Marketplaces are highly dynamic and multi-category environments where customer needs range from fashion to electronics, home goods, and baby products. Shoppers often compare multiple sellers, search for the best deals, and expect a fast, relevant discovery experience.
Effective recommendations in marketplaces should:
Guide users quickly to the most relevant options.
Build trust by consistently surfacing accurate and personalized results.
Maximize cross-sell and upsell opportunities across diverse product types.
What you can achieve with Smart Recommender
Personalized discovery across verticals
Surface the most relevant products by leveraging user affinities (e.g., category, brand). Tailor each user’s homepage to reflect unique browsing and purchase behavior.
Boost engagement with marketplace-wide trends
Highlight platform-wide popularity with features like “Bestsellers” or “This Week’s Top Deals” to create social proof and urgency, especially for first-time visitors.
Drive loyalty to preferred sellers or brands
Reinforce trust by prioritizing products from sellers or brands a user has previously purchased from—especially valuable in multi-seller marketplaces.
Recover the journey with the recently viewed
Re-engage returning shoppers by showcasing products they browsed in past sessions, ideal for long or interrupted purchase journeys.
Cross-sell with complementary items
Increase AOV by recommending accessories or related products on product and cart pages.
Category-specific merchandising at scale
Adapt recommendations to various verticals (e.g., tech, fashion, home) with category-level and dynamic filters.
A/B test to optimize category strategies
Experiment with recommendation logic, widget placement, and personalization depth across verticals or sellers to uncover high-converting approaches.
Walkthrough: Boosting AOV with Cross-Sells
Increasing Average Order Value (AOV) in a marketplace means guiding users toward relevant add-ons that complement their purchase. Because marketplace shopping often spans multiple categories, effective cross-sell strategies are essential.
In this example, we’ll walk through how to test two cross-sell categories on smartphone product pages—Phone Accessories versus Extended Warranty—to see which drives a greater lift in AOV.
1. Create your Recommendation Strategy
It's time to create your first recommendation strategy. Navigate to the Recommendation Strategies and click Create.
Select your page type as Product Detail Page.
Select your algorithm as Purchased Together to recommend suitable products for cross-selling.
Enter the number of products you want to recommend.
Exclude the recently purchased products in the last 4 weeks to keep your customer engaged.
Add a filter for the category attribute to display recommendations from the “Phone Accessories” category.
Add a filter for the model attribute to display suitable phone accessories recommendations from the same model as phone model + matches the item they're currently viewing.
Make sure all the attributes you want to filter are included in your product catalog and marked as filterable. You can create a new custom attribute for “Phone Model” from Product Attributes page.
Then, create the second strategy that you want to test against.
Select your page type as Product Detail Page.
Select your algorithm as Purchased Together to recommend suitable products for cross-selling.
Enter the number of products you want to recommend.
Exclude the recently purchased products in the last 4 weeks to keep your customer engaged.
Add a filter for the category attribute to display recommendations from the “Phone Warranty” category.
2. Launch your campaign
Now, launch your first campaign using your strategies.
Go to the Web Smart Recommender page and click Create.
Select your integration method for the widget.
On the Segments step, pick the audience.
For this example, you can select customers with a low AOV under Purchasing Behavior and set your threshold.
On the Rules step, decide where and when to show your campaign.
Use Page Rules to target the product detail pages of phone products.
On the Design step:
Assign your two strategies to the variants.
Assign traffic allocation for each variant.
Now you’re ready to design your widget. Click Edit Design to open the Advanced Product Card Designer. Here, you can customize your product cards however you like.
Make sure all the attributes you want to display are included in your product catalog. If you need to show more information on your product cards, you can create custom attributes from Product Attributes page.
After finalizing your campaign design, the next step is to select the locales and stores where you want the campaign to appear.
Once your targeting is set:
Review the campaign details.
Confirm that all settings match your objectives.
Click Launch to activate your first campaign.
3. Track your campaign metrics
You’ve launched your campaign—great work! Now it’s time to track its performance.
Go to the Smart Recommender Analytics page.
Locate your campaign under the Campaign and Variant Metrics table. Once the experiment duration ends, click your campaign name.
Compare key metrics, including Direct Revenue, Average Order Value (AOV), and Conversion Rate.
You can see which product category—phone accessories or extended warranty—led to higher AOV for low-spending customers.
If one variant is clearly winning, adjust the traffic allocation to 100%. This ensures the best-performing strategy receives all traffic and maximizes impact.
You can also test and compare additional cross-sell strategies by adjusting the rules and filters based on other product categories to discover which combinations drive the most value.
4. Optimize your campaigns
Once your campaigns are live and running, it’s time to review results and apply data-driven improvements.
Go to the Smart Recommender Analytics page.
Evaluate campaign performance based on engagement metrics.
Track Engagement Funnel Metrics: Understand how users interact with your recommendations at every step. View product impressions, clickthrough rate, add-to-cart rate, and conversion rate for each campaign to pinpoint where you’re driving engagement and where there’s room to improve.
Compare Campaign and Variant Performance: Use the Campaign and Variant Metrics table to review key KPIs like AOV, Conversion Rate, and Direct Revenue. Identify which strategies are delivering the best results and refine or scale your winning variant accordingly.
Analyze Product-Level Impact: Visit the Top 100 Product Analytics to see which products are performing well within your campaigns. Consider giving extra visibility to low-performing but strategic items by highlighting them in future recommendation widgets.
Review Category Trends: Use the Category Analytics view to assess which product categories drive the most conversions. You can prioritize high-performing categories to maximize conversions or spotlight underperforming categories to help boost their visibility and performance.
Use cases based on the page types
Home Page
Seasonal highlights
Surface seasonally relevant collections like “Back to School,” “Summer Tech Deals,” or “Winter Warmers” that align with seasonal shopping intent.
Create a strategy with the Most Popular algorithm to highlight top-viewed seasonal products.
Enable the “Enhance recommendations based on Attribute Affinity” toggle to personalize by user preferences (e.g., electronics vs. fashion).
Add Season + is + Back to School (or your seasonal tag) filter to promote items ideal for the current season.
Use a custom product attribute like Season to tag products with “Summer,” “Holiday,” “Black Friday,” etc. You can then use this attribute to target seasonal collections in your recommendations.
A/B test widgets widget placement (hero vs. scroll area) or visuals (seasonal icons, banners) to boost engagement.
Recently viewed items
Re-engage returning shoppers with items they’ve explored before, like sofas, nightstands, or office chairs.
Create a strategy with the Recently Viewed algorithm to resurface these items.
Exclude already purchased products to avoid redundancy and boost conversion rates.
Segment for returning users to ensure the strategy targets the right stage in the funnel.
Try A/B testing with the User-Based algorithm to evaluate which drives more conversions on repeat visits.
Recently Viewed and User-Based are personalized algorithms that rely on a user's past behavior. To use them effectively, ensure your segments are set to returning users.
Product Detail Page
Complete the looks
Showcase complementary items that match the current piece, such as throw pillows, rugs, or coffee tables that go with the viewed sofa.
Create a strategy with the Purchased Together algorithm to recommend items commonly bought with the currently viewed product.
Filter by Category + is one of + Rugs, Coffee Tables, Side Tables, Cushions.
Keep affinity off to prioritize purchase behavior patterns over style preferences.
Use headlines like “Customers Often Add These” to encourage upselling and cross-selling.
Real-time style trends
Surface what other users are exploring after viewing similar furniture, such as trending chairs, after browsing desks.
Create a strategy with the Real-Time User Engagement algorithm.
Exclude recently purchased products.
A/B test attention-grabbing titles like “Trending Right Now” or “Hot Picks”.
More for your living room/bedroom/outdoor area
Encourage deeper discovery within the same room or furniture type.
Use the Trending Products algorithm.
Add filters:
Room Type + matches the item they're currently viewing.
Category + contains the currently viewing category's attribute.
Use the OR connector to expand recommendation logic.
Use attractive widget titles, like “More from This Category” or “Must-Haves.”
Create a custom “Room Type” attribute (e.g., Living Room, Dining Room, Office) in the Product Attributes page to support this logic.
Category Page
Deals on furniture in this category
Appeal to bargain hunters by highlighting deals in the specific furniture category.
Create a strategy with the Highest Discounted algorithm.
Add filter Category + matches the items in their currently viewing category (e.g., highlight discounted beds when on the beds category page).
Turn off attribute affinity to prioritize value.
Enhance product cards with discount badges, such as “-30%” or “Limited Offer.” Run A/B tests for widget placement (top vs. bottom of the page).
Best sellers in this category
Help users make confident choices by showcasing what’s popular among others in the same category.
Create a strategy with the Trending Products algorithm.
Apply Category + contains the currently viewing category's attribute filter.
If you’re using hierarchical categories (e.g., Living Room > Seating > Sofas), enable the "Expand category filter to next level" checkbox to increase the product coverage.
Keep “Enhance recommendations based on Attribute Affinity” toggle on to personalize recommendations based on style or color preferences.
Cart Page
Finish the set
Encourage customers to complete their room set by recommending matching side tables, lamps, or décor items.
Create a strategy with the Most Popular algorithm.
Add filter:
Category + is one of + Lighting, Side Tables, Wall Décor, Accessories.
Leave attribute affinity off to surface functionally complementary pieces rather than personalized aesthetics.
A/B test headers like “Complete the Look” vs. “Don’t Forget These Final Touches.”
Boost to free shipping
Increase AOV by encouraging customers to reach your free shipping threshold with attractive add-ons.
Create a strategy with the Checkout Recommendation algorithm with a spend threshold (e.g., 500 USD for furniture).
No filters required, attribute affinity is optional.
Display a visual indicator, such as “Top up to 500 USD for Free Delivery!” with products priced just under that amount.
Alternatively, use the Purchased Together algorithm to display complementary products that naturally increase order value.