Making Money On-line: 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.  

Source

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.

Responsibility

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.  

Transfer

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. 

Integrity

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.

Structure

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

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.

Data Out

We need to remember why we want data. Usually it is to make a decision. For customer purchases, we need to send a confirmation as well as the order for fulfillment. When a customer signs up to our database, we want to welcome them to the company so they don't feel like they are actually on a database. Or we want to send an enriched segment onto our website so that at we can run a multivariate test on them. The data out process is all about planning, structure and purpose.

Why?

If you want to do something there is always a “why” behind it. Think about sending an email campaign—generally you want to inform or sell. An SMS should be sent as a programmatic trigger or as a time sensitive and important message. The why is one of the most critical points, it starts to articulate your purpose into a tactic. I want to nurture a prospect therefore equals a lead nurture email. There is a “why” behind data out and if you figure that out, the rest will come easily.

What?

It's not what are you doing and how you are going to do it? Instead it is what do you want the recipient to do? What do you want the prospect or customer to do? Think about if carefully, we are in the digital world. Whether it's tap, click, or even just read (for my media publisher friends), all our decision points need to be centralised around the customer and what they want and what we need to do to get them there. How's that relevant for data out? Well think about it, we have the data in a platform and now we need to use what we have to fill a customer’s need to drive what the organisation wants. It's a two way stream of value: an organisation gives and then an organisation gets.

Channel

How are we communicating to our customer? With marketing automation comes great power, at a touch of a button I can send an SMS, email, push and display ads to you. The point is we need to be mindful that some channels work better than others, we also need to be mindful that some channels work better for individuals than others. Finally, we need to understand that some channels work better at different points of the journey. Enriched display, is great for prospecting. Display retargeting is great for closing the funnel. Email is perfect for nurturing and building a relationship.

Feedback

I don't know an enterprise organisation that doesn't care about feedback, and how that feedback is processed. I also know several small organisations that look at the feedback. Yours might be one of them. There are different levels, approaches and reasons for feedback processes. Reports are one of them, reports allow you to manage the feedback process and make sense of what has happened. Email opens, display conversions, in app purchased, etc. this is all feedback. Here's the interesting part; you can take that feedback and ingest it into a platform to make decisions and act on it at a later date.

Data in. Data out. And data back in.

It is actually as easy as data in and data out, you do however need to bring structure to your objectives and planning. Would you like help analyzing what state your data is currently in? Download the Modern Marketing Essentials Guide to Data Management to start using your data in wiser and better ways.

During the process, keep in mind that it is only easy once you have these structured plans centralised around people, process and technology.