Measures: Extracting Insights from Customer Insights

A continuation of a series of posts diving into Customer Insights

Looking at a Customer Card or the home screen dashboard in Customer Insights, one of the first things you’ll notice are the tiles that display various numbers, or measures, representing a customer’s interactions with your company. These might include things like a customer’s average purchase when visiting one of your bricks-and-mortar retail establishments, their average online purchase, or lifetime value.

Types of Measures

There are several different types of measures:

  • Customer Attribute – Configuring this type of measure allows you to add a new attribute for display on the merged contact. For example, if you wish to combine all of an individual contact’s purchases from across various systems into one field to show the individual’s total spend.
  • Customer Measure – Similar to the customer attribute above, but with an added dimension like time. For example, if you wish to show how many times on average a customer visits your online store, or how much do they spend across all your systems on average per month.
  • Business Measure – A business measure is a way to look across your entire customer base in aggregate to answer questions at the business level rather than at the individual contact level. This is the type of measure you would configure to answer questions like “what is the average purchase at our retail/POS locations?”
Variables

Variables are operations that you want to perform for each customer record in Customer Insights. One of the more interesting capabilities you’ll come across when building a measure is the Variable Expression editor. It is not intuitive at first. On the right, it will show you the tables and attributes from your connected data that you have chosen as you begin building out your measure. I’ve found that if you click the attribute on the right, it will put it in the expression editor for you, saving you from having to figure out the correct syntax to use if you were to type it in manually.

Double-click the attributes on the right to get them into the Expression area.

After clicking one of the attributes on the right to put it into the Expression area in the correct syntax, you can simply type the mathematical operator you want to use. You can also group operands using parentheses in order to perform more complex operations. For example, you might want to create an expression like “(Total Web Purchases + Total Store Purchases) / RewardsPoints” to determine how many dollars your customer had to spend across both your website and bricks-and-mortar stores to earn each reward point they’ve been granted. (Perhaps your letting some customers earn those valuable loyalty points too cheaply because they’ve figured out how to game your loyalty system!). That expression would look like this:

(eCommerce_eCommercePurchases.TotalPrice + PoS_posPurchases.TotalPrice) / PoS_posPurchases.RewardPointsAdded
Functions

After creating a variable for each unified customer record, you’ll need to apply a function to it. Do you want to look at the average result of your variable operation across your entire customer base? Or a sum or count of those results? That is defined in the Function.

Note: A function creates fields where the results of your measure are stored. Behind the scenes, when you define a measure you are creating a new “entity” that will be listed in the Data area of Customer Insights. If you open that entity, you can also view the fields that were created for it as a result of defining the function.

Creating measures can take some experimentation – it’s worth it to begin exploring your data and playing around to see what types of insights these measures can provide your organization. It’s very likely you’ll uncover some things that weren’t obvious before your customer data was nicely unified.

Published by Matt Wittemann

MVP, Microsoft Business Applications Senior Solution Architect Author, speaker and trainer

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