Cashing in on Bundles – How eCommerce Retailers Can Drive Revenue Growth with Strategic Product Bundles
Overview
Product bundles may not be a novel concept, but they have evolved significantly over time and have proved to be versatile—finding applications across sectors such as fashion, bookstores, tech, beauty, travel, and many more. They present a strategic avenue to increase the number of items a customer adds to their cart, which translates to a higher order value.
When adopting product bundling on your product detail page (PDP), it’s imperative to carefully consider product selection for the bundle, the bundle’s composition, and the steps involved in the implementation process – each a vital contributor to the pursuit of elevated AOV.
- Bundle Products: Essential questions include – Which products to bundle? Can the process be fully automated? Do they require compatibility checks? Does it require merchandising? What form of shopper affinity do you aim to drive?
- Bundle Composition and Layout: How many products should the bundle include? Should the consumer have the option to customize the bundle? Should the bundle display separate groups with alternatives?
- Implementation: Will your in-house developers or third-party integrators develop the bundles on the PDP? Either approach involves backend development to ensure product bundles can be added to the cart, along with front-end development for displaying the bundles in potentially editable, appealing formats.
With Algonomy Recommend™, it’s possible to create and manage comprehensive, effective, and personalized product bundles, simplifying the entire process and ensuring optimized results.
Advanced Algorithms for Product Bundling
Over the years, we have developed algorithms and functionalities that offer customers much more than the conventional ‘Frequently Bought Together’ bundling. Depending on specific business needs, there are several options to choose from for generating optimal product bundles.
Configurable Strategies
Algonomy’s Configurable Strategies allows non-technical users to design their algorithm or strategy by selecting from pre-built models and customization options. This flexibility ensures precise creation of product bundles. This functionality provides the ability to select the AI model to generate the bundle products, apply desired shopper affinity, and adhere to any additional merchandising requirements like restrictions, boosting, etc.
Advanced Merchandising
Algonomy’s Advanced Merchandising utilizes catalog product attributes, enabling merchants to design a personalized shopping experience with their desired level of control. It offers enhanced control over the bundling process for a more tailored outcome.
This includes determining the exact number of products from a certain category, 1WorldSync (formerly CNET) compatibility for the electronics vertical, custom compatibility mapping that enables clients to use their own compatibility mappings to pair compatible products, and creating bundle groups that allow the presentation of alternatives.
Data Science Workbench
Our platform also provides Data Science Workbench, a tool that allows for the creation of custom product recommendation strategies.
For instance, by using the tool, businesses can integrate any external data—such as proprietary complementary data e.g. “complete the look” information or data to rank recommendations on e.g. offline sales—with existing behavioral information and tailor their product bundles just the way they want, based on any shopper affinity.
Bundle Composition, Layout, and Implementation
Algonomy-powered bundles ensure the most relevant bundled products for the shopper by applying personalization. However, keeping the principle of ‘the client is king’ paramount, one can choose for the bundles to be “editable” by providing selected alternatives for groups of products.
Alternatively, consumers can be given the power to “build their own bundle” from the suggested products – the level of customization rests in your control.
Changes or additions to your PDP usually require significant development effort, resources, and time. With the addition of innovative functionalities like Algonomy’s Dynamic Experiences, this burden is lifted. Entire bundles can be designed, created, and added to your site directly from the Algonomy portal, reducing the operational demands on your team.
In summary, Algonomy’s multifaceted solution streamlines the process of creating and managing product bundles, ensuring relevant product recommendations, boosting customer engagement, and ultimately driving sales as the use cases below illustrate.
1 Use Case 1 – Small Change, BIG Impact
Our client, an established player in the bookstore vertical, had been utilizing a basic “Frequently Bought Together” bundle configuration based on a legacy “out of the box” algorithm. Looking to increase their Average Order Value (AOV), they turned their focus on enhancing their bundle setup.
Instead of immediately delving into the complexities of bundle composition and layout, which would necessitate changes in the implementation component, they decided to start out with refining the bundle algorithm.
A new configurable strategy was created focusing on an “Author” targeted algorithm, coupled with shopper affinity. The model chosen for this strategy was the Attribute Best Seller model, with the Author name selected as the attribute to seed off.
In addition, a dedicated affinity configuration was applied with weight given to the category and publisher attributes, ensuring that the bundle shows the most relevant books of the same author based on the shopper’s affinity with publishers and categories viewed and purchased in the past.
The impact of this minor tweak was instant and significant. As illustrated in the chart below, there was a noteworthy increase in their Key Performance Indicators (KPIs) for their bundle performance:
- Click-Through Rate (CTR) saw an impressive lift of 76%.
- Items per Thousand Views (IPVm) increased by 40%.
- Revenue per Thousand Views (RPVm) spiked by 16%.
This case demonstrates how adjusting one aspect of the bundling configuration, in this case refining the bundle algorithm, can significantly drive critical success metrics. Algonomy’s dynamic solutions provided the agility and responsiveness to achieve these outcomes.
2 Use Case 2 – The Power of Compatibility
In tech-related verticals, compatibility between the main product and accessory items is crucial. Our client from the office supplies vertical recognized this and utilized their external data to guarantee compatibility between printers and their associated ink and toners.
With the primary goal of increasing sales, they successfully implemented ‘automatic’ bundles on most categories using Algonomy’s out-of-the-box cross-sell and upsell algorithms. This meant simply utilizing strategies already enabled for their PDP and having Algonomy determine automatically which strategy to play where and when to obtain the best products to recommend in the bundles.
However, when it came to the Printer category, custom solutions were required in order to ensure only compatible cartridges were presented in the bundles.
Using Algonomy’s Data Science Workbench, the client could construct custom algorithms based on their external data. The data uploaded to Algonomy, consisting of lists of compatible product IDs, helped create cross-sell and upsell algorithms.
This approach guarantees that the suggested bundles for printers consist only of compatible ink and toner sets and, at the same time, allows presenting shoppers with bundles of ink cartridges of different colors or yield capacities.
Compared to the regular cross-sell recommendations on these Printer category pages, the results of the compatible bundles were astonishing:
- CTR is 200% higher on the bundles, more than doubling the regular cross-sell compatible recommendations.
- Items per Thousand Views (IPVm) from the bundles is 162% greater.
- Most impressively, Revenue per Thousand Views (RPVm) is 400% higher, quadrupling the revenue from bundles compared to the regular cross-sell compatible recommendations.
This case demonstrates the immense potential of Algonomy’s customizable solution when it comes to creating unique bundle strategies, by capitalizing on data and ensuring compatibility.
“Our previous manual bundle solution was not scalable or sustainable long-term. Algonomy helped implement automated product bundles, leading to a jump from 4% to 80% product coverage, minimising internal maintenance effort and allowing a focus shift to optimisation. We’re really encouraged by the initial results and look forward to building on this together with Algonomy.”
Senior Manager of Conversion Rate Optimisation & Tooling
4 Use Case 3 – Effortless Bundle Implementation and Testing Through Algonomy Portal
Our customer in the health and beauty sector wished to implement product bundles but felt challenged due to resource constraints for backend and front-end development.
They required a solution that allowed them to:
- Create bundles with the look and feel of their Product Description Pages (PDPs)
- Restrict the bundle offerings to certain categories
- Test bundle performance against a non-bundle PDP variant
Algonomy’s Dynamic Experiences functionality proved to be a game-changer. It helped the client set up bundles independently, fitting their unique requirements and constraints. For any additional technical skills, our consultants provided the necessary support for fine-tuning layouts or incorporating custom JavaScript, all done seamlessly via the portal.
The Multivariate Test (MVT) capability, intrinsic to Algonomy’s Dynamic Experiences, simplified the process of setting up a control experiment. The client easily configured a 50/50 test to compare the performance of bundle placements versus pages without bundles.
The metrics from their test surpassed expectations, with an impressive lift in Revenue per Visit (RPV) and Average Order Value (AOV) by 8.42% and 8.24% respectively, showcasing statistically significant results with 99% confidence levels.
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