Fashion is a trend-driven vertical shaped by seasonality, personal style, and timing. Shoppers often browse for inspiration or refresh their wardrobe for a specific occasion, and they respond well to personalized content and style-based groupings.
This article shows how to use Smart Recommender in Insider One to turn that inspiration into orders. It includes an A/B test walkthrough for outfit cross-sells and ready-to-use strategies for each page type.
Before you start: Make sure your product catalog includes the attributes this article filters on, such as Category, Brand, Season, and Style. Create missing custom attributes on the Product Attributes page and mark them as filterable.
What you can achieve with Smart Recommender
Seasonal collections
Feature trend-based or seasonal collections, such as "Spring Refresh" or "Cozy Fall Layers," on the homepage so shoppers see what is relevant right now.
Outfit pairings that grow the basket
Recommend complementary items on product and cart pages, such as shoes with dresses or jackets with tops, to raise average order value (AOV).
Trending products that create urgency
Highlight products that are gaining views and purchases this week, especially on product and category pages.
Personalized style picks
Use past purchases, views, and favorites to prioritize the colors, cuts, and categories each shopper prefers.
Re-engagement of inactive shoppers
Show returning shoppers styles tied to their history, for example, new denim for someone who bought jeans before.
Cart-page add-ons
Surface accessories, hosiery, or care products with "Complete the Look" prompts before checkout.
A/B testing
Test widget designs, headlines, and algorithm settings to find the approach that performs best on your site.
Walkthrough: Boost AOV with outfit cross-sells
Complete-the-look styling is one of the most effective ways to raise AOV in fashion. Shoppers often need help assembling an outfit, and coordinated suggestions encourage additional purchases.
This walkthrough tests two cross-sell strategies on dress product detail pages:
Variant A: Recommend shoes.
Variant B: Recommend bags.
Step 1: Create the recommendation strategies
Navigate to Recommendation Strategies and click Create. Configure the first strategy as follows:
Select Product Detail Page as the page type.
Select Purchased Together as the algorithm.
Enter the number of products to recommend.
Exclude products purchased in the last four weeks.
Add a filter for the category attribute: Category + is + Shoes.
Create the second strategy with the same settings and change only the category filter:
Category + is + Bags.
Note: Keep every other setting identical between the two strategies. If more than one setting changes, you cannot tell which change caused the difference in results.
Step 2: Launch the campaign
Navigate to Web Smart Recommender and click Create.
Select the integration method for the widget.
On the Segments step, select customers with a low AOV under Purchasing Behavior and set your threshold.
On the Rules step, use Page Rules to target the product detail pages of dresses.
On the Design step, assign one strategy to each variant and set the traffic allocation for each variant.
Click Edit Design to open the Advanced Product Card Designer and customize your product cards.
Select the locales and stores where the campaign appears.
Review the campaign details, confirm that every setting matches your goal, and click Launch.
Note: Every attribute you show on a product card must exist in your product catalog. To show more information, create custom attributes on the Product Attributes page.
Step 3: Track campaign metrics
Navigate to Smart Recommender Analytics.
Find your campaign in the Campaign and Variant Metrics table. When the test period ends, click the campaign name.
Compare Direct Revenue, Average Order Value (AOV), and Conversion Rate for the two variants. This shows whether shoes or bags raise AOV more for low-spending customers.
If one variant clearly wins, set its traffic allocation to 100% so every visitor sees the better strategy.
After you find a winner, test other pairings, such as belts, scarves, or jackets, by changing the category filter.
Step 4: Optimize your campaigns
After the campaign has run long enough to collect data, use Smart Recommender Analytics to improve it:
Engagement funnel: Review product impressions, click-through rate, add-to-cart rate, and conversion rate to see where shoppers drop off.
Campaign and variant performance: Compare AOV, Conversion Rate, and Direct Revenue in the Campaign and Variant Metrics table, then refine or scale the winning variant.
Product-level impact: Open Top 100 Product Analytics to see which recommended products perform best. Give extra visibility to strategic products that perform below expectations.
Category trends: Use Category Analytics to find the categories that drive the most conversions, and decide whether to prioritize them or promote weaker ones.
Use cases by page type
Home page
Seasonal picks
Show the most viewed products of the current season, personalized to each shopper's style.
Create a strategy with the Most Popular algorithm.
Turn on the Enhance recommendations based on Attribute Affinity toggle.
Add the filter Season + is + Fall to show items such as boots, sweaters, and trench coats.
If you do not have a Season attribute, create it on the Product Attributes page and tag each product.
Tip: A/B test the widget position (above the fold versus below the hero banner) or the headline ("Fall Must-Haves" versus "Cozy Up This Season").
Top sellers for new visitors
Give first-time visitors a quick view of your best-selling products.
Create a strategy with the Top Sellers algorithm.
Add the filter Category + is not one of + Accessories, Socks to keep low-price items off the homepage.
Target new users on the Segments step.
Recently viewed items
Remind returning shoppers of the products they looked at in earlier sessions.
Create a strategy with the Recently Viewed algorithm.
Exclude products the user already purchased.
Target returning users on the Segments step.
Note: Recently Viewed and User Based rely on each user's past behavior. Target returning users so these widgets always have data to show.
Tip: A/B test Recently Viewed against User Based to see which drives more repeat visits and conversions.
Product detail page
Picks based on recent browsing
Show each shopper products that match their most recent interactions, such as boots after they view a winter coat.
Create a strategy with the User Engagement algorithm.
Exclude recently purchased products.
Place the widget below the product description.
Tip: Try headlines such as "Picked for You" or "Pair It With These."
Complete the look
Show shoes, bags, and jewelry next to the dress the shopper is viewing.
Create a strategy with the Purchased Together algorithm.
Add the filter Category + is one of + Shoes, Bags, Jewelry. Optionally add a Style or Color filter.
On the campaign Rules step, add Product Category + is + Dress so the widget appears only on dress pages.
Place the widget directly above or below the Add to Cart button.
Tip: Test headlines such as "Styled for You" and "Complete Your Look."
More from this brand or style
Keep loyal shoppers browsing with more items from the same brand or style.
Create a strategy with the Most Popular algorithm.
Add two filters: Brand + matches the item they're currently viewing, and Style + matches the item they're currently viewing. Connect them with an OR connector.
If you need a Style attribute, create it on the Product Attributes page and tag products with values such as Boho or Streetwear.
Tip: Use dynamic widget titles such as "More from [Brand]" and A/B test the brand filter against the style filter to see which drives a higher click-through rate.
Category page
Trending in this category
Show what is trending in the category the shopper is browsing, such as dresses or boots.
Create a strategy with the Trending Products algorithm.
Add the filter Category + contains + the category they're currently viewing.
If your categories are hierarchical, select the Expand the category filter to include recommendations from the next category if there aren't enough products to display checkbox, so the widget still fills when the current category has few products.
Turn on the Enhance recommendations based on Attribute Affinity toggle.
Tip: Try headlines such as "Trending This Week" or "Shop What Is Trending."
Budget-friendly finds
Show the most discounted items in the current category to value-focused shoppers.
Create a strategy with the Highest Discounted algorithm.
Add the filter Category + matches + the category they're currently viewing.
Leave Attribute Affinity off. This keeps the focus on the discount.
Tip: Add discount labels such as "40% Off" to product cards and A/B test the widget at the top versus the bottom of the page.
Cart page
Complete the outfit
Suggest last-minute essentials such as tights, belts, or garment care products.
Create a strategy with the Most Popular algorithm.
Add the filter Category + is one of + Accessories, Underwear, Fashion Care, Jewelry.
Leave Attribute Affinity off. Practical relevance matters more than personalization here.
Tip: Test copy such as "Do Not Forget These Essentials" and test the widget above versus below the checkout button.
Reach free shipping
Show items that help shoppers reach your free shipping threshold.
Create a strategy with the Checkout Recommendation algorithm and set the spend threshold (for example, 100 USD).
No filters are required. Attribute Affinity is optional.
Tip: Add copy such as "You are 15 USD away from free shipping." If you do not offer free shipping, test Purchased Together to suggest commonly paired items, such as a blouse and trousers.