How to set up Search Personalization

PS -

When it comes to utilizing Raptor for Search Engines, Raptor tracks and understands the website behavior and integrates to the Search Engine in two ways: 

 

 

ProductCatalogueRank

 

Firstly, we can utilize the data from the website on an aggregated level with which we can sort the prioritization of products based on:  

  • Conversion rates 
  • Click popularity 
  • Trends 
  • Number of purchases 

 

We can add additional inputs such as stock level, margins etc. and we can combine the scores of the different inputs to come up with a sorting that meets your business needs (additional types of sorting such as Price high-low is also available).  

Typically, this output is made available via a static URL to a Blob Storage from which the output can be fetched in batch. The output can be updated daily or hourly. The output will simply contain the ProductId and a Priority that needs to be fetched and sorted ASCENDING. The output is available in CSV, XML or JSON.  

Example:  

[{"ProductId":"13243747","Priority":"1"}, 

{"ProductId":"13251010","Priority":"2"}, 

{"ProductId":"15791021","Priority":"3"}, 

{"ProductId":"15799363","Priority":"4"}, 

{"ProductId":"14711288","Priority":"5"}, 

. 

. 

. 

{"ProductId":"13243063","Priority":"14998"}, 

{"ProductId":"15791025","Priority":"14999"}, 

{"ProductId":"15799194","Priority":"15000"}] 

 

PersonalSearchBoost

Secondly, we can personalize the search engine output on a 1:1 level, which means that the results of the search engine accounts for and is personalized the users’ preferences. Depending on the configuration of the Search Advisor module, the output can be a combination of:  

- User’s purchase history 

- User’s clickstream history 

- Twin Analysis 

- Cross & Upselling 

- Trends 

Again, additional inputs such as stock level, margins, campaigns etc. can be accounted for. Whereas the first sorting is a batch file for all users, this, on the contrary, is a personalized real-time dynamic output that matches the preferences and expectation of the users. For our Search Advisor to work, we typically make the following endpoints available:  

  • Brand Recommendation Endpoint 

This module can be used to rerank a search result based on the individual customers preferences and affinity towards specific brands. 

API call for raptor 

https://api.raptorsmartadvisor.com/v1/{CustomerId}/GetSearchPersonalBrandIds/10/{apikey}?CookieId={CookieId}&json=true   

 

Output    

[{"BrandId":"A","Score":"2.153985"},{"BrandId":"B","Score":"1.441762"},{"BrandId":"C","Score":"0.999654"}] 

  • Product Recommendation Endpoint 

This module can be used to rerank a search result based on the individual customers preferences and affinity towards specific products. 

API call for raptor 

https://api.raptorsmartadvisor.com/v1/{CustomerId}/GetSearchPersonalProductIds/10/{apikey}?CookieId={CookieId}&json=true   

 

Output    

[{"ProductId":"A","Score":"2.153985"},{"ProductId":"B","Score":"1.441762"},{"ProductId":"C","Score":"0.999654"}] 

  • Category Recommendation Endpoint  

 

This module can be used to rerank a search result based on the individual customers preferences and affinity towards specific product categories.  

 

Example :  

API call for raptor 

https://api.raptorsmartadvisor.com/v1/{CustomerId}/GetSearchPersonalCategoryIds/10/{apikey}?CookieId={CookieId}&json=true   

 

Output    

[{"CategoryId":"A","Score":"2.153985"},{"CategoryId":"B","Score":"1.441762"},{"CategoryId":"C","Score":"0.999654"}] 

 

The exact API calls and the specific documentation for the different endpoints can be found in the Controlpanel under Search Advisor. The output of the different endpoints can be used as inputs in your Search Engine Index. The endpoints can be called with whatever frequency you need. 

Since the majority of Product Listing Pages (PLPs) are results of the Search Engine’s Index, implementing Raptor Search Advisor means personalizing the actual search results in the search bar and also the order with which products are presented across the different PLPs.  

 

If you have any further questions, please reach out to our support at support@raptorsmartadvisor.com. 

 

 

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