Kea Labs: Recommendations

Develop by Shopify

$59-$899

/ Month

14 Days Free Trial

Recommendation system with custom-made algorithms

Detailed analytics

A/b testing

Personalized product recommendations

Custom-tuned algorithms

Saas with professional team

Models trained on your data

Accurate complex item recommendations

Automated product bundles

Enhanced related item algorithm

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About Kea Labs: Recommendations

Launched May 10, 2020

Built by Shopify

Address

Garden Town Phase 03 E-Block Plaza No 21 1st floor, Near Musa Super Store, Gujranwala, 52250, PK

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Description

Recommendation system with custom-made algorithms solving your business needs.

Kea Labs Recommendations is an advanced platform of personalized product recommendations. Apart from common blocks like ‘You may like’, ‘Related’ or ‘Similar’ items, Kea Labs algorithms are tuned for your use-case. We focus on solving business needs and provide a unique combination of SaaS with a professional solution team. If you are tired of limitations of ready recommendation services, Kea Labs is the solution for you. You get a custom-made level of recommender system on SaaS-level costs.

Models trained on your data, with your rules and solves your business needs
Accurate recommendations even for complex items
Automated bundles, compatible products and enhanced algorithm for related items
Real-time personaliation without storing and processing personal data
Profitability optimization with A/B testing, and detailed drill-down analytics

Pros

Custom-made algorithms tailored for specific business needs
Combination of SaaS with a professional solution team
Offers advanced personalization beyond common recommendation blocks
Models trained on client-specific data and rules
Accurate recommendations for complex items
Automated creation of bundles and related items
Real-time personalization without storing personal data
Profitability optimization through A/B testing
Detailed drill-down analytics for performance evaluation

Cons

May not be ideal for businesses with simple recommendation needs due to complexity
Potentially higher setup time compared to out-of-the-box solutions due to customization
Requires integration and management of client-specific data, which might be resource-intensive
May be more costly for smaller businesses despite SaaS-level costs