E-mail marketing is not dead. It’s on the upswing. A whopping 362 billion (yes, billion) e-mails are expected to be sent EVERY DAY in 2024.
But how do brands ensure the health of their e-mail marketing campaigns and ensure that their budgets are going toward those people not likely to simply dump your precious message into the trash bin (or, worse yet, report your company as a spammer)?
AtData, an email address intelligence provider, recently launched the AtData Quality Score. It helps marketers identify the most valuable email addresses for improved e-mail marketing campaign engagement, deliverability, response, and conversions.
The Quality Score was built via a proprietary machine-learning model that trains on the marketers’ list of top customers using billions of open, click, and web activity signals combined with demographics, purchase behavior, and spend propensity.
According to AtData, it goes beyond traditional RFM (recency, frequency, monetary value) analysis. The score uses those factors but then ranks an email on how well it fits the profile of a high-quality subscriber.
We had the privilege of speaking with AtData CEO Tom Burke about this new e-mail marketing tool.
Does the Quality Score work for both B2B and consumer lists.
“Yes, the AtData Quality Score was designed to work with any marketers’ customer lists. Using advanced AI and machine learning to assess the value of email addresses and the individuals behind them helps marketers identify the most promising contacts leading to more effective campaigns, better reach, and increased sales. In addition to helping retail and nonprofit marketers, the Quality Score is optimal for CRM and database managers as well as affiliate marketers and lead generators.”
Is it just called the Quality Score or does it have a clever name?
“It is called the AtData Quality Score. We recognize “quality” is in the eye of the beholder, but the power of this score is that it can be trained and tuned to identify contacts that look like your best customers.”
Does the Score vary based on product category?
“The Quality Score varies from company to company based on the marketers’ unique customers, the products they sell, and the activity and spending of the people being scored. For example, someone’s email may score high for a shoe retailer and score low for a fast-casual restaurant. Thanks to machine learning, the Quality Score evolves with new purchase and propensity data.”
How was it tested/proven effective?
“The Quality Score was born out of an evolution of our existing email address intelligence products, and it was beta tested with a cross section of select clients across several industries.”
If someone has a low Quality Score, does a MULO brand have any hope of ever converting them?
“Yes, there is, but it’s likely to take more effort. Leveraging AtData’s Quality Score helps identify and reach consumers who are more likely to respond or buy, leading to quicker results at less cost.”
Imagine a world where you’re only getting offers for things you might buy or use? We’re all looking forward to better-targeted messages in our inboxes! Just think of what you will do with all that extra time and mailbox space!
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