Getting Started with Predictive Analytics in Your Email Marketing

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As companies grow and their customer lists with them, it’s easy to lose sight of personalization in your email marketing strategy. But that doesn’t have to be the case.

When 52% of people say they will find somewhere else to shop if an email is not personalized, it’s important to take the extra step. Why lose those sales if you can use the data and customer information that you already have to send them a relevant message that is more likely to result in a sale? 

Personalization is an important step in email marketing for nearly every industry. From media and entertainment to travel, customers like to see personalization in their inbox. Make the shopping experience easier and give them what they’re looking for. Image courtesy of Marketing Land.

The use of predictive analytics can help marketers continue to reach customers on a more personalized level. Predictive analytics allows you to use a lot of the data you already have, and new data you may decide to collect to improve email marketing through personalization and segmentation. 

The right predictive analytics strategy can help you grow your customer lists, increase customer lifetime value, and build better relationships with your customer base. It can also help improve accuracy and track customer data in real-time, allowing you to always have the most accurate information. Something that the manual data entry process of the past could never provide.

Predictive analytics won’t only benefit your customers by providing them with the most relevant products and content. It also provides your teams with a less manual process that eliminates the human error factor that comes with manual data entry. Image courtesy of Small Business Trends.

When you first hear about the idea, it might sound overwhelming — but it’s easier than you think to get started in the predictive analytics game. Let’s take a look at how any company, large or small, can get started using predictive analytics to their benefit.

Here’s a sneak peek at what we’ll discuss throughout this article: 

  • How implementing predictive analytics into your strategy is easier than you think
  • Customer relationship management systems can help you manage and analyze the data
  • Why email and predictive analytics are a match made in heaven

How to Get Started With Predictive Analytics

Here’s the good news — getting started with predictive analytics is easier than you think. There’s no special skill set (although the more analytical you are the better), or degree that is needed to take advantage of the improvements to your email marketing strategy that predictive analytics can provide.

In fact, you probably have almost everything you need to get started. Chances are good you’re already collecting data on your customers and site visitors, you just might not know how to dissect this information or what data is valuable.

Here’s some of the data you’re probably already collecting from users that can help improve your email marketing strategy with the help of predictive analytics.

  • The shopping preferences of users
  • How people are browsing your website
  • What their product interests are
  • How people are finding your site
  • What emails customers are engaging with

Although these are just a few examples, there is a long list of information you can collect from visitors on your website and email list. The problem that most companies run into is actually having the ability to manage this data in real-time — something predictive analytics and your email marketing system can help with. 

Use the Data Your Email Marketing Software Provides

If you have an email marketing strategy in place and using are using a customer relationship management (CRM) system to manage it, you’re already ahead of the game. If you don’t have a team focused solely on analytics, your management system can help you easily understand the data of how your customers are interacting with your emails.

A few of the types of email interaction data that can help improve personalization include:

  • The number of emails each customer is opening
  • What are people purchasing from your emails
  • Who might soon become inactive in your system due to no interaction
  • How many users are clicking through emails to your website
  • What subject lines are the most popular for your customer base

Each step of an email marketing campaign provides you with more data on your customers. Knowing who is opening, clicking, converting, and then becoming return customers can help you know what to serve a customer in the future. If you know a customer tends to drop off before converting, maybe a coupon will help get them to make a purchase. Image courtesy of Social Media Impact.

All of this data provides you with information on how each customer shops and provides you with new opportunities to personalize each interaction with them. If you know a customer often purchases a certain product, you can send them related products. Or, if a certain subject line performs well, you can begin to understand what verbiage and content your customers want to see.

Why Predictive Analytics for Email Marketing Works

Whether you’re looking to implement predictive analytics across all of your marketing efforts or just getting your feet wet, your email marketing is the perfect place to start. Not only are you able to collect a vast amount of information, but your CRM can help you understand and test the information. No matter your skill level, predictive analytics is within reach.

Customers want to receive personalized offers and content. If you’re willing to take the time to improve your personalization and give customers relevant information (with the help of predictive analytics) you’ll find retention and engagement rates will improve. Image courtesy of Finances Online.

You Already Have Lots of Data

Because most companies already have a customer list for emailing purposes, it eliminates the need to compile new information. This means you can get started today with the customer information you already have on hand.

Use this data you have to build segmented lists based on customer behavior. From there, you can continue to learn more about your customers and provide them with an even more personalized experience. The more relevant information you send, the more likely a customer is to convert. 

Use Your CRM to Your Advantage

With the help of a CRM system, email is easy to implement and you have full control of the message and audience. If you already have a CRM in place, all you have to do is create the email content, upload it to your email templates, and segment your lists — it’s as easy as that!

Having the ability to determine what the message is, and who it is going to help you to learn more about each different segmentation in your strategy. It also offers you the opportunity to analyze the results of your marketing campaigns with easy to read stats on each email that is sent out.

A/B Test for Best Results

Email allows you to easily A/B test to determine the best results. A few of the areas you can test for performance include the subject line, call to action, and imagery. By using an A/B testing method, you can test emails within different segments to see what works best with those customers.

As you analyze these results and learn what performs well and what doesn’t, you can apply these changes to future emails to improve performance. This will improve future email campaigns that you send out and provide your audience with more of what they want and less of what they don’t. 

A/B testing lets you understand your customers better and increase conversion rates. With the help of predictive analytics, you can start to understand the patterns and predict what your customers may want next. Image courtesy of Nelio Testing.

Let Predictive Analytics Improve Your Email Campaigns

Predictive analytics might just be what you need to take your email marketing to the next level. With the ability to utilize the data you already have and provide customers with a more personalized experience, you’re bound to increase conversions.

Although the capabilities of predictive analytics go far beyond what we discussed in this article, it’s much easier to get started than you may have thought.

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