How human is your CRM?

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How human is your CRM?

“AI is serendipity. It is here to liberate us from routine jobs, and it is here to remind us what it is that makes us human.”

The first time I heard that quote from Kai-Fu Lee, it made me think about how in this ever-increasingly digital existence we have lost some of our compassion and creativity. If AI is to liberate us and allow us to focus on our more ‘human’ aspects, then the obvious place to start would be customer engagement applications like CRM.

Having worked in the business applications space for over 15 years across a variety of roles ranging from product development to delivering enterprise scale solutions, I wanted to take a step back and look at some of the core processes and how make them more human. According to Wikipedia, “CRM is an approach to manage a company’s interaction with current and potential customers. It uses data analysis about customers’ history with a company to improve business relationships with customers, specifically focusing on customer retention and ultimately driving sales growth.” In this article, I have focused on the interactions themselves, but there is a similar case to be made about other areas like data analysis, retention and engaging potential customers.

A customer interaction could be about a sale or service request, and coming in from any channel but there is always an intent, expectation and desired response. Clearly easier to assess these face to face but that is an increasingly rare occurrence. So how do we get more human without compromising our efficiency? Enter AI micro-services – a set of APIs to see, hear, speak, understand and interpret your customer’s needs through natural methods of communication. Services like Azure Cognitive Services, and Amazon’s Lex and Rekognition allow us to deliver AI in a very targeted and human way.

It’s easier to see these in action so let’s take an example: “I haven’t heard back from the San Francisco support team and my Finance system has been down for hours. This is unacceptable. Call me back as soon as possible.”

Running this through the Azure Text Analytics API, we get the following results:

Microsoft CRM AI

We are now able to identify intent and key phrases which allows us to easily categorise the interaction, but, more importantly, prioritise our response based on factors like sentiment.

If you received the same message in German, the API would identify the language, translate the text, and provide similar results:

There are similar APIs around vision and speech, and the way I like to think about them is that they analyse interactions and present us with markers and insight which allow us to get to the intent, expectation and desired response as quickly as possible. Now our human side can take over and we can communicate with a level of information and empathy that was previously not possible. Instead of mechanically collecting information, we can immediately start focusing on our customer’s needs and how we can help them get there.

The best part of this story is that these APIs are extremely easy to consume with very favourable pricing. In fact, at eBECS, all customer support interactions are analysed for intent, keywords and sentiment with the results stored in our Dynamics 365 system. The solution was built in just a couple of days and our support team uses it to manage their queues and identify potential escalations.

This is of course just one part of the puzzle as we also see strong adoption of other AI capabilities in CRM systems including Customer Insights/360 view, Bots, Knowledge APIs and Recommendations APIs.

If you would like to know more about how to incorporate AI into CRM processes or just share your thoughts on this topic, please drop us a note at cloud@ebecs.com.

Author: 
Amir Jafri

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