Michael Ethan, Manager of Blue Mail Media says, predictive analytics is powerful than any other email marketing technique in terms of creating a long-term relationship with the audience. It helps you better manage your customer base and increase the sales rate, all at the same time.
Predictive analytics is one of the modern trends used by email marketers today. And it’s likely to become even more popular as marketers are slowly realizing that making data-driven decisions using predictive analytics can have an enormous influence on customer engagement and overall sales rate.
CUSTOMER DATA PLATFORM (CDP) BUYERS’ GUIDE 2019
Welcome to the 2019 edition of CDP Buyers’ Guide. As customer data platforms are becoming increasingly necessary for enterprise marketers, it is also becoming more complex to choose the best fit CDP platform amongst the pool of new and old vendors.
In simple terms, a better understanding of your customer’s likes and dislikes, smarter segmentation, and a higher return on investment is what predictive analytics does for your email-marketing program. This secret power can help marketers create more effective email campaigns and start selling in a smarter way by scrutinizing the data of email subscribers and website visitors.
Understanding the Basics of Predictive Analytics
Firstly, what is predictive analytics? As discussed above, it is simply using data to identify customer’s interests and thereby predict their future behavior. By studying the gathered data such as purchase behavior, website browsing behavior, customer relationship management (CRM) data, social media interactions, and email engagement metrics, one can create smarter marketing campaigns that resonate better with the prospects.
Predictive analytics also leverage artificial intelligence, machine learning, statistical algorithms, and modeling to analyze existing data and predict imminent changes. Some standard predictive-modeling techniques for analyzing data are given below:
- Marketing Spend Analysis: It examines how existing customers are acquired and engaged and then forms the most successful acquisition and retention strategies for the future.
- Collaborative Filtering: This predictive-modeling technique studies customer’s profiles and purchasing patterns to recommend products or services they would be spending on.
- Clustering Algorithms: It segments the audience list based on demographics and certain customer behaviors to predict their impending decisions.
Impact of Predictive Analytics on Email Marketing
Now, the question is – How much of an impact will predictive analytics have on email marketing? Forrester surveyed 579 marketing decision-makers to help you answer this question. The result is as follows:
- 82% agree that predictive marketing will be essential to stay on edge.
- 81% are planning to increase the usage of predictive analytics to drive email marketing decisions.
- 78% say that all marketing approaches will soon become predictive.
- How Can Predictive Analysis Improve your Email Marketing Performance?
1.Recognizing the Customers and their Interests
Once a potential customer subscribes to your email list, your only motive will be to generate sales. However, to avoid sounding pushy, you may follow specific steps to pull them into your sales funnel, such as:
- Welcoming the subscriber with a generous message or a welcome gift.
- Performing A/B test to determine how this message goes.
- Sending some more promotional messages to draw them closer to your brand and so on.
Leveraging predictive analytics can simplify the steps mentioned above. This intellectual approach segments the existing subscriber list into smaller groups and creates a model based on what it learns from them. With this data, you can discover who your real customers are along with their interests.
Consider this welcome email from The School of Life. It conveys the purpose of their business, offers an incentive to make a purchase, and promotes various assets for customers to choose from.
Image Source: theschooloflife.com
Here customers segment themselves by clicking on the interested section. You can apply predictive analytics on this segmented data to track exactly what they’re looking for so that you can send them a relevant email later on.
2.Offering Better Experience with Personalized Content
Predictive analytics is the key to making your customers happy. It identifies how customers are most likely to respond to a specific email or promotional offers, and thereby helps you create appropriate and personalized content like never before.
The Adestra State of Digital Personalization report looked at the customer’s attitude towards email personalization.
Image Source: adestra.com
This advanced and AI-driven technique identifies the user on a granular level. It focuses more on displaying content and messages to the customers based on their intent. There are plenty of examples of predictive email personalization around the web, where Netflix is the most popular one.
The extensive catalog of movies and shows on Netflix makes it virtually impossible to create a unique experience for each of its 158+ million subscribers. However, the service utilizes content-customization algorithms to understand the type of content people are interested in and populates the same on the individual email.
By providing this custom recommendation for each subscriber, Netflix ensures that users actively see the value of their pack. This approach resulted in a relatively low 9% churn rate, which is lower than other subscription streaming services.
Image Source: parksassociates.com
3.Keeping Your Customers Active Throughout
It’s unavoidable that some prospects unsubscribe from your email list. But wouldn’t it be great if you are able to identify those people who are most likely to do so in the coming days? By using predictive marketing, you can locate the inactive users and take preventive actions by forwarding reengagement or win-back “we-miss-you” campaigns.
Image Source: bananarepublic.gap.com
In the above example, Banana Republic tries to win customers back with a coupon. Such emails play a significant role when it comes to reaching out to users before losing them to an inactive status.
With the help of predictive information, you can also identify the suitable discount level for your inactive customers.
For instance, if you offer 20% off to a customer who spent less amount on your service, you may suffer losses from the acquisition price. Whereas, providing a 20% discount to a customer who has spent $500 helps you earn more from them in the future.
Now it’s your turn
If email marketers aren’t taking the advantage that comes along with predictive analytics, now is the time to do so. The chances are that you may have the data required to create an astounding email marketing experience, but to reap the desired benefit out of it, you will have to understand it thoroughly. The tips mentioned here on how to use predictive analytics in your email campaigns can help you in this area. Using those techniques, you can quickly impress your subscribers with the insight and turn them into lifelong patrons.