9-Figure Women’s Apparel Brand Uses AcquisitionAI For Best-in-Class Direct Mail Prospecting

The largest and fastest growing brands are always looking to diversify their acquisition channels. It’s simply too expensive and risky to fully rely on digital prospecting to hit net new acquisition targets, especially during peak periods like BFCM. And the brands that hit scale look at their marketing holistically, with multiple touchpoints that compound to lift all channels.

Enter: prospecting with direct mail. 

Although we officially launched our prospecting feature, AcquisitionAI, to the world in September 2024, a number of brands served as early beta testers, including a 9-figure women’s apparel brand.

In testing AcquisitionAI, their team sought to answer two questions:

  1. Will prospecting with direct mail work?
  2. Will AcquisitionAI-built lists yield better results than lists provided by the leading third-party data provider? 

The answer to both? Read on to find out. 

The Test Process

Beyond simply proving that prospecting with direct mail worked for this brand, we wanted to prove that AcquisitionAI could beat the leading third-party data provider. So, we split tested a list built by the data provider alongside proprietary PostPilot models, which excluded the retailer’s active customers. 

First, we had the data provider model the brand’s best customers and provide a list of prospects. 

Simultaneously, we used AcquisitionAI to analyze the same customers and build four lookalike models. AcquisitionAI analyzed thousands of specific attributes about the retailer’s VIP customer base, but some high-level attribute categories included:

  • Gender
  • Age range
  • Location
  • Household income
  • Family size
  • Hobbies + interests
  • Purchasing behavior (online and in IRL mass retail) 

Then, our in-house creative team designed postcards for the brand’s approval. 

Once their team approved the postcards, we printed and mailed them via our in-house facilities. In total, we printed and mailed 60k postcards, which included both the data provider’s list and AcquisitionAI’s lists. 

Results + Discussion

The Results

Out of the 60k recipients, 20k were generated by the data provider, and the rest were generated by AcquisitionAI via four models. All postcards were mailed simultaneously.

The numbers:

  • Data Provider: 0.89% CVR
  • AcquisitionAI Model 1: 0.95% CVR
  • AcquisitionAI Model 2: 3.64% CVR
  • AcquisitionAI Model 3: 1.79% CVR
  • AcquisitionAI Model 4: 1.65% CVR

Overall, the AcquisitionAI-built models outperformed the data provider-built model by 124%. 

Discussion

By itself, the 124% is a phenomenal result and an exciting win, but it’s even more exciting for a couple main reasons:

  • This test used postcards. For prospecting, postcards typically do not perform quite as well as larger mailers like catalogs. Catalogs offer vastly more room for merchandising features and to tell your brand’s story, so more customers tend to convert after receiving them.
  • This was a first test. AcquisitionAI learns from and improves with every send. These results were incredibly strong despite it being the first campaign.

Additionally as we tracked the results in real time, we found that conversion volume on the retailer’s campaign was actually accelerating at the 30-day mark and was still driving conversions after 60+ days.

In other words, the postcards had staying power in homes. 

Based on our other research and experience, many people tend to keep mailers for weeks, usually keeping them on tables, desks, and even on their refrigerators—it’s like having an IRL prospecting ad that keeps running, for less than the cost of a click. 

The bottom line? AcquisitionAI has started out strong, and it will get stronger. 

More results coming soon.

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