Product bundles can be powerful for upselling and increasing order value. But after creating a bundle, many merchants struggle with a simple question. Is this bundle actually working?

Without clear data, it is hard to tell whether bundles are driving new revenue or simply discounting products that customers would have purchased anyway. Measuring bundle performance allows you to identify successful bundle strategies, optimize pricing, and avoid profit loss. This guide will cover the key Shopify bundle metrics, where to find the relevant reports, and which tools help you analyze bundle performance effectively.

👉 If you’re new to Shopify and looking for a complete guide to product bundling, read our guide here: Shopify Product Bundle Completed Guide: Strategies, Best Apps & Tips

1. Key metrics to track bundle performance on Shopify

1.1 Bundle conversion rate

Bundle conversion rate measures how often visitors who see a bundle actually buy it. This metric can reveal:

• Whether the bundle offer is appealing
• Whether the pricing and discount are convincing
• Whether the bundle placement on the product page or cart page is effective

For example, if a bundle page receives 1,000 views but only generates 20 purchases, the conversion rate is 2%. That may suggest the bundle needs improvement in pricing, composition, or visibility.

Typical e-commerce product page conversion rates often range from 1% to 3%, though this varies by industry and traffic quality. A bundle conversion rate within or above that range usually indicates the offer is reasonably attractive.

1.2 Bundle revenue

Bundle revenue tracks revenue generated specifically from bundle purchases. Merchants typically monitor 2 numbers:

• Total revenue from bundles
• Percentage of total store revenue coming from bundles

These metrics show the real contribution bundles make to overall store performance. For example:

• Bundle revenue: $12,000
• Total store revenue: $80,000
• Bundle contribution: 15%

This helps answer questions such as:

• Are bundles a meaningful revenue driver for the store?
• Which bundles generate the most sales?
• Should the store invest more in bundle campaigns?

Over time, merchants can also track bundle revenue trends to see whether bundle performance improves after optimizing pricing, placement, or product combinations.

1.3 Average order value (AOV) impact

One of the main reasons merchants create bundles is to increase average order value (AOV). To evaluate this impact, merchants compare:

• AOV for orders containing bundles
• AOV for orders without bundles

If bundles are working well, orders that include bundles should typically have higher order values and more items. Example comparison:

This comparison helps merchants understand whether bundles truly encourage customers to purchase more products together. A bundle that increases both AOV and items per order usually indicates a successful upsell strategy.

1.4 Bundle attach rate

The bundle attach rate measures how frequently a bundle appears in customer orders. It is commonly used to evaluate upsell effectiveness.

Two common formulas are used.

The 2nd formula is particularly useful when a bundle is designed to upsell a specific product. For example:

• Orders containing Product A: 500
• Orders containing Product A bundle: 120

⇒ Bundle attach rate = 24%

A higher attach rate usually indicates that the bundle offer is relevant and well-positioned in the buying journey.

Attach rate can also reveal:

• Whether customers notice the bundle offer
• Whether the bundle complements the base product
• Whether bundle placement near the add to cart area is effective

1.5 Product cannibalization rate

Not all bundle sales represent new revenue. Sometimes bundles simply replace purchases that would have happened anyway. Product cannibalization analysis helps determine whether bundles create incremental revenue or simply shift sales from individual products.

Merchants often evaluate this by comparing product sales before and after launching a bundle.

Typical approach:

1. Track single product sales before bundle launch
2. Track single product sales after bundle launch
3. Compare bundle sales with any decline in individual product sales

Example scenario:

• Product A sold 800 units per month before the bundle launch
• After the bundle launch, single product sales drop to 600 units
• Bundle sales generate 250 units of Product A

In this case, the bundle may still create net growth, but the merchant should analyze whether discounts are reducing profit unnecessarily.

Cannibalization analysis is especially important for bundles that include best-selling products.

1.6 Bundle profit margin

Revenue growth does not always translate into higher profits. Bundles often rely on discounts, and deep discounts can significantly reduce margins. Bundle profit margin helps merchants evaluate whether bundle campaigns remain financially sustainable.

Basic calculation:

When evaluating bundle profitability, you usually track:

• Bundle selling price
• Total cost of products in the bundle
• Total discount applied
• Net profit per bundle order

For example, suppose a bundle is sold for $60, and the total cost of goods for the included products is $35. The store earns $25 profit per bundle order.

Even if bundles increase order volume, the margin should still remain acceptable for the business. Otherwise, higher sales could come at the cost of reduced profitability. 

Common bundle performance scenarios and what they mean

2. Where to find bundle performance data in Shopify

In most cases, bundle performance data comes from 3 main sources:

• Shopify Analytics dashboard
• Shopify apps with built-in features 
• Specialized tools 

2.1 Shopify analytics dashboard (native bundle reports)

When merchants create bundles using the Shopify Bundles app, Shopify Analytics automatically provides several dedicated bundle reports. If you use third-party apps, Shopify Analytics usually does not display these native bundle reports.

Below are 4 main bundle reports available in Shopify Analytics.

2.1.1 Bundle total sales over time

This report shows the number of orders and total revenue generated from bundles over time.

By default, Shopify displays the data as a line chart, often compared with the previous 30-day period. This visualization makes it easier to identify trends in bundle performance.

Merchants commonly use this report to:

• Monitor bundle revenue growth
• Identify seasonal changes in bundle demand
• Evaluate whether bundle campaigns improve sales over time

For example, if bundle sales increase after placing the bundle widget near the add to cart button, the trend line can confirm whether that change improved performance.

2.1.2 Total sales by bundle

This report shows the net number of bundles sold and total sales generated by each bundle.

The data is usually displayed as a horizontal bar chart, which makes it easy to compare bundle performance at a glance.

This report helps merchants quickly answer questions such as:

• Which bundles sell the most
• Which bundles generate the highest revenue
• Which bundles may need pricing or product adjustments

Many merchants use this report to identify best-selling bundles within the last 30 days and prioritize them in promotions or product page placements.

2.1.3 Total sales by bundle component

This report breaks down bundle performance at the individual product level. Instead of showing bundle sales as a single unit, Shopify lists each product inside the bundle separately and shows:

• The number of items sold
• The total sales generated by that product within bundles

For example, if a bundle contains shampoo, conditioner, and shower gel, each product will appear as its own row in the report. This insight helps merchants understand:

• Which products contribute the most to bundle revenue
• Which bundle components customers value most
• Whether certain products make a bundle more attractive

These insights are useful when optimizing bundle composition or product combinations.

2.1.4 Bundle component and product comparison

This report compares sales of products bundled with other products versus sales of the same products sold individually.

Shopify usually displays this data in a grouped bar chart, where each product has 2 values:

• Sales when the product is purchased as part of a bundle
• Sales when the product is purchased individually

This comparison helps merchants determine whether bundles generate additional revenue or simply shift sales from individual products.

For example, if a product sells significantly more through bundles while maintaining stable individual sales, the bundle is likely generating incremental demand. However, if individual product sales drop sharply after bundle launch, it may indicate product cannibalization.

2.2 Shopify bundle apps with built-in analytics

While Shopify’s native analytics mainly focuses on order and product sales, bundle apps help you track how customers interact with bundle offers throughout the buying journey.

A popular example is BOGOS (5.0 ⭐- 3,400+ users) – one of the most widely used bundle and promotion apps on the Shopify App Store. The app provides a dedicated analytics dashboard that helps merchants monitor bundle performance in real time. Compared to standard Shopify analytics, bundle apps often offer more granular performance metrics tailored to promotional campaigns.

Key bundle metrics:

• Total order revenue – the total revenue from orders that include bundles and any other offers.
• Total bundle revenue – revenue generated from bundles only.
• Orders with bundles – the number of orders that contain bundle offers.
• Average order value (AOV) – the average value across all orders during the selected time period.
• Add-to-cart value – calculated by dividing total bundle revenue by the number of times bundles were added to the cart.
• Total bundles purchased – the total number of bundles successfully purchased.

Bundle conversion funnel

This visualizes how customers move through the bundle purchase journey. A typical funnel looks like this:

• Bundle view – the total number of times customers viewed the bundle offer.
• Add to cart – how many times the bundle was added to the cart.
• Orders – the number of completed orders that include the bundle.

By analyzing the conversion rate between each step, merchants can quickly identify where customers drop off in the funnel.

For example:

• If bundle views are high but add-to-cart is low, the offer may not be compelling enough.
• If add-to-cart is high but orders are low, there might be friction during checkout.

Additional performance insights:

Bundle analytics dashboards also often include supporting reports and visualizations, such as:

• Bundle revenue charts showing revenue trends over time
• Orders with bundle charts to track bundle purchase trends

• Order lists that show which orders include bundle offers and the type of bundle purchased

These insights help merchants continuously optimize their bundle strategy by testing:

• bundle pricing
• bundle composition
• bundle placement on product pages or upsell widgets

Overall, bundle apps with built-in analytics offer a more detailed, actionable view of bundle campaign performance, helping merchants refine their offers and improve conversion rates.

2.3 Profit analytics tools

For larger Shopify stores, bundle performance should be evaluated not only by revenue but also by profitability. A bundle may increase sales but still reduce margins if discounts, product costs, shipping, and ad spend are not considered.

Profit analytics tools help merchants:

• Measure bundle contribution to total revenue
• Analyze profit margin by product or bundle
• Track customer lifetime value (LTV) to see if bundle buyers generate more long-term revenue

Below are 3 popular profit analytics tools used by Shopify merchants.

These tools are especially useful when:

• Your store is running multiple marketing channels
• You spend significantly on paid advertising
• You want to understand true unit economics, not just revenue

3. Tips to improve Shopify bundle performance

• Test bundle pricing: Do not assume a bigger discount will always perform better. Try a few price points such as 5%, 10%, or a fixed amount off, then compare conversion rate, AOV, and margin to find the level that lifts revenue without cutting profit too much.
• Test bundle composition: The best bundle is usually the one that feels useful, not the one with the most items. Start with products that naturally go together, then test different combinations to see which set gets more adds and fewer abandoned carts.
• Highlight savings clearly: If customers cannot see the value fast, the bundle is easier to ignore. Show the original total price, the bundle price, and the amount saved in a simple format so the benefit is obvious at a glance.
• Place the bundle near the add to cart area: A good bundle offer should appear when buying intent is already high. Put it close to the product price, variant selector, or add-to-cart button so shoppers can evaluate the offer without extra steps.
• Use post-purchase bundles: Some shoppers do not want to make all decisions before checkout. A post-purchase bundle can work well because the main order is already complete, so the shopper is more open to adding another relevant offer with less friction.

4. Bottom line

In short, bundles only work when you measure them properly. Track metrics like conversion rate, AOV impact, and bundle revenue to see whether your bundles actually increase sales or just add discounts. Once you have the data, it becomes much easier to optimize pricing, product combinations, and placement.

5. FAQs