On the one hand, marketing, one of the most controversial areas of the business world (and not only), loved and hated, misunderstood (“but what is it for ?”, “It’s just advertising, “but why is it a science? “), and, as such, sometimes cheeky. On the other hand, Artificial Intelligence, one of the most mysterious areas in the technical field (“ah, you deal with AI, so, are you a robot?”)Everyone would like to be part of it and use it.
Many think it is the best possible way to study. Although some are still skeptical and unaware, they met, and, as opposites attract, this marriage has to be done! A reality made up of small and medium-sized companies. We still have to get used to this winning combination elsewhere. It has long been an indispensable “must-have,” a combination from which great results and ideas are born that guarantee considerable advantages.
Marketing Is Not Just Advertising
Well yes. Advertising is a step in marketing, a subset of marketing, a part of the world. It is the “wit” that meets market research and analysis. Trend analysis, competition analysis, customer analysis, product analysis, market research, and consequently projection of the relative results. And to carry out research and analysis, what do we use, if not statistics and concepts such as “the average annual turnover,” “the market with the highest ROI,” “the customer with the most considerable CLV”?
And if, as now usually happens, with large quantities of heterogeneous, dirty, and incomplete data, the analyzes are simplified if not through the use of data mining (extraction of useful information from large amounts of data), preceded by appropriate automated processes of data preparation and optimization, and machine learning? The latter plays a vital role in a marketer’s life. Machine learning can help achieve, with a considerable saving of time and a limiting “manual intervention,” an optimal result corresponding to what the marketer himself is looking for, combining the features he wants to focus on.
Let’s think of a big fashion company whose marketing analyst wants to collect information about customers with similar personal and behavioral characteristics. For example, in this case, it could benefit from certain types of clustering, depending on the available data. In this case, AI marries analytical marketing.
Marketing, Strategy, And Proactivity
Then it’s time for strategic marketing. In this case, the marketer conducts more in-depth analysis, not only descriptive but also predictive. He will ask himself what could happen, and, consequently, he will try to implement strategies to avoid or at least limit damage or consolidate or strengthen an advantageous position. The strategic interventions marketers are most interested in are customer loyalty and the averted loss of market shares.
Machine learning comes in handy with churn prediction analysis, to name one, which allows us to understand what the customer churn rate could be, extracting potentially unfaithful ones from the heap and identifying their characteristics. It is then up to the analyst to understand why the client abandons and how to intervene to avoid it. Also, on an operational level, it is possible to combine business ideas and projection of results through machine learning techniques to help understand whether the strategic choice will have more or less positive consequences.
Marketing Is Emotion, And Yes, Advertising Too
When the “flicker” meets the technique, NLP techniques can be used to evaluate, for example, the feedback regarding your brand, events, marketing campaigns, or good ideas such as that of Norwegian Airline (ah! If only you could do a little Twitter data crawling referring to the week of that September 2021, how many #hashtags you would find about the Airline and its excellent marketing campaign!). The most sensible evolution of the union between “spirit” and AI is to set up prescriptive analyses that improve the customer experience through the use of captivating graphics.
