Is the machine learning the future of customer experience? If we analyze it, we can conclude that, without a doubt, The future of the customer experience will, surely, go through the prediction of behaviors.
In this sense, until now the behavior of the client was analyzed and measured before the value proposition of each company. But we have done it out of necessity, because the client demands more; it demands why it is in a position to demand, it demands because we are in an economic cycle where supply exceeds, as never before in history, demand, demands because consumption levels are exaggerated and because the American compulsive buying culture has settled in Europe and Asia
These facts make any management team have to “wind their brains” to make the purchase an experience in itself, which generates certain differential feelings for customers. The product itself is no longer differential; the products are copied or, even worse, improved in record time that makes their life cycle so short that it makes no sense to analyze it. But nevertheless, The experience is a plus for customers.
In recent years we have seen that a differential advantage could be an NPS -Net Promoter Score- high (recommendation rate from one customer to another), however, this index is, on multiple occasions, very pernicious and misleading for the management of companies, since, for example, it can be done at a wrong time, measured with the employee present or that the employee induces the positive response.
In order to improve these failures, the discipline of Customer Experience has deepened its measurement methodology –Including the key moments of a relationship with the client, the facts he lives and his perceptions with the brand– and that has allowed us Obtain quality data that allow us to know and anticipate what is vital for our client.
Thus, at this time, the methodology already allows us to go one step further, allows us to move forward; both in relationships online, as in the offline, we can, thanks to a good customer journey, have data of such quality that allow us to anticipate what the customer wants.
But what is next in customer experience?
Everything suggests that behavior prediction should be, not just anticipation. Hence the resurgence of machine learning. And I say it resurfaces, because it is not new or born yesterday.
However, it is at this historical moment when it is easier to put it into practice. Mainly for two reasons: we are now able to have multiple quality data and it is cheap to store them.
So, on the one hand we know that the machine learning It is a branch of artificial intelligence that allows us to learn from the data, identify patterns and make decisions with some human intervention, while, on the other, we know that the methodology of customer experience is ultra contrasted and that, thanks to it, we get increase the KPI (Key Performance Indicator) of business with new designed experiences.
So why not join both methodologies?
The potential and findings, to date, of using both methodologies simultaneously brings great benefits:
1. Business decisions can be made on a solid scientific basis.
2. You can understand what aspects are key for the client, what bothers him, what he likes to answer and gives us and what not. That is why we could save thousands of euros in harmless quality studies.
3. The need and requirement of the client can be anticipated.
4. You may be surprised with a higher level of success.
Definitely address a process of Customer Centric it makes sense today and, even more, with the solid methodologies that exist and with experts in machine learning. The challenge is there. It's beautiful, it's innovative, it's transformative.