AI engine analyses customer on-site behavior and comments to suggest complementary products and promotions
A LIVE CASE
eCommerce companies need actionable insights and recommendations in virtually real-time. Customers leave their opinions, behavior on-site as they browse products. Can these two be combined to personalize the customer experience?
eComtics AI-powered sentiment analysis use sophisticated algorithms to analyze social media comments, on-site behavior to determine ‘customer sentiment’ and derive insights that help eCommerce companies to recommend appropriate products and promotions in almost real-time, enhancing the customer experience as well as the suitability of their products.
eComtics sentiment analysis combines machine learning techniques with rule-based systems to assign weighted scores to topics, entities, themes within customer comments to find out customer sentiments. The rule-based system can be effective for parts-of-speech tagging and simple sentiment analysis, while machine learning techniques will shoulder complex natural language processing tasks, such as understanding double-meanings.
eComtics sentiment analysis is a hybrid system leveraging the advantages of both ML techniques and rule-based systems together with social media monitoring, correlating insights gained with actual customer experience to deliver useful customer and product insights.
- Understand the Brand effectiveness, overall sentiment score for the product/service
- Capture all the social media metrics and analyze posts/tweets for public sentiment