Turn Data Into Email EngagementApril 14, 2014 By Erik Severinghaus
As mobile continues taking over consumers' screen time, marketers are forced to adjust how they send marketing email. Constant connection, lack of attention and increasing expectations for responsive design are just a few of the hurdles marketers must overcome to satisfy customers' demands.
But to rank best in class, you have to take it a step further and create personalized customer experiences across all marketing channels, and email in particular. In fact, according to SimpleRelevance's recent study, customers open their email up to 23 out of 24 hours a day, but only click through during one specific "magic hour" each day. That hour varies by men and women, income level, education level, job status and other customer attributes, making it increasingly difficult to lump groups of email recipients into vague segments.
Replacing the days of batch and blast with one-to-one personalized messaging has proven to be the answer for customers' always-on way of life. Using demographic, social, psychographic, transactional and on-site behavioral data, marketers can provide unique, end-to-end experiences.
Small Data, Big Opportunity
Marketers have been deluged with data from every platform, in every form, but generally in silos. Now partnerships, integration capabilities and consolidation of marketing technology companies overall has given marketing officers more visibility into their data.
Rather than spend the time pouring over mounds of data sets looking for a needle in a haystack, you can leverage data reporting companies to see which customer attributes matter most to your bottom line and hone in on them. Or on the flip side, you can see which customers they have the least amount of data on and append third-party information to create more robust profiles. Either way, you are more empowered to focus on the customers who will add the most incremental revenue to now and in the future.
Don't Guess, Predict
It doesn't stop at knowing which customer data points to analyze. Marketers then have to apply the data for their email marketing needs. In the same study, men were more likely to click through an email in the early morning hours, while women lagged a few hours behind.
Should you segment based on location, gender, income or family construct? One, two or three variables? There is no need to decide which attribute is most important for every campaign sent. Rather than segmenting based on just a few categories, there are predictive analytics tools that pull in customer data from several different sources creating comprehensive customer profiles. Then they plug in to an email service provider filling in the gaps for best time to send, best performing subject line, most enticing call to action or deal offer, and so on, taking the guesswork out of email programs.