Data In. Data Out. The Secret to Data Driven Marketing

Data In. Data Out. The Secret to Data Driven Marketing

Data In. Data Out. The Secret to Data Driven Marketing
You’ve likely heard the old one-two punch from the digital marketer: “It’s as easy as data in and data out.” Well that might be the process, granted but there is a little bit more to it and let me tell you why.

So let’s start with “data in.”

When talking about marketing automation, cross-channel marketing and programmatic marketing, it all starts somewhere with a single point of data. Usually a form submit of some sort or a manual data entry somewhere—bringing to light five key areas of focus for the much spoken term data in.

The source of the data is key, it might be in a CRM, it might be in a traditional on premise data storage solution, it could be in a marketing orchestration engine; it doesn’t really matter. What matters is understanding where the data is. Need customer contact details—where is it stored? Need purchase history—well what table is it stored in? Need engagement behaviour? Well I’m sure you get the point.

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For every treasured piece of data there is a person in front, guarding it. Some guard things a little more strongly than others, due to their seriousness—e.g. PI data or financial data. But guess what, you have just found your new best friend. Now this is not really a blog post about the workings of inter-office politics, but I do suggest that you find out who is responsible for the source that the data is in and then you educate them on why you need it.

While you are talking to your new best friend, I suggest that you also start to have a chat about how the data is coming across. There is work and sometimes a lot of work when you start to look at the transfer of data. Is it sent over via API or is it batched, oh and if it is batched—then how often? What if the job fails, who will be notified? All of these questions will start to ring around your head and you need to have process documentation to clearly identify the data flow.

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It goes without saying that you want the cleanest data. There is no use being a retailer and sending men information on women’s clothing via email. If that’s the case, your sales won’t be improving anytime soon. I once heard a colleague tell a co-worker he doesn’t care about 99% correct, he cared that it was 1% wrong. The integrity of the data is key, especially if you are starting to look at segmentation.

Never, ever, ever just ask for everything. 1: if you have to ask for every piece of information your company has on someone, odds are you don’t actually have a plan. I’d suggest you first start there. 2: those people whose responsibility it is to look after that data, they are also going to think you have no idea. 3: come on… Do you really want everything? I know data scientist that have cut off data streams at two years because it wasn’t relevant 

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Never, ever, ever just ask for all of the data. If you have to ask for every piece of information your company has on someone, then odds are you don’t actually have a plan. Those in charge of the data are going to know that you don’t have a plan. Do you really need everything?

If you were to break that down into five key areas of organisational focus, you need to align people, process and technology. Within these areas are five key focal points for data in: source, responsibility, transfer, integrity and structure.

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