Modelling the Influence of Technology on the Customer Experience – Introduction to the Series

Geoff is a technology and business leader who provides holistic thought leadership to complex customer problems using pragmatic solutions. He authors business-related technology topics, holds numerous patents, and has won several industry awards. He can be reached via LinkedIn.

Imagine sitting through another technology demonstration that promises to solve one of your customers’ most common complaints. Sound familiar? How does this story usually end? Large capital investment? Long implementation timeline? Or, perhaps you’ll be testing a “beta” version of the product?

“You’ve got to start with the customer experience and work back toward the technology – not the other way around,” - Steve Jobs

This is the first in a series of short articles that will explore the relationships between customer expectations, customer experiences, Net Promoter Scores, and the technologies that influence these relationships. In this introductory article, I will present a simple model that will be used throughout the series to help predict customer sentiment. Future postings will look at airline service, self service, product substitution, and high-cost customers, just to mention a few.

There are plenty of good articles related to the customer experience such Tony Bodoh’s micro-moments and blogs by TimeTrade. The intention of this series is to specifically examine the impact of technology on the customer experience and explore some hypotheses.

The model shown here is intentionally kept simple, but could be used as a foundation for building Systems Dynamics models and mathematically predicting fluctuations. More sophisticated manifestations of the model could also include variables such as churn, repeat purchases or visits, premium pricing, business policies, etc. 

The technologies to be explored here are ones that are available – sometimes simple – and in-use today, versus futuristic or conceptual ideas; but there is nothing preventing the use of any technology in the model.

Subsequent articles will use the model below to analyze real-world situations in order to qualitatively predict or explain the customer experience using heuristics. The model has 5 discreet steps and one feedback loop representing technology changes impacting the future customer experience. At the end of each step there is positive (+), neutral (o) or negative (-) sentiment. At the end of the Experience Crescendo we will analyze sentiment and make predictions for NPS (or whatever metric makes sense) and present the outcomes to management for consideration.

Future articles will model the following experiences:

• Airline Service

• Self-Service

• Product Substitution

• Banking – Overdraft, Fraud

• CarPlay

• Frequent / Abusive Callers

• Online Security

• Agile MVP

Here are some initial hypotheses:

• A combination of technologies tends to improve CE

• CE can impact NPS in expected and unexpected positive (+) and negative (-) ways

• Overshooting CX has a large negative (-) impact to NPS

• MA’s typically take a Minimalist approach to technology spend

• Technology dimensions’ impact CE

Please share your ideas and feedback for other experiences to model and ideas on how to improve it. Follow me on LinkedIn so you don’t miss subsequent postings to see the model in action and interact with others on this topic.