It’s hard to believe that email has been around for 45 years. Most marketers today have never lived in a world without email.
Yet despite being woven into the fabric of everyday life and business for so many of us for so long, the email user experience has evolved little since the first message was sent in 1971.
Sure, we can now access email on more devices, pretty much anytime anywhere, but the basic process hasn’t changed. The sender hits send at an arbitrary time, the message goes to an inbox and waits for the receiver to open it, hopefully before deleting it.
Periodically through the years, pundits have predicted email’s disappearance, replaced by newer and cooler messaging apps. But like Mark Twain, reports of email’s death have been greatly exaggerated. It remains an important and oft-used line of communication between businesses and customers – no longer the only one, for sure, but a critical part of the mix.
Roughly 100 billion business emails are sent every day, and the number of business email accounts is expected to grow to 4.9 billion by the end of this year. Email remains especially popular in B2B, as it allows for longer and deeper communication when compared to social media and other forms of messaging. In fact, B2B marketers say email marketing is 40 times more effective than social media in generating leads
Not only isn’t email going away anytime soon, but the future looks bright, thanks to artificial intelligence technology that is poised to re-vitalize the email experience. By analyzing recipients’ behavior patterns in opening, deleting and acting on emails, AI can help marketers tailor their email outreach to customers’ and prospects’ specific preferences.
Until now, much marketing innovation around email has centered on content. There’s an entire industry dedicated to helping create the most relevant email message to solicit a response and action. Other innovations have focused on lists. Sourcing lists. Growing lists. List hygiene.
All of that is important, but understanding when and why recipients open emails has remained largely a mystery – and it is an important one to solve. Send too much, and you risk annoying customers. Don’t send enough of the right type of email – at the right time – and you risk getting lost in an increasingly crowded fight for inbox real estate.
While marketers have taken painstaking effort to personalize content, attention on customizing the delivery process has been sparse. Until now, marketers have timed mass email distribution through intuition or vague evidence collected from large groups and analyzed manually. In addition to guestimating when emails are likely to be read, this back-of-the-napkin analysis doesn’t truly address when people are more prone to respond and take action.
To win, marketers will increasingly be required to personalize the delivery of email-based marketing messages just as they have personalized the content of those messages. Thanks to advances in AI and machine learning, this type of delivery personalization is becoming a reality.
The technology is emerging to help marketers predict the best time to send a message. For example, systems can learn that Sean is more prone to read and take action on new emails at 5:45 PM while on the commuter train home. Trey on the other hand often reads his email before bed at 11 PM but never takes action until sitting at his desk the next morning.
Machine learning systems can detect email optimizations patterns, remember them and optimize schedules to deliver messages to the top of the inbox during the optimal engagement window.
As marketers, we also appreciate that prospects have a growing list of preferred communications channels. Text message. Social media messaging platforms. Push notifications to a mobile app.
Soon, the machine learning systems optimized for email delivery preferences can learn the preferred channels to deliver messages. The right content, delivered at the right time, through a time-specific preferred channel.
Every interaction you have with customers matters. Every interaction you have with customers is an opportunity to incorporate feedback that enhances their buying journey in new and different ways. Everyone has different buying patterns.
Traditionally, marketers have spent endless hours trying to map out linear buying journeys for large groups of customers and then poured cement over the process. Systems have no way to adapt to inevitable changes in individual buying patterns and can’t react to any environmental changes.
With email expected to remain a vital link between companies and customers, AI’s role in teaching a 45-year-old dog new tricks is a welcome development. Marketing automation systems must now think about every customer, every piece of content, and match them in real time to meet business goals. Smarter email delivery needs to be a crucial part of that.
