One of my colleagues recently wrote a blog which compared the change in Customer Journey mapping to the advancement from ancient maps to satellite imagery. To build on that comparison, I think the evolution of customer experience is similar to the changes that have taken place when planning a car trip.
Planning a trip used to involve studying a roadmap, then along came MapQuest. Today, satellite navigation and Google Maps have made things a lot easier, automatically re-calculating your route and providing drivers with alternative routes if there is traffic or an accident ahead. However, I believe further improvement in these systems could be made because all of the insights are reactive. There is no way to plan for rush hour or other delays before they happen. A true benefit would be for the system to predict delays at the beginning of the journey and provide alternative routes before it is too late.
Similarly, the customer experience and expectations have changed over the years. In the past, almost all transactions were done face-to-face such as getting cash from the bank teller, dealing with a store employee, or getting insurance through an agent. Companies began using direct mail and email to contact their customer with new offers and services to increase revenue and loyalty. The digital and mobile revolution have enabled companies to interact with their customers across multiple channels.
To support this new customer experience, companies are investing in Customer Journey Analytics. It enables companies to connect data, analytics and interactions to send the right message to the right customer at the right time. From the outside, customer journeys seem simple. However, behind the scenes, a customer journey may involve multiple destinations or even multiple journeys concurrently. For example, a banking customer may be refinancing their property and getting a car loan for a new vehicle at the same time. Targeting the exact needs of your customer is essential. It isn’t enough to be reactive. The customer journey must be predictive and in most cases in real time