Jobs Theory demonstrates that the struggle to get the job done causes a purchase. We call this struggle an "unmet customer need." To determine which customer needs are unmet, we rate the importance and satisfaction of every customer need in the JTBD.
Need satisfaction is a function of the speed and accuracy of executing a job step. If a customer cannot take the action described in the need quickly or if the variable in the need is inaccurate, this causes customer anxiety and low customer satisfaction.
Using speed and accuracy enables us to estimate the satisfaction level for each need. To assess speed, we consider the time it takes the customer to finish the action in the need with current solutions in the market including all manual execution activities. To assess accuracy, we estimate what percentage of the time the variable is inaccurate when the customer executes the job.
To validate the satisfaction and importance scores, we conduct a customer survey, asking job executors to rate each need on a scale of importance and satisfaction.
The percentage of customers who rate the need as important gives us an importance score. For example, if 97% of drivers say that determining the optimal sequence to make planned stops is important, then this need would have an importance score of 9.7.
We use the same method to calculate a satisfaction score for needs. For example, if only 12% of drivers say that determining the optimal sequence to make planned stops is satisfied, then this need would have a satisfaction score of 1.2.
An underserved market has high importance and low satisfaction levels. We calculate an opportunity score for a customer need using a simple formula: Opportunity = Importance + (Importance - Satisfaction).
An Unmet Need in "Get to a destination on time"
We can measure the speed and accuracy of the need determining the optimal sequence of planned stops by analyzing how a customer attempts to satisfy the need with competitive products.
For a busy person with multiple meetings, appointments, and errands throughout a day, determining the optimal sequence using Apple Maps or Google Maps would require entering destination A, calculating the time and the route to destination B. Then entering destination A, calculating the time and the route to destination C, comparing the two A to B and A to C routes, determining which was quicker and repeating the process for every possible combination of destinations.
The time it takes to do this and the accuracy of doing this with current products can be measured. With Apple Maps and Google Maps satisfying the need to determine the optimal sequence of planned stops is manual, time-consuming and inaccurate.
As a result, this is an unmet need in the market because a driver might not be able to determine the optimal sequence at all. You can use surveys to validate that the job executors perceive the need to be unmet, as this analysis indicates.