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You’re Up! How Customer Service Leaders Can Prepare for Interactions with Machine Customers

By Christopher Sladdin | September 16, 2022 | 0 Comments

Customer Service and SupportDigital and Self-Service Customer Service

This is part two in a mini series on Machine Customers and the impact on the Service Function. If you missed part one on the prevalence of Machine Customers in our everyday lives, make sure to read that post first. 

Did that last blog get you thinking? Perhaps you discovered that your peers already have a machine customer incorporated into one of their latest products? At the very least, I imagine you’ve now realized how reliant we already are on machine-initiated service to reduce our own effort contacting customer service and support. The machine customer is definitely here, and if it hasn’t reached your industry yet, it isn’t far away. So, here’s the question I imagine you, as a Customer Service leader are asking right now (I’ve heard it a lot in the past few months): 

What does my Service function need to do to prepare for Machine Customers? 

First things first – we don’t all need to rush to build a machine customer right now – while that might be the case in some industries, in many others it would still be premature. Here’s a high-level perspective on the action required in each industry, based on where we’re already seeing machine customers in action.

Machine Customer Readiness by Industry - Arts, Entertainment and Education should prepare, Banking, Medical Devices, Insurance, Tech Manufacturers, Telcos, Transportation, Travel and Hospitality should act now, and eCommerce, Retail and Utilities are already behind.

If your industry is in either of the “act now” columns, then now is the time to be developing machine customer functionality, either in your own products, or building on existing third party solutions (e.g. smart devices). But regardless of what column you’re in, leaders must do four things now in preparation to act: 

  1. Partner with the wider organization to assess the potential impact machine customers could have on the Customer Service function. For example, you should identify which steps in your customer service journey are low-value and rote –  that’s where you are likely to see demand for machine customer intervention. In fact, a lot of our guidance on chatbots is equally applicable in the Machine Customer space – start with the repeatable and low complexity tasks, and look to enable more nuanced and high complexity tasks later.
  2. Make sure that you know who in your organization is responsible for developing machine customers (whether they are products developed by your R&D or product organizations, or functionality deployed by IT, service or product organizations on a third party solution like the smart speaker in your customer’s living room). Work with these stakeholders to understand what these products will be capable of, how they might interact with the Customer Service function, and what you need to do to prepare for, identify, and action these requests when they materialize.
  3. Machine customers put distance between the Service function and the customer by automating service requests. While this preemptive and proactive approach is lower-effort, Customer Service leaders must also decide when to loop in the human customer given the increasing demand on Customer Service leaders to drive additional value for the business. So ask yourself two questions; what type of human contact presents the best opportunity for you to drive growth / ROI? And when would you as a customer want to speak with a human for added reassurance? Delivering on this priority when all of your opportunities for interaction are eliminated by machines will be significantly harder.

Want help? Schedule an inquiry with me or a fellow Customer Service & Support expert today to think through your approach to machine customers and prepare to deliver the next generation of Customer Service. You can also listen to more Gartner experts discuss the topic of Machine Customers in a recent podcast.

The Gartner Blog Network provides an opportunity for Gartner analysts to test ideas and move research forward. Because the content posted by Gartner analysts on this site does not undergo our standard editorial review, all comments or opinions expressed hereunder are those of the individual contributors and do not represent the views of Gartner, Inc. or its management.

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