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This document contains information and data that AAUM considers confidential. Any disclosure of Confidential Information to, or use of it by any other party, will be damaging to AAUM. Ownership of all Confidential Information, no matter in what media it resides, remains with AAUM. AAUM Confidential Ordo Ab Chao leveraging social media sentiments
- 2 - Problem DescriptionCurrent Process Market Segments Size of Addressable Market Only about half of the businesses using social media networks like Facebook, Twitter, or LinkedIn have any idea as to a return on investment. Businesses doesnt know how to leverage the insights effectively for their operations. Sound understanding of business objectives will be helpful to devise appropriate methodologies to extract/analyze information from web. Many players existing to categorize sentiments based on text mining techniques but no solution existing on predicting social media based on advanced analytics real time to benefit the business goals. Articulating the current scenario in social media The Problem Most of the businesses have presence in web, get feedback to gather from comments and derive insights manually or by leveraging software (just classification) available in the market. All business segments – No differentiation Assuming 40% of the companies have presence in the web. And 50 % of them have adopted social media or using social media techniques. This is a very captive market looking at the impact made by social media in the recent years.
- 3 - Solution DescriptionProposed Process Market Segments Size of Addressable Market Aaum have developed a working concept to predict/categorize social media comments by various business parameters. Customized advanced analytical algorithms, dictionary have been developed to accomplish this. This product has potential to change the business paradigm. With continuous data mining and right infrastructure, it is now possible to know peoples choice specific to the business. Just the tip of the iceberg and Sky is the limit! Please refer to the proof of concept in the next slide. Aaums solution envisioned Our Solution Automatic sentiment mining from social media. Predict social media opinions real time based on advanced analytics to benefit the business objectives. All business segments – No differentiation Assuming 40% of the companies have presence in the web. And 50 % of them have adopted social media or using social media techniques. This is a very captive market looking at the impact made by social media in the recent years. Business objectives Generate more word of mouth Increase customer loyalty Bring outside ideas into organization Increase product/brand awareness Improve new product success ratios Improve public relations effectiveness Reduce customer acquisition costs Reduce customer support costs Reduce market research costs Reduce product development costs Prioritized business Generate more word of mouth <2 Increase customer loyalty <4 Bring outside ideas into organization <3 Increase product/brand awareness <5 Improve new product success ratios Improve public relations effectiveness <1 Reduce customer acquisition costs Reduce customer support costs Reduce market research costs Reduce product development costs
- 4 - Problem DescriptionCompetitive comparison Competitive positioning by key factors Social media is sunrise industry. Many software companies are making tools to come up with solutions to categorize the comments based on basic text mining techniques None of these tools have good predictive solutions for the business to derive insights for their operations. Aaums solution is a blue ocean product to leverage the benefits of analytics in social media. Competitive landscape Competition A few commercially available packages SAS, SPSS – Performs text mining and categorizes by key words – Adopts a generic approach Customized solutions (Many vendors) Based on dictionary classification and partially on advanced analytics Visibli, Semioboard, viralheat, etc – More of web analytics A comprehensive solution with continuous monitoring is lacking in this space! DifferentiatorsAaums solutionCompetition Text mining and automatic comments extraction Partial Prediction by business parameters Partial Prediction by advanced analytical techniques and therefore better prediction/accuracy Continuous mining of data and hence not limited to one time api search
Case Study: Comparative Sentiment Analysis on Pongal release movie What people expressed before the release & post the release Case Study
- 6 - Data collected from various sources based on the business rules formed....
- 7 - Removing the bias factor is a very important process in our approach in addition to other data cleansing activities and transformation techniques Nanban Vettai
- 8 - Key insights Did the movie meet the expectations of the crowd – Pre-release vs Post release How did the movie perform? – 7 days before vs 7 days after Key Enabling factors Key Deteriorating factors Scope for improvement – Preventive and corrective actions See all by yourself in our Movie-meter dashboard!!! – Prediction based on our training algorithms
- 9 - With out bias With bias Post release Pre release Our classification techniques are based on advanced analytical algorithms
Insights from our analysis Pre release analysis shows a very good support for both the movies. A very few negative criticisms Heavy promotions witnessed in case of Vettai Removal of bias factors provides an altogether different perspective! Post release analysis also shows a very good support for both the movies. Nanban as clearly emerged a victor More positive comments about the movie, direction and the hero And nobody cares for songs from any of the movies!!!
Possible applications Ordo Ab Chao - our analytical product, a powerful listening tool to mine social media sentiments – Local movies chosen to initiate buzz and to create viral marketing The product demonstrated finds wide application areas especially – FMCG companies – To understand the customer behavior and usage patterns. Effectiveness of campaign launch, advertisements –Company, Competition and Customer e.g. New brand launch – Social media companies/Communities – to cater their services effectively to their customers. e.g. Twitter? – Entertainment industry - To understand the customer sentiments. Academy awards, News channels, etc
Want to see trends, changing audience perspectives on the movie attributes? vs Take a dive into the next slides
Nanban –Insights for movie and hero Pre & Post release insights
Nanban –Insights for director and heroine Pre & Post release insights
Questions/Feedback? Contact us 01 N, 1st floor IIT Madras Research Park, Kanagam road, Chennai – Tel :` , Fax: Twitter: AaumAnalytics, Web: Facebook: LinkedIn: About Aaum Aaum Research and Analytics founded by IIT Madras alumnus brings in extensive global business experience working with Fortune 100 companies in North America and Asia Pacific. Incubated at IIT Madras Incubator ecosystem with a focus on researching and devising the sophisticated analytical techniques to solve the pressing business needs of corporations ranging from Health Care, Entertainment, FMCGs, finance, insurance, retail, Telecom. Aaums office at IIT Madras Research Park