About Predictive Analytics and Demographics

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Mailchimp’s conversion insights dashboard displays predictive analytics, which uses AI to analyze purchase history, browsing behavior, and email engagement to forecast future buying patterns. Predictive demographics uses data science to predict the gender and age of your contacts. These insights help you identify high-value prospects, re-engage customers at risk of churning, and send marketing messages at the exact moment a customer is ready to buy.

In this article, you’ll learn how predictive analytics and demographics work, how to view your data, and how to identify key characteristics to refine your marketing and increase engagement.

Things to know

Here are some things to know.

  • This feature is included with the Standard plan or higher.
  • SMS-only contacts without email addresses won’t display predictive analytics.
  • You must have a connected online store. To learn more about connecting an e-commerce store, check out Connect Your Online Store to Mailchimp.
  • You must have sent at least one email campaign to your audience to generate predictive analytics.

How it works

Mailchimp’s AI analyzes data from your connected store and your marketing activity. The platform then generates predictions for all contacts in your audience, including prospects who haven't purchased yet and one-time buyers.

Predicted demographics is based on shared Mailchimp account information from around the world, and uses the same gender and age range categories as Google Ads. This way, you can easily apply Mailchimp demographic insights to your other marketing efforts.

Note

Demographics data is tied to your audience. If you delete an audience, gender and age range data will be removed as well.

About predictive analytics

Predictive analytics helps you identify which contacts to segment and create automation flows for.

Likelihood to Purchase

This score predicts how likely a contact is to make a purchase in the next 60, 90, or 365 days. It helps you identify subscribers ready to buy so you can target them with promotional campaigns.

Predicted Customer Lifetime Value (CLV)

This metric estimates the total revenue you can expect from a customer over time. It combines their likelihood to purchase with their estimated order value, helping you prioritize your most valuable audience segments,.

Predicted Time to Next Purchase

This model predicts the specific date a previous customer is likely to buy again. You can use this to automate “nurture” emails that arrive shortly before their expected reorder date,.

Customer Churn Risk

This metric analyzes purchase frequency to identify customers who are at risk of not buying again. Customers are categorized as High, Medium, or Low risk, allowing you to trigger “win-back” automations for those most likely to leave.

View predictive analytics

To view predictive analytics, follow these steps.

  1. Click Analytics, then click Conversion Insights.
  2. If you have more than 1 store, click the Store drop-down and choose the one you want to work with.
  3. If you have more than one audience, click the Audience drop-down and choose the one you want to work with.
  4. Click the Customers tab.

The Customers tab displays an overview of your audience broken down by their buying potential.

  • Subscribers ready to buy High-potential prospects you should target immediately.
  • Customers ready to buy again Repeat buyers approaching their next purchase date.
  • Customers at risk of not buying again Customers who have deviated from their purchasing cycle and need re-engagement.

About predicted demographics

Predicted demographics data appears in contact profiles and email reports. Each area provides slightly different information.

Contact profile

Each contact profile displays the predicted age range and gender for that contact. Combine this data with other profile information, such as recent activity, to learn who your contacts are and how they interact with your content.

Email reports

Email reports display the percentage of recipients in each predicted demographics category. Filter demographics by total recipients, opened, and clicked. If you've enabled e-commerce link tracking in your email, you can also view demographics based on available purchase data.

Turn predicted demographics on or off

The predicted demographics feature is automatically enabled for eligible users. If you don’t want to access this data in your account, turn off predicted demographics in your data settings.

To turn predicted demographics on or off, follow these steps.

  1. Click your profile icon and choose Account & billing.
  2. Click the Settings drop-down menu and choose Manage my data.
  3. Scroll to Data analytics settings.
  4. Uncheck the box next to Turn on predicted demographics in this account to turn predicted demographics off. Check the box to turn predicted demographics on.
  5. Click Save.

You're all set! A success message will confirm that your settings have been updated.

What you can do with predictive analytics and demographics

Predictive analytics and demographics work together to help you understand not just who your customers are, but how they are likely to behave in the future. You can use these insights to target specific segments of your audience with timely, relevant marketing.

  • Anticipate customer needs Use predictive data to identify when to engage. Create segments based on forward-looking criteria like Customer Churn Risk (High, Medium, or Low) or Predicted Time to Next Purchase. This helps you to prioritize high-intent shoppers or to intervene before a customer drifts away
  • Automate based on behavior Turn insights into action by triggering automations based on predictive changes.
  • Refine messaging with demographics Use demographic data to tailor what you say. Age and gender data can help you make messages that appeal to your main audience or find ways to reach new people.
  • Combine data for precision targeting After you analyze your audience, combine these signals to create more detailed custom segments.

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