It is common to find companies of a certain size with continuous feedback collection processes from their customers. Classic tools such as NPS (Net Promoted Score) have been the main tools used to date.
For a few years we have already known that customers also share their feedback on products and services on social networks, blogs, online stores, etc. Some companies have seen it and have incorporated this information into their NPS.
BSH, a #lexic client, is an example of customer orientation in everything it does, also in relation to #analytics. They receive hundreds of thousands of calls, thousands of emails, and tens of thousands of messages through chat channels. During 2020 they realized that all these conversations with clients were pure gold and, at a global level, they started several initiatives with the aim of analyzing them with a perspective of continuous improvement.
For this task they chose us and we share 4 relevant aspects of this initiative:
The truth and nothing but the truth: The feedback we find on the internet or the NPS has a lot of bias. It is known to all that there is a "review manufacturing" industry and that the NPS, many times, obtain "canned" and little elaborate answers that do not allow to investigate in a deep way. However, with a call, or with a chat conversation, the frustrations and joys of the customer surface without filter, without bias. Capturing them, treating them and turning them into relevant information is like receiving a complete check-up at the doctor. You know where it hurts and where you are healthy, openly.
Just to improve Customer Service?: Customers tell you everything: "they cannot pay with PayPal, the installer has been very kind and professional, they have not received the order confirmation email, they are interested in changing the washing machine, they do not understand the warranty, the fridge tray has been broken, they miss more colors, the coupon does not work, ..." Adding and analyzing all this information and using it in real time is a fundamental input for all the departments of an organization: digital channel, logistics, technical service, product and innovation, crm, marketing and sales, etc.
Satisfied customers? Well, they are because the NPS said so about it. There were complaints about customer service but in general all very positive. How is satisfaction measured? with an NPS🤔. Measuring, in real time, user satisfaction using the information that is being shared with us at that moment is, without a doubt, a paradigm shift. Now BSH can know the satisfaction of the user in real time and with the granularity of the conversation and the topic of the same thanks to some AI algorithms.
Data and Action!: the data must be used. It is not worth having a diagnosis without later using that information to heal or improve ourselves. At Lexic we are working on two types of actionable data:
Triggers and Alerts: "f my payment gateway does not work, if customers call to ask for the configuration of the "homeconnect", if the black friday coupon does not work" then I have to notify the person responsible for the solution in real time
Early detection: in an internal line of research we are designing algorithms that are capable of identifying "small" problems that can become "big". Contextual prediction (the one that has to do with my business) is a fundamental tool for a company to go from a reactive relationship with the client to a proactive one.
Data processing (meant to be for data scientists) of these conversations has many more applications within companies. We remind you that, behind, what the Lexic platform generates is a gigantic dataset with classified, clustered, labeled information, etc.
Merging this unstructured data with sales data, web traffic, conversion of promotions, CRM, etc. would eliminate silos of knowledge, improve the intelligence of companies and, finally, be a real "data-driven-company"
In another post we will talk about how to use this analysis to automate customer front-end processes.
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