Background: 

A company serving customers in over 160 countries through their eCommerce business had recently surpassed 1,000,000 client interactions. It needed help understanding who was buying what, what was driving their behaviour, and if there were patterns that could be used to refine their business and marketing efforts. Our team worked directly with the CEO and VP marketing.

Challenge:

The challenge was to make sense of the vast data provided and turn it into useful insight.

The Approach:

Advanced Analytics and Research Lab performed a customer behavior analysis using a clustering algorithm to segment customers by purchasing recency, frequency, and monetary value of each transaction. From this, distinct customer segments could be derived based on lifetime value of repeat purchases, purchase size, churn, cost of acquisition and cost to serve. The next step was to calculate the total value and profitability of the different behavioural segments.

Lastly, a multivariate regression technique was used to further identify the most profitable behavioural segments by country and industry.

Results:

The client was able to use this information to optimize marketing spend by being able to identify unique strategies for each customer group. Further, the client was able to concentrate on the most profitable customer segments in each geographic and industry segment  based on their buying behavior.