I’m a huge fan of analytics… so long as they can remain actionable. You hear the term actionable data insights quite a bit these days. Well, for me it actionable means the insight applies to or results in a tactical impact to marketing initiatives.
The umbrella of analytics as it relates to marketing is voluminous and confusing to say the least. The nature of analytics as a practice and skill is by definition a platform that can “do anything”. Having been a part of many teams in my own past that deliver analytics to support marketing initiatives I can say with confidence that any analytical project needs direction. A data scientist might call this direction a hypothesis statement.
Of all the possible ways analytics can impact marketing initiatives, as a marketer, I think there areas 3 to focus on more so than others that will yield ROI.
1. Customer Segmentation
Foundational in nature, a strong customer segmentation is key in the test, learn and react cycles for marketer’s specifically for measurement of ROI. Encourage your analysts to build less than 10 customer segments that are based on data attributes that are:
- Easy to understand
- Stable in that they are present (i.e. populated) for the vast majority of customers in the database
2. Offer Mix
What offers are available, who are they being presented too, in what channel and why… In the very first tests the offer mix may seem subjective in nature but remember to ensure that a “size of prize” analysis is done to understand the following:
- How many customers are eligible for each offer
- What does each offer cost to serve / fulfill
- What is the gut feel for response rates for each offer
- What is the ROI of the offer
After the first few tests come back with results analytics can step in with all kinds of algorithms and methods to optimize the mix, it may not seem like it but this is actually the easy part. The challenge is to structure the hypothesis statement or give the appropriate direction. Here are some guidelines to use, as a marketer, when giving direction to analyst on optimizing offer mix:
- Define success metrics explicitly
- Delineate short term success vs. long term success
- Define “what if” parameters in your strategy for the analyst
At a minimum if you give this direction you’ll end up with a platform of analysis that produces enough results to facilitate test, learn and react cycles that will increase ROI.
3. Long Term Impact of Offers
Driving organizational value from marketing programs is a game of inches. Every once in a while you have to pick your head up from the day to day rigor and look at the scoreboard. Here are a few best practices:
- Ensure you create and maintain a universal control group
- Regularly (perhaps quarterly) analyze movement in your customer base. Who’s new, who’s leaving and who’s shifting
- Establish an internal benchmark for long term performance as well as an industry benchmark to compare against
The analysis conducted in this area of focus is almost certainly a marketer’s most valued product delivered to their organization.
- Josh Smith -