From segmented marketing to singularity marketing: how far can we really personalize the digital customer experience?
To get out of mass marketing, specialists and advertisers have bet on the segmentation-targeting-positioning triptych in order to personalize the relationship between brands and their customers and prospects.
In other words, the finesse of client segmentation on the basis of essentially socio-demographic, psycho-graphic or historical criteria.
If this approach has long been considered the Grail, it now poses, in the era of real-time online experience, two main limits.
On the one hand, website visitors are categorized according to “ cold ” data which may no longer be current at the time of their visit.
On the other hand, it classifies visitors into immutable categories which may not have a real link with their needs at a time T in their navigation. There is no guarantee that these data from the past are in line with the expectations of the visitor at the precise moment of their visit.
Does being categorized as ” a housewife under the age of 50 ” really mean that one is more likely to buy a soup spoon at an instant T than ” the millennial with framework status “?
Even if we understand the reasoning behind this segmentation, it remains purely… theoretical.
Is cold data, or data from the past, enlightening as to our needs and expectations online at an instant T? Should we target a consumer of classical music according to their visit history when they return to the site in order to give a gift to their nephew fan of Hard Rock?
So here are some of the limitations of static manual segmentation…
Understand visitors’ purchasing intention in real-time using AI
A visitor’s intention to buy on a brand’s website is a singular fact; it is not directly correlated with socio-professional status, age or geographic location. It also evolves overtime at the scale of a single visit.
This is revealed by all the real-time analyzes of “ hot ” data from visitors to the websites of major brands and companies.
Indeed, Artificial Intelligence makes it possible to decrypt this “ behavioral ” data called “ intention data ” revealed for example by the time spent on the site, the source and source of traffic, the pages visited, the buying opportunities ( urgent or no n), the frequency of visit (recurring visitors, new visitors ), the search engine and the device used or the time of exit from the site.
Machine learning algorithms have the immense advantage of instantly processing all of this data in its complexity and volume, without any bias. Their sole objective is to predict the visitor’s conversion or non-conversion or even their degree of indecision, in other words, their intention.
Offer a relevant online experience
AI thus offers very interesting new perspectives in the context of the online experience. It makes it possible to follow, in real-time, the evolution of the purchasing intentions of each visitor in order to automatically trigger, at the appropriate time, individualized experiences with messages, content, and offers that respond precisely to their intention.
This is called singularity marketing. It proposes to respond directly to the behavior of each visitor to a site – for them and not for their profile.
If many brands find it difficult to personalize the online experience, it is because their approach to customer data is still too often focused only on the analysis of cold data linked to the past and liabilities of their visitors without taking take into account their real-time behavior.
Thus, one of the main mistakes of brands is to use only cold data to personalize the digital experience and not take sufficient account of the needs of visitors in real-time.
We can, of course, customize according to criteria such as the last orders, but that is no longer enough.
Let’s take an example: a customer goes to a site where he bought a washing machine 2 weeks ago. He is currently sailing to find a gift for his friend whose birthday is approaching, he would like to find him a travel guide for Spain.
Based on the ” previous purchases ” criterion, the brand will logically offer them washing machines. However, this is not what this visitor is looking for at the moment. Furthermore, based on these criteria, it is impossible to personalize the experience of visitors who have never converted on a site.
Digital personalization, as we can see, is real-time and in many ways overcomes categorical thinking. The visitor’s real-time behavior data and the measurement of its evolution are essential to effectively personalize the digital experience.
Predicting visitors’ intentions, an opportunity for customer-centric brands
In the case of the online experience, manual segmentation can respond to certain simple use cases but it is interesting to combine it with the real-time predictive approach to go further in personalization and therefore visitor engagement and conversion.
Brands are beginning to appreciate the power of machine learning algorithms to personalize the experience of each visitor.
It is no longer just a question of optimizing merchant sites but of considerably increasing their performance.
This new era of singularity marketing represents an opportunity for brands committed to making digital a value-creating channel.
The benefits are numerous: incremental improvement in conversion rates and visitor engagement, generation of qualified leads, increase in ROI from marketing campaigns and generation of additional turnover.
Consider that each visit is unique and be able to respond precisely by individualizing the relationship between the visitor and the brand, technology now allows it. Everyone has their digital experience!
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