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Kainic

Develop by Kainic
Free plan available

Personalized Products Recommendations & Customers tracking

Ai recommendations
Behavior analysis
Customer tracking
Customizable tracking
Upsell suite
Order value increase
Event collection
Activity-based suggestions

About Kainic

Built by Kainic

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Description

Kainic-Plugin makes recommending products simple, and helps you understand customers' needs.

With Kainic-Plugin, your customers can view related products to the any product , increasing the order value and your revenue. We built this app to bring recommendation-like feature into Shopify and, since then, more and more options have been added to create a full-featured product upsell and recommendation suite. Kainic-Plugin is unbeatable because our AI algorithm has been continuously trained , enhanced and polished to drive higher conversion rates & collecting customers behavior also.

With Kainic-Plugin, your customers can view related products to the any product , increasing the order value and your revenue. We built this app to bring recommendation-like feature into Shopify and, since then, more and more options have been added to create a full-featured product upsell and recommendation suite. Kainic-Plugin is unbeatable because our AI algorithm has been continuously trained , enhanced and polished to drive higher conversion rates & collecting customers behavior also. more
  • Collecting customers events for tracking customer behavior and data
  • Controlling about what the customer's events types that want to be tracked
  • Providing a list from of recommended products based on the customer activites

Pros

  • Increases order value and revenue through product recommendations
  • Integrates seamlessly with Shopify
  • Offers a full-featured product upsell and recommendation suite
  • Continuously trained and enhanced AI algorithm for higher conversion rates
  • Tracks customer behavior and events for improved marketing strategies
  • Allows control over the types of customer events to be tracked
  • Provides personalized product recommendations based on customer activities

Cons

  • Potential privacy concerns with extensive data tracking and behavioral analytics
  • Dependence on AI algorithm performance which may not always meet business expectations
  • Integration complexity might increase as more features are added
  • May require ongoing tuning and management to ensure effective recommendations
  • Initial learning curve for users unfamiliar with AI-driven recommendation systems

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