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.

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.
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