doors discussing minute details and ship out a basic, simple version as soon as possible. Let the customers show you where to go next.
The feature you are wasting hundreds of hours on might not even be a real need from your customers, why waste time with it?