Datamining and Advanced Analytics
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The document discusses the significance of risk analytics in risk management, highlighting its reliance on diverse data sources to inform decision-making related to products and services. It also covers customer segmentation and predictive analytics, which aid businesses in understanding consumer behavior, enhancing marketing strategies, and optimizing pricing. Overall, the document positions the consulting firm as a leader in analytics and data-driven solutions across various industries.
Datamining and Advanced Analytics
- 1. Risk Analytics Risk Analytics has become an important part of Risk Management due to the ever-growing volume and multichannel and platforms where the data is available. Risk Analytical models use a massive number of data from various sources, including financial statements, regulatory filings, social media, and additional publicly available information to define KPIs which has helped the Risk Managers and Governance team to that risk and make informed decisions related to the product, services or online reputation. The Customer Model is a data-driven approach to understanding customer behavior. The model helps in understanding the likes and dislikes of customers, their purchase behavior, and also their interaction with the company’s social media channels. The model can be used to identify the promising customer segments for marketing campaigns and the success of the targeted product and services. Customer Segmentation Model Advanced and Predictive Analytics has become the center of several organizations to remain ahead of their competition and to grow the market share and retention. We are one of the leading Business Intelligence, Analytics, and Big Data consulting services and solutions. Our consultants come from the diverse field of Data Science and Statistics creating complex models which not only help the decision- makers to go beyond inferring information from dashboards and KPI reports but to take more effective decisions giving a competitive advantage for organizations Predictive Analytics Predictive analytics solution has helped clients analyze intake from customer data, customer segmentation models, predictive models, social media analysis, pricing models, and customer support applications. The solutions use advanced algorithms to generate customer scores based on these parameters. These models have helped our clients in the underwriting process utilizing the ranking system but could be used by retail, banks, and healthcare areas like fraud detection, credit risk management, and health care. The goal of these models is to quantify the risk and recommend mitigating actions. The predictive models use historical data to identify patterns that can be used to predict future events. Marketing Analytics The marketing data mining model using statistical techniques helped identify patterns, relationships, and trends within data about sales transactions or marketing campaigns. Marketing data mining is a proven technique to help businesses save up to 40% on customer acquisitions and improve campaign targeting, for instance, or targeted promotional offers. Pricing Analytics Pricing analytics applies data mining and predictive modeling techniques to price optimization. Our Consultant has helped our retail client in datamining historical sales data to identify patterns and trends in customer behavior to predict future demand better and optimize prices accordingly. Datamining and Advanced Analytics We have helped our clients with Datamining and creating Statistical Models utilizing Social Media and Digital signals to analyze customers' sentiments on products or services. www.scalar-solutions.com E:Info@scalarsol.com