Machine learning is the science of setting up computer programs to analyze information and making intelligent decisions like human beings.
Machine learning and artificial intelligence are being practically used in many forms by businesses all over the world, and that includes marketing and CRM. According to Gartner, humans will not be managing around 85% of customer interactions by 2020.
At SendPulse machine learning and AI are driving our success in maximizing open rates for our clients. We want all our clients emails to be at the top of their recipient’s email box every time. We use AI and Machine learning to drive this feature. You can learn more about this at Personalized Sending from SendPulse.
Machine learning and predictive analysis can be a game changer for email marketing. In a survey by YouAppi, 37% CMOs said that they are planning to invest in machine learning in 2017, more than any other option given in the survey.
Machine learning can use the data points and identify useful patterns in customer behavior. Businesses can use machine learning and artificial intelligence to automate email marketing.
Note that we are not talking about the typical autoresponders. These are highly relevant and personalized emails. Machine learning is an ongoing process and the best part is, computers can continuously learn and use new data to improve results.
Let us show you how machine learning can take your email marketing to the next level.
Send highly relevant emails:
In a study of 235 marketers by Adobe, 77% said that real-time personalization is very important for businesses. However, 60% were of the view that it’s not easy to personalize content.
It is not really possible to take various data points into account for hundreds of users and include personalized content in the emails. This is where machine learning can be of help. It can generate personalized emails with relevant content or offers on its own. Even better, you can teach it about different conversion goals and it will modify the content to suit conversion goal.
That is more powerful than segmentation because segmentation enables you to send personalized email to targeted groups, whereas machine learning enables you to send personalized email to individuals.
Amazon is a good example. They send customized emails with products and offers related to the categories that they have browsed in the past.
Send transactional emails that convert:
Transactional emails perform much better than any other type of email. According to Experian, they can generate 6 times more revenues and result in 8 times high open rates, compared to newsletters.
Take abandoned cart email as the example. A study by eMarketer suggests that the conversion rate is highest when abandoned cart email is dispatched within an hour. Machine learning can not only send an abandoned cart email almost instantaneously, it can also personalize content while keeping the recipient’s browsing history in view.
It works like a seasoned salesperson who knows how to deal with a customer who just walked in the store because he has the experience of dealing with similar customers in the past.
Automation has shown great results even without the power of machine learning. According to DMA, more than 75% of revenue comes from triggered emails. Imagine how much more powerful automation can be when coupled with machine learning?
81% of online customers are likely to make a purchase when they get an email based on previous shopping or browsing behavior, according to eMarketer.
Get real results:
Email marketers are usually stuck with vanity metrics like open rate or bounce rate, even though a high open rate cannot add anything to your bottom line. Machine learning can help you focus on real results like engagement rate and conversions.
An email marketing study by Experian suggests that personalization can increase open rate by 29% and clicks by 41%. As earlier explained, predictive analysis can help you create personalized emails, which are bound to get a high engagement rate.
Delivery time is another factor that affects engagement rate for email campaigns. A study by Adobe found that lots of users check emails while in bed (70%), when they are watching TV, and even when they are in the bathroom (57%).
Businesses usually try to optimize delivery time for entire segments or groups of subscribers. However, two persons from the same segment and identical demographics can have totally different habits or preferences when it comes to checking emails. Machine learning can take care of that. It can analyze the past behavior and find the ideal time to email a specific individual.
Machine learning technology was successful in predicting when and why a specific customer will get in touch. It made use of more than 7000 factors and customer behavior data to come up with 88% accurate predictions about the products that customers will be looking for in their next contact.
Businesses can use a similar technology to predict which product or offer will work well with a specific customer in the next email. That is how powerful machine learning or artificial intelligence can be for email marketers. The best thing is … it can improve on a constant basis.
Take this as an example: A report by EveryAction tells that nonprofit organizations lose around $15,000 in a year because 1 out of 8 emails ends up in spam. Machine learning can not only predict how likely a message is to end up in spam, it can also learn to create messages which are less likely to go in junk.
As you can see, the automation with machine learning does not start and stop at creating and sending emails. It continues to test, learn, and improve the messages for better results. This is something we could only associate with humans in the past. That is why Artificial Intelligence is predicted to replace 16% jobs by the end of this decade, according to Forrester.
SendPulse is one of the very few platforms that allow you to incorporate machine learning and predictive analysis into your marketing campaigns. Some of the salient features include automatic personalization, segmentation, and predictive analysis. You can take advantage of predictive analysis or machine learning for Push notifications and SMS marketing as well.