7 Ways to Take the Guesswork Out of Marketing with Data Science

1. Know which customers are the most valuable

A marketing platform powered by data science can ensure that you're spending your marketing time effectively. It tells you who is most likely to buy and can even predict a customer’s lifetime value.

Purchase likelihood is a metric that analyzes the relative probability that a customer will purchase from your business again in the future. By combining this information with purchase history and shopping patterns, a customer lifetime value (CLV) assessment is possible. This means you can see what revenue you might expect from each contact over the whole span of their relationship with you. This insight helps you determine the segments of your audience most likely to boost your bottom line over time.

A toy website, for instance, might create VIP holiday offers for their high-CLV customers to both thank them for their business and encourage more purchases during this key season.

“There’s a tendency to think of your audience as a monolithic entity whose members are all contributing equally,” says Neel. “But realistically, a lot of companies are getting most of their value from a pretty small subset of their audience.”

Creating segments based on purchase likelihood or CLV can ensure you’re spending your time on the contacts who are most likely to help your business grow and succeed.

2. Connect with people who mirror your contacts

Individuals similar to your current contacts are among the best sources for new business. Using marketing data science, Mailchimp’s lookalike audience finder identifies these high-potential prospects by analyzing your current audience to find a network of people with the same characteristics and interests. You can then reach out to them with postcards that direct them to your website or store.

An online women’s style consultant, for example, might want to find customers similar to her young, fashion-conscious female audience in her area. Lookalike audience members, found using data science, would be high-potential prospects who she could target with a postcard directing them to sign up for her newsletter on her website.

“One of the ways data science helps small businesses is by connecting them with people who are likely to be interested in what they offer,” says Michelle Monaco, Senior Product Marketing Manager at Mailchimp.

3. Turn people’s actions into personalized marketing

Using a marketing platform with data-driven tools allows you to create relevant messages for specific audiences. It’s a good idea to seek out a marketing platform with a customer relationship management (CRM) feature that helps you keep track of customer information, actions, and behaviors so that you can create personalized messaging for each segment of your audience.

Advanced marketing platforms not only let you capture information about your audience, but also make it easy to use that data for targeted marketing campaigns. Behavioral targeting, for instance, is powered by information on how your audience interacts (or doesn’t) with your products, marketing campaigns, website, or app.

“Behavioral targeting can help increase the timeliness and relevance of your marketing efforts,” says Michelle. “If you know that someone just visited a specific page on your website, you could use behavioral targeting to trigger an email that re-engages them with a relevant message. Let’s say a personal trainer has a page on her website dedicated to yoga—she could send an email campaign to visitors that includes a free trial yoga class.”

4. Write subject lines that work

Marketing data science can also improve the effectiveness of your email subject lines. Real-time, data-driven feedback on character and word count, punctuation, appropriate emoji use, and more can help you create subject lines that grab your contacts’ attention and increase email open rates.

Taking it one step further, you can run an A/B test—where 2 subject lines are compared against each other—and send your next mailing using the winner.

A software provider, for example, might be tempted to use several emojis in their subject lines—but best practices show fewer is often better. They can also use an A/B test to find out if customers would respond better to a 10% off offer or a 2-months-free offer. A small test is run, comparing the subject lines, “Upgrade to premium service for free” and “Get 2 months on us” to see which generates higher open rates and purchases. The winner is then rolled out to the full audience. A/B testing can also be used to test email content, design, or even how different audience segments perform.

5. Generate personalized recommendations

For e-commerce businesses, using data science to include relevant product recommendations in your marketing messages can help you sell more stuff. By showcasing your new or best-selling products or by offering personalized recommendations based on someone’s previous buying or browsing history, you can increase the likelihood that someone purchases.

For instance, bookstore customers who regularly buy mystery titles would likely appreciate email updates on new thrillers and mysteries, instead of generic news on unrelated genres. This could be great content to pull into an email about upcoming book signings by mystery writers.

“Marketing that feels generic is a huge turnoff for consumers,” says Neel. “Using data science to gain audience insight helps you better understand who you’re marketing to, so you can tailor your messaging and make it relevant to who you want to reach without a lot of additional effort.”

6. Send emails at the right time

Send time optimization uses data science to determine when your contacts are most likely to engage with your emails. Based on this data, it automatically sends emails at the time each contact in your audience is most likely to open them.

For example, a trucking business trying to reach manufacturers across the globe needs guidance on when the best time is to reach these professionals based on their time zones and individual engagement habits. Send time optimization can help them determine whether their contacts are more likely to open emails early in the morning, in late afternoon, or even on the weekend when their inbox isn’t as cluttered.

Hitting your contacts’ inboxes at the right time is essential so they’re more likely to open and read your message, rather than hitting delete in a rush.

7. Identify the next best action to engage customers

Good marketing never truly ends—after a success, the right ongoing outreach keeps customers informed and loyal. Data-science-driven recommendations on what to try next can improve open and click-through rates, lower unsubscribes, and optimize your overall email performance.

When someone downloads a gourmet grocer’s mobile app, for instance, it’s important to engage them immediately so they’ll begin using it regularly and deepen their relationship with the business. A welcome email series might be suggested as the next best action to show new users how to get the most out of the app, or an A/B test might be recommended for the next newsletter.

Improve with each campaign

Relying on data for answers arms you with information to make the right decisions with confidence and speed. When you have data about what’s working, it’s much easier to plan for future campaigns.

“Data science helps you create relevant marketing,” says Michelle. “When you have data on how a campaign performs, it’s easy to make decisions about how to make your next campaign even better.”