How AI-Driven Predictive Analytics Can Improve Email Conversion Rates

For years, email marketing reigned as the primary form of digital engagement, but as people live in a world where an overwhelming inbox has become a standard practice, it's clear new opportunities are needed to foster increased conversion rates. That's where AI-based predictive analytics comes in to change the game when it comes to email marketing. With the integration of real-time data, behavioral analytics, and machine learning, email marketing becomes an incredibly more pleasurable experience.

Gone are the days of having to project what someone might do days later in response to an email; now, it's possible to tailor messages upon receipt and send emails precisely when someone needs to see them. Thanks to predictive analytics, companies have the opportunity to project consumer intent and levels of engagement to effectively pinpoint email campaigns for new levels of conversion opportunity. This means everything from personalized subject lines to individualized CTAs (calls-to-action) are now possible with the hope of increasing click-throughs, purchases, and brand loyalty.

Understanding Predictive Analytics in Email Marketing
Predictive analytics is the capability of email marketing software, enhanced by AI, to analyze previous data and trends to forecast and project future behavior. For instance, if a given message was opened last quarter, there is a greater chance it will be opened this quarter, and AI will advise how to best apply marketing techniques to accommodate that projected behavior. However, even the most accurately targeted email is useless if it doesn’t reach the inbox. How to test email deliverability effectively becomes a crucial step to ensure that these predictive strategies are actually seen by the intended recipients.

Therefore, marketers can use predictive analytics to suggest a marketing blowout one day early for a projected purchase reminder or adjust sending times based on past opening patterns. For example, if someone opens every marketing email at 8 a.m. every day, that will be suggested as the time for future sends.

Optimizing Subject Lines and Content with AI Predictions
The first way to increase email conversion is to ensure that customers open the emails in the first place. AI predictive analytics can enhance subject lines by reviewing past engagement trends and determining which styles, tones, and vocabularies achieve the highest open rates.

For example, if one brand's audience responds more positively toward suspenseful subject lines, suggesting that there will be a reveal at a future date, than not, AI will suggest those kinds of subject lines for future emails. If, however, a segment of the audience only opens emails with limited-time offers, AI will suggest the second email should be a one-day flash sale.

In addition, if AI can predict what kind of body message per recipient each desires, it can help tailor that message on a person-by-person basis. For example, if a person opens all emails about a new puppy but clicks through on all links about training, AI may surmise that they prefer educational-based messages over descriptions for pet product messages and suggest a body for the next email accordingly.

Personalizing Offers Based on Predictive Analytics
Predictive analytics facilitates hyper-personalized email content. By using data such as user activity and purchase history, companies can determine what content will be best sent. Where previously companies would send out an email blast of seasonal discounts to every customer, now they can use AI to determine what discount should be sent to which specific customer.

For instance, a clothing e-commerce website could see from a customer's activities that they've viewed jackets for several weeks without putting them in their cart or purchasing them. AI might reveal that sending a 20% off coupon through email is more likely to result in a sale than a 20% coupon through email that pertains to shirts, which the customer never views.

For example, business-based subscription services can predict when a customer will need a renewal and send targeted communications as follow-ups with discounts to attempt to retain the subscription. Using predictive analytics gets rid of the one-size-fits-all marketing approach and instead generates hyper-targeted communications that are likelier to succeed.

Predicting the Best Send Times for Maximum Engagement
If there's one thing that makes emails successful, it's timing. And with the aid of AI-based predictive analytics, companies can send emails exactly when recipients are poised to read them. Some strategies indicate sending emails during working hours or only on Tuesdays and Thursdays (to avoid weekend deletions), but AI studies how each person interacts with email and when correspondence should be sent.

This doesn't mean that a cohort of customers will open their emails at 10 p.m. every night and another cohort at 5 a.m. AI won't take that into consideration. Instead, one group may get the 10 p.m. email and the other get the same message at 5 a.m. The difference is that instead of sending both groups the same email at one specified time, the AI auto-sends at the time most appropriate to each person's behavior patterns.

When companies can anticipate when to send an email, they'll ensure that their correspondence floats to the top of the recipient's inbox when they're most active, and it will lead to better open rates and greater conversions.

Reducing Churn and Re-Engaging Inactive Subscribers
It's not only conversions that predictive analytics can improve. Predictive analytics can reduce churn, too. For example, AI can flag customers who are at risk for churning based on their engagement with email. If someone stops opening emails or fails to engage with content, using predictive analytics can formulate re-engagement blasts that provide this person with something on the line.

For example, someone who frequently books vacations through a travel agency may not open a travel newsletter for a few months. However, predictive analytics may say that sending this person a specific blast with a tailored coupon to places they've previously visited may encourage them to re-engage. An e-commerce company might do the same with AI assessing what types of coupons are likely to re-engage subscribers. When companies try to avoid customer churn preemptively, they're more likely to succeed at retention when established customers don't leave unintentionally.

AI-Powered A/B Testing for Continuous Optimization
A/B testing is not a foreign concept in email marketing. But using AI predictive analytics to accomplish the task is next-level. Where businesses would have to A/B test subject lines, body of emails, or CTAs over the course of different campaigns, AI can A/B test anything and everything simultaneously and in real-time to determine which options are most successful.

For instance, if a specific email layout generates the highest conversions within an AI-driven campaign, that layout will be flagged for similar audiences in the future. If a specific CTA generates more clicks than all the rest, the AI will recommend that same verbiage or placement in future campaigns.

When A/B testing is in constant play with AI for certain aspects of emails, the capacity for enhancement is endless, and companies do not have to waste time A/B testing themselves to foster greater engagement.

Enhancing Customer Journeys with Predictive Email Sequences
AI-driven predictive analytics facilitate companies in sending automated email sequences that guide the user down the funnel more effectively than drip campaigns. Where there would typically be a drip campaign with an email sent on this day and that time, AI monitors user activity and adapts in real time.

For example, if a user clicks on a specific email regarding a new product launch and fails to purchase it four days later, they will receive a launch-related follow-up email from the company with either a more in-depth description or a testimonial. If someone registers for a free trial, AI can predict when that person is most inclined to convert to a paid offering and send out an email at just the right time to facilitate the process. These automated, tailored email sequences empower companies to better nurture their leads and provide each person with the appropriate content at just the right time and position of their journey.

The Future of Predictive Analytics in Email Marketing
As A.I. and machine learning expand, predictive analytics will gain its own nuances that allow for even deeper email campaigns and accuracy. One can predict that the future will hold real-time, A.I.-driven email content based on engagement with recipients, response to an email via voice activation, and predictive engagement prediction to adjust emails even before a campaign launches.

In addition, A.I. will continue to blend into omnichannel marketing such that predictive analytics from email campaigns will help adjust and modify other touch points social media interactions, chatbot responses, SMS marketing to further personalize and enhance customer experiences and increase conversion and retention rates.

Conclusion
What does the future hold for email marketing? Predictive analytics via AI. With this technology, companies can predict what users will do with their emails, enabling them to customize and immediately adjust engagement efforts as necessary. Utilizing AI to edit the subject line and then create subsequent dynamic sequences and learn the best times to send further boosts a company's email conversion rate.

Companies that leap forward into the future with such technological enhancements to their email marketing campaigns will have a competitive advantage after all, data-driven content renders the experience more precise and relevant, fostering better relationships and optimized engagement for every campaign.