Text Analytics Command Center - Vendor Briefing
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In this presentation, we describe how a text analytics command center can help you create a strategy for analyzing & integrating both social & private data.
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Text Analytics Command Center - Vendor Briefing
- 1. REAL TIME TEXT ANALTYICS Vendor Briefing September 7, 2011 Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 2. Making Sense of Social & Private Data Deluge How does an organization unify social & private text analytics? Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 6. Processing large volumes of data quickly
- 7. Real-time, unsolicited, voice of customer or employees
- 8. Weak signal can be sign of emerging trend or issuesProprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 9. Building a Platform for Handling Social & Private - A Text Analytics Command Center(TACC) Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 11. Immediate. Real-time, unsolicited, true voice-of-customer
- 12. Brand and product mentions but they may be embedded with other themes, topics and interests
- 13. Niche but expanding. May represent only a portion of a business’ total consumer audience
- 14. Narrow S-CRM focus. Need is expanding beyond Marcom/PR to loyalty, customer service, product development. Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 16. Inexpensive and easy to set up
- 17. Quick results for “exact” terms and phrase matching
- 18. Cons
- 19. Inefficient at white-space or open-ended analysis
- 20. Become more brittle as each expression is added to include or exclude data
- 21. Problems with ambiguity and granular filteringProprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 23. It’s estimated that 80% of business data is unstructured
- 24. Fluid Time Frame. Broad time range: data sources from last year or last week
- 25. Existing Systems. Organization may have existing teams or technologies in place to analyze data
- 26. Narrow focus. Used by customer service call centers to process data they already own to optimize service. Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 28. Analyze part of speech & parsing content to diagram context
- 30. Cons
- 31. Slow on large, unstructured text
- 32. Time-consuming to adjust to shifting content
- 33. Linguistic rules can be cumbersome when applied to social mediaProprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 34. Collective Intellect can unify Social & Private Data Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 35. Collective Intellect seeks to maximize the value of text Brand Selected Social handle Daypart Gender Location Subjective Dimensions: Taste, Quality Sentiment: Negative Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 40. 50 million unique authors
- 41. 2 million fan pages/user groups
- 43. Private Community Conversations (External & Internal)
- 44. 15 million unique blogs
- 51. 70 million unique authors
- 58. Private news, research, feeds
- 59. 600 thousand unique consumers
- 61. 25 unique review sitesProprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 63. applies the same standard and rigors to both social and private data analysis
- 64. addresses the inaccuracy and bluntness of keyword search & the speed and cost disadvantages of NLP
- 65. surfaces customer and market insight from social media in real-time
- 66. makes data discoverable in a repeatable, measurable process
- 67. solves the problems of gaining insight from massive amounts of unstructured data in real time
- 68. available as both SAAS self-service and embedded analytics engineProprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 72. Slow on large, unstructured text
- 74. High Performance for Speed and Precision
- 76. Used for Highly Accurate Categorization
- 77. Spam identificationProprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 78. Text Analytics Command Center Optimized to filter and organize big volumes of unstructured data Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 79. Collective Intellect has an approach that achieves high levels of categorization out of the box Collective Intellect Semantic Categorization of “Reuters-21578, Distribution 1.0” Test Collection (92% correctly categorized in top 2 rankings) Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 80. Text Analytics Command Center Dimensions extract language meaning Safety Loyalty Awareness Price Consideration/ Preference Intent Dimensions Interest Dimensions Problem Purchase Quality Referral Innovation Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 83. Blended Qualitative & Quantitative
- 86. KPIs TrackingCollective Intellect Semantic Analytics EngineMillions of social media conversations per day across 200+ million authors Billions of social media conversations available for back-scoring Ability to integrate client’s “private”conversational data Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 87. Customized analysis that is designed specifically to discover and trend KPIs relevant to a business Proprietary and confidential. Not to be used or distributed without the consent of Collective Intellect, Inc. Usecase: Analysis of client feedback forms Client XYZ used Collective Intellect’s software to determine which issues caused the most dissatisfaction among guests. Previous attempts with a legacy analytics system had proven inability to determine the most dominant issues, to quantify specific root causes within each issue, or to provide supporting verbatim in a satisfactory manner. Outcome By plugging those same surveys into CI’s text analytics suite, the client was able to determine key issues and rank them accordingly. Thereafter, supporting verbatim was retrieved as well. Client XYZ now has a clear understanding of where to focus capital for improvement and how to adjust messaging. Example of Customized Dashboard
- 88. REAL TIME TEXT ANALTYICS DEMO Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 90. Multi-Channel Marketing. Developing strategic partnerships to integrate our platform into large data-base marketing (DBM) and Marketing Automation applications to enable 1:1 multi-channel marketing activation. Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
- 91. REAL TIME TEXT ANALTYICS Thank You! Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.
Editor's Notes
- A white paper released today from IDC revised the research firm's earlier estimates to show that by 2011, the amount of electronic data created and stored will grow to 10 times the 180 exabytes that existed in 2006, reflecting a compound annual growth rate of almost 60%.There is lots of data out there much of it unstructured, which may contain enormous business insights. Much of this unstructured content is from social media conversations or if it is internal data, it might be surveys, chat or video transcripts or email threads. How do you address the analytical requirements of both social/private data? How do you begin to unify and integrate the analysis and research?
- "Over the last 20 to 25 years, companies have been focused on leveraging maybe up to 5% of the information available to them," said Brian Hopkins, a principal analyst at Forrester Research Inc. in Cambridge, Mass. "Everything we didn't know what to do with hit the floor and fell through the cracks. In order to compete well, companies are looking to dip into the rest of the 95% of the data swimming around them that can make them better than anyone else.”http://searchbusinessanalytics.techtarget.com/news/2240039382/Big-data-poses-big-challenges-for-traditional-analytics-approaches
- 2011 values - Twitter 75m user accounts, LinkedIn over 50m members & Facebook 350m active users
- If you are wanting to conduct open-ended or white space analysis, Keyword & Boolean is simply unable to derive meaning and context for large data sets.
- Existing systems – organization may have processes or systems in place that may not scale or are unable precise insights
- The command center will serve customers having various social media and private data analytics needs, allowing them to simply use or integrate our data and technology into their business environment serving various departments. The following diagram describes the overall functionalities offered by the command center. CI will own the first three layers (CI Inputs, CI Engine and CI Outputs) and will integrate through partners/client own applications.
- This is not a new way of doing business – delighting your customer with the right message. But never has the customer had such a powerful and amplifying platform to inform you of their opinion and perspective. A successful business engagement requires a two-way conversation with the customer. Without collecting and understanding your consumer’s input and responses, you are missing out on valuable and increasingly critical information
- Industry research estimates 127 million people, or 57.5% of internet users visited a social networking site at least once a month in 2010. Not only is the number of users growing quickly, but the audience demographics continue to widen. In 2010, it’s estimated that 59.2% of adult internet users will visit social networks monthly, up from 52.4% in 2009.Research estimates predict a steady rise in social media users by 2014, with 2/3 of all internet users, 164.9 million people, visiting social network sites on a regular basis. Ideally, your listening tool is able to manage both unstructured social data but also private, internal data. Otherwise you are analyzing data in a vacuum.
- -LSA in particular is the "secret sauce. It is an evolving system versus an analysis of word groupings at a single point in time, this makes it far more flexible/nimble than competitors in the NLP space. It compares 600,000 documents for the meaning of each word results in more accurate analysis and better "listening". The semantic services layer essentially broadens the end market to anyone who needs more accurate search - this includes web search (as long as the user is willing to "wait"), e-discovery, email archiving, and potentially more accurate video search based on descriptions/reviews/tagging, etc.CI’s semantic search and analytics technology is unique with its proprietary approach to how data is handled, categorized and measured for relevancy. The proprietary technologies isolate important attributes from groups of authors and reveal unique considerations and preferences in addition to providing the ability to identify unknown associations occurring through natural online conversation. CI’s technology is used in a compounding fashion, starting with topic categorization, to theme extraction, then to trait extraction.Based on highly precise categorization functionality, once the semantic processing engine has been trained for accurate categorization ongoing analysis becomes repeatable, scalable and reliable.
- Applying semantic technology to large volumes of data LSA in particular is the "secret sauce. It is an evolving system versus an analysis of word groupings at a single point in timefar more flexible/nimble than competitors in the NLP space. It compares 600,000 documents for the meaning of each word results in more accurate analysis and better "listening". LSA is a method for exposing latent contextual-meaning within a large body of text – more relevant terms carry more weight to construct more accurate vectors of how consumers are talking about a category, brand or productAble to apply contextual meaning to topics – select conversations based on meaning Social Search - Categorizing ConversationsThe semantic services layer essentially broadens the end market to anyone who needs more accurate search - this includes web search (as long as the user is willing to "wait"), e-discovery, email archiving, and potentially more accurate video search based on descriptions/reviews/tagging, etc.semantic technology is able to isolate and categorize contentGet all the conversation, not filtered like a google or yahoo searchSemantically Surfaced Author DetailsAssign important attributes to authors or groups of authors and reveal unique considerations and preferencesExamine actual language used to describe the company, brand or productApply traits to posts then average these traits together to produce author profile
- Semantic analysis is able to differentiate between “goldfish” the fish and goldfish the cracker.
- Latent Semantic analysis allows users to perform an advanced form of filtering called dimensions to extract language around pricing, quality, loyalty. Simply cannot be done using keyword
- Dimensions Extract specific language around customer service, pricing or issuesDemographics