Getting to know customers who do not express themselves: mission impossible? Not if you use the right tools! Welcome to the world of predictions and inferences.
All brands dream of having the gift of clairvoyance so that they can know what is really going on in the minds of their customers. What if the dream comes true? Artificial intelligence is now being applied to customer relations, prompting the development of predictive models. How? By basing itself on existing consumer data, software can now provide companies with inferred feedback from those customers who have hitherto remained silent. “Today, there are solutions that make it possible to analyze consumer journeys by digging into basic consumer data, namely who does what and when”, sums up Thierry Aubert, COO of Mediatech Solutions.
A little feedback, a lot of information
Knowing the customer’s journey and better addressing it lies at the heart of corporate warfare. For this, companies have several methods at their disposal: surveying customers to directly solicit those interested about all or part of their purchasing behaviour, collecting spontaneous insights (via posts and opinions expressed on forums, social networks …), and finally processing complaints.
These different sources of information, coupled with the data that brands possess about their customers, provide a first overview of the customer journey as a whole. “Each source, especially a survey, increases our contextual and emotional understanding of the customer, at one or more moments in his journey,” states Thierry Aubert.
Yet some customers slip through the net and do not express themselves. Although they have an opinion, they cannot be forced to share it. The solution? Set up a feedback management system that integrates artificial intelligence to deploy a predictive model. “From the data, we can set up standard profiles according to the experiences perceived by customers, and from this point we make use of predictive models to allow us to anticipate the customer journey with a high degree of reality”, explains Thierry Aubert. In other words, a global understanding of customer insight lies in the assembly and analysis of data collected by actual customer feedback, plus predictions that can be made for those who did not wish to express themselves.
To illustrate this with an example: “Two customers with similar profiles, who do not know each other, stay in the same hotel at the same time. The first customer expresses his dissatisfaction by leaving an unfavourable opinion about his bad experience, for example, noisy renovation work and restricted access to the swimming pool. Even if the second customer says nothing, it’s still a safe bet that he shared this negative experience… The predictive model will thus make it possible to anticipate and trigger commercial actions for this customer, who has not made any mention of these negative points”.
Capitalizing on the predictive
Being able to predict the satisfactions, the recommendations and the dissatisfactions of silent customers means being able to optimally adapt one’s commercial strategy. “These solutions are particularly interesting in terms of customer bounce-back. Thanks to these predictions, the brand is able to promote the right service at the right time, create a “wow” effect by offering an ultra-targeted promotion to a customer who did not expect it, as well as retaining loyalty and limiting attrition “, considers Thierry Aubert.
In parallel, these targeted and pertinent actions allow the brand to make savings in effort and time. “Companies that do not make use of predictive techniques can only send messages via bottles thrown into the sea by launching, for example, an expensive and inefficient emailing campaign… Inferred elements are predictions that concern the present, not the future. The nuance is critical. The analysis and management of inferred feedback, offers the possibility to customize messages and interactions with customers”, further underlines Thierry Aubert.
Towards the end of surveys?
Is it reasonable to contemplate a model that is 100% driven by artificial intelligence, without surveys or any form of consumer solicitation by brands? “No”, replies Thierry Aubert, “because this is the only way to really know what’s going on in the customer’s head … His perceptions and expectations vis-à-vis a brand are two insights that can only be obtained through surveys”.
In the same way, a customer relationship that is fully robotized and under the control of artificial intelligence is utopian. A system that would be self-sufficient thanks to technology alone is not conceivable. “The analysis of the root causes of customer behaviour, as well as the prioritization and development of an action plan will always require human competence. Predictive technology does not replace previously used practices but supplements and augments them”, concludes Thierry Aubert.