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Published on 27 April 2018
As the start of a series of articles, I want to look at how we join up customer data and offer some simple first steps. Many people think that customer insight is all about customer surveys, capturing satisfaction (CSAT), advocacy (NPS) and Customer Effort for instance. These are almost universal now and a valuable start point.
Understand customer experience
In particular, take the time to read, understand and share customer comments. They are a valuable data source and can be quantified by categorisation, manually or automatically (using interaction analytics). This insight engages colleagues (at all levels) and can underpin a customer centric culture. Alongside this data, feedback from frontline teams and more complex or qualitative research is often really important in truly understanding what is important. If your quality process is focussed on customer outcomes, this can also be a great source of ideas. There are downsides to surveys however – with burnout cutting response rates and creating biased samples for instance. To counter this, mature insight teams are building tools for effective prediction of customer experience, with data from internal systems. At BT for instance, a database tool (COACH) has been used to prioritise coaching needs. This collates data from many sources on customer interactions.
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First published in the 2018 Best Practice Guide
Author: Leanne McNamee
Categories: Library, Data, Analytics & Insight