Email marketing isn't dead. It is on an upward trend. By 2024, 362 billion (yes, one billion) emails are expected to be sent every day.
But how can brands ensure the health of their email marketing campaigns and prevent people who are unlikely to simply trash your valuable messages (or worse, report your company as a spammer)? Will we ensure that the budget is allocated to the budget?
AtData, an email address intelligence provider, recently launched AtData Quality Score. This helps marketers identify the most valuable email addresses to improve engagement, deliverability, response, and conversion of email marketing campaigns.
Quality Score is built by a proprietary machine learning model that uses billions of open, click, and web activity signals combined with demographics, purchase behaviors, and spending habits to train a list of marketers' top customers. I did.
According to AtData, this goes beyond traditional RFM (recency, frequency, monetary) analysis. The score uses these factors, but it also ranks emails by how well they fit the profile of a high-quality subscriber.
I had the pleasure of speaking with Tom Burke, CEO of AtData, about this new email marketing tool.
Does Quality Score work for both B2B and consumer lists?
“Yes, AtData Quality Score is designed to work with any marketer's customer list. Using advanced AI and machine learning to assess the value of email addresses and the individuals behind them. Quality Score helps marketers identify the most promising contacts, leading to more effective campaigns, better reach, and increased sales. It’s great for CRM managers, database managers, affiliate marketers and lead generators.”
Is it just called Quality Score or does it have a fancy name?
“This is called the AtData Quality Score. We recognize that 'quality' is in the eye of the beholder, but the power of this score is to identify contacts who are likely to be your best customers. It is something that can be trained and adjusted. ”
Do scores vary by product category?
“Quality scores vary from company to company based on the marketer's unique customers, the products they sell, and the activities and spending of the people being scored. For example, a person's email may have a higher score than a shoe retailer's fast-casual restaurants may receive lower scores. Thanks to machine learning, quality scores evolve with new purchase and trend data.”
How was effectiveness tested/proven?
“Quality Score was born out of an evolution of our existing email address intelligence product and was beta tested across a selection of clients across several industries.”
If someone has a low quality score, is the MULO brand likely to convert them?
“Yes, it does, but it may require more effort. By leveraging AtData's Quality Score, you can identify and reach consumers who are more likely to respond or purchase. It leads to faster results at a lower cost.”
Imagine a world where you are only offered things that you would buy or use. We all look forward to better targeted messages arriving in our inboxes. Think about what you'll do with the extra time and mailbox space.
