Micro segmentation over 1:1 personalisation

Even when data is readily available to inform highly targeted engagement, someone actually has to produce the creative and copy to trigger the engagement.

I was on a panel at an Adobe event late last year when the topic of 1-to-1 marketing came up. I have always been a huge advocate of trying to get as close as you can to 1-to-1 marketing, but that comes with a caveat. The cost to get to the elusive everyone is individualized is massive. When I say as close as you can, what I mean is start from the top of your customer list (not by alphabetical order, but by some worth and frequency or potential worth metric) and work as far down that list as you can to create 1-to-1 marketing for your best customers. The other customers you want to have as many segments as makes sense, but always allow the data to drive those segmentation decisions,

Automating up-sell and cross-sell campaigns

Marketing is the only function in the business that actively communicates across the entire spectrum of the customer lifecycle, from the inquiry to a loyal customer. That raises two very interesting questions that data-driven marketing has answers for:

Should marketing own the customer lifecycle?
How should marketing allocate time, budget, and effort across the customer lifecycle?

As I commented on recently in my article Retention is King, retention's the first place I start when implementing a marketing automation program. The customer lifecycle should be owned by marketing. Marketing has all the tools to automate the communications in the relationship and target based on behavioral and demographic data. When it comes to the question of time allocation, make sure the retention programs are dialed in. They will never be finished and you will always be tweaking, but then you can move on to acquisition and reactivation. It is much easier to cross-sell or up-sell a loyal customer than it is to acquire a new one.

A/B testing on landing pages and email campaigns

According to the 2014 Gleanster Marketing Resource Management report, only 60% of small and mid-size firms conduct A/B tests on email, landing pages, and website properties. It’s actually shocking to learn how much you really don’t know about your customers when you run A/B tests on creative and copy.

In sales they say "ABC", Always Be Closing. In marketing automation and data driven businesses we should say "ABT", Always Be Testing. The caveat to this saying is there needs to be an understanding of a baseline first. So if you are implementing a new program, let it run for a bit (unless it is a total disaster), use analytics to look for opportunities and test those opportunities. Don't just test for the sake of testing, always let the data drive the opportunities and then test the hypothesis.

Machine learning is your best friend

One consistent theme that keeps coming up in our advisory sessions is that marketers want help in data analysis. Thanks to advances in computing power, data analysis that previously took days can now be done in seconds and often in the cloud. Machine learning applies rules to data sets and looks for correlations between data. Does this do the job of a marketer? Heck no! What machine learning does for marketing is help isolate trends that should be investigated further. Marketers still need the context about customers and products to translate those correlations in the data into action.

As I said just above, let the data drive your testing. Machine learning and data mining techniques can uncover insights within your data that the human eye could never perceive just by looking. Many marketers want a predictive modeling tool to spit out an answer as to what they should do and just go do it. If that were the case, why do we need the marketer? It is important to make sure to understand what the outputs of these tools provide and test their findings. Without the business acumen, the output could be very flawed. Don't jump to a conclusion, use the insight to form hypothesis about your customers and test away. Remember as I wrote before, Data + Insight = Action.