Recipes that use location data such as city, state, zip code and coordinates. Featured recipes (☆) are listed first. Expand a recipe to see its use cases, requirements and how it works.
Recipes for other industries: Cross-industry · Retail · Media · Marketplaces · Automotive · Online Learning
New users
For users who have recently joined or started engaging.
☆ Featured · City-state popular, trending, recent items
Popular or trending or recent items by city and state
☆ Featured · City-state popular, trending, recent items
Popular or trending or recent items by city and state
Use cases
Show case your most popular or trending offerings to your new customers by specific city and state.
Alert all users to recent additions to your catalogs by specific city and state.
Alert all users to seasonal or sponsored promotions by specific city and state.
Win back your inactive customers with exclusive but popular items by specific city and state.
Backfill other recommendations.
Requirements
Events with product_ids in payload.
Item Catalogs matching those product_ids.
City and State attributes in item catalogs.
Inputs
City-State Name.
One of the precomputed rankings for each city state combination.
How it works
Popular, Trending, Recent items based on all user activity on your sites and apps by each city and state.
City popular, trending, recent items
Popular or trending or recent items by city
City popular, trending, recent items
Popular or trending or recent items by city
Use cases
Show case your most popular or trending offerings to your new customers by specific city.
Alert all users to recent additions to your catalogs by specific city.
Alert all users to seasonal or sponsored promotions by specific city.
Win back your inactive customers with exclusive but popular items by specific city.
Backfill other recommendations.
Requirements
Events with product_ids in payload.
Item Catalogs matching those product_ids.
City attribute in item catalogs.
Inputs
City Name.
One of the precomputed rankings for each city.
How it works
Popular, Trending, Recent items based on all user activity on your sites and apps by each city.
Zipcode popular, trending, recent items
Popular or trending or recent items by zipcode
Zipcode popular, trending, recent items
Popular or trending or recent items by zipcode
Use cases
Show case your most popular or trending offerings to your new customers by specific zipcode.
Alert all users to recent additions to your catalogs by specific zipcode.
Alert all users to seasonal or sponsored promotions by specific zipcode.
Win back your inactive customers with exclusive but popular items by specific zipcode.
Backfill other recommendations.
Requirements
Events with product_ids in payload.
Item Catalogs matching those product_ids.
Zipcode attributes in item catalogs.
Inputs
Zipcode Name.
One of the precomputed rankings for each zipcode.
How it works
Popular, Trending, Recent items based on all user activity on your sites and apps by each zipcode.
Active users
For users who engage regularly.
Similar items to previous block with custom filters per selection
Use products in previous blocks to recommend similar items
Similar items to previous block with custom filters per selection
Use products in previous blocks to recommend similar items
Use cases
Use products in previous blocks to recommend similar items.
Multi block personalization based on recent activity.
Requirements
Events with product_ids.
Item catalogs with matching product_ids.
Inputs
Previous block name.
Number of items to consider from recent activity. Default value is 1.
Max radius within which properties to be recommended.
If insufficient properties, should zip and msa level backfill be considered?
Price variance percentage for filtering. Enter as number (e.g. 15 for 15%).
Should bathrooms also be matched? Currently matching for full bathrooms only. Not half baths.
How it works
Items related to previous block with backfills. Similarity is based on user session and transaction activity with other users. Various filters to be applied can be selected.
Feed type
Product-Product
Next best items
Post activity follow up alerts
Next best items
Post activity follow up alerts
Use cases
Post activity follow up alerts.
Abandoned search/browse/list follow ups.
Homepage recommendations.
Engagement recommendations.
Requirements
View or equivalent events with product_ids.
Item catalogs with matching product_ids.
Inputs
Recent activity timeline.
Number of items to be considered from recent activity.
Product similarity rankings based on other users with similary activity.
City-State level backfill. Select None, if not required. For recommended items count < return count.
Zipcode level backfill. Select None, if not required. For recommended items count < return count.
Site-wide backfill. Select None, if not required. For recommended items count < return count.
How it works
Top items to consider after recent activity based on users with similar history.
Feed type
Product-Product
Similar items to previous block
Use products in previous blocks to recommend similar items
Similar items to previous block
Use products in previous blocks to recommend similar items
Use cases
Use products in previous blocks to recommend similar items.
Multi block personalization based on recent activity.
Homepage recommendations.
Requirements
Events with product_ids.
Item catalogs with matching product_ids.
Inputs
Previous block name.
Number of items to consider from previous. Default value is 2.
Number of items to recommend per previous block item. Default value is 2.
City-State Level Ranking.
Zipcode Backfill. Select None, if not required. For recommended items count < return count.
Site-wide backfill. Select None, if not required. For recommended items count < return count.
How it works
Items related to previous block with backfills. Similarity is based on user session and transaction activity with other users.
Next best items
Post activity follow up alerts
Next best items
Post activity follow up alerts
Use cases
Post activity follow up alerts.
Abandoned search/browse/list follow ups.
Homepage recommendations.
Engagement recommendations.
Requirements
View or equivalent events with product_ids.
Item catalogs with matching product_ids.
Inputs
Recent activity timeline.
Number of items to be considered from recent activity.
Product similarity rankings based on other users with similary activity.
City-State level backfill. Select None, if not required. For recommended items count < return count.
Site-wide backfill. Select None, if not required. For recommended items count < return count.
How it works
Top items to consider after recent activity based on users with similar history.
Similar items to previous block with custom filters per selection v2
Use products in previous blocks to recommend similar items
Similar items to previous block with custom filters per selection v2
Use products in previous blocks to recommend similar items
Use cases
Use products in previous blocks to recommend similar items.
Multi block personalization based on recent activity.
Requirements
Events with product_ids.
Item catalogs with matching product_ids.
Inputs
Previous block name.
Number of items to consider from recent activity. Default value is 1.
Bedroom filter.
Price variance percentage for filtering. Enter as number (e.g. 15 for 15%).
Use user affinity categories to identify candidate products.
Max radius for search - WIll be used as default if user max radius or neighbourhood radius not available.
How it works
Items related to previous block with backfills. Similarity is based on user session and transaction activity with other users. Various filters to be applied can be selected.
Intermittently active users
For users who engage now and then.
New in building floorplans
Show new floorplans based on past user activity
New in building floorplans
Show new floorplans based on past user activity
Use cases
Show new floorplans based on past user activity.
Requirements
Events with product_ids.
Item catalogs with matching product_ids.
Inputs
Bedroom filter, property filter price filter to be applied.
Custom prioritization.
How it works
New floorplans in buildings user has previously engaged with filtered on basis of recent activity to show items with custom filters (price, bedrooms, property type) and stepped relaxation of filters as pre-configured.
Churned users
For users who have stopped engaging.
☆ Featured · Similar Items per alert attributes with custom filters per selection
Similar items per alert attributes set by user with custom filters…
☆ Featured · Similar Items per alert attributes with custom filters per selection
Similar items per alert attributes set by user with custom filters…
Use cases
Use alert attributes to recommend items that fit that at regular cadence via newsletter Use alert attributes to recommend items that fit when user visits app/website.
Requirements
Events with product_ids.
Item catalogs with matching product_ids.
User profile with alert attribute.
Inputs
Previous block / recent activity.
Custom filters (bedroom, price, property type).
Supplement with user affinity categories?
Custom Priority.
How it works
Items on the basis of alert attributes supplemented with recent activity products that are provided as previous block. Similarity is based on user session and transaction activity of all users. Various filters to be applied can be selected.
All users
For users at any lifecycle stage.
☆ Featured · Live content - similar items to seed_items
Use products in seed items to recommend similar items
☆ Featured · Live content - similar items to seed_items
Use products in seed items to recommend similar items
Use cases
Use products in seed items to recommend similar items.
Multi block personalization based on seed items.
Homepage recommendations.
Requirements
Events with product_ids.
Item catalogs with matching product_ids.
Inputs
Seed Items Array.
City-State Level Ranking.
Zipcode Backfill. Select None, if not required. For recommended items count < return count.
Site-wide backfill. Select None, if not required. For recommended items count < return count.
How it works
Items related to seed items with backfills. Similarity is based on user session and transaction activity with other users.
☆ Featured · Items based on user lat/long
To provide recommendations for new users with insufficient history
☆ Featured · Items based on user lat/long
To provide recommendations for new users with insufficient history
Use cases
To provide recommendations for new users with insufficient history.
Requirements
User profile with lat/long.
Product catalog with lat/long.
Inputs
User lat/long variables.
Radius for search.
How it works
Retrieve lat/long from user profile Find nearest products. Since this is meant for new users, there will be no filters as there will not be sufficient activity. For recent activity based recommendations, use other recipes.
Items matching user city attributes
Popular items matching user attribute joined on city attribute
Items matching user city attributes
Popular items matching user attribute joined on city attribute
Use cases
Popular / Trending items personalization based on specific user attribute.
Mix and match with pre-computed user rankings.
Daily / Weekly Newsletters.
User specific promotions / sponsored items.
Requirements
User attribute value matching city values from product catalog.
Inputs
User City Attribute Name.
City Ranking.
How it works
Popular items from user city attribute joined with item catalogs. The string attribute must match what is available in catalogs and are case sensitive.
Live content - popular items by city-state
Live content on site or in app when users are actively in session
Live content - popular items by city-state
Live content on site or in app when users are actively in session
Use cases
Live content on site or in app when users are actively in session.
Requirements
Live Content request payload with city & state.
Item Catalogs with matching city-state.
Inputs
City-State level rankings.
Name of event payload attribute for city & state.
Number of items to be recommended per city-state combination.
Side-wide Backfill. Select None, if not required.
How it works
Based on city & state in recommendation context, recommend other popular city-state items.
Items matching user zipcode attribute
Popular items matching user attribute joined on zipcode attribute
Items matching user zipcode attribute
Popular items matching user attribute joined on zipcode attribute
Use cases
Popular / Trending items personalization based on specific user attribute.
Mix and match with pre-computed user rankings.
Daily / Weekly Newsletters.
User specific promotions / sponsored items.
Requirements
User attribute value matching zipcode values from product catalog.
Inputs
User Zipcode Attribute Name.
Zipcode Ranking.
How it works
Popular items from user zipcode attribute joined with item catalogs. The string attribute must match what is available in catalogs and are case sensitive.
Live content - popular items by zipcode
Live content on site or in app when users are actively in session
Live content - popular items by zipcode
Live content on site or in app when users are actively in session
Use cases
Live content on site or in app when users are actively in session.
Requirements
Live Content request payload with zipcodes.
Item Catalogs with matching zipcodes.
Inputs
Zipcode level rankings.
Name of event payload attribute for zipcodes.
Number of items to be recommended per zipcode combination.
Side-wide Backfill. Select None, if not required.
How it works
Based on zipcodes in recommendation context, recommend other popular zipcode items.
Connect with Blueshift for personalized recommendations
Whether you're exploring new ways to use recommendation recipes or looking to design a custom model for your business, our team can guide you through the next steps.
Reach out to [email protected] or your Customer Success Manager (CSM) for assistance.
What's next
Learn how Recommendations Studio works and understand the workflow for creating personalized recommendations.
How Recommendations Studio works →