In recent years, more and more companies have been reshaping their internal processes and projects to become data-driven, across businesses of every size and in industries ranging from automotive to food.
Given this wide variety of businesses, there is no one-size-fits-all strategy for using data, especially in marketing, which can pursue very different strategies depending on its goals.
Data has revolutionized corporate marketing by making it possible to move away from extremely expensive advertising campaigns designed to reach as many people as possible. Thanks to data, marketing decisions and sales strategies can now be backed by relevant information, allowing advertising to target likely buyers at the right time and in the right way.
All of this reduces costs and, most importantly, delivers stronger returns.
Many have recognized the importance of data for marketing, including Philip Kotler in his latest book, “Marketing 5.0,” an evolution of his two previous books.
According to Kotler, in the coming years we will increasingly use data to communicate more precisely with our target audiences, giving rise to what is known as “marketing to one” — strategies so finely segmented that they target a single person or a group of people who share the same characteristics.
In his book, the author also discusses using consumption patterns to make upselling offers (encouraging a customer to buy a more expensive product than originally intended) and cross-selling offers (encouraging the customer to buy a product that complements the original purchase) to consumer groups with established patterns.
Notably, many companies around the world are already using artificial intelligence and data strategies to support strategic decisions, whether for new marketing campaigns or new product launches.
What are other companies doing?
One of the best examples is McDonald’s, whose app lets customers place, customize and pay for orders right in the app.
By collecting data, the company can suggest new combos and promotions to customers who prefer certain menu items over others, or offer them exclusive deals. This shortens lines at its restaurants, offers customers greater convenience and builds loyalty.
But it is not just major restaurants and fast-food chains using these new technologies. AB InBev, for example, has been using its data to brief its team on specific advertising campaigns so they communicate more effectively with customers.
Lexus, one of the leading luxury car brands in the United States, used its database and AI to analyze which marketing campaigns had been most effective over the past 15 years, identifying what they had in common in order to create an entirely new campaign that carried the hallmarks of past successes.
How banks are using these strategies:
Finally, these technologies are advancing rapidly in banking, particularly generative AI combined with data strategies — specifically, data-driven strategies.
These strategies enable banks to offer personalized services and target specific audiences, as Kotler suggests. Many banks in Brazil also recognize that, in the very near future, companies will need to adapt and use data strategies combined with AI-generated insights.
It is also worth noting that these strategies are fully aligned with stronger data security policies, made possible by Data Mesh strategies, which democratize data without sacrificing security. As a result, innovation becomes faster and more customer-focused.
How can Digiage help?
Digiage is Starburst’s partner in Brazil, the company bringing Data Mesh to thousands of businesses around the world. With Starburst, marketing professionals can access the company’s key data sources.
Through a semantic layer, teams across the business can get the information they need without any loss of security, protecting sensitive data and meeting every LGPD requirement.
To learn more about Digiage and Starburst, get in touch with us