Retrace your customers’ steps For the love of data #2
A.I. driven Attribution Models reveal a complete view of your complex Customer Conversions.
We all know that a good love story is as much about the journey as the happy ending. And the same is true for your customer journeys – the road from first encounter to final click can be complex and revealing, so why use Attribution Models that only pay attention to the final step?
What do Attribution Models do?
Think about the last time you made an online purchase, booking, or investment. Now, try to map out how you got there… Where did you first hear about the brand? What were your encounters with them since then? Have you purchased with them before? What’s kept them on your radar?
These are exactly the sorts of questions you need to ask about your own customers when you think about Attribution Modelling.
Go beyond the last click
Attribution Modelling is just a fancy name for the rule, or set of rules, that we use to dole out credit for a sale to the channels in our comms mix.
The most common is the Last Click Attribution Model, where all credit is given to the final channel that led a person to purchase – the last click. There are a few other common models; all have their uses. But any out-of-the-box Attribution Model used in isolation can only ever tell you so much.
Attribution Modelling becomes valuable when you start to really understand what you’re looking at – to see the information from lots of angles, to zoom in on the fine details, or zoom out to see trends. There’s no ‘right way’ to do it – it all depends on your business.
Customers, not Channels
A good place to start, though, is to change how you think about Attribution Modelling: not in terms of channels, but in terms of customer journeys.
At Distil.ai, this is our starting point: people. Our Attribution Models are based on individualised customer data, that then forms individualised customer journeys. Imagine this like lots of little threads which we can then use in Attribution Models to bundle them together in lots of different ways.
By doing that, and doing it in a way that’s channel agnostic, you can start to really understand what in your comms mix is working and how: what’s bringing customers in, what’s keeping them loyal, what’s prompting them to purchase, and how it all works together.
Put your Attribution Models to work
Once you start using Attribution Models like this, the possibilities are endless. Every new discovery will prompt new questions, and help you experiment and refine.
Maybe you’ll discover that Facebook doesn’t bring in new customers, but keeps them coming back.
Maybe you’ll realise that email is effective but only for a certain audience at a particular time.
Maybe you’ll find that one half of your customer base is clicking on your search ads, but the other half couldn’t care less. And maybe you’ll start to understand why…
The more you know, the more you’ll want to know, which is why you need a constant flow of rich data, and the ability to slice and view your Attribution Models in different ways. So that when you find yourself wondering ‘OK, but is that true for my trade customers?’ or pondering ‘What about if they’re subscribed to my mailing list first?’ you’ve got an intuitive set of tools that lets you find out.
Attribution Models upgraded. Channels harnessed.
Fuelled by the right data, treated in the right way, Attribution Modelling can become an extraordinary weapon in your marketing arsenal, helping you understand and adjust your comms to streamline spending and deliver results.
Drop us a line at email@example.com to see how Distil.ai can help you understand your Customers better.