Email Open Rates: Leveraging Personalization to Be Ever in Your Favor
Over fifty percent of consumers say they delete at least half of all brand marketing emails in their inboxes without ever opening them. Even if they don’t delete the email, there is no promise consumers will open it. Thus, low email open rates. I’ll bet most inboxes look something like this:
The email that doesn’t go to the primary inbox is not SPAM. The vast majority of that is caught by ISPs, but the tremendous volumes of email looking to reach individual consumers are what is making marketers’ jobs infinitely more challenging; a challenge marketers bring upon themselves.
The stakes are high. Email offers significant ROI, so more emails are sent in order to tap into the potential revenue gains. But with primary inbox placement is tied to multiple factors, including Email Engagement. Email deliverability experts consistently point to the relevancy of message as a key to increasing placement.
So by focusing on email open rates, a marketer could stand to increase overall email performance more effectively. The challenge is that most strategies for improving email performance are tied to email conversion. To solve that, here’s a primer on tactics that can help boost opens.
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Go Beyond “Dear [First Name]” in Subject Lines
Consumers today expect Personalized Service and Communication that reflects their interest and behavior.
To build engagement with and earn revenue from individual customers, email marketers must personalize in two distinct ways: Leveraging information about a customer’s prior behavior and incorporating unique interest profiles created for each customer. Personalized subject lines that include a consumer’s name, products they specifically are interested in, or products they are individually predicted to purchase can materially improve email open rates and email revenue.
Using simple field insertion for a customer’s name can increase email open rates by upwards of 18% while using a personalized product recommendation in a subject line can increase email open rates by 41%. There is significant downstream impact as well with personalized product recommendations in subject lines boosting purchase conversion rates by 188%.
Take a look at online retailer JustFab, for example. Personalization is baked into the brand’s DNA. This billion-dollar retailer uses Machine Learning to look at each customer’s unique interests to serve email subject lines (and email content) leading with the product category and product style each individual customer prefers.
Example: JustFab customer Samantha from New Jersey will buy any handbag animal print, and Indira from California loves wedge heels. JustFab’s unique user profiles allow the retailer to send an email that leads with a hook that speaks directly to each customer’s specific and personal interest. In this case, Samantha might receive a subject line that says “Bags and more in prints that roar” and Indira would be served with “Wedges and more in prints that roar.”
With this approach, JustFab increased email revenue by 19%.
Personalize Email Send Time
Your friends know when to – and not to – reach out. I’m an early riser and early-to-bed kinda guy. So, anyone who messages me after 9 pm will not get a response until the following morning. My good friends know this, so they simply don’t reach out.
Brands should – and can – do the same.
Even when I’m up at 5 am, I will not check my personal email to see what’s on sale for the day. I’m most likely to do that at 2 pm when I take an afternoon coffee break. There are few brands that respond to this signal by sending me an email in the early afternoon rather than at the crack of dawn. The emails at the top of my inbox at 2 pm are far more likely to open than the ones 100 spots down on the list.
Business Insider and JustFab are two brands that personal email sends time in this way. By using historical open data, the brands can automatically deploy email messages at the ideal time of day for their individual consumers. For JustFab this approach increased email revenue from top customers by six percent and 41 percent from new subscribers.
Trigger Based on Predictions
77 percent of Email Marketing ROI is generated from targeted, triggered messages. Welcome series, post-purchase series, abandonment series, subscription renewals, and other transactional are powerful messages when consumers are highly engaged.
But, trigger messaging is reactive – triggers by a specific behavior. By integrating predictive analytics into campaign management, brands can further increase the ROI of triggers by pre-empting action.
Rather than waiting for a purchase to take place, predict when a customer will purchase? how much she will spend? and what she will specifically buy? And then deploy a pre-purchase series that guides her to make the purchase. Follow that up with your traditional post-purchase series.
Instead of waiting for an audience member to disengage, predict if he disengages in the next 30 days and sends a re-engagement message before he’s not even paying attention to your Email Marketing.
By implementing tools like Artificial Intelligence and Predictive Analytics, marketers can take this valuable insight and leverage it to better connect with prospects in ways that prove to work for each unique, individual customer. Subject line content, send time, and purpose of the campaign offer opportunities for increasing email revenue while appealing directly to customers.
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