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From Strangers to Acquaintances Multidimensional Customer Profiling
MeaningCloud
July 15, 2015
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Agenda
Why basic Sentiment Analysis is not enough
Using multichannel, unstructured content to profile customers: Scenarios and benefits
How to implement this using MeaningCloud today!
Conclusions
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Basic, aggregated detection of mentions and sentiment is no longer enough
Technology allows to process social media and other unsolicited, unstructured customer feedback sources and detect mentions, polarity
This enables to understand the general view, but…
How is each specific customer like? Who says what? Why do they say that? What opportunities are out there?
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What if you could use all customer feedback and…
…Turn Strangers into Acquaintances!
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So many useful data that you can extract NOW…
Turn your customer expressions into personal data
Demographics
• Age
• Gender
• Location
• Education
• Occupation
• Family…
Psychographics
• Opinions
• Attitudes
• Affinities
• Lifestyle…
Customer journey
• Awareness
• Consideration
• Decision
• Purchase
• Loyalty
• Advocacy…
Online surveys Social conversations Contact center interactions
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How you can leverage all that data
Male 25-35 Pragmatic Brand ++
Female 45-65 Skeptic Brand -
Female 45-65 Conservative Brand +
Male 25-35 InnovatorBrand ++
Male 25-35 InnovatorBrand ++
Female 45-65 Conservative Brand -
Female 35-45 Pragmatic Brand +
Male 45-65 Skeptic Brand ++
Female 45-65 Conservative Brand -
Female 35-45 Pragmatic Brand -
Female 35-45 Pragmatic Brand -
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How you can leverage all that data
Male 25-35 Pragmatic Brand ++
Female 45-65 Skeptic Brand -
Female 45-65 Conservative Brand +
Male 25-35 InnovatorBrand ++
Individual Profiles Scores Signals: purchase, churn…
Male 25-35 InnovatorBrand ++
Female 45-65 Conservative Brand -
Female 35-45 Pragmatic Brand +
Male 45-65 Skeptic Brand ++
Female 45-65 Conservative Brand -
Female 35-45 Pragmatic Brand -
Female 35-45 Pragmatic Brand -
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How you can leverage all that data
Male 25-35 Pragmatic Brand ++
Female 45-65 Skeptic Brand -
Female 45-65 Conservative Brand +
Male 25-35 InnovatorBrand ++
Aggregate Segments Personas (archetypes) Perception analysis Competitive analysis Product ideas & issues
Individual Profiles Scores Signals: purchase, churn…
Male 25-35 InnovatorBrand ++
Female 45-65 Conservative Brand -
Female 35-45 Pragmatic Brand +
Male 45-65 Skeptic Brand ++
Female 45-65 Conservative Brand -
Female 35-45 Pragmatic Brand -
Female 35-45 Pragmatic Brand -
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Why YOU should be doing this: actionable insights
1:1 Engagement Personalized messages and experiences throughout each consumer’s journey E.g., customer complains on Twitter Contact him directly
Product development Need identification, improvement ideas E.g., lots of customers identify issue in present product
Market targeting and competitive positioning Who are my most promising target customers and what should I tell them? E.g., brand personality, messaging and creative
Campaign planning and management How can I reach them? E.g., media selection and planning
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Customer Profiling with MeaningCloud
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MeaningCloud: “Meaning as a Service”
Register and use it FREE at http://www.meaningcloud.com
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Text analytics
Extract meaning and actionable insights from unstructured content
Automatization of costly manual activities
MeaningCloud provides this in a convenient, web service-based offering
OpinionsFacts
Concepts
Organizations
People
Semantic
Analysis
Relationships
Themes
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APIs services of MeaningCloud Sentiment analysis Global Aspect-based
Classification Standard models
Topic extraction Entities Concepts Dates Addresses Economic quantities Time expressions …
https://www.meaningcloud.com/demos/media-analysis/ 13
Topic Extraction Disambiguate appearances of brands, companies, organizations, people… and many more
Contextual disambiguation
Apple = company (not fruit)
Coreference
Based on standard ontology
Extendable/customizable dictionaries
In a filing with the SEC today, Apple revealed that CEO Tim Cook has donated the equivalent to approximately $6.5 million in Apple stock shares to charity this week. Since becoming CEO in 2011, Cook has promoted charity as a key part of Apple’s mission. Upon taking over, Cook initiated an employee charity program. Apple has also expanded its offerings for employees to help their communities.
Topic detected
Semantic information
Tim Cook Person, Timothy Donald Cook, Executive Apple Inc.
Apple Company, Apple Inc., Technology, USA
SEC Organization, Securities and Exchange Comission, Government, USA
$6.5 million Monetary amount, USD, 6.5 million
charity Concept, charity
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Text Classification (featuring standard models, e.g. IAB) Mix machine learning and rules to accurately classify text according to predefined categories
The World Cup is the best way to see the potential football can have for your inbound travel, economic success and positive public image: The 2006 World Cup in Germany was a prime example of this power with: $200+ per day average tourist spending, 50,000 new jobs created, 18 million people at Fan-Fests, total worldwide TV viewership at 30 billion and 4.2 billion official webpage views. In a survey, 90% of foreigners who visited the World Cup said they felt welcome there and would recommend Germany as a holiday destination. "The World Cup marks an enormous gain in Germany's image, even if it's difficult to put an economic figure on this change in image, the economy as a whole will certainly benefit from it." the German economics minister, Michael Glos, said.
Categories Relevance
Sports – World soccer 0.7
Travel - Europe 0.2
Arts & Entertainment - Television 0.3
Hybrid technology
Machine learning and/or rules
Features standard classification models
IPTC (news), IAB (advertising, public beta), etc.
Customizable classification models
IAB (English)
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Sentiment Analysis Assign multilevel polarity to entities and other aspects, discriminate facts from opinions and detect irony
IBM stock fell another 1.51%, while their cloud business revenue rose 60 percent in 2014.
Aspect Sentiment
IBM - stock N
IBM - revenue P+
Global NEU, DISAGREEMENT, OBJECTIVE, NON IRONIC
Aspect Sentiment
Excelsior Hotel - landscapes P+
Excelsior Hotel - rooms N-
Global NEU, DISAGREEMENT, SUBJECTIVE, NON IRONIC
5-level polarity (plus absence of polarity) scoring
Aspect-based analysis
Objective (fact) / subjective (opinion) discrimination
Irony detection (beta)
Customizable sentiment models (in beta, contact us)
Excelsior Hotel has the most amazing landscapes I've ever seen, but the rooms are disgusting.
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Customer Profiling Use the profile and content generated by the user to infer his demographic attributes
20% of companies say process digitization yields actionable #analytics Is your IT team talking SMAC (#social, #mobile, #analytics, & #cloud)? Five Rules of Modern Icon Design http://bit.ly/1y3B6i6 What Twitter Can Be. http://wp.me/p2Gq8C-6E Just if they'd play nice with the ecosystem ... #socialtv #recommendation What your name says about your age, where you live, your politics & your job http://wapo.st/1RkqDcA
Londoner, hooked on data science, NLP and REST.
Social posts
Social profile
Atribute Value
Person/Organization Person
Gender Male
Age 25-35
Location London
Occupation Engineer
Person /organization
Gender
Age
Location
Occupation
…
Now in private beta
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Customization tools
Create your own dictionaries, classification models, and sentiment analysis (beta)
Graphical user interface - no programming!
Improve precision & recall
Learn more about customization in this webinar 18
Add-in for Excel
Totally integrated in Excel experience
Easy to use - No programming!
The most convenient way to evaluate, prototype and use MeaningCloud
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Democratizing the extraction of meaning
High quality semantic analysis
Optimized technology mix
Continuously updates semantic resources
High-level APIs, e.g., Customer Profiling
Customizable to customer domain: models, dictionaries, sentiment
Affordable, no risks
Mature, tested technology
Test and use for FREE (40,000 requests per month)
Pay per use
No commitment or permanence
Commercial plans beginning at $99 /mo
For developers and non
technical users
Add-in for Excel
Standard web services APIs
Plug-ins and SDKs for diverse environments and languages
Plug-and-play approach
OpinionesTemasHechos
Conceptos
Organizaciones
Personas
Relaciones
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A platform for leveraging unstructured content in Voice of the Customer / Customer Experience contexts
What you should expect from MeaningCloud in the coming months
GA
Mention detection & theme
classification
Granular sentiment analysis
Corporate reputation (ES)
Customization tools
Q3 2015
Demographic profiling
Industry- and app-specific
dictionaries and models, e.g., IAB,
banking
Q4 2015
Trend emergence and analysis
Q1 2016
Customer journey stage &
actionable signals
Q2 2016
Perception maps & brand
personality
Competitive analysis
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Customer case: SocialBro
Customer: leader in Twitter community analysis and marketing tools Problem: process massive amounts of tweets (1,000 tweets per sec peaks)
Our Solution: based on user’s social comments and profiles, we inferred demographic profile of community members and analyzed aspect-based sentiment toward specific brands Insights / results: data-based, actionable segments and better marketing campaigns targeting
Social profile
Social posts
Social posts
John Smith
Person
Male
35-45 yr.
London
Doctor
Mary Doe
Person
Female
45-55 yr.
Berlin
Pilot
Social profile
Male 35-45 year Big cities Business owner Positive brand attitude
Female 45-55 year Mid-sized cities Professional Negative brand attitude
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Conclusions
Unstructured content in social media and other channels offers untapped possibilities to understand customers
Text analytics technology can turns this content into actionable insights: profiles, signals
MeaningCloud is the easiest, most customizable and most affordable way to do it
Interested? See our demo tomorrow Workshop Track, 9:20 am
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Thank you for your attention!
Questions, suggestions...
Find us in or booth, see our demo tomorrow or contact us directly
Antonio Matarranz
Jarred McGinnis
MeaningCloud LLC
1120 Broadway, Ste. 805
New York, NY 10010
USA
Phone: +1 (646) 403-3104
http://www.meaningcloud.com
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