is a powerful product recommendations engine that uses machine-learning to select the most relevant, data-driven personalized product recommendations for each customer interaction.
Homa uses machine learning to understand and predict human behavior in a helpful way. recommendation engine is used in real-time to deliver highly relevant suggestion to micro-segments of consumers.
User behavior analytics
Gleaning and analyzing user behavior patterns from “high-information users” (highly engaged users), such as the number of times the user clicks the picture of a particular make of a vehicle, the amount of time the user spends on the product information page, etc.
Graphbeen will can crawl websites while actively looking for a set of keywords that would trigger a specified action. This keywords can determine the category, specs, facts, tags or etc.
web crawling setup can do the job if it’s programmed to fetch content from a website that has a set of keywords which will be analyzed and matched in tree of knowledge
|Machine Learning Based||Elimination of the guesswork of product recommendations|
|Real-time Recommendations||Relevant recommendations since the consumer will still be in the market for the product or service|
|Continuous Machine Learning||A smarter system that updates and improves recommendations increasingly over time|
|Scalability to millions of products and consumers||Increased efficiency of marketing campaigns and cost savings|