Grouping products in bundles can boost average order values and even conversions. The challenge is knowing which bundles perform the best.
Rather than guess, marketers can build a framework to:
- Measure bundle performance in terms of AOV and conversion rate,
- Identify high-performing bundles,
- Predict bundle outcomes.
Product Bundle Basics
An ecommerce bundle or kit is a group of products sold for a single price. Bundling is a marketing technique since the price of the group is generally lower than the sum of individual items.
Beyond improved AOV, bundling can spur slow-moving products and simplify purchasing.
Product bundles typically fall into several patterns.
- Quantity bundles, wherein buying three of the same item is less expensive than separate purchases. Examples are a five-pack of razors and a six-pack of Coke. Quantity bundles are sometimes “restricted,” meaning the item is available only in a group.
- Mixed-item bundles feature related items around a theme. Gift baskets, for example, are often mixed-item bundles.
- Sample bundles combine groups of the same product type, but in distinct flavors, scents, or similar. A beard oil kit containing spruce, pine, and lavender scents is an example.
- Category bundles let shoppers select products from a given category at a set price. Imagine three blouses for $99, for example.
The first step in measuring performance is to assemble and sell the bundles within a testing framework. Use Optimizely, VWO, or built-in A/B testing tools in some ecommerce platforms.
Design these experiments to include:
- Randomization to ensure shoppers are exposed to bundles in no particular order or method. Consider testing bundle configuration, type, or pricing.
- Control groups for a set of customers who don’t see any bundles to help measure their effect.
- Timeframe. A period long enough to obtain a statistically significant number of conversions but short enough to iterate and learn quickly.
Next, track performance, ensuring the tested bundles have unique SKUs or IDs. Monitor:
- Bundle(s) observed,
- Bundle(s) added to cart,
- Bundle(s) purchased,
- Total order value,
- Total items in the order.
The data may come from the A/B testing software, analytics, product experience tools such as Hotjar or Qualaroo, an ecommerce platform, or a combination.
Analyze the data at the end of each test period, examining performance metrics.
- Conversion rate. The number of times a product bundle was purchased divided by the number of times shown.
- Average order value for transactions containing the bundle.
- Bundle effectiveness score. A combined metric to track, say, volume and revenue — for example, the conversion rate times the AOV.
- Bundle comparisons. How the variations performed relative to each other.
- Bundle profit versus control groups to learn if the bundles increase sales of individual items.
- Customer segments to understand how particular bundles appeal to a given customer group.
- Seasonality to consider the impact of seasons on bundle performance. For example, do snowboard bundles sell better in the autumn, winter, or spring?
- Inventory levels. The effect of bundles on purchasing or warehousing.
- Reorder rate. How bundles impacted repeat sales.
Take what’s learned in initial product bundle tests to inform new approaches, optimizing for profit, sales, or AOV. This could include adjusting composition — changing the items in the group — or changing the prices.
Then elevate winning bundles by investing in advertising to drive traffic. A product bundle that is profitable and increases overall AOV or customer loyalty is likely more than worth the investment.