Email Segmentation, Personalization, Automation: Getting Important Data Into Your ESP

Email Segmentation, Personalization, Automation: Getting Important Data Into Your ESP

What kinds of data should you be uploading into your ESP? Columnist Andrew King outlines that and more to help boost the relevance of your emails.

As an email marketing consultant, I frequently talk to marketers about the benefits of segmentation, personalized content and automation. Marketers are generally in favor of all these things and usually agree with most of my recommendations.

However, when it comes to implementation, we frequently run into the issue of how to get the required data into their email platform. This issue doesn’t just come up once in a while; it comes up all the time.

So, I want to discuss the types of data that you should be uploading into your email service provider (ESP), how this data can be used to enhance the relevance of your emails, and finally, how to get that data into your ESP.

Useful Types Of Data

Demographic
This is your basic A/S/L (age, sex, location) data that you might collect from subscribers when they sign up or make a purchase. This type of data generally doesn’t change very often; people don’t change their name, gender or location too often (although all of those things could change), which makes this type of data ideal for basic segmentation, personalization and automated emails.

  • Name
  • Age
  • Location
  • Gender

Preference
Preference data is usually collected through a preference center that your subscribers fill out during the signup process and might include data regarding their preferred products, services, brands, size or frequency of mailing.

You need to be careful how you use this data as it can go out of date very quickly. For example, someone might tell a travel company that they’re interested in visiting Thailand, but that doesn’t mean you should only send them emails about Thailand for the next two years!

I also want to note that many people won’t update their preferences if they do change, unless prompted, so it might be worth setting up an automated email to remind subscribers to do this periodically.

  • Product
  • Service
  • Destination
  • Category
  • Size
  • Frequency

Transactional/RFM (Recency, Frequency, Monetization)
Liberating your transactional data from its e-commerce platform prison is one of the best things you can do for your email program. Importing this data into your ESP will dramatically improve your segmentation and personalization, and opens up a new world of automated emails.

This data allows you to identify who your best customers are, who’s about to lapse, or who hasn’t made a purchase yet.

  • First purchase date
  • Last purchase date
  • Total amount spent
  • Number of purchases
  • Average order value
  • Past products purchased

Behavioral
Recent behavioral data is the most reliable indicator of what your subscribers are interested in right now. This type of data might be collected from an email (opens/clicks) or from your website (pages browsed/items carted).

The most common type of behavioral email is a cart abandonment trigger, which usually goes out within 24 hours of subscribers abandoning their cart. However, many technologies are now available which allow you to follow up pretty much any action that a subscriber takes on your website. That sounds a bit stalker-ish, but I assure you that it can be used to send helpful, relevant emails based on the products, services or topics they have recently browsed.

  • Product/Service/Web page browsed
  • Cart abandonment
  • Form abandonment
  • Email opens/clicks

What Are You Planning To Do With This Data?

There’s no point in doing a data integration if you don’t know what you plan on doing with that data — unfortunately, this is a far-too-common scenario.

I suggest that you create a very specific plan and mock examples of what you’d like to do with the data available to you and then work out how you are going to get the required data into your ESP. Typically, your ideas will fall into segmentation, personalization or automation.

Segmentation
Having a rich data set within your ESP opens up some great opportunities to create highly targeted segments, which combine demographic, preference and transactional data.

For example, you could target people of a particular gender, who are interested in a particular product category, have made a purchase in the last year, and spent over a certain amount. Now that’s a targeted segment!

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