This document summarizes a webinar about applying deep text analytics to market intelligence. It discusses how deep text analytics can help integrate multiple data sources, generate actionable insights, understand customers and language in depth, analyze the competitive environment, and detect early signs of growth. The webinar presents MeaningCloud as a solution that can understand language at a deep level and extract complex insights from text to make market intelligence more scalable and useful for strategic decision making. Questions from attendees are invited at the end.

1. Deep Text
Analytics for More
Valuable and
Scalable Market
Intelligence
June 24, 2020
MEANINGCLOUD – 2020
Webinar

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MEANINGCLOUD - 2020
We hope you are safe and well

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How to participate
• Send questions using the chat feature,
or
• Click the “Raise your hand” button to
speak and we will enable your mic
• Afterwards, you’ll be able to access a
recording of the webinar and its
contents as tutorials on our blog
Before we get started…
Rob Wescott
Business
Development
Manager

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MEANINGCLOUD – 2020
Why this webinar?
Market / Competitive
Intelligence is very valuable
How to make it more
scalable and actionable?

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Agenda
• Introduction to Market Intelligence
– Benefits and limitations
• Applying deep text analytics
– Integrating multiple sources
– Discovering business opportunities
– Understanding our customers in depth
– Analyzing the environment
– Detecting signs of growth
• Conclusions and questions
rwescott@meaningcloud.com

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Market Intelligence
Market
Intelligence
Customers
Competitors
Partners and
supply chain
Investors
Environment
Actionable information for making strategic decisions

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Why Market Intelligence?
Market
Intelligence
Custo-
mers
• Needs
• Segments
• Perceptions, opinions
• Business opportunities
Compet-
itors
• Preferences and positioning
• New entrants
• New developments in competitors
Partners
• Buy/partner opportunities
• Developments in supply chain
• Investment opportunities
Environ-
ment
• Emerging technologies
• Relevant regulation
• Economic situation
• Achieve competitive
advantage
• Refine business model
• Quick respond in the face of
changing environments

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What is (and what is NOT) Market Intelligence
Market
Intelligence
Competitive
Intelligence
Business
Intelligence
Mainly external sources
Mainly internal sources
Environment
Partners
Customers
Products
Competitors and
other rivals
Customers
Operations

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The truth is our there
Leave all this information untapped is not an option
Social networks
Forums
Blogs
Media
Websites

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Capture – Analyze - Act
Harvest external
data
Analyze millions
of external
documents and
postings
Share and distribute

11. Present Market Intelligence
solutions: some limitations

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Digesting all that information
Many tools are limited to basic
text classification and
information extraction

13. Context is everything – from that comes the understanding of meaning.

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All relevant information?
False alarms
(low analysis
precision, e.g.,
“apple” instead
of “Apple, Inc.”)
Missed targets
(information sources
not covered, low
analysis recall)

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Market Intelligence challenges
From data… to actionable insights
Manual, inefficient processes:
LOOKING FOR A NEEDLE IN A
HAYSTACK

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Deep automatic understanding of text is not easy
Volume: quantity
Variety:
languages, formats
Velocity: immediacy
Ambiguity:
natural, informal language
Automatic means are needed… but not anyone can cut it

17. MeaningCloud:
applying Deep Semantic Analytics
to Market Intelligence

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MeaningCloud: Meaning as a Service
Standard APIs (SaaS and on-premises)
Use it free at www.meaningcloud.com

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Success in this scenario depends on three factors
Integrate any source
Niche, domain-specific
sources
Generate actionable
insights
Business oriented, enabling
decision making
Understand
language
Ambiguity,
specialization

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MeaningCloud’s approach to Market Intelligence
Harvesting content from
social networks, blogs,
forums, review sites…
Deep Text Analytics
Language understanding
Actionable
insights

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MeaningCloud’s approach to Market Intelligence:
two improvement areas
Integrate any source
Generate actionable insights

22. 1. Integrate any source

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Extracting information from any source
Standard integrations
A variety of social networks and
information providers
Web scraping technology
Browse web sites like a human user: authentication,
session management, querying, and data extraction
Other tools are limited to most popular social networks and media

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All the sources that you can extract
Forums, review sites
Customer insights,
competitive analysis,
financial sentiment
Social networks
Customer insights,
competitive analysis,
influencer analysis
Competitors
New products, projects
and partnerships
News
Competitive analysis,
financing events
Government and regulators
Regulation, administrative
authorizations
Industry sites
Supply chain, shortages
Customers (e.g.: buyers)
New projects and partnerships,
procurement solicitations

25. 2. Generate actionable
insights

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MeaningCloud understands language
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Performs a deep morphosyntactic and
semantic analysis of text
Disambiguation technology
“Washington”: city / football team / surname
Standard tools to detect themes, entities,
concepts, sentiment, emotion, intention,
discover new themes, user profiling
Customize to your application/domain
to increase accuracy

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Totally customizable text analytics
• Create your own dictionaries, classification
models, sentiment analysis, etc.
• Graphical user interface - no programming!
• Improve precision & recall
More information:
• Customization tools: recorded webinar
• Dictionaries and sentiment models: recorded
webinar, tutorial
• Text classification models: recorded webinar,
tutorial
• Deep categorization models: recorded
webinar, tutorial

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Traditional text analytics: leaving meaning behind
Entities
Themes
Sentiment
Discover the deep
meaning of complex
documents

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Deep Semantic Analytics
Extraction of
• Passage-level categories
• Semantic relationships
John
Smith
Industrial
Manufacturing Inc.
Global
Technologies Corp.
Has acquired
Is executive
Business-
Mergers&
Acquisitions
Business-
Corporate
executives
John Smith
Industrial Manufacturing Inc.
Global TechnologiesCorp.
Theme: Business-Companies

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Examples of deep insights
• New products
“DataCorp has launched its new product for artificial intelligence
NextAI, targeted at the online banking segment.”
• Supply chain
“ChemCorp can’t sell plants in Ireland , moves to close them.”
• Mergers and acquisitions
“Some investors are already discounting the coming acquisition of
Industrial Manufacturing by Global Tech.”
Launching company Product launch Product category
Product name Market segment
Agent company Supply chain event Location Supply chain event
M&A rumor
Acquired company Acquiring company
Actionable
insights

31. Discovering commercial
opportunities

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Your customers are buying

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Discovery and analysis of purchase processes
Scraping&Crawling
Deepsemanticanalysis
Filtering&Mapping
CRM

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Sales opportunity generation
From a pool of unstructured
documents… … to a set of qualified and
QUANTIFIED sales opportunities
SITE OPPORTUNITYNAME COUNTRY CONTACTO PRODUCT PRESENTATION QUANTITY PRICE DATE
USGov.gob 500,000Protectivemasks US JohnSelf N95masks 1,000uds 500,000 10,000,000$ 2020-03-15
EUPublic.eu 1,000,000CoronavirustestsGermany SelinaStreet Molecular(RT-PCR)tests10,000uds 1,000,000 30,000,000€ 2020-03-03
NHS.uk 10,000MechanicalventilatorsUK StevenSimon BiPAPVentilators1ud 10,000 £400,000,000 2020-04-04
SITE OPPORTUNITYNAME COUNTRY CONTACTO PRODUCT PRESENTATION QUANTITY PRICE DATE
USGov.gob 500,000Protectivemasks US JohnSelf N95masks 1,000uds 500,000 10,000,000$ 2020-03-15
EUPublic.eu 1,000,000CoronavirustestsGermany SelinaStreet Molecular(RT-PCR)tests10,000uds 1,000,000 30,000,000€ 2020-03-03
NHS.uk 10,000MechanicalventilatorsUK StevenSimon BiPAPVentilators1ud 10,000 £400,000,000 2020-04-04
SITE OPPORTUNITYNAME COUNTRY CONTACTO PRODUCT PRESENTATION QUANTITY PRICE DATE
USGov.gob 500,000Protectivemasks US JohnSelf N95masks 1,000uds 500,000 10,000,000$ 2020-03-15
EUPublic.eu 1,000,000CoronavirustestsGermany SelinaStreet Molecular(RT-PCR)tests10,000uds 1,000,000 30,000,000€ 2020-03-03
NHS.uk 10,000MechanicalventilatorsUK StevenSimon BiPAPVentilators1ud 10,000 £400,000,000 2020-04-04

35. Understanding our
customers deeply

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Opinion, emotion, intention, satisfaction
Forums, review sites, communities… are an immense source of information
Sentiment
Analysis
Emotion
Recognition
Intention
Analysis
Multidimensional
Satisfaction
Learn more in this recorded webinar and tutorial
An integrated view of our customers

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Understanding purchasing criteria and preferences
Concerns and
delighters
• What concerns
them and what
they love about
our category?
Key
purchasing
criteria
• What attributes
are the most
relevant?
Perceptions
• How do they
consider us,
when compared
to the
competition?
Preferences
• Why do they
purchase from
us? And from
the
competitors?

38. Analyzing the environment

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Anatomy of patents/scientific articles/regulations
Classification according to
(custom-built) relevant
taxonomies, e.g.: related to
our product categories
Identification of (custom-
defined) relevant topics, e.g.:
extraction of medical
vocabulary
Similarity-based grouping
Discovery of emerging
themes, e.g.: coronavirus
Theme X Theme Y Theme Z

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Automatic summarization:
extraction of meaningful
sentences
Passage-level categorization:
subtopic structure, e.g.:
provisions in a law
Extraction of complex
insights, e.g., semantic
relationships
“”reductions in the size of the training set may
not be assumed to cause algorithm bias”
Variation sign Causal variable
Effect Result variable
Anatomy of patents/scientific articles/regulations

41. Detecting growth signals

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Looking for a company to partner with or to invest in?
News
Social
Jobs
Growth
Signals
• Media presence (SOV, sentiment)
• New customers
• New products
• New projects
• New partnerships
• New recruitments
• New investments
• Mergers and acquisitions

43. Influencer analysis

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Understanding influencers and audiences
• Influencer profiling: publication and
audience themes, engagement
• Influencer targeting
• Fake news detection

45. Conclusions

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Analyze your industry’s complete lifecycle
Funding and financing
• Foundation events: “Serial entrepreneur XXX has funded
electronics company to develop ZZZ.”
• Financing events: “Investor XXX has invested $1 million
in electronics company YYY.”
Business
• Mergers and acquisitions: "Rumors signal interest of
XXX in acquiring company YYY.“
• Alliances and collaborations: "electronics companies
XXX and YYY announce collaboration to develop ZZZ.“
Research
• Research topics: "This article explores the application of
XXX technique to build YYY.“
• Patents: "Patent granted to Company XXX for a new YYY
technology.“
Development
• Prototypes: "New doubts cast over product XXX after
disappointing pilot test."
Regulatory and administrative
• Approval: "FDA granted approval for medical device
XXX."
• Bans: "The government has banned the import and use
of XXX as a component of YYY."
Supply chain
• Supply chain and manufacturing: "XXX reaches
agreement with YYY for the manufacturing of ZZZ."
Marketing
• Product launch: "XXX launches new product YYY."
• Usage experience: “Product XXX is very easy to use."

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Conclusions
Limitations in present technologies
reduce the value of Market /
Competitive Intelligence
The integration of a broad variety
of sources and the extraction of
deep insights enable to make it
more scalable and actionable

48. Q & A time

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Stay tuned to our blog and emails
We’ll be posting a recording of the webinar and
its contents as tutorials soon

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MEANINGCLOUD - 2020 www.meaningcloud.com
Automating the extraction of Meaning from any information source.
+1 (917) 930-76003537 36th Street
New York, NY 11106
rwescott@meaningcloud.com
Thank you for your attention!