It's 2019, so why data-driven marketing is still a myth rather than applied marketing?

Data-driven marketing belongs to marketers' beloved buzzwords. Whenever you refer to it you sound smart and nobody ever asks you to go into details. Still, we somehow agree that the way marketers organize data and use it to fuel their media activation is crucial to their businesses. Where's the beef then?

Marketing strategy

Although painfully repeating truisms is never an option, this one is apparently not obvious enough: data strategy stems from marketing strategy, not otherwise. As long as you don't know who your customers are (or will be), where are they on their path to purchase, what your offer is, which sales and communications channels you would employ, and skip many others aspects of strategic marketing, all the data you collect in the digital ecosystem is useless. Whereas it is not my goal to dive deep into marketing strategy, I would like to discuss the ways it influences data collection and analysis. First of all, let's deal with the question "who" aka your existing and future customers.

STP or segmentation, targeting and positioning framework was introduced a couple of decades ago and followed the classic 4Ps model. It's primary goal was to help companies identify and properly describe their customers and then pick the best marketing channels to approach them. First attempts were usually based on demography and basic psychography available through market researches conducted every now and then. The emergence of Internet and digital transformation dramatically enlarged the volumes of user-related data and made very granular and precise segmentation possible. Simultaneously segments, or groups of customers sharing similar characteristics evolved into personas and marketers began to categorize their users from online behaviour angle. Data strategy-wise personas are one of the key elements of a marketing strategy.

The second one is the sales and communication channels, especially within digital ecosystem. Every channel, no matter if it's advertising, CRM, e-mailing or a webiste, generates multiple contact points associated with a user. These contact points are stored, analysed against repeatable patterns and used to inform marketers on users customer journey and other aspects of their digital presence.

Smart marketers spend lots of time on proper personas identification and understanding their characteristics and are aware of the importance of data signals collected upon every single contact point. Having these two makes them ready to work out and execute a meaningful data strategy.

Data Strategy

So, now it is time to connect the dots. You already know who and know where and want to reap beneftis from this knowledge. In my opinion a good data strategy consists of only two, but pretty challening elements:

• translation of data signals to personas
• understanding where each user is on their customer journey

What is also very important, though, is the ability to match data coming from multiple sources and correctly tie them to users. Unofrtunately, as a matter of fact, marketers use many tools simultaneously and very often find it hard to do the user matching. And sometimes it is not possible at all. Although a single customer view is hardly achievable as sometimes tools will force us to compromise and accept a certain level of information loss, any effort regarding data should be made with the use of unifying framework and technology.

Data strategy document doesn't have to be long or robust, but it is extremely important that it builds the seamless connection between personas and user data and triggers relevant action towards customers. The most useful tool for that purpose is a matrix or a taxonomy presenting the connection between the data source and type and each persona. It is also necessary to build awareness around limitations of current technologies. In the end of the day a strategy is useless as long it is not applied, and CDPs or DMPs are crucial in terms of execution.

Summary

Sounds simple so far? Then why creating a good data strategy is still such a big deal? My answer is that most companies lack structured thinking about their customers and are somewhere between 1980s and 1990s in terms of their marketing strategy. Some of them seem to forget that in such a complex world as 2019 digital ecosustem, there are no shortcuts. Programmatic, Marketing Automation, DMP/CDP and others require time and effort in order to be properly implemented and customized, and they are all but plug&play. And, what is probably most important, automation and abundance of data should not be taken as an excuse for the lack of organized approach and seamless process architecture.