C2S Technologies worked with
Microsoft to solve
client problem in three approaches

Customer Opinion

Enabled Capabilities

HDInsights & Machine Learning, NLP + Text Mining. Supervised training for classification.

Outcome

  • Over the last three years the program has been successfully rolled out and has been recognized by customer and has been rated 4.6 stars out of 5 for our successful deliverables.
  • Customer was able to customize product offerings before new product roll out.

Customer

Impact Created

Recommended Microsoft to customize products offerings, returns and customer opinion.

Summary

C2S Analytics team helped an IT giant Microsoft proactively to identity people's opinion during holiday season to figure it out what people are talking about Microsoft in social media with respect to their products, customer satisfaction and dissatisfaction. They also enabled Microsoft to get people's sentiments from various segmentation. This analytics included text mining, opinion mining, and sentiment subjectivity vs objectivity.

Challenge

Microsoft wants to read social media data to figure it out how they have been spoken out in social media regarding their recently launched products and offerings during holiday season or during the launch of new product. This is the long-term business objective goal for every year. Though the long-term objectives were clear, but there is no analytics platform to solve these problem on need basis insights and live analytics.

Approach

C2S Technologies worked with Microsoft to solve client problem in three approaches.

Phase I

During phase I, we treated this project as POC to gain the customer confidence to make sure whether we have right tools, right team, and right knowledge to solve customer problems using customer low priority data. This phase we exhibited our text analytics competency practice including text categorization, text clustering, concept extraction, sentiment analysis, document classification.

Phase I

Once we built the confidence, we analyzed the real data from social media such as Facebook, Twitter, LinkedIn, and Blogs. Our data scientist team built statistical models using R and generated desired insights.

Phase I

Once we built the confidence, we analyzed the real data from social media such as Facebook, Twitter, LinkedIn, and Blogs. Our data scientist team built statistical models using R and generated desired insights.