Developing a data strategy can be a daunting task for a marketer because, simply put, you were never trained to think about data. That being said, step one is to admit what you don’t know so you can surround yourself with the people who do. You want a savvy data scientist or data analyst by your side, and you need someone from IT who will understand the terminology, the players, and the ways you can access and prioritize data. These are important hires, and not ones to take lightly. It should also be stated that you should have these people in-house. Agencies and consultants are nice, but they reside outside your company and will never know as much as an embedded data scientist on your team will know.
Once you have the right people, you need to know what kinds of data you have. Data comes in two dimensions, each divided into three primary subdivisions each. Many people will tell you (and sell you) far more complicated methodologies, and for good reason, but as a marketer talking to another marketer, I'd say this is the simplest way to view the complex world of data.
The first dimension refers to the format the data comes in. I simplify these to raw, aggregated and refined. Raw data is unstructured, voluminous and overwhelming, but it provides you with a foundation to work from. The second way to access the data is in an aggregated form, where there is a common taxonomy in place, the data is structured and you can make some basic sense of the asset you have. The third format is refined -- or the type of data that has been analyzed, with insights gleaned. These insights are typically in a usable form and ready for activation through a channel or partner.
The second dimension of the data refers to where the data comes from (the source), which is simplified as first-party, second-party or third-party. First party refers to data that is exclusive to you, but finite in nature. Third-party data refers to publicly available data from any number of third-party data providers. This type is infinite -- but everyone has it, so it provides very little, if any, competitive advantage.Second-party data refers to partner-to-partner data exchanges where two companies share data for use in co-marketing, etc. This data is more scalable and semi-exclusive, so it tends to create strong competitive advantages.
Once you have identified the format and source of the data, you can prioritize which signals are most important, which create true competitive advantages and what you can do with the data. The uses of data, or what the output of your data strategy should be, is also based on three use cases: targeting, personalization and measurement. Targeting is a matter of efficiency and eliminating waste. Personalization refers to messaging, ensuring that a tailored message is delivered to the targeted audience. Measurement refers to closing the loop and understanding the impact of the data. If you know the format, the source and the use of the data, then you are far down the path to developing a data strategy.
Of course there is more to it -- for example:
As a marketer who loves data, this is exciting to me. It should be exciting to you, especially when you break down the data into usable, more easily understood nuggets of wisdom.
Are you developing your data strategy --or are you waiting for someone to tell you need to get started? My hint for success: Don’t wait. This is far too important.