Customer Purchasing Behavior Analysis - (New Business Integration)

In this article. I have explained how to perform an analysis of customers buying behavior when business integration occurs.

Scenario. Lets consider Company A has been taken over by Company XZY. And Its been 6 months past from the time of integration. Now we would like to see the customer behavior analysis in purchasing perspective.

The following visualization shows how the customers AOV(Average order value) has been changed over a time.

In the below section I have explained the definitions of the dimensions and measures.

* First 3 orders AOV : Customers who have placed 3 orders in the first three months after the business commenced its operation.

* Last 3 order AOV : Last 3 orders of the customers who have placed 3 orders in the first three months after the integration was completed.

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We should read the data on the visualization as follows:

1. First 3 Orders AOV (0-1200₹) - Last 3 Orders AOV (0-1200₹)

82.33% of the customers who were ordering between 0-1200₹, falls under the same bucket for the last 3 orders value 0-1200₹. (The buying behavior of these customers is not changed).

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2. First 3 Orders AOV (0-1200₹) - Last 3 Orders AOV (1200-2400₹)

6.63% of the customers who were ordering between 0-1200₹, now they have moved to 1200-2400₹ AOV bucket.(The buying behavior of these customers has been increased and

now they will fall under 1200-2400₹ AOV bucket).

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3. First 3 Orders AOV (0-1200₹) - Last 3 Orders AOV (2400-3600₹)

4.5% of the customers who were ordering between 0-1200₹, now they have been moved to 2400-3600₹ AOV bucket. (The buying behavior of these customers has been increased and now they will fall under 2400-3600₹ AOV bucket).

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4. First 3 Orders AOV (0-1200₹) - Last 3 Orders AOV (3600₹ +)

6.54 % of the customers who were ordering between 0-1200₹, now they have been moved to 3600₹ + AOV bucket. (The buying behavior of these customers has been increased and now they will fall under 2400-3600₹ AOV bucket).

The reading of the data follows the same way for the rest of the First 3 orders value & Last 3 orders values.

2. Cross-tab members in percentage

3. Cross-tab members actual values.

This is one of the best way to perform the customers purchasing behavior. In the next articles, I will explain the required custom SQL query's with a sample data. And the data which I have presented above are assumed values.