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Personalized Product Recommendations

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Level 2

I need some advice on the best way to proceed with this use case...

 

I have personalized product recommendations for each one of my customers in an offline CRM database that my sales team uses. I would like to be able to show these recommendations to the user when they visit my site. I have a login capability and I capture their ID in Analytics with an eVar that never expires. 

 

Ideally I would be able to create a segment that included all known visitors based the eVar that captures their ID. At which point I can create an experience for those users specifically and then showcase their recommended products on the page. I'm just not sure the best way to have the data for each user's recommended products available within the experience in Target.

 

To detail this a bit more... let's say this is the data for two customers:

 

User IdFirst NameLast NameRecommended Products
123456JaneSmithprod2,prod4,prod5,prod7
654321JohnSmithprod1,prod3,prod8,prod9

 

What would be the best way to have the data in the Recommended Products column available for display in Target. 

 

My preference is to not use mboxes and just use data upload capabilities. 

 

 

1 Accepted Solution

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Correct answer by
Community Advisor

I assume you are talking about the Recommendations product. It may not be the most elegant id, but you could create a product for each user id and upload your own custom criteria for recommendations.

 

https://docs.adobe.com/content/help/en/target/using/recommendations/criteria/recommendations-csv.htm...

 

In order for it to work, you would need a database of products:

 

https://docs.adobe.com/content/help/en/target/using/recommendations/entities/feeds.html

 

Only weird part will be that you need to pass that customer id in to Adobe Target as an entity.id parameter ... and now you have customer ids in your product database which doesn't scale super well if you have a bunch of users. 

 

Another idea would be to create a profile parameter for each of your users. Something like:

 

profile.recs = 'a,b,c,d,g,h,z';

 

And you could set up an automated personalization campaign to return products based on rules. This has scaling issues based on how many recommendations you have. 

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3 Replies

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Correct answer by
Community Advisor

I assume you are talking about the Recommendations product. It may not be the most elegant id, but you could create a product for each user id and upload your own custom criteria for recommendations.

 

https://docs.adobe.com/content/help/en/target/using/recommendations/criteria/recommendations-csv.htm...

 

In order for it to work, you would need a database of products:

 

https://docs.adobe.com/content/help/en/target/using/recommendations/entities/feeds.html

 

Only weird part will be that you need to pass that customer id in to Adobe Target as an entity.id parameter ... and now you have customer ids in your product database which doesn't scale super well if you have a bunch of users. 

 

Another idea would be to create a profile parameter for each of your users. Something like:

 

profile.recs = 'a,b,c,d,g,h,z';

 

And you could set up an automated personalization campaign to return products based on rules. This has scaling issues based on how many recommendations you have. 

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Level 4

@patrickb8312284 You could create a cutom criteria on Recommendations and use it within a Target Recommendations activity.

Since you want to go with the data upload capabilities, you could upload a CSV file to customize your recommendations.

 

More information on this can be found here: https://docs.adobe.com/content/help/en/target/using/recommendations/criteria/recommendations-csv.htm...

 

Regards,

Karan

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Administrator

@patrickb8312284 @karand53490614 @Eric_Vidana Join us tomorrow during the next Adobe Target Community Q&A Coffee Break, where Senior Adobe Target Product Manager, Rob Hornick, will be sharing insights and answering questions related to his areas of expertise, which include Recommendations, Auto-Target, Automated Personalization, and more on AI and Machine Learning. If you can't join, you can also post your questions for him now in the event thread and he will post his answer during the break tomorrow: https://adobe.ly/31VNuJI