Make text analytics the basis of CX programmes

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Customer experience management is about listening to your customers, analysing what they say, and acting on the insights. But without text analytics, this is an almost impossible task.

The advantage of text analytics is that it helps to mine unstructured data, such as open-ended survey comments and calls to contact centres. However, according to a recent report from Forrester[1], whilst most professionals working in customer experience are comfortable with analysing structured feedback from surveys, only 27% of them use text analytics. By using manual processes, these professionals are spending far too much time sorting through, and classifying, the reams of customer data that they are undoubtedly bombarded with on a daily basis. 

Imagine collating the data that comes from social media, review sites, survey questions, website enquiries and call centres on a daily basis. Then imagine how much more time it takes to aggregate all of this data and spot trends. Crucial to this is detecting the sentiment of each comment, understanding the emotion and effort that goes into interactions, so the issues that arise can be assigned to the correct departments in the business. This can be time-consuming and often, by the time it is completed, the original question or complaint will no longer be relevant and the customer will be long gone.

Clearly many customer experience professionals are aware that text analytics are important, and relevant, to their business, but one barrier to adopting the technology is that it’s not always easy to pick the right solution. Many aspects have to be considered from the linguistic text processing capabilities and user interface through to delivery and deployment options. It’s important to do some homework and identify what is under the hood of the text analytics tool before making the final decision.

One thing is for sure, however, without the support of text analytics it will be challenging to make sense of what customers are saying. A dedicated platform allows all the customer data, whether it is structured or unstructured to be normalised.  This is important because it is just as vital to understand what customers are saying of their own volition as it is to understand what they say in response to direct questions. Unsolicited feedback is like gold-dust and this has made it the differentiator in many customer experience management programmes. In addition, companies need tools that help to categorise and quantify customer emotions and the level of effort they exert when they interact with the company and its services. This provides clues that allow companies to really understand the impact they are having. What’s more, customers need to be able to communicate using the channels they prefer, when and where they want and not only when it’s convenient for the company. After all, this is the age of the customer.

Organisations that are using customer feedback to inform and design their own product and services pipeline are already half-way there, but if they really want to make customers happy, they need to drill down into the feedback so they can act on it. Text analytics enables this, creating happy customers and putting the business one step ahead of the competition.


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