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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  • 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
  • Text Analytics Command Center - Vendor Briefing

    1. 1. REAL TIME TEXT ANALTYICS<br />Vendor Briefing<br />September 7, 2011<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    2. 2. Making Sense of Social & Private Data Deluge<br />How does an organization unify social & private text analytics?<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    3. 3. Making Sense of Social & Private Data Deluge<br />Big data presents both unique challenges & potential business <br />insights<br /><ul><li>Shifting categorization or theme patterns
    4. 4. Spam, duplicates, misspellings
    5. 5. Volume and velocity
    6. 6. Processing large volumes of data quickly
    7. 7. Real-time, unsolicited, voice of customer or employees
    8. 8. Weak signal can be sign of emerging trend or issues</li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    9. 9. Building a Platform for Handling Social & Private - A Text Analytics Command Center(TACC)<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    10. 10. Social Media Characteristics<br />Changing the way consumers interact with brands, products & services<br /><ul><li>Volume. The number of consumers adopting and using social media platforms continues to grow
    11. 11. Immediate. Real-time, unsolicited, true voice-of-customer
    12. 12. Brand and product mentions but they may be embedded with other themes, topics and interests
    13. 13. Niche but expanding. May represent only a portion of a business’ total consumer audience
    14. 14. Narrow S-CRM focus. Need is expanding beyond Marcom/PR to loyalty, customer service, product development. </li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    15. 15. Analyzing Social Media<br />A number of technologies use keyword and Boolean expressions<br /><ul><li>Pros
    16. 16. Inexpensive and easy to set up
    17. 17. Quick results for “exact” terms and phrase matching
    18. 18. Cons
    19. 19. Inefficient at white-space or open-ended analysis
    20. 20. Become more brittle as each expression is added to include or exclude data
    21. 21. Problems with ambiguity and granular filtering</li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    22. 22. Private Text Characteristics<br /><ul><li>Varied Data Sources. Comprises multiple formats: chat, email, video transcripts
    23. 23. It’s estimated that 80% of business data is unstructured
    24. 24. Fluid Time Frame. Broad time range: data sources from last year or last week
    25. 25. Existing Systems. Organization may have existing teams or technologies in place to analyze data
    26. 26. Narrow focus. Used by customer service call centers to process data they already own to optimize service. </li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    27. 27. Analyzing Private Text<br />A number of technologies rely on Natural Language Processing (NLP)<br /><ul><li>Pros
    28. 28. Analyze part of speech & parsing content to diagram context
    29. 29. Enterprise-class technology
    30. 30. Cons
    31. 31. Slow on large, unstructured text
    32. 32. Time-consuming to adjust to shifting content
    33. 33. Linguistic rules can be cumbersome when applied to social media</li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    34. 34. Collective Intellect can unify Social & Private Data <br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    35. 35. Collective Intellect seeks to maximize the value of text<br />Brand Selected<br />Social handle<br />Daypart<br />Gender<br />Location<br />Subjective<br />Dimensions: Taste, Quality<br />Sentiment: Negative<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    36. 36. TACC Transforms Data Into Intelligence<br />Private Data<br />Social Data<br /><ul><li>20 million unique authors
    37. 37. 500 unique forums/boards
    38. 38. 800,000 posts/day
    39. 39. Survey/Focus Group Verbatim
    40. 40. 50 million unique authors
    41. 41. 2 million fan pages/user groups
    42. 42. 1 million+ posts/day
    43. 43. Private Community Conversations (External & Internal)
    44. 44. 15 million unique blogs
    45. 45. 1 million+ posts/day
    46. 46. 10,000 new blogs/day</li></ul>Social:<br /><ul><li>180M unique authors
    47. 47. 300K new authors/day
    48. 48. 10M posts/day</li></ul>Private:<br /><ul><li>Any text-based data
    49. 49. Setup within hours
    50. 50. Call Center/Email/Chat Transcripts
    51. 51. 70 million unique authors
    52. 52. 9million tweets/day
    53. 53. 100,000 new authors/day
    54. 54. Text-Translated Video
    55. 55. 2.5 million authors
    56. 56. 40,000 unique sites
    57. 57. 200,000 posts/day
    58. 58. Private news, research, feeds
    59. 59. 600 thousand unique consumers
    60. 60. 60 thousand reviews/day
    61. 61. 25 unique review sites</li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    62. 62. Text Analytics Command Center<br />Latent Semantic Analysis – Optimized for Speed & Accuracy<br />CI’s semantic engine uses latent semantic analysis<br /><ul><li>supports enterprise-wide business intelligence efforts
    63. 63. applies the same standard and rigors to both social and private data analysis
    64. 64. addresses the inaccuracy and bluntness of keyword search & the speed and cost disadvantages of NLP
    65. 65. surfaces customer and market insight from social media in real-time
    66. 66. makes data discoverable in a repeatable, measurable process
    67. 67. solves the problems of gaining insight from massive amounts of unstructured data in real time
    68. 68. available as both SAAS self-service and embedded analytics engine</li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    69. 69. Text Analytics Command Center – Semantic Engine<br />Pre-filter:<br /><ul><li>Narrows large data-sets for analysis with more sophisticated semantic processing
    70. 70. Issues with ambiguity
    71. 71. Difficult to provide granular filtering</li></ul>Keyword/Boolean<br />LSA<br />Speech analysis:<br /><ul><li>Parsing content to diagram context
    72. 72. Slow on large, unstructured text
    73. 73. Time consuming to adjust with changing content</li></ul>NLP<br />Insight:<br /><ul><li>High Quality Similarity Measures
    74. 74. High Performance for Speed and Precision
    75. 75. Easier Maintenance
    76. 76. Used for Highly Accurate Categorization
    77. 77. Spam identification</li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    78. 78. Text Analytics Command Center<br />Optimized to filter and organize big volumes of unstructured data<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    79. 79. Collective Intellect has an approach that achieves high levels of categorization out of the box<br />Collective Intellect Semantic Categorization of “Reuters-21578, Distribution 1.0” Test Collection<br />(92% correctly categorized in top 2 rankings)<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    80. 80. Text Analytics Command Center<br />Dimensions extract language meaning<br />Safety<br />Loyalty<br />Awareness<br />Price<br />Consideration/ Preference<br />Intent Dimensions<br />Interest Dimensions<br />Problem<br />Purchase<br />Quality<br />Referral<br />Innovation<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    81. 81. Text Analytics Command Center<br />Product Suite<br />Professional <br />Services<br />VIEW<br />INSIGHT<br />LEARN<br />Custom Research<br /><ul><li>Qualitative/Quantitative Reports
    82. 82. Insights & Recommendations</li></ul>Software<br />Analytics<br /><ul><li>Multi-dimensional analysis
    83. 83. Blended Qualitative & Quantitative
    84. 84. Demographics/Personas
    85. 85. Integrated consumer conversation analytical hub (text mining center)</li></ul>Trending<br /><ul><li>Executive View
    86. 86. KPIs Tracking</li></ul>Collective Intellect Semantic Analytics EngineMillions of social media conversations per day across 200+ million authors<br />Billions of social media conversations available for back-scoring<br />Ability to integrate client’s “private”conversational data<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    87. 87. Customized analysis that is designed specifically to discover and trend KPIs relevant to a business<br />Proprietary and confidential. Not to be used or distributed without the consent of Collective Intellect, Inc.<br />Usecase: Analysis of client feedback forms<br />Client XYZ used Collective Intellect’s software to determine which issues caused the most dissatisfaction among guests. <br />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. <br />Outcome<br />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.<br />Client XYZ now has a clear understanding of where to focus capital for improvement and how to adjust messaging. <br />Example of Customized Dashboard<br />
    88. 88. REAL TIME TEXT ANALTYICS<br />DEMO<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    89. 89. Future Applications of CI’s TACC<br />Emerge as the central text-mining engine for bringing consumer conversational content into other broader-based applications<br /><ul><li>Social CRM. Developing strategic partnerships to integrate our platform into large ISVs to enable 1:1 customer experience management.
    90. 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. </li></ul>Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />
    91. 91. REAL TIME TEXT ANALTYICS<br />Thank You!<br />Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.<br />

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