Marketing is considered by many people as a soft discipline, one in which you do not rely much on technical skills and STEM subjects. This of course is a misconception, a false impression derived by the enlarged use of the word “marketing” to signify “advertising”. In reality marketing has always had a foundation of numerical and statistical analysis, a “scientific” and analytical basis on which decisions are taken. So it is by no means surprising that nowadays marketing and artificial intelligence are becoming so close.
With artificial intelligence and machine learning you can perform sophisticated analysis and make predictions working on enormous data sets, and the findings of this analysis are like treasures for marketers. In fact, artificial intelligence has many applications in marketing, from the analysis of customers behaviour to the automatic writing or reports, from users segmentation to purchasing behaviour prediction.
AI and data analysis
One of the most significant changes to the digital marketing ecosystem is the advent of so-called “big data”: enormous quantities of data from various origins (i.e. coming not only from the infamous cookies but also from geo localization, in store purchases, voice assistants like Alexa or Google Home, interactions with the customer care, etc). This mass of information is now available to companies but in order for it to be used, it first needs to be cleaned, stored, analysed and interpreted.
The problem is that these data sets are so big (and growing literally each second) that no human could possibly manage them. And here, artificial intelligence makes its entrance. Through powerful machine learning or AI algorithms you can automatically scan and analyse zillions of data, you can extract evidence, you can detect structures and regularities, you can make predictions, you can even make decisions or trigger actions. So for example, you can automatically write after sales emails targeted for a certain kind of user and decide the best timing to send them. Or you can collect and interpret data from in store purchases: gender, age, body language, behavior, you can track down nearly everything and use these data to improve the in-store experience for your customers. Artificial Intelligence gives you possibilities that only 5 years ago you couldn’t even imagine.
Automated text generation and reporting
If content is king, producing good contents it’s really important, albeit cumbersome and time-consuming. But there is good news out there: automated text generation and summarisation using AI techniques has evolved so much that now you can machine generate entire texts and summaries of outstanding quality. An outstanding advancement, saving time and money and having a product compliant with all the SEO constraints and topic data.
Taking things to the extreme, you could even imagine producing personalised contents for each user. You could also generate various kinds of emails, personalised for each user and based on interactions with the website, wish list, previously appreciated contents, intent of similar users, etc. And you could use AI to enhance customer care, both on the CRM side and on the live interactions, using chatbots.
Segmentation, clustering and prediction
To reach the target you are interested in you first have to analyse your users data (the ones you know and the ones you can understand from their behaviour). Artificial intelligence can do magic when it comes to clustering and segmentation. AI algorithms can not only identify and classify your existing customers, but can also look for users similar to the ones that are of interest for your marketing or PPC campaigns. Even more, AI and machine learning tools can also predict customer’s actions: for example they can identify when a customer is about to leave, or her intention to purchase. Furthermore, they can trigger actions to keep customers engaged or even prompt them to buy using the right strategy for that particular individual. They can decide which segments should be better included in which campaigns, they can propose certain products to the customers that are more likely to buy them, or they can engage them with the most effective communication for that particular segment.
People nowadays do expect a personalised experience when they visit a website, even more if it’s an e-commerce website. While before personalisation was made according to explicit choices of the customer or on the basis of her past purchases, now with AI tools you have much more personalisation possibilities available. Bringing things to extremes, you could even produce just in time contents (including social media contents) specifically made for that particular customer, on the basis of what you’ve learned of her, or of her location, or of the things that she is doing at that moment. All the surveys suggest that this approach to content personalisation can greatly improve the main KPIs.
Of course to implement these AI based tools you need highly competent and skilled people, who are up to date with the latest developments but are not purely technical profiles. Instead, they must know how a company works and be able to interact with all the company’s functions. People coming from dedicated courses like the Data science & AI master by Talent Garden could be an excellent choice since they are taught all the core competencies that a company needs, that may be quite diverse and multifaceted.