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How does predictive analytics enhance email personalization?

How Does Predictive Analytics Enhance Email Personalization?

Email marketing continues to be an essential and effective business communication channel. However, traditional email marketing often overlooks the potential contained within data. To improve, marketers must rely on more than just the brute force of segmentation and A/B testing. They must become better readers of their data and understand what their data tells them about their customers’ past and future behavior and preferences. In short, marketers must leverage the insights gleaned from data to make emails better in every way that counts—from making them more relevant, to making them more likely to engage the reader.

Understanding Predictive Analytics in Email Marketing

Using historical data, algorithms, and machine learning methods to predict future events is what we call predictive analytics. In the world of email marketing, this means companies are not just looking at who opened or clicked on an email but are digging deeper and using all available intelligence to enrich these surface-level metrics.

Their goal is to get a better understanding of not only the email as a touchpoint in their customer journey but also the customer itself. Who is this person? What do they want? When do they want it? Why do they want it? These are the kinds of questions top-performing companies are now trying to answer.

A recent study by HubSpot, for instance, found that personalized emails result in six times higher transaction rates. This stat underscores the not-so-hidden role of predictive analytics in making email engagement better. With consumer data in hand, businesses can do some pretty nifty audience segmentation, making damn sure that the marketing itself is truly focused on the right individual.

How Does Predictive Analytics Enhance Email Personalization?

Email personalization is mainly enhanced by predictive analytics, and one of the main reasons for this is advanced segmentation. Companies can now segment their audiences in very sophisticated ways. They not only take into account the traditional dimensions of segmentation—like demographics and geography—but also use a host of new data to arrive at much better segmentation decisions. For example, a company might segment its audience based on a set of predefined behaviors.

In addition, predictive analytics can enhance the timing of email campaigns. By determining when a customer is most likely to open an email, a business can communicate with that customer at the optimal time. According to Campaign Monitor, an email service provider, the right message sent at the right moment can see a 22 percent higher open rate than a message sent at any random time. And better email open rates can lead to better conversion rates, too.

Implementing Predictive Analytics for Better Email Campaigns

Integrating strong data collection systems is the first step in using predictive analytics to its full potential. The collected data should encompass:

Data pertaining to the demographic features
History of browsing
Payment records
Metrics related to how engaged a recipient is with an email (open rates, click rates, etc.)

Moreover, companies must allocate resources toward appropriate tools and technology. Investments in solution spaces such as CRM systems, marketing automation platforms, and predictive analytics software can yield dividends in the form of real-time insights. Consider, for example, using Salesforce Einstein or Google Analytics to help your marketers interpret the data you’re gathering. These tools will allow them to make informed decisions based on what your customers are actually doing.

Real-World Examples of Success Through Predictive Analytics

Numerous businesses have effectively applied predictive analytics to improve their email personalization techniques. For example, Netflix employs highly developed algorithms to notate recommendations of kinds of shows to certain kinds of viewers. The notations made by these algorithms push the user further down the engagement funnel and increase the user’s loyalty, as the user receives nudges toward content in line with their preferences.

A different instance is Amazon, which uses predictive analytics to make its email marketing more personal. When we receive an email from Amazon, it is based on our history of purchases and our behavior while browsing the site. The email itself is not the recommendation. The recommendation happens at the moment the email is received, and it is more curated and personalized than anything you could find in a store. This is in part why Amazon’s sales figures are extraordinary. More than 35% of their revenue comes from personalized recommendations.

The Future of Email Personalization with Predictive Analytics

The technology behind predictive analytics is evolving fast, and companies can expect even bigger gains in the personalization of email as a result. Email has the potential to be an incredibly personalized medium, and with the advancements mentioned earlier—like machine learning and natural language processing—businesses are diving deeper into their data and coming up with even sharper, more sophisticated segmentation and targeting strategies.

The use of artificial intelligence (AI) in predictive analytics is transforming how businesses approach email marketing. It is helping marketers to identify complex patterns in large datasets and understand customer behavior like never before. And this is enabling them to deliver hyper-personalized content that resonates with their audience.

To wrap it up, grasping how predictive analytics amps up email personalization is vital for today’s marketers. By utilizing not just good old historical data but also the latest in what’s hot and happening jumbo tech, businesses now have the means to craft very much on-point targeted email campaigns that, if you squint and look at them from a certain angle, kind of resemble the good old days when you could still get away with just using your brain.

Conclusion

Email marketing is most effective when it delivers the right message to the right person at the right time. For this reason, many small and large businesses alike have turned to predictive analytics. These technologies help us understand not only what our customers are doing but also why they are doing it. When we factor in the newfound knowledge of our customers (and their predilections) into our email marketing campaigns, we are pretty much guaranteed a leg up on the competition—nothing our competitors can do will eclipse the intimacy we now share with our customers.