Data is hot. It’s literally on fire right now and if you’re not working on a Data Strategy for your marketing and advertising needs, then you’re likely going to be stumbling in the next 12-24 months, and stumbling badly.
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 in the development of your Data Strategy is to realize, and admit, what you don’t know so you can surround yourself with the people who do. You want a Data Scientist or savvy 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. Agency’s and Consultants are nice, but they reside outside your company and will never know as much as an embedded Data Scientist on your tam will know.
Once you have the right people, you need to know what kinds of data you have. Data comes in 2 dimensions, with 3 primary definitions 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, 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 from the data. 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 1st party, 2nd party or 3rd party. 1st party refers to data you have and is exclusive to you, but finite in nature. 3rd party data refers to publicly available data from any number of 3rd party data providers. 3rd party data is infinite, but everyone has it so there is very little, if any, competitive advantage. 2nd 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 advantage.
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 3 use cases, adding a third dimension to your data matrix. The uses of data are targeting, personalization and measurement. Targeting is a matter of efficiency, and eliminating waste. Personalization refers to messaging, and ensuring 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 for use in your marketing.
Of course there is more to it; for example:
- Where should the data reside?
- What tools do we need to activate the data?
- Which partners do we need to enable use of the data?
- And more…
You can quickly see why you need to surround yourselves with the right people to help develop and execute your Data Strategy. 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.