Text Analytics Command Center - Vendor Briefing

1

Vendor Briefing

September 7, 2011

Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.

REAL TIME TEXT ANALTYICS

2

Making Sense of Social & Private Data Deluge


How does an organization unify social & private text analytics?

3

Making Sense of Social & Private Data Deluge


Big data presents both unique challenges & potential business

insights

Shifting categorization or theme patterns

Spam, duplicates, misspellings

Volume and velocity

Processing large volumes of data quickly

Real-time, unsolicited, voice of customer or employees

Weak signal can be sign of emerging trend or issues

4

Building a Platform for Handling Social & Private - A Text Analytics Command Center (TACC)


5

Social Media Characteristics


Volume. The number of consumers adopting and using social media platforms continues to grow

Immediate. Real-time, unsolicited, true voice-of-customer

Brand and product mentions but they may be embedded with other themes, topics and interests

Niche but expanding. May represent only a portion of a business’ total consumer audience

Narrow S-CRM focus. Need is expanding beyond Marcom/PR to loyalty, customer service, product development.

Changing the way consumers interact with brands, products & services

6

Analyzing Social Media


A number of technologies use keyword and Boolean expressions

Pros

Inexpensive and easy to set up

Quick results for “exact” terms and phrase matching

Cons

Inefficient at white-space or open-ended analysis

Become more brittle as each expression is added to include or exclude data

Problems with ambiguity and granular filtering

7

Private Text Characteristics


Varied Data Sources. Comprises multiple formats: chat, email, video transcripts

It’s estimated that 80% of business data is unstructured

Fluid Time Frame. Broad time range: data sources from last year or last week

Existing Systems. Organization may have existing teams or technologies in place to analyze data

Narrow focus. Used by customer service call centers to process data they already own to optimize service.

8

Analyzing Private Text


A number of technologies rely on Natural Language Processing (NLP)

Pros

Analyze part of speech & parsing content to diagram context

Enterprise-class technology

Cons

Slow on large, unstructured text

Time-consuming to adjust to shifting content

• Linguistic rules can be cumbersome when applied to social media

9

Collective Intellect can unify Social & Private Data


10

Collective Intellect seeks to maximize the value of text


Daypart Gender Location Subjective

Brand Selected Social handle

Dimensions: Taste, QualitySentiment: Negative

11Proprietary and confidential. Not to be used or reproduced without the consent of Collective Intellect, Inc.

20 million unique authors 500 unique forums/boards 800,000 posts/day

70 million unique authors 9 million tweets/day 100,000 new authors/day

2.5 million authors 40,000 unique sites 200,000 posts/day

50 million unique authors 2 million fan pages/user groups 1 million+ posts/day

Social Media Consumer Generation

Social media vertical Sub-sector Representative players

Networks/platforms - Social networks- Professional networks

Content creation, distribution and customization - Content customization- Livecasting and over-the-top video- Location-based services- User content publication and aggregation- User-generated video

Communication and interaction tools - Microblogging- Real-time communication

15 million unique blogs 1 million+ posts/day 10,000 new blogs/day

Social Media Consumer Generation

Social media vertical Sub-sector Representative players

Networks/platforms - Social networks- Professional networks

Content creation, distribution and customization - Content customization- Livecasting and over-the-top video- Location-based services- User content publication and aggregation- User-generated video

Communication and interaction tools - Microblogging- Real-time communication

Social: 180M unique authors 300K new authors/day 10M posts/day

Private: Any text-based data Setup within hours

600 thousand unique consumers 60 thousand reviews/day 25 unique review sites

Survey/Focus Group Verbatim

Private Community Conversations (External & Internal)

Call Center/Email/Chat Transcripts

Text-Translated Video

Private news, research, feeds

Private DataSocial Data

TACC Transforms Data Into Intelligence

12

Text Analytics Command Center


CI’s semantic engine uses latent semantic analysis

supports enterprise-wide business intelligence efforts

applies the same standard and rigors to both social and private data analysis

addresses the inaccuracy and bluntness of keyword search & the speed and cost disadvantages of NLP

surfaces customer and market insight from social media in real-time

makes data discoverable in a repeatable, measurable process

solves the problems of gaining insight from massive amounts of unstructured data in real time

available as both SAAS self-service and embedded analytics engine

Latent Semantic Analysis – Optimized for Speed & Accuracy


Pre-filter: Narrows large data-sets for analysis with

more sophisticated semantic processing› Issues with ambiguity› Difficult to provide granular filtering

Insight: High Quality Similarity Measures High Performance for Speed and Precision Easier Maintenance Used for Highly Accurate Categorization Spam identification

Speech analysis: Parsing content to diagram context

› Slow on large, unstructured text› Time consuming to adjust with changing

content

Keyword/Boolean

LSA

NLP

Text Analytics Command Center – Semantic Engine

14



Optimized to filter and organize big volumes of unstructured data


Collective Intellect Semantic Categorization of “Reuters-21578, Distribution 1.0” Test Collection

(92% correctly categorized in top 2 rankings)

Collective Intellect has an approach that achieves high levels of categorization out of the box

16

AwarenessPrice

Quality

Problem

ReferralInnovation

Purchase

Consideration/ Preference

Loyalty Safety

Inte

rest

Dim

ensi

ons In

tent D

imensio

ns



Dimensions extract language meaning

17

Collective Intellect Semantic Analytics EngineMillions of social media conversations per day across 200+ million authors

Billions of social media conversations available for back-scoringAbility to integrate client’s “private” conversational data

Analytics Multi-dimensional analysis Blended Qualitative & Quantitative Demographics/Personas Integrated consumer conversation

analytical hub (text mining center)

INSIGHT



VIEW

Trending Executive View KPIs Tracking

LEARN

Custom Researcho Qualitative/Quantitative Reportso Insights & Recommendations

Professional Services

Software

Product Suite

18

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

19

DEMO



20

Future Applications of CI’s TACC


Social CRM. Developing strategic partnerships to integrate our platform into large ISVs to enable 1:1 customer experience management.

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.

Emerge as the central text-mining engine for bringing consumer conversational content into other broader-based applications

21

Thank You!



Technology

Text Analytics Command Center - Vendor Briefing