Category Development and Future Value meet up in a typical Marketing Budget Experiments project.
I commonly develop twelve-month future demand projections for customers with varying attributes in a first purchase. I build a Logistic Regression model to predict how likely a first-time buyer is to purchase again next year ... and I build an Ordinary Least Squares Regression model to predict how much a first-time buyer will spend in the next year if the customer repurchases. Coefficients from both models are input into a spreadsheet so I can experiment with various customer attributes.
Essentially, I have a series of predictive inputs ... AOV on a first order, items purchased on a first order, share of demand from new items, share of demand from items selling below their historical average price point, month of first purchase are all included on the left side of the image above. The middle set of coefficients represent different merchandise categories that the customer could purchase from. The right-side set of coefficients represent different marketing channels that the customer purchased from in a first order.
So, this customer spent $100 on three items, buying only existing items at/above the historical price point of the items purchased. The order was in August, the customer bought from Category 19, and the customer bought from Marketing Channel 4 (which in this case was email marketing).
- 43.9% chance of buying again next year.
- $185.08 spent if the customer buys again during the next year.
- $81.18 future demand value.
The data is only useful if we compare the customer to another customer, correct?
Let's say that the attributes are identical, but instead of the customer being acquired in August the customer is acquired in December. Does the story change?
- 42.1% chance of buying again next year.
- $153.99 spent if the customer buys again during the next year.
- $64.90 future demand value.
Acquire a customer in August and get $81.18 in future demand value.
Acquire a comparable customer in December and get $64.90 in future demand value.
The foundation of Marketing Budget Experiments is this work ... we first need to understand how valuable different customers are. Once we understand how valuable the customers are, we can simulate five-year customer value and determine the optimal monthly marketing spend to achieve our business goals. And yes, Category Development plays a key role here ... we'll see later this week how important different Categories are to building high-value customers.
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