Building a Great Email Schema | Part 2: Data Wishlist

By now, you’re good on the different kinds of data you can include in your schema. You’ve taken time to consider how explicit and implicit data points can help you develop highly targeted audiences. Very thoughtful of you, well done. Highly targeted audiences are of course key because 269 billion emails were sent each day in 2017, according to Campaign Monitor. 

When you’re evaluating the data points you want to include, think about the values associated with those data. There’s likely four categories…

Type Definition Examples
Binary Values that are either true or false Subscribed to emails
Words/Phrases Any alphanumeric value First name, SKU
Numbers Anything that is a number, shockingly Age
Dates Time stamped actions Last purchase date

Now it’s time to put together your wishlist – all the data points that can help you inform your email segmentation and personalization. It’s helpful to think of it in these terms because there are data you want to improve the relevance of your emails through personalization, but wouldn’t be relevant for segmentation. For example, first name – you probably wouldn’t build a list for everyone named “Kevin” – but it would be nice to customize an email with Kevin’s name to drive better engagement.

Here’s an example of s list help you get started – there’s likely things that are unique to your business that you’ll want to include. 

Data Field Values Data Type Purpose
First Name Alphanumeric Explicit Personalization
Last Name Alphanumeric Explicit Personalization
Email Alphanumeric Explicit
UserID Alphanumeric Implicit
Registration Date Date Implicit Segmentation
Last Visit Date Date Implicit Segmentation
Lifetime Value Number Implicit Segmentation
Last Item Purchased Alphanumeric Implicit Segmentation
Last Purchase Date Date Implicit Segmentation
Birthday Date Explicit Personalization
Age Number Implicit Personalization
Email Subscription 1 Binary Explicit Segmentation
Email Subscription 2 Binary Explicit Segmentation

After you’ve got your wishlist together, it’s time to chat with your technical resources. They’ll be able to help you understand what data points can be accessed and packaged to deliver to an email service provider.

There are two primary ways to deliver data to an email service provider – either as a batch file or through an API. A batch file will aggregate all the changes from a time period – mostly likely the previous day, and deliver those records all at once at a specific time. Batch files will have latency, or a delay in syncing information between systems. An API on the other hand can send updates in near real-time to an email service provider as users engage with your site.

When you chat with your tech team, be sure to understand not only the data points that you can use, but also the delivery method by which you’ll deliver those data as it could change the conversation about what’s available to you.

2 Comments

  1. Hi Adam, great article. Question for you on data delivery – it seems like API would be the obvious choice over a batch file due to the real time updates, is there any reason to continue to use batch files instead of working through an API?

    • Thanks for the question, Megan! APIs are great for many reasons, one of the most significant advantages is the one you mention – having access to data in near-real time. The challenge in with APIs in this context is that the API must be able to access and return all the data you’re interested in for your email schema. Companies have lots of APIs that can do lots of cool things – but they’re developed to serve a set of particular needs. If your tech team is ready, willing, and able to support you by leveraging an API to access all the data you want to include in your email schema, the more power to you! Flat files are often an easier way to exchange data and require less development time, but totally agree, APIs would be preferred if all things were equal.

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