How Does CX Analytics Deal With Sizing the Importance of Topics?

How does CX analytics deal with sizing the importance of topics?


So the question is how does CX analytics actually deal with it?


Contexts information should be a part of analytics. If gender influence what’s important, it should be in the model, it is then a variable saying “one”, it’s a woman, “zero” it’s a man and this variable is influencing the outcome. So with this context variables in the model, the model can learn, can attribute this outcome to the context, or whether it is really driven by the topic. If you could give the model the information, it can find it out by themselves. That’s the intention to use the data you have. You may argue, Oh I don’t have the data for certain contexts information. You will never have a perfect data set. We are not in the business of proving the ultimate truth. We are in the business of making better decisions.


That’s basically what we can do. We can take some data that we already have, and we can work on having better data tomorrow, but everything comes with a price, the price to learn about the ultimate truth is very high. It has the best ROI to get insights that are just closer to the truth, than everything else so far.

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