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NPS.AI

Discover hidden loyalty drivers.
Just two input needed: A NPS and an open question.

The challenge:

The strength of the NPS approach is that it is so simple and cost-effective to implement, making customer retention management scalable. Unfortunately, the data collected is no longer sufficient to determine how loyalty can be increased. It turns out that the frequency evaluation of the open end question “Why?” has a huge blind spots.

The solution:

NPS.AI has a two-stage approach. In the first step, it trains an AI-based NLP (Natural Language Processing) software, which can then assign large amounts of remaining text data to meaningful content categories. Level two is a self-learning driver analysis that determines which content categories are actually responsible for high and low loyalty.

Your benefit:

Based on your scalable loyalty survey, NPS.AI identifies hidden loyalty drivers. In addition, you will receive open entry categorization for any number of cases – no matter how large.

Here is more: We present a case study on NPS.AI at the ESOMAR World Conference 2018 in Berlin.