In my previous post we covered the database strategy. This time I wanted to dig into tactics, mainly looking at email which is currently the core database marketing channel for most e-commerce businesses (my strong suspicion is that won’t be true soon).
Anyway, given the strategic objective of maximising the value of the database, let’s look at some tactical considerations:
1. Are we simply bringing forward sales that would have happened anyway?
2. Are we offering a discount to a customer who would pay full price?
3. Are we mailing at the right frequency?
4. Is the content right?
5. What product personalisation should we be using?
6. How strong an offer do we need?
7. Who could be a Member-Get-Member advocate?
8. Who is at risk of leaving us?
On reflection, it becomes clear that there just isn’t one answer to these questions. They are fundamentally questions about segmentation.
The first question should really be “Who is going to buy anyway and who needs to be prompted?”. The other questions could be re-written in a similar way.
These questions are inherently much more complex than our strategic question which could be answered with one simple formula to measure the value of the database. There’s a lot of crossover between the questions: some people probably do need a strong offer at a high frequency for example.
These sort of complex, multivariable questions are very well suited to machine learning where we can just put a bunch of data into an API and action what comes out.
This is what we are currently working on at our new startup Machine Labs. If you are interested in joining us as a beta customer then please get in touch.
