In the digital age, to be able to stay afloat in the oceanic quantity of data produced on a daily basis (user generated content in particular is instrumental in this proliferation), we have to give them meaning and invest, therefore, in data analysis.
The estimates are talking about 18 billion dollars currently spent around the world for this purpose. However, if we consider that 90% of the data produced remains unused, we can understand that margins for growth and potential gain are almost unlimited.
Indeed, Artificial Intelligence has the undoubted advantage of knowing how to process an extremely large amount of data in real time, identifying the most effective moment, channel and message in encouraging the consumer to be more receptive towards the brand’s communication.
But, doesn’t this technological approach to data perhaps risk making marketing, which for decades has identified the creativity of its advertisers as its main asset, too impersonal? Actually, as Giorgia Lupi writes in the Data Humanism Manifesto, the numbers, understood as a quantitative narrative of human life, must be the starting point for a more complete narrative that is also able to embody the “human” aspect of the relationship.
Thanks to Content Intelligence and solutions like THRON that integrate it, we can also collect qualitative data on people’s interests (read how here) that allow us to get to know all our targets in a non-standardized and non-generic way. This, therefore, allows us to offer them personalized experiences.
We discussed this with Federica Brancale from Marketing Freaks, author of the book “Data-Driven Marketing” and creator of a well-defined method that allows marketing initiatives to be set up from a data-driven perspective. In this way, brands can be successfully guided by data in their communication strategies.
Q: In your opinion, how could Artificial Intelligence help businesses to take full advantage of data to make the right business decisions?
A: I’ve always thought that technology has a clear objective: to simplify work for mankind, so that mankind can do what a machine will never be able to do, or rather, think creatively. In this sense, Artificial Intelligence could learn the best existing marketing techniques, analyze data to achieve efficiency, and automate repetitive work. It will certainly manage to do this. But, the greatest discovery of all will be the fact that it is able to recuperate time for us humans so that we can think and innovate.
Q: In your book “Data-Driven Marketing”, you speak about a digital analytics journey. Please could you explain to us briefly what this is and what role data play within this strategy?
A: In an ideal world, before going online, companies would start to do some research. Unfortunately, in real life, it is unusual for this order to be respected: usually, the website is created, investments are made, and only later on is the question asked about why these investments are not bringing results. The method we are talking about is entirely focused on the user and is, therefore, user centric.
In the first phase, the company does some research, develops a strategy, collects data, activates its campaigns, and starts to perform analyses for continuous improvement. The strategy, campaigns and analyses are always carried out on the user and on their conversion paths. Once the pre-analysis is complete, the optimization process continues indefinitely, checking the browsing data, user behavior and campaign performances. It is only thanks to consistency that a strategy works. If you would like to learn more, you can find an introduction to the book here.
Q: At the Web Marketing Festival, you spoke about the importance of combining quantitative data on consumer behavior with other qualitative kinds that analyze the individual and their action context. Please could you explain why it is so important to collect both kinds of data to have a comprehensive overview of the audience we are addressing?
A: The risk of using data is linked to the fact that, during the analyses, if we only think in terms of numbers, we forget that behind the numbers are people. Therefore, the biggest limit is losing sight of the reading key. For this reason, it is important to proceed with analyses on numbers (quantitative) and on people (qualitative). Only in this way are we able to create a strategy that works thanks to data, but that is successful thanks to its empathy.