Newsletters play an integral role in keeping subscribers informed and connected to your brand and business. Done right, they can increase a subscriber’s interest in your brand. Done poorly, they can lead subscribers to loathe you pretty quickly.
One of the biggest challenges email marketers face is how to segment their newsletter sends so customers continue to open emails, keep buying and generally feel engaged. Here are a few methods you can test to optimise your newsletter program based on behavioural targeting:
Email opens are the first indicator you can draw on to identify that someone is engaged. However, instead of segmenting based only on who does and does not open your message, why not couple that with other behavioural data, such as time of day and subject line?
Time of Day and Day of Send
If you send one to two newsletters per week, and the content is consistent and not time-sensitive, consider testing your sending time to see if you get an uplift. Most ESPs nowadays have the capability to monitor when a subscriber specifically opens an email and can calculate the optimum time or day to send. If the majority of your base opens on a time or day different to your traditional send date, shouldn’t you make the necessary adjustments to give subscribers what they want?
In every marketing department across the world, there are endless discussions about what the subject line should be for the next newsletter. Rather than only finding the one that works best for the upcoming send, create a list of several subject lines that reflect the personality of your subscriber base. Some people like humour, others like facts, and still others prefer a question to pique their curiosity.
You’ve sent your newsletter two times per week for the last month, and you’ve noticed some people ordered and some didn’t. Furthermore, as with every send, some of your links received more clicks than others. How much more meaningful would this data be if you categorised each link and reviewed the results at the end of the month? You would be able to see which category links were most clicked on and how this influenced a purchase. Instead of sending a generic newsletter again, use this data to create segments and content based on specific links clicked. Perhaps you can include an incentive to subscribers who haven’t already purchased but expressed an interest in a particular category over the past four weeks.
You could even suppress purchasers of a particular category and introduce them to new ones. Or you could suppress them from receiving emails for the rest of the month as your objective to obtain a purchase has been met. The biggest advantage is you can use this information to create real-time preferences based on a recent engagement with your subscribers, as opposed to relying on static and sometimes out-of-date preferences that no longer reflect the true range and depth of your content. A click is a much stronger and more accurate indicator of a subscriber’s interest level.
If you know a subscriber’s purchasing history, you can use this to personalise the content of your newsletter based on average order value (AOV) or purchase frequency. For AOV, showcase products within categories recently purchased that are in the subscriber’s average order spend. For frequency, let’s assume the customer received the post-purchase series but didn’t buy the recommended upsell. Create a newsletter series that introduces them to another category that’s complementary to the product recently purchased. Start off with information and problem-solving tips, then refine with specific products and an offer.
It’s essential to utilise the data and information you glean from your previous sends to make future sends more meaningful. How would your subscribers respond if you sent them an email with their preferred subject line, on a time and day they like to read, filled with relevant content based on their previous click and purchase history? I would certainly be more likely to respond, wouldn’t you?