Lob Launches Confidence Score for Direct Mail Deliverability

Lob, a direct mail automation company, has released the Lob Confidence Score, a API feature that assesses mail deliverability.

Lob has delivered hundreds of millions of pieces of direct mail in 2020. This new functionality leverages Lob's mail tracking data to create a score between 0-100 that predicts the likelihood of delivery for each address, allowing businesses to increase their audience for direct mail campaigns without increasing return-to-senders.

Undeliverable mail costs companies $20 billion a year, according to U.S. Postal Service (USPS) data. Lob pairs USPS information with its own data from tracking and scanning successful mail deliveries. With the Lob Confidence Score, businesses can accept addresses that were previously returned as undeliverable.

Lob automates direct mail for more than 7,000 businesses. The company sends millions of pieces of direct mail per month and has processed billions of addresses through its Print & Mail and Address Verification APIs. One in four households in the U.S. has received mail generated through its platform. That mail tracking data feeds the Confidence Score algorithm to tell companies how deliverable that address is. With each piece of mail Lob sends and tracks, the machine learning algorithm improves the accuracy of the Confidence Score.

"This year has proven that mail still very much matters to Americans," said Harry Zhang, co-founder of Lob, in a statement. "Verifying addresses is a seemingly small step that makes a big difference in outcomes for consumers that need their mail and for businesses that are spending millions of dollars on undeliverable mail and packages. Our intuitive Confidence Score applies Lob's millions of pieces of data points from real-world mail delivery to help companies understand address quality rather than relying solely on postal data."

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