Retail Engine, 2026
From version 18.1
edited by Mariia Safronova
on 2026/09/07 11:49
Change comment: There is no comment for this version
To version 22.1
edited by Anastasia Zanina
on 2026/09/08 03:26
Change comment: Renamed back-links.

Summary

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1 -Main.Loymax_AI.WebHome
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16 16  * Achieve business objectives;
17 17  * Automate marketing activities and test hypotheses.
18 18  
19 -Product recommendations are generated using the [[Retail Engine AI>>doc:Main.Loymax_AI.WebHome]] module whose algorithms enable fast and accurate processing and analysis of large data volumes. Marketers and analysts can focus on developing business strategies while delegating technical big-data processing tasks to artificial intelligence for specific business purposes.
19 +Product recommendations are generated using the [[Retail Engine AI>>doc:Main.Retail_Engine_AI.WebHome]] module whose algorithms enable fast and accurate processing and analysis of large data volumes. Marketers and analysts can focus on developing business strategies while delegating technical big-data processing tasks to artificial intelligence for specific business purposes.
20 20  
21 21  Business goals achieved through personalized communications using product recommendations:
22 22  
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42 42  
43 43  Data sources for receipts, customers, and products from the product catalog used to generate product recommendations include the **DWH BI** data warehouse and/or the **ClickHouse SmartCom** database management system. This data is transferred to the **Retail Engine AI** module, where it is processed and product recommendations are calculated using ML algorithms. The resulting recommendations are then delivered via API to **data marts**. The **API-proxy server** validates incoming requests and formats responses for Smart Communications. **Smart Communications** retrieves responses from the **API-proxy server**, enriches them with data (images, product names, links, prices, etc.), inserts them into predefined templates, and sends mass messagings containing the generated product recommendations to customers.
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45 -|(% style="border-color:#ffffff; text-align:center" %){{lightbox image="product_recommendations_overview.png" width="1200"/}}
45 +|(% style="border-color:#ffffff; text-align:center" %){{lightbox image="product_recommendations_overview_1.png" width="1200"/}}
46 46  
47 47  Currently, 5 algorithms are available for generating product recommendations:
48 48  
product_recommendations_overview.png
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Created 2025/10/22 03:38
Last edited 2026/09/09 09:38

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