Advanced data analytics is a game-changer for marketing organizations. A McKinsey DataMatic study showed that firms in the top quartile of analytics performance were 20 times better at attracting new customers and more than 5 times better at retaining existing customers.
Marketing & Analytics: A New Dream Team
With the rise of the digital ecosystem, marketing analytics have a bright future. The intersection of marketing and analytics has enabled teams to adopt a more customer-centric approach. Examples range from using specific offers to retain existing customers, delivering highly-targeted offers, serving targeted content to prospects, using payment network partnerships to facilitate the delivery of time & location-sensitive offers, and much more.
Realizing all of these goals hinges on customer knowledge. Without inputs on who customers are and how they behave, organizations have no insight on how to leverage them. This is, after all, the age of the customer, where consumers are the driving force behind business decisions. Customers no longer blindly accept what’s offered to them — self-education now precedes purchasing decisions. This has forced marketers to re-think how they reach potential customers at all phases of the buyer journey.
Customer Knowledge: Reloaded
Knowing customers is not a new idea, but the concept has evolved in our modern, data-driven environment. Customer insights are now the province of big Data, where consumer behavior, actions, and trends lie hidden in vast quantities of heterogeneous data. Knowing and segmenting your customers is truly a data problem: how do you get marketers to drive their campaigns based on data rather than gut feeling?
The answer is that it involves a fair bit of change not only at the tactical and organizational levels, but also at a personal level with the skills marketers will need to have to execute. But it doesn't mean all marketers need to become data scientists overnight — instead, the answer is collaboration.
For example, rather than the unrealistic expectation that marketers should be experts in data science (or the dream that each marketing team has its own data scientist or other data expert on staff), it's critical to centralize data (including projects, processes, and knowledge surrounding it) in a shared environment, allowing team members to pick up the work of their colleagues, keeping tabs on progress and allowing marketing analysts to collaborate efficiently on data projects.