- What do you need to know about your audiences to communicate effectively?
- What relevant distinctions exist among your audiences?
- How do you know you’re right?
To help corral the answers from these questions, I suggested a data strategy brief, much in the way that a marketer uses a creative brief. Let’s explore what this brief should contain.
Why a brief?
First off, consider the format. Data make for an unruly menagerie. Getting control of that mess requires sophistication. However, a marketer can easily get too caught up in the details and miss the point. A data strategy brief serves as a polestar, simple document that orients the marketing organization towards success. Ideally, the brief should take no more than two pages.
What to cover
- Goal: Every strategy--creative strategy, media strategy, social networking strategy--needs a goal. Naturally, most goals in marketing come down to “sell more stuff.” However, the marketer needs to put that goal in terms of how the data help the marketer sell more stuff. Do the data help drive customer intimacy? Find the right time to make an offer? Create the most effective offer? Make it clear.
- Key Measurement: In concert with the goal, the key measurement should help the marketer measure progress. As a result, the key measurement should reflect the goal directly. So if the goal is to create the most effective offer, the measurement should reflect offer success, in terms of conversion rate, order size or some other indication of a relevant offer.
- Most Relevant Data: While a marketer may have dozens--even hundreds--of member-level data points at his or her disposal, only of few of them strongly correlate to communication performance. Not only should the brief list these data points--ideally three to five--but also how they differentiate the customers. So, for instance, if family composition emerges as a key data point, the brief should explain why (e.g. “families with kids tend to buy larger product sizes”). With this information, a marketer coming up to speed on the data strategy can understand which data points require the most urgent attention.
- How to Employ the Data: while the “Most Relevant Data” section above may render use of the data obvious, it nevertheless helps to have explicit rules for data use spelled out. More to the point, data usage may have specific nuances that require explaining, kind of like “eat this, not that.” In the above example, the use of family composition data may work in onsite cross-selling, but not necessarily in email, based on the results of testing.
- Data Hierarchy: In many cases, more than one data point may have an impact on communication performance. It behoove the marketer to create a sort of flow chart explaining which data points take priorities over others. Again, using the above example, family composition may work best for determining best offer in one product category, but most recent order size may work best in another.
You could probably add a lot more here, such as data requirements (especially important for highly regulated fields such as health care or financial services). However, these five areas should cover the most of it.
Got anything to add? Let’s hear it in the comments!