VizMaster uses GUI to show a company’s performance by using portfolio and outer layer social information to extract, analyze, process data and visually present it on map highlighting business impact by region. Integrating knowledge from multiple sources, the resulting analyses are displayed as easy to use graphs to visualize core business information like for simple interpretation and analysis.
Vizmaster™ collects data from multiple sources and inputs them on HDFS to rapidly process the data using R/SAS, followed by development of GUI platform using Java and HTML. It also uses Big Data and Machine Learning techniques to predict the future growth of the business.
Vizmaster™ uses external agency data, social data, and portfolio information to produce a rich visualization, which will predict growth of the business. There are different predictive models like survival analysis which have been developed using machine learning techniques. Automatic schedule to run the predicted data to produce summarized numbers on a very user friendly interface; The final outcome is in the form of Graphs and data is presented on the map showing region wise performance and prediction. VizMaster is fast and flexile to use since it takes data through HDFS system, highly customizable, works in all major browsers, and you can even use on mobile and tablet devices.
RecENGINE™ is a first of its kind business intelligence & analytics tool that dynamically recommends offers at the customer level, effectively optimizing marketing best practices. RecENGINE™ uses advanced, proprietary algorithms to completely analyze personalized consumer behavioral data and accurately predict the credit and risk worthiness of a customer profile.
RecENGINE™ processes complex data sets using R/SAS based on a predictive algorithm, which accurately defines the risk profile of a customer followed by rule based segmentation to define characteristics of a particular segment to be targeted for a particular offer. Data is dynamically updated for each customer to recommend offers.
Gain an in-depth understanding of the credit card portfolio; Profile customer base to bring forth clear segments in the portfolio; Measure risk that existing segments within the credit cards portfolio hold; Align risk to customer threshold; Propose appropriate and attractive product offerings to existing customers to achieve maximum growth in revenue from higher utilization
Sentimentics is a customizable system designed for sentiment analysis of Companies on the web. Sentiments can be identified as positive, neutral, or negative comments on the web from any publicly accessible site or app where users post comments including Twittter, Facebook, LinkedIn, Instagram, Glassdoor, Angie’s list etc. Resulting analyses are displayed as easy to use graphs for simple interpretation data.
Sentimentics is built on a capabilities framework, which involves complex logic & processes like Online Crawler, Big Data, Data Mining and Machine Learning Data Analysis, Sentiment categorization, Visualization, Features and Improvements, Identifying Fraudulent comments, Comparative comments, etc.
Web URLs are variable parameters defined in configuration files – at anytime new web URL can be added or removed from web crawling and data mining; Categorization of the Sentiments are predefined; Sentiments are defined as positive and negatives words as per the AFINN dictionary; Automatic schedule to run the sentiment data analysis of to produce reports; The end reports can be produced in the form of Graphs, data is spreadsheets for further processing; Sentiment tracking can use multiple dimensions for analysis to allow for proactive, customer insight driven actions