Building a Great Email Schema | Part 1: What kind of data?

Email is awesome. It’s one of the few mediums where we can get close to that sacred one-to-one level of communication. You know what’s not awesome? Being blasted, whether by an email, or something else.

Email marketing remains the best digital marketing channel for return on investment, according to the Data & Marketing Association’s 2017 Study —Forbes

When I hear marketers talk about email blasts it makes me cringe because it implies, right or wrong, that they’re not taking the time to build highly targeted audiences to leverage the opportunity for the one-to-one nature of email. In digital marketing, it all starts with data. The more you collect, store, and process, the better off you’ll be when you’re ready to use that data as the foundation to one to one messaging.

To capitalize on the power of email as a medium, we have to start with a well defined schema – or predetermined set of attributes and associated values (a.k.a. the data) by which we’d want to segment our audience – so we’re not blasting them, but rather gently showering them with highly relevant content. Now because you’ve taken the time to follow your customer through their experience with your product or service, you have some inkling of what type of data you might want to include in your schema.

Think about it this way – there are two types of information you get from a user, both of which are important to your schema – explicit data and implicit data. Think of explicit data as the data that a user enters in their profile. They’re explicitly sharing the information with your business through your interface. Implicit data on the other hand, is data your business can infer from behavior. For example, if a user begins browsing products in a similar category, but doesn’t buy one, you can infer that they’re in the market for said item, despite the fact that they didn’t explicitly tell you as much in their profile. The key to unlocking the explicit and implicit data have depends on whether you store that information.

Segmented email campaigns have an open rate that is 14.32% higher than non-segmented campaigns —MailChimp

Let’s try on an example, see how it fits. Take your electronic medical record (EMR) – the digital repository of your medical history. There are explicit pieces of information you share for your EMR when you first see a doctor – name, DOB, things like this. Then over time your doctor adds notes to your EMR about your symptoms and supplements those notes with details he or she concludes based on his or her experience – implicit details if you will. Then let’s say you have to switch doctors. You can request a transfer of your EMR which is great, but the record is only as good as the information stored in it.

It’s the same with your email data! Consider explicit and implicit data points when starting to plan out your schema. Find out how data is stored and map those data points to the customer journey to make sure they’re telling you something of value that you can then act upon – i.e. when to send a highly targeted, hyper relevant email.

In the next part, we’ll discuss attributes and their values.

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