Overview

Best Sellers in Category recommendations surface the most-purchased items in a specific category from your catalog, based on aggregated purchase data over a selected time period. Unlike Best Sellers, which ranks items across the entire catalog, Best Sellers in Category scopes the ranking to a defined category — so a best-selling sofa ranks above a best-selling lamp even if the lamp has higher catalog-wide purchase volume.

Because Best Sellers in Category rely on aggregated purchase data rather than individual user history, they work for all users. The category is not fixed when you create the strategy. At serve time, it is resolved from a constant value, a user property, or, in the case of Live campaigns, a triggering event property. This means the same strategy can serve different categories without reconfiguration.

Use Cases

Best Sellers in Category recommendations work best when category-scoped, purchase-driven discovery is needed, as follows:

• Category pages and promotional email campaigns: Highlights top-performing products within a specific category. For example, a category-specific email featuring the top-selling items in the Skincare category helps subscribers shop with confidence.
• Push notifications: Re-engages users with category-relevant best sellers. For example, a push notification to users who have browsed the Home Appliances category, highlighting the most purchased items in that category over the past week.
• SMS campaigns: Drives category-specific conversions through social proof. For example, an SMS to opt-in users featuring the three best-selling products in the Footwear category ahead of a weekend promotion.
• Reliable fallback slot: A dependable default when a primary strategy cannot return sufficient results within a category.

Strategy

Best Sellers in Category recommendations rank items based on total purchase activity within a defined category scope over a specified time window.

During setup, you select the purchase event that defines what counts as a sale and configure the catalog columns that determine how category groupings are identified.

At serving time, items are retrieved within the requested category and ranked from highest to lowest by total purchase frequency within the configured window. The category scope is provided when the recommendation is requested, so the same strategy can serve multiple categories without separate configurations. For example, a single Best Sellers in Category strategy can return the most purchased items in Furniture for one campaign and in Lighting for another.

Common interaction events include:

Required Inputs

The following inputs are required:

Create Best Sellers in Category Strategy

This section helps you set up a strategy that surfaces the most-purchased items in a specific category from your catalog.

Prerequisites

Before you begin, check if the following are in place:

• A catalog is uploaded and active.
• At least one purchase event is being tracked, such as Order Placed or Charged.
• The tracked event references the same item ID as the catalog identity column. If they do not match, purchases cannot be attributed to catalog items.
• The catalog contains at least one column suitable for category grouping that has a limited number of distinct values. Columns with a high number of unique values are not supported.

Set Up Best Sellers in Category Recommendation

This section walks you through the steps to create a Best Sellers in Category strategy. Let us take an example: an apparel retailer wants to surface the most purchased items in the Apparel category over the last 30 days.

1. Select Strategy Type
2. Select Catalog
3. Define Consideration Criteria
4. Define Catalog Columns for Category Grouping
5. Map Catalog Column to Event Property
6. Enter Basic Details

Select Strategy Type

Select Best Sellers in Category as the strategy type.

Select Catalog

Select the catalog to use. The catalog must be active and contain the items you want to recommend. For example, select the catalog containing your apparel inventory.

Define Consideration Criteria

Pick the single event that defines a purchase within the category. This determines what gets counted toward the ranking.

For example, select Charged as the purchase event and set the lookback period to Last 30 days. This tells the system to count purchases from the past 30 days when ranking items within each category.

You can click + Filter to apply property filters that narrow the number of purchases counted. For example, filtering Charged by Gender = Female counts only purchases from female users when identifying best sellers within a category.

Define Catalog Columns for Category Grouping

Select the catalog column that defines how category groupings are identified. Items are grouped by the distinct values in this column, and the requested category value at serve time determines which group is returned.

For example, select Best by Category to group items by their category values. This allows you to retrieve the most-purchased items in the Apparel category or any other category, independently, using the same strategy.

Map Catalog Column to Event Property

The catalog column you select must be the column designated as the unique item identifier when setting up the catalog. This is the column the engine uses to match the event to the correct catalog item.

For example, map the catalog identity column to the Product ID event property of the Charged event..

After setting up the Catalog & Criteria tab, click Next to enter the following basic details:

After adding these details, click Save. Once the strategy is saved and purchase events are evaluated, the strategy becomes Active and can be used for campaign personalization.

In this case, the strategy surfaces the most-purchased items in the Apparel category over the past 30 days. Because no individual user history is required, the ranked list is consistent for all users browsing the same category, making it suitable for a category landing page, a category-specific push notification, or an SMS campaign that drives category-level conversions.

Personalize Campaign Using Recommendation

Once the strategy is active, you can use it to personalize recommendations in your campaigns. To configure recommendations within a campaign, click Personalize to open the Set up Personalization panel, then select the Recommendations tab.

Configure the following:

Strategy

Select the primary strategy to use for recommendations. For example, select "Best Selling Apparel Last 30 Days" to surface the most-purchased apparel items for users browsing the category page.

After selecting the strategy, configure how the Category scope is passed at serve time:

Optionally, enable Fallback Strategy to specify one or more fallback strategies that activate when the primary strategy cannot return enough items. Fallback strategies are evaluated in order of priority, with the last fallback used only if all preceding strategies return insufficient results. Fallback items are deduplicated against the best-seller results before being returned.

Inclusion Criteria

Define rules to restrict which catalog items are eligible for recommendation. You can add Catalog-Based Rules to filter by catalog attributes or Event-Based Rules to filter by user behavior. For example, adding a catalog-based rule Gender = Female ensures only women's products appear in the recommendation block.

Exclusion Criteria

Define rules to explicitly remove certain catalog items from recommendations. For example, adding a catalog-based rule Brand = Wrangler ensures Wrangler-branded products do not appear in the recommendation output.

Final Outcome

Specify how many items to recommend and which catalog attributes to return for each item. For example, set Items to Recommend to 3 and select Name, ImageUrl, Brand, Category, and Price as the Item Attributes to Recommend, so the campaign can render each product with its name, thumbnail, brand, category, and price. Once configured, click Apply to save the personalization setup for the campaign.

FAQs

What is the difference between Best Sellers in Category and Best Sellers recommendations?

Best Sellers ranks items across the entire catalog. Best Sellers in Category ranks items by purchase volume within a specific category, returning the most-purchased items in that category. Use Best Sellers for catalog-wide purchase leaders and Best Sellers in Category when the context is already scoped to a product category.

Are Best Sellers in Category recommendations personalized?

No. Best Sellers in Category recommendations reflect aggregated purchase data within a category and are not user-specific. The same ranked list is returned for all users requesting the same category. However, because the category scope is passed dynamically at serve time, you can use user attributes, such as a preferred category, to determine which category to request, making the experience feel contextually relevant.

How is the Best Sellers in Category score calculated?

Items are ranked by total purchase frequency within the requested category and configured time window. The most purchased item in that category appears first. All purchases within the window count equally — no time-decay weighting is applied.

What happens if there are not enough best-selling items in a category?

If the primary Popular in Category strategy returns fewer items than requested, the configured Fallback Strategy fills the remaining slots. Fallback items are deduplicated against the primary results, so you will not see the same title recommended twice.

The fallback dropdown only shows strategies that meet all the following requirements:

• Must be a Popular or Trending strategy
• Must use the same catalog as the primary strategy
• Must not itself be category-scoped

If you have not yet created a plain Popular/Trending strategy in the same catalog, the Add Strategy option remains empty even after selecting Fallback Strategy.

When should I use Best Sellers in Category recommendations?

Use this strategy when you want to highlight top-performing items within a specific category context, for example, on category landing pages, in department-specific campaigns, or as a social proof layer for category-based promotions.