Personal information, behavioral data on preferences and purchasing habits, interests and psychographic data, as we know, are the basis of an effective profiling strategy , but how much is it possible to know the users who interact with the digital and non-digital properties of a brand or with its ADS campaigns ?
One fact stands out significantly: in Italy only 1.8% of visitors, on average, choose to reveal their data and leave contact information on a website or eCommerce .
This means that over 98% of users list of albania consumer email interact anonymously, an important fact that represents a great challenge but also a huge opportunity. Even when anonymous, in fact, users, in the various occasions of interaction with the brand, release valuable information (geographical areas from which they connect, devices used, content viewed, etc.) that can still be used to enrich profiles and give life to subsequent personalization and progressive profiling activities.
This is where data enrichment processes come into play , which, as the expression itself suggests, have the objective of enriching the user profile , whether known or anonymous.
Data Enrichment Strategy : Why is it so important?
The expression “ data enrichment ” refers to the process through which it is possible to enrich, but also update, data and information concerning the individual user.
The goal, as you can easily imagine, is to create a complete and real-time updated user profile , that unified customer view that, as we know, is the basis of every effective customer experience enhancement strategy. Faced with the much-heralded deprecation of third-party cookies, data enrichment
activities have taken on a central role, especially with regard to anonymous user profiles .
data enrichment - what it is and advantages
As we know, audiences profiled through first-party data represent an important asset for marketers, advertisers and publishers, but their limitations often require adopting different logics to still achieve numerically relevant reach and performance.
A data enrichment strategy thus becomes fundamental both for anonymous and known users: in the first case it allows for the enrichment of data and information starting from navigation contexts , rather than from probabilistic models , while, in the second case, it can be implemented with progressive profiling activities through forms, surveys, polls, just to give a few examples.
