A Leading UK-based
Office Supplies Company
Drives Revenue Through
incremental revenue uplift
of Attributable Revenue
of Attributable Sales through cross-sell using Recommend™
Overview The client is an office supplies company that is owned by a European multi-specialist distributor of professional supplies and equipment. They started as a small store in Los Angeles in 1960 and now have operations in 11 countries. They are primarily focused on B2B sales, but also have a growing consumer clientele.
They have been partners with Algonomy since 2017. They chose Algonomy as their personalization engine for our expertise and specialization in the field.
The client’s key objectives are to drive customer engagement and incremental revenue by increasing repeat purchases and relevant cross-sells.
They have made a strategic investment in cross-sell recommendations because they drive up average order values and incremental revenue.
They activated Algonomy’s Recommend™ and Engage™ personalization engines to be able to deliver the right and most relevant product recommendations at various touchpoints of their customer’s journey with their website.
Using Recommend™, the client is able to deliver the right product recommendations on the add-to-cart page, product pages, and even on the homepage.
Transforming Product Recommendations
The platform leverages Algonomy’s Xen AI to provide context-aware recommendations based on both user behaviors and affinities and merchandising parameters. It is able to deliver recommendations based on factors more likely to increase relevance for the customer and revenue for the business.
With over 150 pre-built strategies such as visually similar products, compatible products, cross-sell, upsell, and top sellers, businesses can choose to deploy the strategy that is right for them. In addition, custom strategies can also be created for niche business requirements.
Deploying Cross-Sell Strategies Effectively
The client is keen on making cross-sell work, and for very good reason. The incremental revenue this strategy can drive is remarkable. Of the 10% attributable revenue achieved using the Recommend™ platform, 40% is because of cross-sell. Customers like seeing complementary products after adding a product to cart because it makes their purchase journey easier.
The client uses advanced merchandising to generate compatible cross-sell product lists. They collaborate with Algonomy to build custom strategies using the Data Science Workbench, using compatibility data to recommend complementary products in each product family.
For example, if a customer adds a printer to cart, the recommendation engine dives into the merchandising data to bring up inks and toners that are compatible with the model added to cart.
In addition, they use the replenishment strategy to recommend products that the user has previously purchased and is likely to regularly re-purchase. Based on this algorithm, personalized models are built for customers and the strategy is deployed on the Cart page.
They also use advanced merchandising and purchase co-occurrence strategies to create automated product bundles on the product page. This means they are able to combine products that are complementary to each other (such as printers and inks or pencils and erasers) or frequently bought together, and show them as a bundle with a nominal price markdown to entice customers to buy the bundle and therefore increase AOVs.
The client also combines Engage™ with Recommend™ to show personalized category tiles on the homepage. These category tiles take into account customer affinities, and the images shown on the category tiles are based on the customer’s previous purchases.
Moreover, the client uses advanced merchandising rules in the Algonomy personalization engine to create compatible and alternative product recommendations that can be shared across their enterprise systems via custom data extracts. This helps them create product bundles and relevant recommendations on other channels such as in-store and catalogs.
Algonomy also creates several custom monthly reports for the client—at overall business level and at country-specific levels. These reports help them track and measure the value and benefits of personalization across the customer journey in each country.
The client uses Algonomy’s personalization products on their websites in eight countries because of the platform’s superior ability to recommend the right and most relevant products to customers. These smart recommendations also help the client considerably increase customer engagement and brand loyalty.
Algonomy continues to help the client drive personalization that caters to their business goals and drives conversions up. Currently, they are working with Algonomy to deploy more content personalization strategies via the Engage™ platform.