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Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
Stephen darori developing big data  capabilities to govern and  influence sentiment
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Stephen darori developing big data capabilities to govern and influence sentiment

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  • 1. Developing Big Data Capabilities to Govern and Influence Sentiment A Maturity Model for Social Media COLLABORATIVE WHITEPAPER SERIES
  • 2. COLLABORATIVE WHITE PAPER SERIES: Developing Big Data Capabilities to Govern and Influence Sentiment The rise of social media has been at the epicenter of the Big Data “megatrend”. The universe of Big Data is expanding at an accelerating rate, and increasingly the data growth is driven by sources of unstructured or machine-generated Big Data (e.g. from social media, blogs, the “Internet of Things”). The latest IDC Digital Universal Study reveals an explosion of stored information: more than 2.8 zettabytes of information was created and replicated in 2012 alone. To put this number in perspective, this means that 95 terabytes of information were produced per second over the course of a year. Organizations are increasingly aware that this explosion of Big Data represents an opportunity to better segment and target customers, and enhance products and promotions according to trending attitudes in the market. A recent Harvard Business Review survey suggests that 85% of organizations had funded Big Data initiatives 1 in process or in the planning stage. With regards to social media, this means that businesses require new models for measuring sentiment. Despite the planning and commitment, 70% of organizations are unaware of the impact that negative comments 2 on social media have on their brands. This is evidenced by the fact that on Twitter 3 56% of customer tweets to companies are ignored. Organizations that see social media as a potential means to gain competitive advantages must align capabilities that support social media-intensive business initiatives. This paper helps organizations address this challenge by: • Establishing common business rationale for harnessing social media to measure sentiment • Defining a maturity model for sentiment analysis which helps organizations assess their existing social media capabilities • Enumerating capabilities and entrance criteria along advancing levels of social media maturity I. Rationale for Increasing Social Media Maturity Social media is a numbers game. The number of Facebook friends you have, how many people follow you on Twitter, or the size of your contact network in Linkedin projects a measure of influence an individual entity has on the expanding social universe. Beyond the superficial nature of individual social rank is the enormous volume of information that is available and increasingly relevant to organizations. Here are some facts that establish the reach of social media: 70% of 1 billion Facebook users and 36% of 517 million Twitter users get their news from other friends or followers4 2
  • 3. Every month, users spend5: for mentions of seismic activities, organizations have established tactics that leverage the power of social media in response to events moving real-time across the social media universe. • 6.5 hours on Facebook • 3.3 hours on Google+ • 21 minutes on Twitter Of the use cases listed, a good starting point for most organizations is sentiment analysis. Measuring, analyzing, and ultimately influencing customer sentiment drives an organization’s ability to formulate and adjust effective social marketing promotions, and thus can help improve customer loyalty and generate revenue. As organizations can “close the loop” and positively impact sentiment in their favor, then users will feel comfortable in vocalizing information relevant to the complex events that organizations need to monitor in these public forums. Thus organizations that most effectively measure and manage sentiment across the social media universe will establish the benchmark in a maturity model for social media. • 17 minutes on Linkedin While every organization is different and the relevance of social media will vary from industry to industry and department to department, there are several established use cases for organizations looking to increase their social media awareness. These use cases include:6 Sentiment Analysis: Social media is about interactions, and from these interactions emerge attitudinal trends or prevailing opinions in a public forum. To give you the degree of sharing, here is the level of interaction that occurs every minute across the social media spectrum: • 100,000 Tweets are sent II. A Maturity Model for Social Media • 684,478 pieces of content are shared on Facebook Maturity models are established mechanisms that help organizations assess their capabilities along a particular domain of interest, and how much further they need to grow in order to reach the desired end-state. One of the most common examples of a maturity model is the Capability Maturity Model, which defines 5 levels of maturity relative to software engineering.7 Rarely do organizations reach CMM Level 5 and those that do are not guaranteed success. Still, it is a good practice for organizations to adopt a model, target an appropriate maturity level, and monitor its progress to a desired maturity level. • 48 hours of video are uploaded to YouTube Social Promotions: As the following figures suggest, social media promotions have a measurable influence on social interactions: • 67% of customers will like a Facebook page to save 25% or more on products / services • 17% of users will tweet or re-tweet a deal to save 25% or more • More than 50% of Twitter users follow companies or brands The maturity model for social media (Figure 1) is a conventional view of a maturity model applied to a unique use case, sentiment analysis. As with most maturity models, the X-axis represents the maturity level, and capability is represented by the Y-axis. - 79% of US Twitter users are more likely to recommend these brands - 67% of US Twitter users are more likely to buy from these brands Figures 2-6 represent important aspects of the maturity model. Specifically key capabilities are enumerated in the matruity model, along with “entrance criteria” to indicate when each level of maturity has been achieved. • 80% of social media users prefer to connect with brands through Facebook Complex Event Processing: Whether it is a pharmaceutical company listening to adverse events or the United States Geological Survey establishing a Twitter account 3
  • 4. COLLABORATIVE WHITE PAPER SERIES: Developing Big Data Capabilities to Govern and Influence Sentiment Figure 1: Maturity Model for Social Media Figure 2: Level 1: Motivated Level 1: Motivated Level 1: Motivated Capabilities: • Sentiment perceived, not measured • Processes, skills and technologt unprepared • Anecdotal opportunities / misses become visible Level 1: Motivated • Business case defined • Executive sponsorship and commitment Entrance Criteria: • ROI for sentiment analysis programs Capabilities • Sentiment perceived, not measured • Processes, skills and technology unprepared Entrance Criteria• Ability to align to business initiatives • Competitive • ROI for sentiment analysis programs analysis, i.e. what is the market doing with regards to competitive analysis • Ability to align to business initiatives • Anecdotal opportunities / misses become visible • Competitive analysis, i.e. what is the • Vendor RFI market doing with regards to competitive analysis • Business case defined • Vendor RFI and RFP • Executive sponsorship and commitment 4 and RFP
  • 5. Figure 3: Level 2: Organized Level 2: Organized Level 2: Organized Capabilities: Entrance Criteria: • Strategic Planning • Comprehensive gap analysis, particularly with regards to new roles and skills (e.g. Data Scientist) Capabilities Entrance Criteria • Tactical planning of initial implementation • Existing sentiment analytical models across • A Planning • Strategic joint business / technology / skills Blueprint & • Comprehensive gap analysis, particularly departments identified with regards to new roles and skills (e.g. • Proof of concepts formulated Data Scientist) prioritized • Social media sources Roadmap defined • Tactical planning of & acquisition • Skill development initial implementation • A joint • Point “SAaaS”/ solutions - Sentimentskills as a business technology / Analysis Service Blueprint & Roadmap defined • Vendor technology selected • Existing sentiment analytical models across departments identified hybrid • Deployment models (e.g. cloud deployment, 8 • Skill development & acquisition onsite / offsite) defined • Proof of concepts formulated • Social media privacy and terms of use published • Point “SAaaS” solutions - Sentiment Analysis as a Service 8 • Social media sources prioritized 5 • Vendor technology selected
  • 6. COLLABORATIVE WHITE PAPER SERIES: Developing Big Data Capabilities to Govern and Influence Sentiment Level 3: Aware9 Figure 4: Level 3: Aware Level 3: Aware9 Capabilities: Entrance Criteria: • Social Media lab environment • Data scientist roles filled with the properlyexperienced or trained Entrance Criteria individuals Capabilities • Initial data collection (i.e. subset of social media sources) • Sentiment analytical models refined through a joint • Social Media lab environment • Data scientist roles filled with the properly iterative effort between business and IT experienced or trained individuals • Application proof of concept demonstrates business • Analytical model experimentation • Initial data collection (i.e. subset of social • Emerging data science media sources) value • Sentiment analytical models refined • Tactical a joint iterative effort between through“Quick wins” (e.g. promotions) identified business and IT • Analytical model experimentation • Emerging data science • Application proof of concept demonstrates business value 6 • Tactical “Quick wins” (e.g. promotions)
  • 7. Level 4: Informed Figure 5: Level 4: Informed Level 4: Informed Capabilities: Entrance Criteria: Capabilities Entrance Criteria • Proven analytical models • The social media science lab evolves and becomes “productionalized” • Refined data science techniques • Proven analytical models • The social media science lab evolves and • Integration between sentiment analysis becomes “productionalized” and existing • Social media sources identified in blueprint • Refined data science techniques aligned to processes, systems internal applications • Integrationanalysis is visible and embedded in • Sentiment between sentiment analysis and existing processes, systems everyday operations and analysis • Social media sources identified in sentiment • Product and marketing strategies aligned to blueprint aligned to internal applications • Advanced customer segmentation and targeting • Sentiment analysis is visible and embedded in everyday operations and analysis • Product and marketing strategies aligned to sentiment • Advanced customer segmentation and targeting 7
  • 8. COLLABORATIVE WHITE PAPER SERIES: Developing Big Data Capabilities to Govern and Influence Sentiment Figure 6: Level 5: Assertive Capabilities: Level 5: Assertive Level 5: Assertive Entrance Criteria: Capabilities Entrance Criteria • “Closed loop” between product / campaign strategy and sentiment • A culture of sentiment analysis and social data science established • A culture of sentiment analysis and social data science established • “Closed loop” between product / • Complex Event Processing campaign strategy and sentiment • Complex Event Processing 8
  • 9. Figure 7: Collaborative Consulting’s “Little” Big Data Services References 1. http://blogs.hbr.org/cs/2012/11/the_big_data_talent_ gap_no_pan.html 2. http://thesocialskinny.com/216-social-media-andinternet-statistics-september-2012/ 3. http://www.huffingtonpost.com/brianhonigman/100fascinating-socialme_b_2185281.html 4. Pew Research Center: 2012 State of the News Media 5. http://thesocialskinny.com/216-social-media-andinternet-statistics-september-2012/ 6. Statistics from http://thesocialskinny.com/216-socialmedia-and-internet-statistics-september-2012/ 7. For established examples of maturity models, please reference http://www.sei.cmu.edu/cmmi/ III. Conclusion 8. SAaaS example from Klout Social media is changing the ways in which individuals interact and share information, including their preferences and sentiment regarding products and services. There is a clear opportunity for organizations to take progressive steps to engage and monitor these interactions. Organizations that formulate a game plan to enhance their social media maturity will be positioned to measure, respond to, and ultimately influence sentiment through enhanced products and promotions aimed at targeted segments of potential customers. 9. For an overview of Hadoop, please see Collaborative Consulting’s Whitepaper “The Fast-Track to Hands-on Understanding of Big Data Technology (Part 1)” 9
  • 10. COLLABORATIVE WHITE PAPER SERIES: Developing Big Data Capabilities to Govern and Influence Sentiment Collaborative is a leading information technology services firm dedicated to helping our clients achieve business advantage through the use of strategy and technology. We deliver a comprehensive set of solutions across multiple industries, with a focus on business process and program management, information management, software solutions, and software performance and quality. We also have a set of offerings specific to the life sciences and financial services industries. Our unique model offers both onsite management and IT consulting as well as U.S.-based remote solution delivery. To learn more about Collaborative, please visit our website at www.collaborative.com, email us at sales@collaborative.com, or contact us at 877376-9900. Copyright © 2013 Collaborative Consulting, LLC. All rights reserved. This product is protected by U.S. and international copyright and intellectual property laws. WP.1113.03

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