Posted by Chris Donald On December 19, 2017 in story time I 0 Comments
One-size-fits-all emails do not work (well) anymore. Each business is different. As email marketers, you need to use the abundance of data at your fingertips in the right way—namely by leveraging said data to provide a 1:1 experience for your subscribers. The word you’re looking for here is “Personalization.”
Personalization in email marketing is about sending authentic, relevant and targeted content to the right subscriber group at the right time.
Here are some effective personalization tactics you can include in your email marketing strategy to get better results out of your campaigns:
Subscribers who opt-in for your brand’s emails join for different reasons. They may be looking for coupons or discounts, information about their products, or products/services for loved ones and friends.
For example, if you are an e-commerce fashion site, your customers and subscribers will be both male and female, different ages, and yet search for different items. If you send an email about women’s apparel to subscribers who aren’t seeking those items, you may turn them off to your brand.
Don’t be afraid to ask your subscribers about what they’re looking for—or better yet, WHO they’re looking for. After all, using our fashion example, you may have male subscribers who aren’t shopping for themselves. With that information, you can send more targeted and relevant emails.
Once you gather the information, you need to group similar subscribers together according to their personas. According to Ascend2, 51% of marketers say that email list segmentation is the most effective personalization tactic. Segment your email lists according to demographics, psychographics, interests, browse and purchase history, and other behavioral data. From here, you can then create targeted content for each segment.
Your subject line is the second most prominent of your email in the inbox—aside from the From Name. Personalized subject lines increase email open rates by 26%. Experian research shows that brands that include personalized subject lines in emails witness 11% higher click-to-open rates and 27% higher unique click-rates.
Triggered emails tend to have higher open rates than non-triggered emails. Such triggered emails can be sent to customers for multiple actions such as re-engagement, up-selling, cross-selling, etc. Here are a few examples:
This email from Human shows the user’s weekly activity on their application. With first name personalization and real-time tracking, the email gives a detailed report of the user’s daily walking activity.
Here’s one from Grammarly.
Grammarly uses machine learning to keep track of each individual user’s activity on their site. This email shows a yearly summary of the total number of words written and the accuracy of the subscriber.
You can utilize Artificial Intelligence and Machine Learning to rapidly find content that is most likely to drive conversions for each individual subscriber. Machine learning helps your system find out what resonates best with specific users and can be helpful in creating subject lines, email copy and CTAs that are optimized for each user.
Another great to send relevant, targeted content is deliver product recommendations based on prior engagement with your brand. You can track subscribers’ purchase and browsing history and map them with their interests to select recommended products for them. Check out this email example from END.
Going a step further, you can fully deliver personalized content through the use of dynamic content. Combining the concepts of machine learning, browse and purchase history, etc., brands can deliver dynamically changing content in emails to make them more relevant. For example, showing subscribers some items related to the ones in their cart can be a great tactic to entice them to buy the recommended products too. Check out this email from Adidas that makes use of dynamic content for emails to be sent to men and women.
Email send time is critical—yet sometimes overlooked—aspect of email marketing. Easier said than done, you need to send emails at times when your customers are most likely to open. Using machine learning, your system can learn when each individual recipient is most likely to open an email. Use this data to optimize your email delivery time for each subscriber. (Note: If you don’t have machine learning, simply do test groups at different times of day and see what times work best for your audience.)
Great use of personalization in your email marketing campaigns can get your customers more engaged with your brand. Collect the right data and leverage it in the right manner to improve your email marketing program.