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Michael Epstein

Co-CEO of PostPilot

Channel-surfing: Finding the Right Avenues of Growth

From Postcards to Purchases: Direct Mail Attribution

From CMO, to PE/VC operating partner, to now Founder and Co-CEO of PostPilot, Michael’s experience in eCommerce is second to none. He’s led growth and turnarounds for over a dozen 8 & 9-figure DTC brands.

In This Article:

How do we know direct mail is actually working?

How can we attribute revenue to postcards, CardalogsTM, or catalogs?

Let’s discuss.

From Postcards to Purchases

The 101: Attributing Direct Mail

At baseline, direct mail attribution comes down to strong data.

You need to be able to tie approximate mail delivery dates with mail recipients’ purchases over a particular attribution window. If you’re able to map this out, you can get a general idea of how what you’ve sent influences buying behavior.

Whether you’re doing this manually or with a mail provider, it’s important to have access to your first-party purchase data via API (e.g., Shopify, SFCC, or BigC) and build a model based on a ~60 day timeframe.

Example of a Dr. Squatch postcard for retention. Note: QR and specific code not shown.

At PostPilot, we provide real-time attribution using these data points.

  • We know approximately when a customer receives a piece of mail.

  • Via our Shopify integration, we know when a customer who has received mail makes a purchase.

  • We typically evaluate campaigns over a 60-day attribution window. If the purchase occurs within 60 days, we attribute it to the mail.

The 201: Maximizing Success

To increase the true impact of this framework, we’re often targeting customers and prospects who are unlikely to engage via email or other channels.

For example, if a customer who has unsubscribed from your email/SMS receives a postcard and purchases 12 days later, it’s a safe assumption that the postcard drove the purchase.

Results from a campaign sent to a group of customers who had unsubscribed from owned channels.

We can be more certain the longer the customer has been unsubscribed and the longer it’s been since they’ve last purchased—due to the lack of exposure to the brand.

But why?

The 301: Why This Works

This is based on classic Recency segmentation (part of broader RF or RFM segmentation), which has been used since the 80s as a powerful predictor of customer behavior.

Recency since last purchase has been shown to be the #1 predictor of subsequent purchases. The longer it’s been since a customer has purchased, the less likely they are to purchase.

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