Customer’s Job Circumstance (Video)

Attribute Data Is A Poor Predictor Of Customer Demand


Video Transcript

Innovating can be a painfully hit or miss experience for many of our companies. In fact, research shows that three out of four of innovations fail. Because of high failure rates, many of our companies choose to play it safe and innovate at the margins — focusing on low-risk, incremental improvements. Unfortunately, most incremental innovations are “me, too” efforts that are guided by a desire to keep pace with what our competitors are already doing, regardless of whether or not such innovations are perceived as truly valuable by customers.

You would think that we would have reliable customer data to guide us as we innovate. After all, today we have access to more data about our customers and competitive environments than ever before.

Yet despite the abundance of customer data, most managers seldom know enough about the underlying forces that drive customer demand for their products and services! This is one reason why so many products do not live up to their potential.

That’s because the easiest customer data to acquire and analyze has to do with the characteristics, attitudes and behaviors of customers themselves. We call this attribute data. The problem is that this data by itself does not tell us the ways customers are struggling to get a particular job done and how well current solutions help them get this job done.

Only by understanding the messy details of job circumstance can we discover important and unsatisfied customer needs — the prime targets of innovation. Attribute data becomes much more useful in the context of job circumstance.

I am not saying that customer attribute data does not sometimes correlate with customer choice. Sometimes it does. But attribute alone data does not tell us why customers make the choices they do.

For this reason, attribute data is a poor predictor of customer demand. Yet many of us still rely completely on attribute data to target innovation efforts. This helps to explain the widely reported observation that 74% of innovation efforts end in disappointment.

To make full and proper use of our customer data, we need to reconnect it to the job the customer is struggling to get done. By doing so, the data will reveal a more complete picture of customer priorities. Target these priorities and you will succeed every time.

In order to reliably create, maintain and improve products and services that our customers perceive as more valuable than our competitors’ solutions, we need to know the job circumstance that drive customer perceptions of value. Understanding the job context holds the key to understanding what customers value and that holds the key to innovating. We’ll start working on that understanding the job context in our next challenge.