This document provides an overview of how to identify emerging technologies using a company database. It discusses searching the database to understand sectors, identifying top themes and growth areas using bar charts and timelines, finding top investors and their focus areas, and discovering more similar companies. The goal is to go through an end-to-end workflow to understand emerging markets and technology trends from company data.

1. TECH SCOUTING
In this session you will learn how to go through an end-to-end workflow to identify
emerging technologies

2. A B OU T TEC H SC OU TIN G
GOAL:
The goal of this session is to go through an
end-to-end workflow within the companies
database as well as explore advanced features
can be utilized to enhance your analysis
capabilities.
We will review searching, manipulating the
data, and drawing insights from the views
generated
1. The companies database can be used to
understand emerging sectors in a market
landscape, identify investment, map
innovation, find adjacency opportunities,
understand transaction trends, and source
companies.
2. The patents database can be used to
understand emerging sectors in a technology
market and perform due diligence on a specific
company or area of interest.
3. Academic papers can be used to understand
technology researched and developed in
universities
For this session, we will be focusing on
exploring companies and patents
METHODOLOGY:

3. ID EN TIFYIN G EMER GIN G SEC TOR S U SIN G TH E C OMPA N IES D ATA B A SE
Understand what companies are emerging and what technology trends are
The Process:
1. Create Boolean search based on area of interest
2. Refine search using companies search page
3. Visualize the network and rename clusters
4. Identify top themes and general growth areas
5. Identify top investors & their focus areas
6. Identify innovative companies in different sectors

4. 1. C R EATE B OOLEA N SEA R C H B A SED ON A R EA OF IN TER EST
As with many other search engines, Quid utilizes Boolean search terms to query the database of news articles.
These queries are built using AND, OR, & NOT operators in conjunction with keywords in order to specify what
articles the user would like to return.
Example Question:
What companies are involved in the artificial
intelligence and internet of things space?
Keywords:
Artificial intelligence – AI, artificial intelligence
Internet of things– internet of things, iot
Query:
(AI OR “artificial intelligence”) AND (”internet of
things”~3 OR iot)

5. C OMPA N IES SPEC IFIC SEA R C H OPER ATOR S
Operator Example Description
name: name:diabetes Search by company name but not the detailed description
body: body:insulin Search the company technical description
description: body:insulin Search by the short business description
founded: founded:2000, founded > 2011 Search by founding year
kind: kind:public, kind:Public Search by Public, Private, or Investor
city: city: London Search by city (company headquarters)
state: state:alaska Search by state (company headquarters)
country: country:china Search by country (company headquarters)
acquirer: acquirer:google Search by acquirer
owner: owner:google Search by owner (parent company)
investor: investor:google, investor: (google AND intel) Search by investor
$total: $total:50M
Seach by total investment amout, logical operators (<, >, <=, >=, ==) are
available
$in: $in:100M
Search by individual funding round investment, logical operators (<, >, <=,
>=, ==) are available
$out: $out:100M
Search by a companies investments, logical operators (<, >, <=, >=, ==) are
available
exit: exit: 'Merger/Acquisition' Search by the exit type
dataset: dataset: quid or dataset: (quid OR expanded) Narrow the search results by dataset (expanded, other, quid)
keyword: keyword:cell Search by extracted keyword
While the overall search logic for companies is similar to that reviewed in with news and blogs, there are several search
operators which can help you narrow and refine you search.

6. 2. R EFIN E SEA R C H U SIN G C OMPA N IES SEA R C H PA GE
Related terms:
Related terms allow you to select other search terms that
you may want to add to your query based off of your current
search terms
Companies Returned:
Once you run a query, Quid will display how many
companies were identified in our database based on the
query run. The query will search each companies
description which is provided by our data partners and
augmented by Quid’s own propriety database.
Relevance:
Relevance is determined by looking at instances of the
search query within the company description according to 3
main components: use of the query in the title, frequency of
use in the body, and how early within the body the query
term was used.
Filtering:
There are a variety of ways to filter the data once a query has been run
Similar:
Also know as the Discover More feature – by clicking this
button Quid will search its database for other companies that
are similar to the ones you have selected. You can discover
up to 500 other similar companies.
• Amount of Funding (in a range)
• Date (in a range)
• Type of Investment
• Description Type
• Total Private Funding
• Investors
• Acquirers
• Exit Type
Within the search page, there are several ways to refine your search in order to surface the most relevant companies within a given space

7. Once you arrive at the visualize page, you’ll be able to rename clusters using the Cluster Legend on the right
3. VISU A LIZE N ETW OR K A N D R EN A ME C LU STER S
Cluster Legend:
The legend will provide a reference for
the coloring of any visualization. This is
a dynamic panel so you can select any
of the options in the legend to highlight
the data point that the coloring applies
to. By default, the legend with reflect
cluster coloring.
Export:
Once you have a visualization that you
like or you have a curated network you
may want export the data into a
Powerpoint, CSV, or image to share with
colleagues or clients.
Information Panel:
The info panel reflects general
information on any visualization within
Quid. Depending on the dataset,
different information will be displayed.
This is a dynamic panel and will reflect
whatever is selected on the screen.
Key information that can be found here
are: keywords, investment amount,
investors, investment rounds and
company information.
Search In Network:
Allows you to search for specific
words, people, or entities within a
network.
Control Panel:
The control panel is the
navigation hub within Quid,
enabling the user to pivot and
analyze the data across different
views and lenses. The options
vary by dataset and view. Typical
views found in all three integrated
datasets include network,
scatterplot, bar chart, histogram,
and heatmap .
Tagging:
Tags displays the network tags
that you have created within the
visualization. Tags can be a great
way to add a personal touch to an
analysis. Tags can be created
through several methods including
search in network and selection.
Filtering:
The filtering menu allows you to filter the
displayed data across available attributes
within the network. This is a great way to
focus your insights and cut the data differently
for deep dives.

8. QU ID METR IC S
An important part of any analysis is understanding what data is available for your analysis. The following are
some important metrics which may help you as you create your analysis.
Q U I D G E N E R AT E D M E T R I C S
Betwenness Centrality:
Represents how connected a node is within the network. Nodes with high betweeness centrality have
many connections that extend to disparate parts of the network. Nodes with low betweeness centrality
have connections that are close together.
Degree:
Degree is a measure of the number of shared connections in a given node. A node with a degree of 5 is
connected to 5 other nodes in the current view (will not take into account filtered or deleted nodes). A
node with high Degree is highly representative of other nodes in the same area.
Initial Degree:
Initial Degree measures the number of connections for a given node prior to any filtering or network
editing.
Flow: Flow represents the combined strength of all of a node’s connections. Nodes with a high flow
have more shared language and more connections with other nodes in the network. Nodes with
a low flow can be thought of as outliers, containing language that is more peripheral to the network.
Inter-Cluster Connectivity: Inter-Cluster Connectivity is a ratio of how many direct connections to a
node are within the same cluster. A node with high Inter-Cluster Connectivity contains language that is
shared by nodes in multiple different clusters. A node with low Inter-Cluster Connectivity is not connected
to many other clusters. Clusters with high Inter-Cluster Connectivity can help you identify news stories or
companies that bridge multiple topics.

9. QU ID META D ATA : C OMPA N IES
Metadata Description
Founding Year The publically disclosed year the company was founded
Operating Status Shows whether a company is currently operating, out of business, reorganizing, a subsidiary, or acquired.
Company Type Company type denotes whether a company is public, private, an investor, or government entity.
City The city where the company is headquartered
State The state where the company is headquartered
Country The country where the company is headquartered
Industry Code A code which helps determine what industry a company is classified as by our data partners.
Investment Received Amount The disclosed dollar value of all investments that a company has received.
Investment Received Count The total count of investment rounds, including those which were undisclosed.
Investors
A list of publicly disclosed investors (the number appearing next to an investors name in parentheses denotes the number of times
they have invested)
Acquisition Made Amount The disclosed dollar value of all the acquisitions that a company has made.
Acquisition Made Count The total count of acquisitions, including those which were undisclosed, is shown in parenthesis.
Acquisition Received Amount The disclosed dollar value of all the acquisitions that a company has received.
Acquisition Received Count The total count of acquisitions, including those which were undisclosed, is shown in parenthesis.
Parent Company The parent organization, if a company is acquired or an subsidary
IPO Amount The disclosed dollar value of the IPO
IPO Count Total number of times a company has gone public
Exchange Tickers If a public company, the exchange ticker
Exit Type Information detailing whether exits were mergers, acquisitions, or IPOs.
Keywords Keywords are the most meaningful words and phrases extracted from company descriptions.

10. B A SIC C OMPA N Y VISU A LIZATION S
While most of the visualizations within the companies dataset are the same as news, with the exception of HeatMap, the data provided can
lead to very different insights
Network Map: Shows the overall search, relationships, emerging and prominent clusters.
• Companies colored by cluster
• Clusters colored by cluster (high level view)
• Stories colored by sub-cluster (more granular view)
5 Main Visualizations & Typical Views:
Scatterplot: Can be instrumental in looking at up to 4 variables at once. The x axis, y axis, and nodes can all represent
different variables/metadata.
• Market maturity vs. investment amount – assessing emerging vs. mature segments of the market
• Market maturity vs. investment count
Bar Chart: Bar chart view is a standard way to quantify Quid insights – with each axis being customizable
• Investors colored by cluster – to assess leading investors within the space and the places
• Acquirers colored by cluster – to assess coverage by topic
• Top company by Investment amount/count or acquisition amount/count
Timeline: Enables you to see how particular conversations and themes are changing in volume overtime – can identify
themes that are event driven or changing
• Count of investments over time colored by cluster
• Count of investment amount overtime colored by cluster
Heatmap: The Heatmap layout provides a summary view, highlighting valuable statistics across clusters, sub-clusters,
or tags within a Companies network.

11. IN TR OD U C TION TO H EATMA P
The companies Heatmap can be a powerful way to identify market opportunities. When you create a Heatmap
by cluster, you can quickly see where money is flowing (or not) within a set of companies.
Within a Heatmap, quickly see summary statistics for any of the following:
• Number of Companies
• Median Founding Year
• Total Number of Investments Received
• Total Investment Amount Received ($USD)
• Median Investment Amount Received ($USD)
• Mean Investment Amount Received ($USD)
• Investment CAGR
• Number of Exit Events
• Total Exit Amount ($USD)
• Number of Acquisition events
• Total Acquisition Amount ($USD)
• Number of IPO events
• Total IPO Amount ($USD)
We can quickly use Heatmap to answer questions like,
• Which clusters are highly saturated? (Sort descending by Num.
Companies)
• Which clusters have grown the fastest? (Sort descending by Investment
CAGR)
• Which clusters have had the largest exists? (Sort descending by Median
Exit Amount)

12. 4. ID EN TIFY TOP TH EMES A N D GEN ER A L GR OW TH A R EA S ( 1/2)
The bar chart can be used to identify top areas of investment
1. Use the Control Panel on the left to navigate to the Bar Chart view
2. Change the Bar Value within the Axes tab to represent “Investment
Received Amount” in order to visualize areas of high investment
3. Add Labels by navigating to the Labels tab in the Control Panel and
selecting “Show Data Labels”
Example: AI and IOT companies*
Steps
*Based on a Quid network of 1697 companies focused on artificial intelligence and the Internet of
Things
See legend in Appendix

13. 4. ID EN TIFY TOP TH EMES A N D GEN ER A L GR OW TH A R EA S ( 2/2)
The timeline view can be used to identify areas of investment growth and decline
1. Use the Control Panel on the left to navigate to the Timeline view
2. Select types of funding to include in timeline
3. Add Labels by navigating to the Labels tab in the Control Panel and
selecting “Show Data Labels”
Example: AI and IOT companies*
Steps
*Based on a Quid network of 1697 companies focused on artificial intelligence and the Internet of
Things
See legend in Appendix

14. 5 . I D E NTIF Y T OP I N V E STORS & T HE IR F OC US A R E AS
The bar chart can be used to find top investors and key focus areas
1. Use the Control Panel on the left to navigate to the Bar Chart
view
2. Change Bars Represent to Investors
3. Add Labels by navigating to the Labels tab in the Control
Panel and selecting “Show Data Labels”
Example: AI and IOT companies*
Steps
*Based on a Quid network of 1697 companies focused on artificial intelligence and the Internet of
Things
See legend in Appendix

15. 6. ID EN TIFY IN N OVATIVE C OMPA N IES IN D IFFER EN T SEC TOR S
The bar chart can be used to identify top companies receiving investment in different sectors
1. Use the Control Panel on the left to navigate to the Bar Chart view
2. Change Bars Represent to Company Name
3. Add Labels by navigating to the Labels tab in the Control Panel and
selecting “Show Data Labels”
Example: AI and IOT companies*
Steps
*Based on a Quid network of 1697 companies focused on artificial intelligence and the Internet of
Things
See legend in Appendix

16. ADVANCED
CAPABILITIES OF THE
COMPANIES DATASET

17. A D VA N C ED : R A N K IN G - C OMPA N IES EXA MPLE
Using Quid’s CSV output you can use Quid metrics to create a ranking system for people, companies,
institutions, and authors.
While a simple bar chart in Quid is a great way to
understand how a company performs on one metric (e.g.
investment amount) – it doesn’t allow you to assess how
several different metrics work in tandem.
By exporting Quid’s data into a CSV and manipulating
different meta data using a pivot table you can create more
complex rankings that can better reflect the nuances within
a certain concept.

18. A D VA N C ED : EXPOR TIN G TR A N SA C TION D ATA & R EPOR TS
The companies is comprised of a variety of different data tables. Fundamentally, Quid analyzes the
descriptions of the companies, but uses transactional data – “Events” – to layer on temporal investment data
• Select the down arrow icon to the right of the
“Create Network” button
• A drop down will appear with 9 options
• Select “Create Report”
• A pop-up will appear titled “Generate Report”
• Input the kind of report: “Company Profile,” “Event,”
etc.
• Input the desired date range*
*Exports are allowed within the previous 5 years

19. A D VA N C ED : D ISC OVER MOR E C OMPA N IES
Another unique features of the companies dataset is ”Discover More” which allows you expand your search
beyond your current parameters.
The Process:
This is helpful once you've identified a sub-cluster of interest within an
existing network, or if you have a particularly undefined space or set of
companies and are trying to explore that space further.
To do so, click the "Visualize" button, and then click "Run in Background" to
bring you back to the project page. On the right hand side, click on the
arrow pointing down and select "Discover More".
You can add up to 500 additional companies. Note that when your original
network is smaller, you may not want to add 5x as many companies as this
increases the likelihood of noise/irrelevant companies being brought into
your network.
You can choose to add these companies to your current portfolio or create
an entirely new portfolio to keep them separate. Once you've determined
how many additional companies to add, click Discover.
To visualize this network, first click "Create Network" on the right hand side.

20. A D VA N C ED : U PLOA D IN G YOU R OW N LIST OF C OMPA N IES
In addition to querying for a portfolio of companies, you can alternatively analyze a set of predefined
companies - bypassing the search process and use Quid to visualize a custom list of companies.
The Process:
First, you will need a csv with either company names (Quid can attempt to
match the names to the companies contained the database) or company
database ids (can be found in the CSV export of any companies network).
Save a CSV with your names or IDs in on column under the “id” OR “name”
(note that you can only upload 1,000 companies).
To upload the list – you will need to click new search and select the upload
button next to the companies option.
Quid will return a list of all the companies and their matches – it is
important to identify any companies you want to deselect and confirm with
“add selected”.
Once your portfolio has been saved you will be returned to the original
company search page and you can go ahead and visualize the network.

21. APPENDIX

22. N E T WORK M A P
*Based on a Quid network of 1697 companies focused on artificial intelligence and the Internet of
Things
CLUSTERS
A HEALTHCARE 10%
B RETAIL INNOVATION 8.8%
C DIGITAL TRANSFORMATION 7.6%
D UNSTRUCTURED DATA ANALYSIS 7.0%
E INDUSTRIAL IOT 6.9%
F NLP 6.1%
G FINTECH & CRYPTO STARTUPS 6.0%
H ENERGY MANAGEMENT & SMART HOMES 5.5%
I SEMICONDUCTOR CHIPS & DEEP LEARNING 5.5%
J AUTONOMOUS VEHICLES 5.2%
K SOFTWARE DEVELOPMENT 5.2%
L CYBERSECURITY 4.9%
M AUGMENTED REALITY 4.8%
N EDUCATION 4.6%
O AGTECH 4.1%
P SUPPLY CHAIN 3.3%
Q DRONES 1.6%
R FOOD & BEVERAGE 1.2%
S SMART CONTRACTS & INSURANCE 1.1%
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
A
Q
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