Customers experiencing success
Creating better products with iterative improvements
Mapping User Journeys onto the Jobs-To-Be-Done Framework
Consider the following scenarios:
- I am expecting a package that does not arrive when I expect it to. Did I receive a notification? Yes. Did I receive an explanation as to why? No.
- I was planning to fly out to visit family and my early evening flight was changed to the earliest morning flight. Did I receive a notification? Yup. Did I receive an explanation as to why? Nope.
Does this somewhat straightforward pattern sound familiar? Digital services often provide customers as much frustration as they do convenience. The roadblocks to customer success described in these scenarios can be compared easily using the Jobs-To-Be-Done framework: “When ____ I want to ____ so I can ____.” Let’s try re-casting the scenarios:
- When I order a package and it does not arrive by the expected date, I want to receive an explanation so I can know what next steps need to be taken to receive the package.
- When my flight is changed, I want to receive an explanation so I can know what next steps need to be taken to find a flight that works for my itinerary.
If explanations are so useful to customers, why are they so hard to come by? The most obvious answer would be the cost of providing customized solutions. The assumption is that anything beyond a notification would open a Pandora’s Box of potential scenarios (and personas) to solve for.
“After decades of watching great companies fail, we’ve come to the conclusion that the focus on correlation — and on knowing more and more about customers — is taking firms in the wrong direction. What they really need to home in on is the progress that the customer is trying to make in a given circumstance — what the customer hopes to accomplish. This is what we’ve come to call the job to be done.” — Clayton M. Christensen, Taddy Hall, Karen Dillon, and David S. Duncan
Why is the customer doing the job they hired someone else to do?
If we take the cost-saving assumption to be true and we stop at the notification, we might save on those costs. But, we might also lose the customer if they fire us for not being able to perform a simple and relatively straightforward job. Think of what the customer has to do next if the notification does not provide them the information they need:
- Not knowing why the package was not delivered, the customer finds the order information available on the carrier’s website. The package is on hold at a nearby facility but cannot be delivered. The customer talks to a representative after waiting for an hour. The representative explains that it is out of their hands because the shipper has placed a specific delivery requirement on the package, so the customer will need to call the shipper to get it sorted…
- Not knowing why the flight was changed, the customer uses the airline’s mobile app, scrambling to find another similar flight, of which none are available. After three hours of waiting, the customer receives an explanation from the representative that it is out of their hands because all direct PM flights to the destination have been cancelled…
In both of the scenarios described above, the customer has become an unpaid employee of the company, creating workarounds or filling information gaps with a Google search because it is now out of the company’s hands to complete the job to be done.
Although the overall customer experience described in these scenarios were undeniably terrible, the remarkable thing about them is how common they are in the world of digital services. But what if it could be different?
Plausible Alternative Model (PAM)
Below, we imagine some alternative scenarios:
- When the customer’s package did not arrive as expected, a notification appeared on their mobile: “We’re sorry, but the shipper of your package has placed it on hold. Click this link for important next steps.” The link takes the customer to the carrier’s mobile app that describes both the reason the package was not delivered (customer not home) and how to contact the shipper to release the hold on the package.
- When the customer’s flight is changed, they receive a notification on their mobile: “We’re sorry, but your flight has been moved to the early morning because direct flights are no longer available in the PM to this location. Please follow the link for important next steps.” The link directs the customer to booking options pertinent to their original itinerary.
The Plausible Alternative Model (PAM) does not require a great feat of engineering to customize the infinite experiences available to customers needing to receive packages or book flights. Would greater interoperability between the carrier and shipper have provided a better customer experience? Maybe. Would a sophisticated algorithm that could suggest to the customer alternative flights within the same relative PM time-frame be better? Probably. But these are costly, time-consuming solutions.
By focusing on plausible alternatives, we might also leverage both Operational Transparency and the Goal Gradient Effect:
- In addition to the enhanced notification, the customer sees a diagram illustrating where their package is on the journey and how close they are to finally receiving it.
- In addition to being pointed in the right direction for finding a suitable alternative flight, the customer is also provided a diagram or chart indicating the multitude of options available and the proximity of these options to that original flight.
The great thing about PAM is that it is based on a core tenet of User Experience — Iteration. In fact, the solutions described above have already been implemented. The missing step is that they have not been successfully integrated into every step of the customer’s journey.
We start with giving the customer a little bit more information than they had before. We measure the impact of that new knowledge given by measuring interactions:
- How many customers try finding information online and then call for help from a representative?
- How long do they have to wait to talk to a representative?
- How do they rate these representatives when the interaction is over?
- Was the customer able to complete their JTBD without frustration?
If we see these numbers improve, we iterate with more improvements because we have successfully demonstrated the value of mapping a customer’s journey onto their JTBD.
We have narrowed our scope and defined the value of continuously improving a customer’s interaction with our services. If we accomplish our goal of keeping the focus on being hired again to do the next job, we can then start asking what other jobs we need to be doing.
References
Clayton M. Christensen, Taddy Hall, Karen Dillon, and David S. Duncan, “Know Your Customers’ ‘Jobs to Be Done’”, Harvard Business Review, September 2016
Alex Jupiter, “Jobs to Be Done”, Medium, December 2017
Jennifer Clinehens, “How Uber uses psychology to perfect their customer experience”, Medium, October 2019
