Segment how?
In this 2009 article on Advertising Age, some considerations are already listed that even today, after almost ten years, we find ourselves facing to understand how to segment users in this new level of complexity. The interesting points are three:
The rapid change and reliability of the segment: people change homes, jobs, divorce, suddenly become poor or rich. How long is a segment reliable? It is clear that segmentation cannot remain static and must be updated quickly.
The presence of users in multiple segments: in the morning we are workers, in the evening athletes, at the weekend parents passionate about TV series... it is difficult to describe people using only one variable, better to consider more than one creating archetypes that help us describe this greater degree of complexity. The list of argentina consumer email use of Personas can be very useful to us to have a clearer picture of our consumers.
Self-profiling by interests : social media and all the ecosystems of aggregation by interests on the internet have forced us to revolutionize the analysis of people's needs. The value proposition of a product first passes through the pain point and the expression of a need. The possibility of monitoring online behavior helps us to intercept and deduce it before and better than any survey or focus group.
If the incredible amount of data at our disposal makes the work potentially more precise, the need to analyze this amount of data and create unique value propositions for each of these micro targets greatly increases the complexity of the marketing work.
Automated marketing and dynamic segments
Automatic marketing allows us to segment taking into account all the complexity summarized above. It does so mainly by aggregating the greatest possible number of data sources, thus trying to enrich the profiles of our potential consumers as best as possible.
Among the data at our disposal, some are static data, which do not require continuous updating (for example, those of the proprietary database such as gender or age), others that instead change quickly such as the interest of the moment, the product searched for, the need, etc. (which can typically be detected by online browsing or other touch points such as customer care).
Segmentation in automatic marketing then takes a further step: it adds and removes people from the segments dynamically based on their behavior and, managing the information in real time, constantly analyzes each user - or returning user - to continue enriching the profile and learning the main characteristics of that segment. These dynamic segments will therefore be indispensable to be able to propose the right thing, to the right person, at the right time. Marketing automation platforms autonomously know which product or service is closest to people's needs based on their belonging to a segment, taking into account what is happening at that moment. Not only that. This personalized experience can be managed in multi-channel, intercepting people with the right timing depending on the stage of the customer journey they are in at that precise moment.
