AI Recommendation Engine "ZETA RECOMMEND" Now Supports Multi-Angle Recommendation Display
ZETA Inc. has launched "Multi-Angle Recommendation" as an extended feature for its AI recommendation engine "ZETA RECOMMEND." This new feature enables diverse recommendation displays based on product data, genres, hashtags, user context, and behavioral characteristics. It aims to enhance the user's shopping experience by presenting various recommendation approaches in a freely scrollable format, similar to physical store displays, thereby increasing engagement with products and improving customer loyalty in the evolving retail media landscape.
📋 Article Processing Timeline
- 📰 Published: April 15, 2026 at 17:00
- 🔍 Collected: April 15, 2026 at 08:31
- 🤖 AI Analyzed: April 15, 2026 at 23:54 (15h 22m after Collected)
ZETA Inc. (Headquarters: Setagaya-ku, Tokyo; hereinafter "ZETA"), which provides the CX Improvement Generative AI Solution "ZETA CX Series" and supports the enhancement of customer experience value, is pleased to announce that its AI recommendation engine "ZETA RECOMMEND" now supports "Multi-Angle Recommendation" as an extended feature. This feature enables diverse recommendation displays based on elements such as product data, genres, and hashtags, as well as user context and behavioral characteristics.
Approaches to AI recommendations are not limited to highly personalized recommendations based on user attributes and context; recommendations that emphasize "discovery" (serendipity) and trends are also important. "Multi-Angle Recommendation" enhances the user's shopping experience and enables engagement with various products by displaying these multiple recommendation approaches in a freely scrollable format, much like displays or shelves in a physical store.
■ Background of Productization: Improving CX with AI Recommendations in the Retail Media Era
As e-commerce sites evolve into retail media, transforming from mere purchasing platforms into media where users can enjoy the shopping experience, the importance of user-product engagement is further increasing.
Our company has traditionally provided the EC product search and on-site search engine "ZETA SEARCH," the AI recommendation engine "ZETA RECOMMEND," the hashtag utilization engine "ZETA HASHTAG," the loyalty improvement engine "ZETA ENGAGEMENT," and the EC curation engine "ZETA BASKET," among others.
We believe that by seamlessly connecting these in future e-commerce sites, we can provide a more exciting shopping experience for users, thereby further enhancing CX. With this in mind, we have launched the "Multi-Angle Recommendation" feature.
This enables a wide variety of product suggestions on e-commerce sites, much like displays or shelves in a physical store.
For example, vertically, diverse recommendation patterns such as "recommendations by hashtag," "personalized recommendations by browsing history," "recommendations by popular products," and "user-curated recommendations" can be arranged. Within each recommendation pattern, a carousel-like horizontal recommendation can continuously display a diverse range of products.
Furthermore, users can freely set and reorder the vertical axis of recommendations, creating a more immersive shopping experience.
"Multi-Angle Recommendation," centered on our strengths in EC product search, hashtags, and AI utilization, is expected to reduce the operational burden on e-commerce sites and improve loyalty.
■ Features of "Multi-Angle Recommendation"
1. Improves user CX and contributes to increased site stay time by displaying various types of recommendations.
The type of recommendation a user desires varies depending on the timing. By displaying diverse recommendations, it becomes possible to enhance the user's customer experience and allow them to enjoy the purchasing experience itself as if they were in a physical store. Furthermore, by allowing users to customize the types of recommendations themselves, a high-quality CX is achieved.
2. Synergistic effects through collaboration with "ZETA CX Series"
To create diverse recommendations, it is crucial to utilize rich product data and user's 1st Party Data. The "ZETA CX Series" includes an EC product search engine, hashtag utilization engine, review/Q&A engine, and curation engine. By linking the product data and user behavior history handled by these with AI recommendations, a wide variety of recommendations can be realized.
In particular, hashtags can utilize not only product data and user behavior history but also trending words that other users are paying attention to, which is highly effective in improving the shopping experience.
Furthermore, by linking with the EC product search engine, it becomes possible to generate recommendations based on user search queries.
3. Advanced recommendation processing using AI
To utilize detailed product data, diverse user's 1st Party Data, and UGC from other users, the use of AI is essential. "ZETA RECOMMEND," which has many examples in major domestic EC sites and a strong advantage in AI utilization, proposes diverse and optimal recommendations to users, contributing to improvements in CVR (Conversion Rate), AOV (Average Order Value), and LTV (Customer Lifetime Value).
■ Purchasing Experience in the Agentic Commerce Era Provided by "ZETA RECOMMEND"
"Multi-Angle Recommendation" is expected to become an essential element in realizing retail media, which is an approach to utilize EC sites themselves as a place for users to enjoy. Furthermore, there is also the possibility of utilizing multi-angle recommendation displays as retail media advertisements, creating advertising utilization and revenue opportunities within the media. Please utilize this for the purchasing experience in the "Agentic Commerce" era, leveraging UGC and retail media.
ZETA will continue to provide beneficial services to users and EC site operating companies by leveraging its strength in AI-driven data analysis.
【Official SNS】
X Account
[ https://twitter.com/zeta_cx ]
Facebook Account
[ https://www.facebook.com/zetacom ]
【CX Improvement Generative AI Solution ZETA CX Series】
EC Product Search / On-site Search Engine ZETA SEARCH
[ https://zeta.inc/cx/products/zs ]
Hashtag Utilization Engine ZETA HASHTAG
[ https://zeta.inc/cx/products/zh ]
Retail Media Ad Engine ZETA AD
[ https://zeta.inc/cx/products/za ]
Review / Word-of-mouth / Q&A Engine ZETA VOICE
[ https://zeta.inc/cx/products/zv ]
Recommendation Engine ZETA RECOMMEND
[ https://zeta.inc/cx/products/zr ]
AI Chat for EC ZETA TALK
[ https://zeta.inc/cx/products/zt ]
Generative AI Integration Platform ZETA LINK for AI
[ https://zeta.inc/cx/products/zl ]
Generative AI Search Optimization Service ZETA GEO
[ https://zeta.inc/cx/products/zg ]
Loyalty Improvement Engine ZETA ENGAGEMENT
[ https://zeta.inc/cx/products/ze ]
EC Curation Engine ZETA BASKET
[ https://zeta.inc/cx/products/zb ]
OMO / DX Solution ZETA CLICK
[ https://zeta.inc/cx/products/zc ]
Prediction / Personalization Solution ZETA DMP
[ https://zeta.inc/cx/products/zd ]
【Contact Us】
Product Inquiries: info@zeta.inc
IR Inquiries: ir@zeta.inc
■ ZETA Inc. https://zeta.inc
Location: 17F Santowers Center Building, 2-11-22 Sangenjaya, Setagaya-ku, Tokyo 154-0024
Established: August 2005
Capital: 96 million yen (as of October 1, 2024)
Representative: Tokuyuki Yamazaki
Business Activities: Development and sales of CX improvement generative AI solutions
Approaches to AI recommendations are not limited to highly personalized recommendations based on user attributes and context; recommendations that emphasize "discovery" (serendipity) and trends are also important. "Multi-Angle Recommendation" enhances the user's shopping experience and enables engagement with various products by displaying these multiple recommendation approaches in a freely scrollable format, much like displays or shelves in a physical store.
■ Background of Productization: Improving CX with AI Recommendations in the Retail Media Era
As e-commerce sites evolve into retail media, transforming from mere purchasing platforms into media where users can enjoy the shopping experience, the importance of user-product engagement is further increasing.
Our company has traditionally provided the EC product search and on-site search engine "ZETA SEARCH," the AI recommendation engine "ZETA RECOMMEND," the hashtag utilization engine "ZETA HASHTAG," the loyalty improvement engine "ZETA ENGAGEMENT," and the EC curation engine "ZETA BASKET," among others.
We believe that by seamlessly connecting these in future e-commerce sites, we can provide a more exciting shopping experience for users, thereby further enhancing CX. With this in mind, we have launched the "Multi-Angle Recommendation" feature.
This enables a wide variety of product suggestions on e-commerce sites, much like displays or shelves in a physical store.
For example, vertically, diverse recommendation patterns such as "recommendations by hashtag," "personalized recommendations by browsing history," "recommendations by popular products," and "user-curated recommendations" can be arranged. Within each recommendation pattern, a carousel-like horizontal recommendation can continuously display a diverse range of products.
Furthermore, users can freely set and reorder the vertical axis of recommendations, creating a more immersive shopping experience.
"Multi-Angle Recommendation," centered on our strengths in EC product search, hashtags, and AI utilization, is expected to reduce the operational burden on e-commerce sites and improve loyalty.
■ Features of "Multi-Angle Recommendation"
1. Improves user CX and contributes to increased site stay time by displaying various types of recommendations.
The type of recommendation a user desires varies depending on the timing. By displaying diverse recommendations, it becomes possible to enhance the user's customer experience and allow them to enjoy the purchasing experience itself as if they were in a physical store. Furthermore, by allowing users to customize the types of recommendations themselves, a high-quality CX is achieved.
2. Synergistic effects through collaboration with "ZETA CX Series"
To create diverse recommendations, it is crucial to utilize rich product data and user's 1st Party Data. The "ZETA CX Series" includes an EC product search engine, hashtag utilization engine, review/Q&A engine, and curation engine. By linking the product data and user behavior history handled by these with AI recommendations, a wide variety of recommendations can be realized.
In particular, hashtags can utilize not only product data and user behavior history but also trending words that other users are paying attention to, which is highly effective in improving the shopping experience.
Furthermore, by linking with the EC product search engine, it becomes possible to generate recommendations based on user search queries.
3. Advanced recommendation processing using AI
To utilize detailed product data, diverse user's 1st Party Data, and UGC from other users, the use of AI is essential. "ZETA RECOMMEND," which has many examples in major domestic EC sites and a strong advantage in AI utilization, proposes diverse and optimal recommendations to users, contributing to improvements in CVR (Conversion Rate), AOV (Average Order Value), and LTV (Customer Lifetime Value).
■ Purchasing Experience in the Agentic Commerce Era Provided by "ZETA RECOMMEND"
"Multi-Angle Recommendation" is expected to become an essential element in realizing retail media, which is an approach to utilize EC sites themselves as a place for users to enjoy. Furthermore, there is also the possibility of utilizing multi-angle recommendation displays as retail media advertisements, creating advertising utilization and revenue opportunities within the media. Please utilize this for the purchasing experience in the "Agentic Commerce" era, leveraging UGC and retail media.
ZETA will continue to provide beneficial services to users and EC site operating companies by leveraging its strength in AI-driven data analysis.
【Official SNS】
X Account
[ https://twitter.com/zeta_cx ]
Facebook Account
[ https://www.facebook.com/zetacom ]
【CX Improvement Generative AI Solution ZETA CX Series】
EC Product Search / On-site Search Engine ZETA SEARCH
[ https://zeta.inc/cx/products/zs ]
Hashtag Utilization Engine ZETA HASHTAG
[ https://zeta.inc/cx/products/zh ]
Retail Media Ad Engine ZETA AD
[ https://zeta.inc/cx/products/za ]
Review / Word-of-mouth / Q&A Engine ZETA VOICE
[ https://zeta.inc/cx/products/zv ]
Recommendation Engine ZETA RECOMMEND
[ https://zeta.inc/cx/products/zr ]
AI Chat for EC ZETA TALK
[ https://zeta.inc/cx/products/zt ]
Generative AI Integration Platform ZETA LINK for AI
[ https://zeta.inc/cx/products/zl ]
Generative AI Search Optimization Service ZETA GEO
[ https://zeta.inc/cx/products/zg ]
Loyalty Improvement Engine ZETA ENGAGEMENT
[ https://zeta.inc/cx/products/ze ]
EC Curation Engine ZETA BASKET
[ https://zeta.inc/cx/products/zb ]
OMO / DX Solution ZETA CLICK
[ https://zeta.inc/cx/products/zc ]
Prediction / Personalization Solution ZETA DMP
[ https://zeta.inc/cx/products/zd ]
【Contact Us】
Product Inquiries: info@zeta.inc
IR Inquiries: ir@zeta.inc
■ ZETA Inc. https://zeta.inc
Location: 17F Santowers Center Building, 2-11-22 Sangenjaya, Setagaya-ku, Tokyo 154-0024
Established: August 2005
Capital: 96 million yen (as of October 1, 2024)
Representative: Tokuyuki Yamazaki
Business Activities: Development and sales of CX improvement generative AI solutions