Stephen darori developing big data capabilities to govern and influence sentiment

COLLABORATIVE WHITEPAPER SERIES

Developing Big Data Capabilities to Govern and Influence SentimentA Maturity Model for Social Media

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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 in process or in the planning stage.

1 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 on social media have on their brands.

2 This is evidenced by the fact that on Twitter

56% of customer tweets to companies are ignored.3

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

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Every month, users spend5:

• 6.5 hours on Facebook

• 3.3 hours on Google+

• 21 minutes on Twitter

• 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

• 684,478 pieces of content are shared on Facebook

• 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

- 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

• 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

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.

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.

II. A Maturity Model for Social Media

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.

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.

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.


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Figure 1: Maturity Model for Social Media

Figure 2: Level 1: Motivated

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Develop Capabilities to Govern and Influence Sentiment

Level 1: Motivated

Capabilities Entrance Criteria

•Sentiment perceived, not measured

•Processes, skills and technology unprepared

•Anecdotal opportunities / misses become visible

•Businesscasedefined

•Executive sponsorship and commitment

•ROI for sentiment analysis programs

•Ability to align to business initiatives

•Competitive analysis, i.e. what is the market doing with regards to competitive analysis

•Vendor RFI and RFP

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Level 1: Motivated


•Sentiment perceived, not measured

•Processes, skills and technology unprepared

•Anecdotal opportunities / misses become visible

•Businesscasedefined

•Executive sponsorship and commitment

•ROI for sentiment analysis programs

•Ability to align to business initiatives

•Competitive analysis, i.e. what is the market doing with regards to competitive analysis

•Vendor RFI and RFP

Level 1: Motivated

Capabilities:

• Sentiment perceived, not measured

• Processes, skills and technologt unprepared

• Anecdotal opportunities / misses become visible

• Business case defined

• Executive sponsorship and commitment

Entrance Criteria:

• ROI for sentiment analysis programs

• Ability to align to business initiatives

• Competitive analysis, i.e. what is the market doing with regards to competitive analysis

• Vendor RFI and RFP

5

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Level 2: Organized


•Strategic Planning

•Tactical planning of initial implementation

•A joint business / technology / skills Blueprint&Roadmapdefined

•Skill development & acquisition

•Point “SAaaS” solutions - Sentiment Analysis as a Service 8

•Comprehensive gap analysis, particularly with regards to new roles and skills (e.g. Data Scientist)

•Existing sentiment analytical models acrossdepartmentsidentified

•Proof of concepts formulated

•Social media sources prioritized

•Vendor technology selected

•Deployment models (e.g. cloud deployment, hybrid onsite / offsite) defined

•Social media privacy and terms of use published

Figure 3: Level 2: Organized

Entrance Criteria:

• Comprehensive gap analysis, particularly with regards to new roles and skills (e.g. Data Scientist)

• Existing sentiment analytical models across departments identified

• Proof of concepts formulated

• Social media sources prioritized

• Vendor technology selected

• Deployment models (e.g. cloud deployment, hybrid onsite / offsite) defined

• Social media privacy and terms of use published

Capabilities:

• Strategic Planning

• Tactical planning of initial implementation

• A joint business / technology / skills Blueprint & Roadmap defined

• Skill development & acquisition

• Point “SAaaS” solutions - Sentiment Analysis as a Service8

Level 2: Organized


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Level 3: Aware9


•Social Media lab environment

• Initial data collection (i.e. subset of social media sources)

•Analytical model experimentation

•Emerging data science

•Datascientistrolesfilledwiththeproperlyexperienced or trained individuals

•Sentimentanalyticalmodelsrefinedthrough a joint iterative effort between business and IT

•Application proof of concept demonstrates business value

•Tactical “Quick wins” (e.g. promotions) identified

Figure 4: Level 3: Aware

Entrance Criteria:

• Data scientist roles filled with the properlyexperienced or trained individuals

• Sentiment analytical models refined through a joint iterative effort between business and IT

• Application proof of concept demonstrates business value

• Tactical “Quick wins” (e.g. promotions) identified

Capabilities:

• Social Media lab environment

• Initial data collection (i.e. subset of social media sources)

• Analytical model experimentation

• Emerging data science

Level 3: Aware9

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Level 4: Informed


•Proven analytical models

•Refineddatasciencetechniques

•Socialmediasourcesidentifiedinblueprint aligned to internal applications

•Product and marketing strategies aligned to sentiment

•Advanced customer segmentation and targeting

•The social media science lab evolves and becomes “productionalized”

• Integration between sentiment analysis and existing processes, systems

•Sentiment analysis is visible and embedded in everyday operations and analysis

Figure 5: Level 4: Informed

Entrance Criteria:

• The social media science lab evolves and becomes “productionalized”

• Integration between sentiment analysis and existing processes, systems

• Sentiment analysis is visible and embedded in everyday operations and analysis

Capabilities:

• Proven analytical models

• Refined data science techniques

• Social media sources identified in blueprint aligned to internal applications

• Product and marketing strategies aligned to sentiment

• Advanced customer segmentation and targeting

Level 4: Informed


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Level 5: Assertive


• “Closed loop” between product / campaign strategy and sentiment

•Complex Event Processing

•A culture of sentiment analysis and social data science established

Figure 6: Level 5: Assertive

Entrance Criteria:

• A culture of sentiment analysis and social data science established

Capabilities:

• “Closed loop” between product / campaign strategy and sentiment

• Complex Event Processing

Level 5: Assertive

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III. Conclusion

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.

References

1. http://blogs.hbr.org/cs/2012/11/the_big_data_talent_gap_no_pan.html

2. http://thesocialskinny.com/216-social-media-and-internet-statistics-september-2012/

3. http://www.huffingtonpost.com/brianhonigman/100-fascinating-socialme_b_2185281.html

4. Pew Research Center: 2012 State of the News Media

5. http://thesocialskinny.com/216-social-media-and-internet-statistics-september-2012/

6. Statistics from http://thesocialskinny.com/216-social-media-and-internet-statistics-september-2012/

7. For established examples of maturity models, please reference http://www.sei.cmu.edu/cmmi/

8. SAaaS example from Klout

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)”

Figure 7: Collaborative Consulting’s “Little” Big Data Services

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 [email protected], or contact us at 877-376-9900.

Copyright © 2013 Collaborative Consulting, LLC. All rights reserved. This product is protected by U.S. and international copyright and intellectual property laws.


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Stephen darori developing big data capabilities to govern and influence sentiment

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