Now You Can Predict Your Customers' Buying Habits

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What if you could predict your customers’ buying habits with precision? Klaviyo’s predictive analytics makes that possible. This feature helps you make smart, data-driven decisions to boost sales and engage your customers more effectively. It predicts key metrics like Customer Lifetime Value and the expected date of the next order.

Today, I’ll guide you through how to leverage this tool to its full potential. Keep reading to learn more!

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What is Predictive Analytics in Klaviyo?

Predictive analytics in Klaviyo combines data science and machine learning to analyse your account data. This gives you actionable insights that can significantly improve your marketing efforts.

Here’s a detailed look at the different types of predictive analytics data available in your Klaviyo account and how you can use it effectively. Note that, CLV stands for Customer Lifetime Value.

The Predictive Analytics Section of a Profile

You’ll find the Predictive Analytics section on the Metrics and Insights tab of a profile. This section provides valuable information about each contact, including:

Customer Lifetime Value (CLV)

Klaviyo automatically calculates a Customer Lifetime Value (CLV) model using your company’s data, updating it at least once a week. While individual predictions aren’t always exact, they offer a reliable forecast when averaged over many customers.

Example: You might see predicted CLV values like 1.43, 0.25, 3.12, 0.78, and 2.97 orders. These numbers may seem imprecise for single customers, but when grouped together, they help predict the total number of orders or spend for the group. So, if you have five customers with these predicted orders, you can expect around 9 orders in total.

Expected Date of Next Order

This prediction considers the specific customer’s order behavior and the overall order behavior of all your customers. If a pattern is detected, Klaviyo will use it to make a prediction. If not, it will make a reasonable prediction based on general customer behavior.

Example: For customers with clear order patterns, Klaviyo’s prediction will be more accurate. For those without a pattern or with limited data, the prediction will be based on how other customers behave.

FAQs About Predictive Analytics

Here are some common questions we get about using Klaviyo’s predictive analytics for your marketing flows.

Do I need to add past profiles into the repeat purchase nurture series flow?

• No, Klaviyo automatically includes existing profiles and determines which profiles to include moving forward. Every customer with an order has an expected next order date, making this process seamless.

How do we know the expected date for one-time purchasers?

• For one-time purchasers, Klaviyo calculates the expected date of the next order using data across all your customers.

Can the app send reminders based on product-specific replenishment cycles?

• While Klaviyo doesn’t consider specific products in its predictions, you can create multiple Placed Order triggered flows for different replenishment cycles by:

  • Setting trigger filters to restrict each flow to products with the same cycle.

  • Adding time delays that reflect the known cycle, ensuring reminders are sent at the right time.

Important Considerations

There are a few things to keep in mind when using predictive analytics to ensure you get the best results:

• Avoid Repetitive Sequences: Don’t count down to the expected order date in your emails, as this can lead to unsubscribes if customers receive the same sequence repeatedly.

• Use Replenishment Flows: For products with known replenishment cycles, stick to using specific replenishment flows instead of relying solely on predictive dates.

• Nurture First-Time Buyers: Focus on nurturing first-time buyers to encourage repeat purchases, but don’t forget to balance this with maintaining engagement with your regular customers.

Additional Features

Predicted Gender

Klaviyo’s gender prediction algorithm uses a customer’s first name and census data to predict gender (likely male, likely female, or uncertain). While this is an approximation, it can help tailor your communication. Just make sure your targeted messages are inclusive and relevant to all genders.

Maximize Your Marketing with Predictive Analytics

By understanding and leveraging Klaviyo’s predictive analytics, you can make data-driven decisions that optimize your marketing efforts and enhance customer satisfaction. Here are some key benefits:

• Optimize Marketing Spend: Focus your budget on segments predicted to generate higher CLV.

• Personalize Communication: Send targeted emails based on expected purchase behaviors and patterns.

• Enhance Customer Experience: Use predictive data to create timely and relevant engagement, reducing the risk of unsubscribes.

Wrapping Up

Understanding and leveraging Klaviyo’s predictive analytics can make a huge difference in your marketing strategy. By using data-driven insights, you can optimize your marketing spend, personalize customer interactions, and enhance overall customer satisfaction.

I hope this deep dive into Klaviyo’s predictive analytics helps you unlock its full potential. If you have any questions or need further assistance, feel free to reach out. Happy marketing!