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Customer Lifetime Value & Purchase Likelihood

Boost sales with insights into how your customers buy

Our predictive analytics tools help you estimate your customers’ future buying behavior, so you can market smarter with more targeted campaigns.

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Focus on your most valuable customers

Mailchimp analyzes past purchase behavior to predict which contacts will have a high, moderate, or low customer lifetime value (CLV) in the future. We use these predictions to group your customers into pre-built segments you can reach in just a few clicks with special promotions or personalized messaging.

Bring customers back before they’re gone

We predict which customers have a high, moderate, or low likelihood of purchasing from your store again, and turn these predictions into segments you can target. Build positive relationships with your on-the-fence customers by sending them an incentive to come back.

Get predictive insights about customer value and loyalty—without hiring a data scientist.

CLV Benefits List

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Build personalized campaigns that drive revenue

Take action right from your audience dashboard. Predicted CLV and purchase likelihood help you know which customers are driving sales, so you can instantly send personalized messages to these pre-built segments. See what else you can do from the audience dashboard

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Create a smarter marketing plan based on intelligent predictions

Predictive analytics tools like CLV and purchase likelihood use past purchase data to forecast which buyers are likely to be your most loyal and valuable customers in the future. That way, you can think ahead and create a marketing plan based on the people who could bring the most value to your business.

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Everything e-commerce businesses need

Increase sales and grow your business when you use tools like predictive CLV and purchase likelihood together with time-saving automations and a valuable marketing CRM—all in Mailchimp’s easy-to-use platform.

See our e-commerce tools

Learn more about e-commerce tools with these guides and tutorials.

FAQs

  • Predictive analytics in marketing describes the practice of reviewing and analyzing historical data in order to better understand an audience, guide decision-making, and glean valuable predictive insights. Marketers will often input historical data into certain statistical models or predictive marketing software in order to objectively examine campaign performance and create forecasts for future customer behavior. Predictive analytics is an extremely important tool to leverage in any data-driven marketing strategy.

  • Predictive analytics refers to the practice of using historical data sets and statistical tools to predict future events or behavior—hence the name predictive analytics. By leveraging predictive analytics, individuals and organizations can make highly educated guesses as to what will happen in the future.

    Predictive marketing uses predictive analytics to evaluate the likelihood of future actions, behaviors, and trends taking place. Thus, predictive marketing enables marketers to stay ahead of the curve and be proactive in their strategies rather than reactive.

  • Predictive marketing allows companies to better their decision-making and optimize the resources at their disposal. Some of the most valuable predictive insights that can be produced using this method include:

    • Audience segmentation: Using predictive marketing tactics, you can effectively segment your audience based on their previous actions and behaviors.
    • Lead identification: Predictive insights may help to illuminate those who are most likely to make a purchase or engage with your brand.
    • Personalized marketing campaigns: You can leverage predictive e-commerce insights to curate what each customer sees. For instance, with Mailchimp you can automatically identify the purchase likelihood of certain customers and send out personalized messages to those who are most likely to take action.
    • Content recommendations/upselling: Companies such as Netflix and Spotify use predictive analytics to curate content on an individual basis. However, predictive marketing software can also help you analyze past behavior in order to identify ideal upselling opportunities.

  • Predictive marketing is one of the most popular applications of predictive analytics. This is because predictive marketing software can help marketers understand their audience, evaluate the effectiveness of campaigns, and identify valuable marketing opportunities.

    However, predictive analytics has applications across a range of industries. For example, predictive analytics is widely used in the retail and e-commerce industries. Through e-commerce insights provided by predictive analytics software, online retailers can suggest products that customers may like and even forecast profits of product demand. This allows retailers and other sellers to figure out how much inventory they should hold, optimal product price points, when a product will be most popular, and which audience segments will most likely purchase certain products.

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You'll need a Standard plan and a connected store with enough data for us to make accurate predictions for you.

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