What is Social Analytic?
Our product has an immense capacity to monitor, analyze, measure and interpret digital interactions and relationships of people, topics, ideas and contents. Interactions occur in workplace and external-facing communities. Social analytics include sentiment analysis, NLP (natural-language processing) and social networking analysis (influencer identification, profiling and scoring) as well as advanced techniques such as text analysis, predictive modelling and recommendations. Apart from that, we are also skilled in performing automated identification and classification of subject/topic, people and content.
Zanroo Social Listening and Monitoring solutions bring brands on better at sensing on what market wants, consumer demands and industrial trend as well as crisis in real-time.
NPL for multiple languages
NLP for multiple languages analysis in English and local languages like Thai, Mandarin, Bahasa, Japanese, Tagalog, Vietnamese, Burmese and Others
Unique Multi-levelKeywords structure & Auto-Tagging functions allowed users to categorize data easily for Topic Deep Dive & Analysis
Social Listening and Monitoring
Listening is a tool to collect data from social media platforms and other websites by Zanroo technology.
We can track information in detail such as language detection since our NLP uses machine learning to understand details in language, for example, the message sentiment.
The technology we call IR (information retrieval) also assists in retrieving more information from data such as location, emotion, object in image and language percentage.
For monitoring purposes, we optimize our data collector to get faster (near real-time), and data coverage to be more effective for some specific usage such as crisis monitoring.
This is our special business intelligence tool which has the power to analyse data on social media platform, combine all data to specific dashboard and customize it in many different, unique ways.
From our own analytic engine, we can customize deep dive by specifying topic and then produce network mapping.
This will help users tremendously in visualizing the relationship between all the subjects/content that are being analyzed.