Customer Experience - New Approaches

As the core of customer oriented business models moves towards experiences instead of products or services, managing and improving customer experience gain more and more importance. With increased automation and advances in artificial intelligence, it is possible to consider the customer experience as more than simply customer journeys and touch-points.

Designing customer journeys and the corresponding touch-points in detail are critical parts of understanding and managing customer experience in many industries including but not limited to banking, insurance, telecommunications and retail. Understanding the customer experience starting from the awareness and initial contact down to servicing the customer is vital in order to achieve customer satisfaction and to gain competitive advantage through better fulfillment and better identification of further customer needs. As an example, in financial services, it is possible to see very detailed customer journeys covering different parts of the interaction between the institution and the customer. The interaction might include a branch visit, a web-initiated search for an insurance quote or an application for a mortgage loan.

One important thing is that in all these interactions, the journey is usually defined as a linear activity, which starts at a certain point or activity and continues down a line consisting of different interactions and touch-points. In that particular interaction, the customer moves down this path and goes through a number of touch-points, which are considered important in defining the customer experience and to collect information about that specific experience. The touch-point can be a message the company sends, a discussion with the relationship manager or it can be a well-designed product comparison feature in a mobile app. The purpose is to provide outputs, which minimizes hassles and maximizes delights in the customer journey.

As we picture the customer journey as a set of interactions between the customer and different touch-point elements (e.g. branch staff, mobile device, store visit), new elements are being introduced with the developments in areas including digital, artificial intelligence and intelligent automation. Developments in these areas include advanced analytics, intelligent assistants, deep learning models and intelligent automation capabilities. These new developments, combined with business models, have the potential of bringing new approaches to improving customer experience. Some of the ways these improvements can be realized are listed below:

• Advanced analytics combined with artificial intelligence can increase the customization in customer journeys and improve the touch-point performance based on customer profile and preferences (e.g. providing services based on customer type instead of going through standard scripts)
• Chatbots and intelligent assistants can increase the consistency and the quality of interaction with the customer throughout the journey. They can provide customized recommendations and continuously access and analyze the customer contact history to better manage the interactions in customer journey. Instead of contacting with different parties throughout the journey, the customer can contact with her/his intelligent assistant to proceed and get help. The concepts coming with intelligent assistants will enable bi-directional customer experience as these assistants will be able to travel the customer journey map back and forth either to support the customer or to analyze and improve the journey based on customer inputs and feedback coming from thousands of other journey cases. As the customer travels on one side of the journey map, intelligent assistants will be traveling in both directions analyzing and re-configuring the journey.
• Intelligent automation solutions like robotic process automation will improve the management of customer journeys by facilitating interactions, background processing and performance management. It will become easier to find the hassle points and to correct them with to-the-point solutions. Automation will also be important in achieving consistency in the experiences customers have. Instead of having different moment of truths at different touch-points, customers will have consistency in the experiences they have.
• As changes in market conditions and customer segments affect the customer expectations, advanced analytics applications strengthened with deep learning algorithms will be able to adapt to these changes by understanding the patterns and by updating the customer journey accordingly. Although customer journey analysis based on cross-functional teams will still be important but suggestions coming from these algorithms will be able to present different perspectives quickly and effectively.

Customer-oriented approaches are critical to success in many industries and customer experience management will continue to be one of the important levers. Integrating customer experience management with new technologies can be an important game changer in this area.

The views expressed in this article are the views of the author only. This article provides general information and point of view, and should not be considered as professional advice.