By Alen Čapelja
"History doesn't repeat itself, but it often rhymes." —Mark Twain
In a fiercely competitive online marketplace, businesses are constantly searching for that elusive edge that separates them from the pack and helps them snag customers on the lookout for that perfect something.
One of the most powerful ways to gain that edge is to use predictive analytics, which uses past activity and results to help make an educated guess on what could happen in the future. E-commerce companies can use predictive analytics to better predict market demands, forecast customer behavior, enable dynamic pricing, and even detect fraud. Predictive analytics can also be a powerful tool to find relationships between various customer data points, such as past purchases, demographic data, social media sentiment, web activity data, and more.
For Klaviyo users or those considering making the move to the platform, you're in luck: This functionality is already built in and is powered by artificial intelligence (AI).
In this article, I’m digging into what Klaviyo predictive analytics features can do for your business and how to maximize its benefits.
Klaviyo Predictive Analytics: What You Need to Know
If you were to ask 100 e-commerce managers if they would like to predict their customers’ next moves, chances are 100 percent of them would jump at the chance.
Though the predictions aren’t perfect, as Mr. Twain correctly notes, with the right preparation and data, AI-powered predictive analytics functionality like what Klaviyo offers can elevate how your business approaches its operations. In particular, this can help you:
Gain Personalized Insights
Klaviyo's predictive analytics offer personalized insights on how to market products, including creating and refining ongoing nurture campaigns. This means teams can tailor their marketing efforts to individual customer preferences, increasing engagement and conversion rates.
Make Data-Driven Decisions
By leveraging predictive analytics, your e-commerce team can make informed decisions based on data rather than a gut feeling or intuition alone—thus leading to more effective strategies and better results.
Identify Profitable Customers
Klaviyo predictive analytics can help marketing teams identify their most profitable customers and marketing efforts, better allocate resources, and maximize ROI.
Improve Customer Retention
Predictive analytics can even identify customers at risk of churning. Using this information, marketing teams can work with sales to implement targeted retention strategies to keep valuable customers coming back.
Prerequisites to Accessing Klaviyo’s Predictive Analytics Functionality
To leverage Klaviyo's predictive analytics functionality, a business must meet certain prerequisites. Together, the prerequisites below allow the analytics functionality to generate meaningful data based on actual customer behavioral patterns:
- Minimum customer order count: Your store should have a minimum customer order count of at least 500 to ensure sufficient data for analysis.
- E-commerce integration: Klaviyo's predictive analytics functionality requires e-commerce integration—such as Shopify, BigCommerce, or Adobe Commerce—to access relevant data.
- Order history duration: Your business should have a specific order history duration of at least 180 days for accurate predictions.
- Multiple customers with three or more orders: Multiple customers placing three or more orders are necessary to further build up customer behavioral patterns.
Klaviyo's Predictive Analytics Capabilities
Now that we've covered the basics, let's dig into the specific predictive analytics fields Klaviyo can provide insights into:
CLV (Customer Lifetime Value)
Klaviyo offers various CLV insights, including historic CLV, predicted CLV, and total CLV. These values are derived from your store's data and are based on patterns identified in historical data. These insights won’t be 100 percent accurate, and they work best when averaged across multiple customers.
Churn Risk Prediction
Predictive analytics can identify customers at high risk of churning, allowing you to take proactive measures to retain them.
Average Time Between Orders
This metric helps you understand the typical time gap between a customer's purchases, enabling you to tailor marketing strategies accordingly.
5 Best Practices When Using Klaviyo Predictive Analytics
With so much predictive power and the ability to help refine your store’s marketing prowess, you will want to make the most of Klaviyo’s capabilities. Here are five key best practices from SmartBug that will help your team dial in its deployment:
1. Educate your team.
Ensure your marketing and sales teams understand the value of predictive analytics and how to use the insights in their roles. These users can then help shape the metrics collected, data shared, and processes influenced by Klaviyo’s insights.
2. Ensure data privacy compliance.
Be mindful of data privacy regulations (e.g., GDPR, CCPA) when using predictive analytics. This means ensuring your environment has the proper consent and data handling practices in place to protect customer data.
3. Regularly monitor for anomalies.
Keep a vigilant eye on the predictive analytics data being produced and evaluate it for anomalies that may point to underlying foundational data issues. When you identify an anomaly, investigate any sudden changes or unexpected behavior and adjust your strategies accordingly.
4. Benchmark and compare.
Benchmark your team’s metrics and performance against industry standards and compare your predictive analytics results with competitors. This can help identify areas for improvement and introduce new ways to leverage Klaviyo’s data.
5. Use the data to your advantage.
Maximize the ROI of your efforts by leveraging the predictive analytics to optimize email marketing campaigns, segment customers based on CLV values, and identify high-churn-risk customers for targeted marketing campaigns and retention efforts.
Bringing It All Together
In an ever-evolving e-commerce marketplace, predictive analytics is a powerful tool that can give your business a competitive edge and help you stay ahead of your customers’ expectations.
Klaviyo's predictive analytics feature—with its ability to provide personalized insights, drive data-driven decision-making, identify profitable customers, and improve customer retention—is one of the most valuable tools for e-commerce businesses. And by following these best practices and leveraging the insights it generates, you can enhance your marketing efforts, boost customer loyalty, and, ultimately, drive growth in your online business.
To deepen your understanding of how to maximize the benefits of Klaviyo predictive analytics, we recommend exploring SmartBug’s Klaviyo Benchmarks Report & Strategies, which can provide valuable insights into industry standards and best practices for email marketing and customer engagement.
About the author
Alen Čapelja is SmartBug’s E-commerce Service Design Manager. He specializes in next-level problem solving and pushing the limits within the creative and client services departments. Alen employs a user-first approach that he’s refined after more than a decade of e-commerce work. Being part of executing more than a million emails in various ESPs has given Alen a broad understanding of e-commerce marketing and technology capabilities. Read more articles by Alen Čapelja.