How does the Market Basket Analysis help build product bundles?
Learn the mechanics of how Airboxr recommends product bundles.
Saptarshi Nath
Jul 23, 2023
FAQ
Airboxr uses a Market Basket Analysis to help you identify which products are frequently bought together. The analysis also predicts the increase/decrease in the likelihood of product B being purchased if a customer has purchased product A. Here is how it works.
Create an Airboxr account and connect to Shopify to use this analysis.
When you run the Frequently Bought Together Hop, you will see a result like this.
Market Basket Analysis in Airboxr helps build product bundles by identifying products frequently bought together, using metrics like Support, Confidence, and Lift. This analysis aids in making business decisions on product bundling and recommendations.
For a simple interpretation of this data, think of columns C, D, E as:
C: Support: Percentage of total orders that contain both products A and B.
D: Confidence: Percentage of orders containing product A that also contain product B.
E: Lift: A measure of whether combining both the items increases (or decreases) the probability of making a sale. Lift is calculated by dividing the probability of selling product B in the bundle of AB as opposed to selling it alone. If this number is > 1, it means that buying product A increases the chances of buying product B within the same order. If the number is < 1, it means buying product A reduces the likelihood of buying product B.
Let's go into how you can make business decisions the basis of this data. So what decisions can you make with this data? You can use this:
To determine whether you should bundle products together.
To determine if you should show a recommendation to the user to add the second product to their cart.
Look at this output once again to understand how you can feed the information into your product sales strategy and ad campaigns.
In the above example, look at the first row—a high number of orders (19.56%) contain both bread and milk. And 88% of orders with bread also contain milk. Also, since the value of Lift is >1, milk has a better chance of sale to a user who has already decided to buy bread than on its own. So it makes sense to push milk to users who have already added bread to their cart.
With that logic, the last row—coffee mug + french press must be an even better bundle, right? Because 100% of coffee mug orders also contain french press and the Lift is much higher.
Actually, maybe not.
Because the bundle makes up less than 1% of your total orders. It might just not be enough to justify a bundle or recommendation.
To summarize, run this Hop every month (or if you have high volumes of orders, every two weeks). Then go through the following process:
Step 1: Is the Support (column C) high enough to justify a strategy? If yes...
Step 2: Look at the Confidence. If there is a high % of products A and B being bought together, then you may have a winner. But just to verify...
Step 3: Look at the Lift. Make sure it is greater than 1. Remember, higher numbers mean that product B has a higher chance of being sold with product A, than on its own.
If your product B passes through all of these steps, then go ahead and push product B whenever a customer adds product A to the cart.
Now that you know which products complement each other, what can you do? Here are some suggestions:
Prominent Cross-Sell Suggestions: After a customer adds Product A to their cart, prominently display Product B as a suggested cross-sell item on the cart page. Use eye-catching visuals, clear product descriptions, and a compelling call-to-action to encourage the customer to add it to their cart.
Discounts and Offers: Offer a discount or a special bundle price when customers add both Product A and Product B to their cart together. Display the potential savings prominently to motivate them to make the combined purchase.
Limited-Time Deals: Create a sense of urgency by offering limited-time deals or promotions for adding Product B to their cart immediately after selecting Product A. Emphasize that the offer is time-sensitive, which can prompt quicker decision-making.
Social Proof and Reviews: Showcase positive customer reviews and social proof for both Product A and Product B together to build trust and credibility. Seeing that others have successfully purchased both products together can encourage customers to do the same.
Personalized Recommendations: Utilize customer data and browsing history to provide personalized product recommendations. Recommend Product B based on their interests and previous interactions with similar products.
Free Shipping Thresholds: Offer free shipping for orders that meet a certain threshold, which includes both Product A and Product B. This can incentivize customers to add the second item to reach the free shipping requirement.
Product Bundling: Create pre-packaged bundles that include both Product A and Product B at a discounted price. Present these bundles as a convenient and cost-effective option for customers to add to their cart.
Upsell Pop-ups: Implement exit-intent pop-ups that offer a last-minute upsell for Product B with a limited-time discount when customers are about to leave the site or cart page.
Follow-up Emails: If a customer adds Product A to their cart but doesn't complete the purchase, send follow-up emails that remind them about Product B and the benefits of adding it to their cart. Include a direct link to the cart page for easy access.
Relevant Product Descriptions: Ensure that the product descriptions for both Product A and Product B highlight how well the products complement each other. Explain the advantages of using both products together to meet the customer's needs.