In the competitive world of marketing, precision is key. It’s not enough to simply segment your audience; you must also predict their behavior to maximize your return on investment (ROI). One effective approach to achieve this is joint segmentation, where we combine segmentation with predictive analytics to identify the most promising prospects and direct our marketing efforts accordingly. This blog post will walk you through an example of joint segmentation, showcasing how to calculate the likelihood of purchase, expected return, and direct email marketing campaigns based on profitability.

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Joint Segmentation Example

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Step 1: Initial Segmentation and Email Campaign

Let’s start with a hypothetical scenario. Imagine you’re a retailer launching a new product. Your first step is to segment your customer base using demographic, behavioral, and psychographic data. Once segmented, you identify a test sample within each segment to send an initial promotional email.

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Step 2: Observing and Collecting Data

After sending out the promotional emails, you observe which customers make a purchase and how much they spend. This purchase data is critical as it helps refine your understanding of each segment's purchasing behavior.

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Step 3: Integrating Data and Predictive Modeling

Using the data collected from the test sample, you integrate it with other available information, such as historical purchase data, website activity, and customer demographics. This combined data set is then used to build a predictive model.

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Step 4: Calculating Purchase Probability and Expected Return

The predictive model helps calculate the likelihood of purchase for each customer in your broader database. Here’s how you can approach it:

1. Likelihood of Purchase: Based on the observed behaviors and integrated data, the model assigns a probability score to each customer, indicating their likelihood of making a purchase if targeted with the promotional email.
2. Expected Return: For each customer, calculate the expected return by multiplying the probability of purchase by the average purchase value observed in the test sample.

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Formula: Expected Return=Probability of Purchase × Average Purchase Value

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Step 5: Assessing Profitability and Directing the Campaign

Next, calculate the expected profitability for each customer by subtracting the cost of reaching out (e.g., email marketing cost) from the expected return.

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Formula: Expected Profitability=Expected Return−Cost of Reaching Out

Finally, direct your email marketing campaign towards those customers whose expected profitability exceeds the cost of reaching out. This ensures that your marketing resources are used efficiently, targeting only those segments most likely to generate a positive ROI.

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Example in Practice

Scenario: You’ve segmented your customer base and sent a promotional email to a test sample of 1'000 customers.

• Observation: 200 customers made a purchase, spending an average of $50 each.
• Cost: The cost of sending each email is $0.10.

Predictive Model Outputs:

• Customer A: Probability of Purchase = 0.30, Average Purchase Value = $50
• Customer B: Probability of Purchase = 0.10, Average Purchase Value = $50

Calculations:

• Customer A:
  • Expected Return: 0.30×50=$150
  • Expected Profitability: 15−0.10=$14.90
• Customer B:
  • Expected Return: 0.10×50=$50
  • Expected Profitability: 5−0.10=$4.90

Decision: Based on these calculations, you would prioritize sending emails to Customer A, whose expected profitability significantly exceeds the cost of reaching out, ensuring a higher likelihood of a positive ROI.

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Conclusion

Joint segmentation and predictive analytics offer a powerful approach to refining your marketing efforts. By combining segmentation with predictive modeling, you can identify the most promising customers, accurately forecast expected returns, and ensure that your marketing campaigns are both cost-effective and impactful.

Ready to take your marketing strategy to the next level? Contact us to learn how our joint segmentation and predictive analytics solutions can help you achieve greater profitability and efficiency in your campaigns.

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