How to create Measures using Dynamics 365 Customer Insights

October 13, 2020October 16, 2020 Virendra Agrawal6 Comments

In my previous post, we talked about ingesting the data from various sources with the help of different Dynamics Power Query Connectors and use this data to perform unification in Customer Insights and build a unique customer profile (Part 1 and Part 2).

In continuation of the previous posts, let’s see how we can ingest the purchase (eCommerce or POS) data associated with these unique customer profiles to build various measures in Customer Insights.

Before we begin, let’s understand what measures are and how these are useful.

How to create a unified profile (Golden Customer Record) using Dynamics 365 Customer Insights – Part 2

September 3, 2020October 16, 2020 Virendra Agrawal3 Comments

Previously (Part 1), we learned about how we could ingest the data from various sources with the help of different Dynamics Power Query Connectors.

Now, let’s talk about how we could use this data to perform unification in Customer Insights and build a unique customer profile.

Prerequisites:

Customer Insights would require data from at least two data sources to perform the unification. So we’ll need to have the following:

Dynamics 365 Customer Insight Instance;
At least two data sources (we’ll use Dynamics 365 CE for Contact entity and Online Customers from Azure Blob Storage)

How to create a unified profile (Golden Customer Record) using Dynamics 365 Customer Insights – Part 1

September 3, 2020October 16, 2020 Virendra Agrawal6 Comments

I recently had an opportunity to work on Dynamics 365 Customer Insights for a retail client who was envisioning to consolidate their customer’s information to achieve a true customer 360-degree view.

The main objective was to remove the silos of data that represents customer purchases, payments, website visits, marketing & social interactions and customer service requests.

With it’s pre-built AI model, Customer Insights was able to help with ingesting massive amounts of data from separate systems and leverage matching strategies to build a unique profile and showcase customer’s total lifetime value, churn risk, and more.