Create a Recommendation Strategy for Market-Level Recommendations

Follow these steps to create a recommendation strategy with a recommendation type that draws on data from a market.

1. Click COMPONENTS in the top navigation bar, select Recommendations, and then click Recommendation Strategies on the Recommendations page.

   

2. Click CREATE RECOMMENDATION STRATEGY.

   

3. Select the option on the Recommendation Strategy Permission modal to make the strategy either global or local, and then click CONTINUE. For more information about how global and local settings work within strategies, see Global and Local Recommendation Strategies.

   You cannot change the strategy permission after you click CONTINUE.

   

4. Rename the strategy. Click the placeholder title, type the new name into the text field, and then click the green checkmark.
5. If you're creating a local strategy, select from Product Catalog which catalog the strategy should use.

   If you select a product catalog that is not the default one and you select Specific Market or All accounts for this retailer in step 7, then you cannot duplicate into any other account a recommendations experience that uses the recommendation strategy you're creating.

   

6. Select one of the following options from Recommendation Algorithm:
   • Top Selling by Purchase Count — Populates with products from the catalog with the highest purchase quantity; eligible for geographic targeting
   • Top Selling by Gross Revenue — Populates with products from the catalog with the highest gross revenue; eligible for geographic targeting
   • Most Viewed (Product Detail Page) — Populates with products from the catalog with the most product detail page views
   • Purchased and Also Purchased — Populates with products from the recommendation strategy's selected product catalog that other customers most frequently purchased along with the product(s) that meet the criteria that you select from Base Recommendation on Items and From when configuring the recommendation strategy
   • Viewed and Also Viewed — Populates with products from the recommendation strategy's selected product catalog most frequently viewed after viewing the product(s) that meet the criteria that you select from Base Recommendation on Items and From when configuring the recommendation strategy
   • Trending Items by Purchase Count — Populates with products that sold the most in the last 7 days compared to the 30 days prior; premium option

   You must contact your dedicated Customer Success Manager (CSM) to request that the Purchased and Also Purchased and Viewed and Also Viewed algorithms be made available for use with market-level data in a recommendation strategy.

   

7. Select Specific Market from Data comes from.

   The This account only option limits the strategy's algorithm to considering only data from the account in which you're building the strategy. The All accounts for this retailer options allows the algorithm to consider data from all accounts within your implementation.

   

8. Choose an option from Select a Market.

   

9. If you selected Purchased and Also Purchased or Viewed and Also Viewed in step 6, then select from Base Recommendation on Items the type of customer behavior on which to base the recommendations.

   

10. If you selected Purchased and Also Purchased or Viewed and Also Viewed in step 6, then select the session scope option from From on which you want to target the customer behavior. The options available in From are determined by the recommendation basis you selected in the previous step.

    The Last Carted Item(s) option only considers the very last product put into the cart. It does not consider multiple products.

    If you selected Viewed in the previous step, be aware that the page referenced by the Item(s) on the Page and First Item on the Page options in From is the page on which the recommendation action exists. All other options reference the behavior of the customer currently exposed to the recommendation action.

    

11. Select an option from Lookback Period if you selected a recommendation type that requires a time frame from which to collect historical data.

    

12. If you selected Top Selling by Purchase Count, Top Selling by Gross Revenue, or Most Viewed (Product Detail Page) as the strategy's algorithm, then select an option from Geographic Targeting if you want the strategy to consider the customer's location to populate the recommendations:
    • Country targeting — Only products relevant to the customer's country are recommended
    • Region targeting — Only products relevant to the customer's region, as defined by MaxMind's GeoIP2 database, are recommended

    

13. Optionally, toggle Randomize Results to YES if you want the order in which recommended products appear in the slider to be less systematized.

    

14. Optionally, add one or more recommendation filters to further refine the products included in the recommendations. For more information about filtering options and logic, see Filters in Recommendation Strategies.
    1. Click ADD FILTER.
    2. Select an option from SELECT ATTRIBUTE.
    3. Complete the filter equation.
    4. Repeat this step as necessary to add as many recommendation filters as you believe the strategy needs.

    

15. Optionally, configure up to five Boost and Bury filters to influence if recommended products that meet that filtering criteria are more likely (boost) or less likely (bury) to appear for the customer.

    Contact your dedicated Customer Success Manager (CSM) if you want the Boost and Bury feature enabled.

    1. Click ADD ATTRIBUTE.

       

    2. Select an option from SELECT ATTRIBUTE, and then complete the filtering equation.

       

    3. Select Boost to promote the products that meet the filtering criteria, or select Bury to suppress them.

       

    4. Adjust the slider to determine by what percentage the products that meet the filtering criteria are boosted or buried.

       You can only set the percentage using the slider and cannot type a number into the text field to the left it. Furthermore, you can only adjust the percentage in increments of 10.

       

    5. Repeat steps 15a through 15d to add up to four more independent Boost and Bury filters. See Using Multiple Boost and Bury Filters in Create a Recommendation Strategy to better understand how having more than one of this type of filter can impact the recommendations.

       

16. Click SAVE.

    

After you save the strategy, you can preview it from the configuration page in certain situations. See Preview a Recommendation Strategy for more information.