There are a total of 9 different data fields to choose from when designing a segment in BuyerGenomics. These make up all of the dimensions you can implement to add depth each segment you create. 

First, go to “My Segments,” and click on “New Segment.” You will see the 9 fields to choose from.


The following is a breakdown of what each field is and how they can add value to your segments.

1. User Data

User Data (along with Address) is related to a customer’s Personally Identifiable Information (PII) - meaning that it contains information that is associated with each unique individual.

It includes first name, last name, gender, customer type, email/direct mail/phone call subscription information, birthday, and anniversaries.


2. Address

When including Address, you can choose between actual residential street address, or an address including elements of a particular city, state, or country.


3. Transactions

The Transaction button provides you with a wide range of data that can detail different elements of a customer’s transaction history. This includes last transaction date, first transaction date, total amount spent, number of full price purchases, average number of days between transactions, number of transactions via a particular channel, and the next most likely transaction date.


4. Receipt

While the Transactions field focuses on customer transaction summary, the Receipts field is centered on one specific transaction that a customer has made. This includes a full list of particular information to choose from.


5. Scores

Scores are model-ready variables - some of which play a key role in how we calculate Most Valuable Buyers (MVBs), Frequent Buyers, and other smart segments.

For instance, all MVBs have an Amount Score that is greater than 1.


6. Clusters

The Cluster field helps to discern the specific cluster, mega cluster, or life stage that you want the customers in your segment to fall in. Clusters are mutually exclusive, which means that each customer can only be in one Life Stage group at a time.


7. Predictive

Predictive data elements offer powerful indicators of a customer’s propensity to spend - whether they are a high or low spender, or somewhere in between -  as well as their particular lifecycle stage. From there, you can use that information to predict the next category that they are likely to purchase in, and when.


8. Email Touches

Email touches allow you to see whether or not you have sent certain emails to certain individuals and when they engaged with them.

While you can respond to opens and clicks in real time using follow-ups directly in your campaign, you can also use this segmentation field to view your most recently active openers.

For example, you can view and classify your active engagers based upon whether they opened and clicked an email of yours within the last 90 days.


9. Website Touches

Website Touches covers everything involving what a user did on your site - from how they viewed it (tablet, computer, iPhone, Mac OS, etc.) to the type of language used, to what pages, products, and categories were specifically viewed.


Equipped with the knowledge of all of these data fields, you will be able to layer them all together to create complex, valuable segments that describe who they are, what they’ve done, and what they buy in order to create the most efficiently targeted groups as possible in your database.