Repeat purchasers are a critical part of most brands’ overall marketing strategy, often making up 20%-40% of your customers of your customer base. Not only is it cheaper to retain an existing customer than acquire a new one, they become more likely to return with each purchase, driving consistent revenue growth.
How can you encourage more repeat purchases? Instead of relying on generic follow-up timelines or promoting bestsellers, imagine leveraging actual buying behaviors to boost sales and loyalty.
With Klaviyo’s new product analysis dashboard, you gain powerful insights into your repeat buyers related to specific repeat purchases, including:
- The typical time between purchases
- Items commonly bought together
- Items most likely to be bought next
In this lesson, you’ll learn how to access and optimize this data, transforming your post-purchase strategy to increase customer retention and drive higher sales.
Take a tour of the product analysis dashboard
What does the product analysis dashboard do? Explore the cards below to discover each key feature and read a use case for inspiration on how to apply these features to your own brand.
Repeat purchase timing
What this feature does:
This chart visualizes the time between a product purchase and the next purchase, allowing you to craft flows and campaigns relative to when your customers would make a second purchase.
Customer example:
NANI originally followed up with customers 30 days after their purchase. They discovered that customers who bought disposable masks were more likely to repurchase around the 10-day mark after seeing positive results.
With this new data, NANI switched their follow-up to 10 days and saw a surge in repeat purchases and delighted customers. Shortening the post-purchase flow didn’t just keep NANI top of mind—it boosted sales and ramped up customer loyalty, turning a simple tweak into a huge win!
Products bought in the same cart
What this feature does:
This list reveals products purchased alongside your selected product, helping you pinpoint opportunities for cross-selling, bundling, or offering discounts on related items at checkout.
Customer example:
Makeup trends evolve constantly, and observing buyer behavior is key to staying ahead.
SWAK noticed a shift: more customers were buying brow gel along with mascara instead of eyeshadow palettes. To capitalize on this trend and boost average order value (AOV), SWAK started promoting and bundling these products together. This strategic move not only met changing consumer preferences but also effectively increased AOV, demonstrating how adapting to customer behavior can drive significant business growth and customer satisfaction.
Products bought in the next order
What feature does
This card lists products that customers typically purchase after buying a specific product. It helps you craft targeted post-purchase flows, campaigns, or discounts to encourage customers to return and buy products they usually purchase next.
Customer example:
Beantown Coffee's strategic shift, based on buyer insights, led to a highly effective post-purchase approach. They discovered that customers' second purchases were influenced more by roast type than popularity or novelty.
By optimizing their post-purchase flows with targeted discounts and product recommendations based on this new information, Beantown not only encouraged repeat purchases but also enhanced customer satisfaction and loyalty.
Try it yourself!
If you're already using the intelligence section of Klaviyo's Advanced KDP or Marketing analytics, log in and explore these features yourself. Head to Advanced KDP> Intelligence > Product Analysis to access the dashboard.
From there, select your best-selling product in your catalog and follow these steps to update your post purchase flow.
Refine post-purchase flow timing:
Step 1: Review your repeat purchase timing. Do customers usually make a second purchase before or after the standard 30 day follow up? In the example above, customers usually make a second purchase 20 days after their first.
Step 2: With these insights, let’s conduct an experiment. Examine your post-purchase flow. When do you usually begin cross-selling key products? Let’s adjust the timing by adding or adjusting the time delay before you send any cross-sell email to your customers to align with your post-purchase timing with the timing on the repeat purchase timing chart.
Pro tip: Automate follow-ups using Best cross-sell date. Now, you can go beyond manual adjustments and automate follow-ups at the perfect time. Using Best cross-sell date, you can trigger a cross-sell flow exactly when each customer is most likely to return. Instead of relying on static time delays, this AI-powered prediction tailors every individual post-purchase message based on actual buying behavior, helping you increase repeat purchases with precision. Check out this guide for creating a Best cross-sell date flow in Klaviyo.
Enhance post-purchase flow content:
Step 3: On your product analysis dashboard, takea look at which products are usually bought in the next order. In the example above, customers often buy an umbrella after their first purchase.
Step 4: In your post-purchase email from step 2, let’s add a show/hide condition to recommend products with a subsequence purchase rate (in the example above, we would add the umbrella and lilac sweatshirt) for those bestseller purchasers who haven’t yet purchased a lilac sweatshirt or umbrella.
Pro tip: Personalize emails with Next best product recommendations. Take your post-purchase emails to the next level by adding a Next best product dynamic block to your templates. This AI-powered feature automatically recommends the most relevant product based on what each customer purchased last. Instead of guessing which item to promote, let data-driven insights surface the best option, helping you boost conversions with highly personalized product suggestions. Check out this guide for adding Next best product blocks to your messages.
Keep an eye on your post-purchase flow for the next 30 days. Are you seeing any increased revenue and conversion rates by making these small adjustments?
Bonus: Optimize your merchandising strategy with recommended bundles
Step 1: Check the "Products Bought in the Same Cart" card on your product analysis dashboard. What products are usually bought with your best-selling product? In the example above, customers often purchase a crewneck in the same cart.
Step 2: With this insight, create product bundles on your website or inform your merchandising team of a cross-selling opportunity. Then, run a promotional campaign highlighting your brand-new bundle.
After creating and promoting these bundles, do you see an increase in average order value (AOV) or campaign revenue after 30 days?
Exclude specific products and categories from your report and next best product recommendations
Have a product that’s being discontinued or phased out? Want to make sure it no longer appears in your Product Analysis Report or as a recommended next best product? Here’s how to exclude it so your insights and recommendations stay accurate and up to date.
Step 1: Navigate to the settings icon on the product analysis report.
Step 2: On the Catalog exclusions card, select the product categories or specific products you’d like to exclude from the drop downs.
Step 3: Select the Save changes button.