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- Practical examples that demonstrate when to act, how to act and how to recover
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- The impact of user experience and SEO
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Understand Why Personal Stories Connect Better
How To Remember Forgotten Stories
How To Use Customer Experiences As Stories For Your Brand
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Key Takeaways:
- New framework for examining and safeguarding an online reputation
- Tools and techniques to keep you a step ahead
- Practical examples that demonstrate when to act, how to act and how to recover
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Digital platforms are constantly multiplying, and with that, user engagement is becoming more intricate and fragmented.
So how do you effectively navigate distributing and tailoring your content across these various touchpoints?
Watch this webinar as we dive into the evolving landscape of content strategy tailored for today's fragmented user journeys. Understanding how to deliver your content to your users is more crucial than ever, and we’ll provide actionable tips for navigating these intricate challenges.
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- How today’s users engage with content across various channels and devices.
- The latest methodologies for identifying and addressing content gaps to keep your content strategy proactive and relevant.
- What digital shelf space is and how your content strategy needs to pivot.
With Wayne Cichanski, we’ll explore innovative strategies to map out and meet the diverse needs of your audience, ensuring every piece of content resonates and connects, regardless of where or how it is consumed.
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In the world of content creation, many AI bloggers have drifted away from their original vision, resulting in low-quality articles that search engines overlook. Don't let that happen to you! Join us to discover how to leverage AI tools effectively to craft high-quality content that not only captures your audience's attention but also ranks well on search engines.
Disclaimer: Some of the prompts mentioned here are the examples of Matt Diggity. Please use it as reference and make your own custom prompts.
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Discover the transformative power of AI in content creation with our presentation, "Is AI-Generated Content the Future of Content Creation?" by Puran Parsani, CEO & Editor of Cut-The-SaaS. Learn how AI-generated content is revolutionizing marketing, publishing, education, healthcare, and finance by offering unprecedented efficiency, creativity, and scalability.
Understanding
AI-Generated Content:
AI-generated content includes text, images, videos, and audio produced by AI without direct human involvement. This technology leverages large datasets to create contextually relevant and coherent material, streamlining content production.
Key Benefits:
Content Creation: Rapidly generate high-quality content for blogs, articles, and social media.
Brainstorming: AI simulates conversations to inspire creative ideas.
Research Assistance: Efficiently summarize and research information.
Market Insights:
The content marketing industry is projected to grow to $17.6 billion by 2032, with AI-generated content expected to dominate over 55% of the market.
Case Study: CNET’s AI Content Controversy:
CNET’s use of AI for news articles led to public scrutiny due to factual inaccuracies, highlighting the need for transparency and human oversight.
Benefits Across Industries:
Marketing: Personalize content at scale and optimize engagement with predictive analytics.
Publishing: Automate content creation for faster publication cycles.
Education: Efficiently generate educational materials.
Healthcare: Create accurate content for patients and professionals.
Finance: Produce timely financial content for decision-making.
Challenges and Ethical Considerations:
Transparency: Disclose AI use to maintain trust.
Bias: Address potential AI biases with diverse datasets.
SEO: Ensure AI content meets SEO standards.
Quality: Maintain high standards to prevent misinformation.
Conclusion:
AI-generated content offers significant benefits in efficiency, personalization, and scalability. However, ethical considerations and quality assurance are crucial for responsible use. Explore the future of content creation with us and see how AI is transforming various industries.
Connect with Us:
Follow Cut-The-SaaS on LinkedIn, Instagram, YouTube, Twitter, and Medium. Visit cut-the-saas.com for more insights and resources.
1. Sneha
Lundia
UCSC
EXTENSION
|
POWER
OF
MARKET
RESEARCH
Market
Research
Report
WHICH
GEOGRAPHICAL
REGIONAL
CAN
BE
POTENTIALLY
TOUTED
AS
THE
NEXT
SILICON
VALLEY?
2. 2
TABLE
OF
CONTENTS
Executive
summary
................................................................................................................
3
Introduction
...........................................................................................................................
4
Objective
..............................................................................................................................................
4
Background
..........................................................................................................................................
4
Methodolody
.........................................................................................................................
5
Findings
..................................................................................................................................
6
Demographics...................................................................................................................................
6
Responses
........................................................................................................................................
7
Factors
Influencing
Technology
Hub
.................................................................................................
7
Potential
Geographical
Regions
........................................................................................................
9
Ranking
of
Potential
Cities
Based
on
Weighted
Score
Metrics
.........................................................
10
Other
Findings
................................................................................................................................
11
Conclusions
and
Recommendations
......................................................................................
12
Appendices
...........................................................................................................................
13
Appendix
A:
Reference
List
.............................................................................................................
13
3. 3
EXECUTIVE
SUMMARY
• This
report
provides
an
insight
into
the
factors
which
make
a
region
technology
powerhouse.
It
also
devices
metrics
which
governs
the
success
of
a
startup
ecosystem.
• An
online
web
survey
was
conducted
to
understand
which
geographical
region
has
the
potential
to
be
touted
as
the
next
Silicon
Valley.
• The
survey
audience
were
adult
urban
population
connected
to
the
tech
industry.
• The
results
indicate
that
New
York
City,
USA
has
a
good
potential
and
private
investors
and
venture
capitalists
could
consider
investing
in
these
regions
like
New
York
and
Seattle.
• Availability
of
low
cost
and
skilled
working
professionals,
and
with
an
above
average
growth
rate
index
Bangalore
is
also
a
wise
investment
option.
• In
order
to
better
understand
the
situation
from
a
global
perspective,
it
would
have
been
better
if
this
survey
was
done
on
a
more
global
scale.
4. 4
INTRODUCTION
OBJECTIVE
The
market
research
project,
entitled
which
geographical
region
can
be
potentially
touted
as
the
next
Silicon
Valley?
hopes
to
discover
more
information
regarding
the
geographies
which
have
the
potential
to
become
the
next
technology
capital
of
the
world.
Silicon
Valley
is
the
home
to
many
of
the
world's
largest
high-‐tech
corporations
and
thousands
of
startup
companies.
It
is
an
innovation
powerhouse
whose
importance
is
hugely
disproportionate
to
its
small
physical
size.
BACKGROUND
The
purpose
of
doing
this
research
is
my
curiosity
to
know
more
about
why
the
bay
is
called
Silicon
Valley
and
understand
the
features/characteristics
a
geographical
region
must
have
to
be
called
the
technology
powerhouse.
5. 5
METHODOLODY
Based
on
the
insights
generated
from
the
secondary
research,
I
was
able
to
narrow
down
on
a
few
locations
that
have
the
potential
to
be
labeled
as
the
next
Silicon
Valley.
However,
understanding
the
characteristics
of
Silicon
Valley
and
the
critical
question
of
what
makes
it
a
technological
hub
was
not
answered.
More
details
regarding
my
secondary
research
can
be
found
in
Appendix
A.
The
method
best
suited
for
attaining
my
research
objective,
due
to
the
flexibility
and
immediacy
of
response,
was
a
web
survey.
I
designed
a
web
survey
under
the
guidance
of
my
instructor,
Jen
Berkley
Jackson,
and
used
Qualtrics
to
conduct
the
survey.
For
a
population
of
approximately
60,000,000
(Urban
Adult
Population
connected
to
tech
Industry)
to
have
a
confidence
of
90%
with
marginal
error
of
plus
or
minus
10%
the
sample
size
should
be
minimum
of
68.
SHORTCOMINGS
My
actual
sample
size
for
the
analysis
is
45.
For
a
population
of
60,000,000
and
sample
size
of
45,
with
13%
of
marginal
error
I
have
a
90%
confidence
on
my
analysis.
Although
the
sample
size
looks
good
enough
it
has
a
few
limitations.
• Since
my
research
is
trying
to
answer
a
global
question,
the
sample
needs
to
be
geographically
distributed,
but
due
to
limited
network
my
sample
is
skewed
towards
USA
and
India.
• The
population
considered
is
also
an
approximate
value.
CHALLENGES
In
order
to
begin
analysis
on
the
collected
data
from
the
survey,
I
needed
to
export
the
same
from
Qualtrics.
However,
since
I
was
using
a
trial
version
of
the
software,
I
did
not
have
access
to
the
raw
data.
This
was
necessary
to
evaluate
and
cross
tabulate
results.
After
a
lot
of
persuasion,
I
was
able
to
convince
the
Quatrics
Customer
Support
team
to
provide
me
with
the
raw
data
as
a
.csv
file.
6. 6
FINDINGS
Many
cities
around
the
globe,
armed
with
a
sizable
tech
hub,
are
engaged
in
a
fierce
competition
for
global
attention.
Their
byword
and
aspiration
is:
“the
next
Silicon
Valley.”
The
industries
that
comprise
these
regions
invest
greatly
in
research
and
development,
and
they
employ
high
proportions
of
people
from
the
fields
of
science,
technology,
engineering,
and
math,
collectively
known
as
the
S.T.E.M.
fields.
Based
on
the
research
it
is
clear
for
any
region
to
be
the
next
Silicon
Valley,
it
should
have
a
good
mix
of
the
following
characteristics:
• Expand
government-‐
and
corporate-‐funded
R&D.
• Nurture
startups
by
getting
them
capital
and
other
help
• Improve
the
pipeline
of
S.T.E.M.
workers
through
schools,
universities,
and
corporate-‐funded
training
programs
• Collaborate
to
create
local
“ecosystems”
that
encourage
companies
to
cluster
together
Some
other
factors
that
should
be
considered
are:
• Relatively
low
housing
costs
• Low
unemployment
rates
• Median
tech
salaries
higher
than
the
median
salary
for
the
city’s
total
workforce
• The
presence
of
major
tech
companies
• Venture
Capital
funding
to
spawn
new
businesses
Through
my
secondary
research,
I
was
able
to
narrow
down
on
a
few
locations
that
have
the
potential
to
be
labeled
as
the
next
Silicon
Valley.
However,
understanding
the
characteristics
of
Silicon
Valley
and
the
critical
question
of
what
makes
it
a
technological
hub
was
not
answered.
My
primary
research
focused
on
understanding
the
major
characteristics
that
needs
to
be
considered
for
qualifying
a
region
to
be
the
next
Silicon
Valley.
The
survey
consisted
of
multiple
choice,
rank
based
and
other
scoring
questions
to
understand
from
the
audience
what
characteristics
are
important
for
a
region
to
be
a
technology
powerhouse.
Using
the
data
collected
through
primary
research,
a
weighted
scoring
methodology
was
created
to
score
the
prospective
regions
and
finally
be
able
to
state
which
geographical
region
can
be
potentially
touted
as
the
next
Silicon
Valley.
DEMOGRAPHICS
The
target
audience
for
the
survey
was
the
world
urban
adult
population
connected
to
the
tech
Industry.
The
survey
saw
a
healthy
69%
participation
from
people
employed
in
the
tech-‐industry.
The
remaining
31%
were
also
connected
to
the
tech
industry
one
way
or
the
other.
These
included
respondents
from
financial
services,
healthcare
and
consulting
industry.
This
gave
me
confidence
that
the
data
is
going
to
be
representative
of
the
target
audience.
7. 7
RESPONSES
I
received
a
total
of
52
responses.
75%
of
the
responses
were
completed,
while
25%
were
partial
responses.
I
decided
to
consider
the
data
associated
50%
of
the
partial
responses
for
my
analysis
and
discarded
the
rest.
This
decision
was
based
on
thoroughly
analyzing
the
partial
responses
with
respect
to
the
kind
of
questions
answered.
Only
those
responses
were
considered
which
would
add
value
to
the
survey
and
increase
its
efficacy.
FACTORS
INFLUENCING
TECHNOLOGY
HUB
7%
7%
11%
5%
4%
31%
4%
31%
Demographics
Computer
and
Electronics
Manufacturing
Information
Services
and
Data
Processing
Information
Technology
Other
Information
Industry
Scientific
or
Technical
Services
Software
Telecommunications
Other
75%
12%
13%
Responses
Completed
Partial
Invalid
8. 8
Based
on
my
secondary
research
I
was
able
to
narrow
down
on
certain
factors
that
govern
the
success
of
a
technological
hub.
Although
I
had
a
list
of
these
factors,
there
was
no
way
to
determine
how
each
of
the
characteristics
influenced
the
establishment
of
a
technological
hub.
I
used
primary
research
to
create
metrics
for
each
characteristic.
Every
respondent
was
asked
to
rate
the
characteristics
between
one
to
five,
one
being
the
least
and
five
the
most
influential.
These
ratings
were
then
used
to
rank
the
characteristics
based
on
a
weighted
score
mechanism.
As
observed,
76%
of
the
respondents
feel
that
venture
capital
funding
and
an
eco-‐system
to
nurture
startups
are
the
most
influential
factors
that
result
in
a
successful
technological
hub.
A
major
fact
to
note
here
is
that
presence
of
major
technical
companies
plays
a
big
role
in
maintaining
a
healthy
environment
to
nurture
startups.
Surprisingly,
the
importance
of
housing
costs
is
the
least
influential
factor
considering
that
Silicon
Valley
itself
is
in
a
major
real-‐estate
bubble
as
of
now.
Also
surprising
is
the
fact
that
respondents
feel
that
low
employment
rates
do
not
impact
the
tech
ecosystem
too
much.
This
is
especially
unexpected
since
respondents
expect
a
high
compensation.
This
would
seem
to
imply
that
irrespective
of
the
high
housing
costs
and
low
employment
rates,
a
high
compensation
is
good
enough
to
power
technology.
CALCULATING
THE
WEIGHTED
SCORE
To
calculate
the
rank
of
each
factor,
I
used
a
weighted
score
mechanism.
Each
value
of
the
metric
was
assigned
a
weight
based
on
the
responses
and
then
averaged.
The
least
influential
option
was
assigned
weight
one
and
the
highest
influential
factor
was
given
the
weight
5.
Using
this
mechanism,
I
was
able
to
conclude
that
venture
capital
funding
and
nurturing
startups
for
success
are
the
most
influential
factors
5% 5% 5% 5%
12% 12% 10% 14%7% 12% 12% 10% 17%
7% 10%
29%
26%
12% 7%
19% 29%
36% 31% 26%
29%
36%
40% 38%
33%
43% 29%
26% 36%
26%
14%36% 38%
31%
14% 19% 24%
17%
7% 10%
0%
20%
40%
60%
80%
100%
Factors
Influencing
Techo-‐Hub
5
(Most
Influential)
4
3
2
1
(Least
Influential)
9. 9
with
scores
of
4
and
3.9
respectively.
Although
employment
rates
and
housing
costs
have
a
low
score
with
respect
to
others,
looking
at
it
individually,
the
score
is
high
enough
to
conclude
that
they
also
influence
the
technology
growth
environment.
POTENTIAL
GEOGRAPHICAL
REGIONS
The
primary
research
asked
the
respondents
to
choose
a
geographical
region
which
has
the
potential
to
become
the
next
Silicon
Valley.
The
options
given
as
part
of
this
question
were
carefully
selected
after
a
thorough
secondary
research.
The
objective
of
this
question
was
to
gather
a
top
of
the
mind
response
from
the
respondent
based
on
his/her
current
knowledge
and
understanding
of
the
technological
landscape.
4.0 3.9
3.7
3.5 3.5 3.4 3.4
2.9
2.8
2.0
3.0
4.0
5.0
Weighted
Score
of
Each
Factor
17%
44%
5%
5%
3%
7%
7%
12%
Potential
Geographical
Regions
Austin,
U.S.
Bangalore,
India
Boston,
U.S.
London,
United
Kingdom
New
York
City,
U.S.
Paris,
France
Seattle,
U.S.
Singapore
10. 10
The
survey
results
yielded
a
strong
44%
in
favor
of
Bangalore,
India
being
the
next
Silicon
Valley.
This
is
unsurprising
since
we
know
that
there
is
a
bias
with
respect
to
the
ratio
of
respondents
from
India.
New
York
comes
in
a
distant
second
place
in
this
race,
but
again
this
can
be
attributed
to
the
strong
demographic
bias
that
I’ve
already
mentioned.
An
interesting
point
to
note
that
none
of
the
respondents
believed
that
Boston
is
likely
to
be
the
next
Silicon
Valley.
RANKING
OF
POTENTIAL
CITIES
BASED
ON
WEIGHTED
SCORE
METRICS
At
the
time
of
my
secondary
research
I
found
an
interesting
article
titled,
“The
20
hottest
startup
hubs
in
the
world”
via
Business
Insider.
The
report
—
which
last
came
out
in
2012
—
ranked
cities
in
five
categories:
growth
index,
funding,
talent,
market
reach,
and
startup
experience.
Through
my
primary
research
I
gathered
data
from
audience
about
how
would
they
rank
funding,
market
reach,
talent,
startup
experience
and
job
growth
rate
based
on
its
contribution
for
the
success
of
a
technology
driven
ecosystem.
Interestingly
I
observed
that
a
little
less
than
half
of
the
respondents
feel
that
talent
is
the
most
important
metrics
that
govern
the
success
of
a
technology
driven
ecosystem.
Based
on
the
response,
I
ranked
the
metrics
as
follows:
1. Talent:
Availability
of
skilled
professionals
2. Funding:
Availability
of
funds
for
establishing
and
running
startups
3. Market
Reach:
Connectivity
of
the
region
with
its
target
customers
4. Job
Growth
Rate
5. Startup
Experience:
Availability
of
an
ecosystem
to
nurture
the
growth
of
startups
Each
of
the
metrics
were
assigned
weights,
highest
weight
was
assigned
to
rank
one
while
lowest
to
rank
five.
Based
on
the
weights
an
average
score
for
each
region
was
calculated.
24%
15%
48%
6%
7%
Ranking
of
Metrics
Funding
Market
Reach
Talent
Startup
Experience
Job
Growth
Rate
11. 11
By
combining
the
results
of
secondary
research
with
primary
research,
it
is
observed
that
New
York
City,
USA
has
the
potential
to
be
called
the
next
Silicon
Valley.
With
scoring
high
in
funding,
market
reach
and
startup
experience,
this
is
an
expected
result.
OTHER
FINDINGS
• The
growth
of
an
economic
region
is
another
factor
which
is
of
importance.
• A
region
which
has
its
infrastructure
in
place
and
the
cost
of
holding
it
is
low
would
have
a
high
chance
of
attracting
tech
companies
towards
it.
• Australia
has
a
good
potential
due
to
its
location
and
culture.
It
is
close
to
Asia,
the
manufacturing
hub
and
is
good
at
doing
business
with
US
and
Europe
due
to
seamless
communication
with
them.
• A
few
respondents
were
of
the
opinion
that
instead
of
having
one
big
technology
hub,
there
could
be
multiple
small
hubs
distributed
over
the
geography.
• Some
were
of
the
thought
that
there
cannot
be
any
other
Silicon
Valley.
16
14 14 14
12
9
8 8
0
3
6
9
12
15
18
21
New
York
City,
U.S.
Boston,
U.S.
Seattle,
U.S.
London,
UK
Austin,
U.S.
Bangalore,
India
Singapore Paris,
France
Ranking
Based
on
Weighted
Score
Funding
Talent
Growth
Rank
Startup
Experience
Market
Reach
Weighted
Score
12. 12
CONCLUSIONS
AND
RECOMMENDATIONS
The
primary
research
suggests
that
Bangalore,
India
is
the
location
that
is
the
most
likely
to
be
touted
as
the
next
Silicon
Valley.
While
this
may
be
surprising,
few
people
know
that
Bangalore
is
already
referred
to
as
the
Silicon
Valley
of
India.
The
primary
research
also
yielded
a
ranking
of
metrics
which
make
the
Silicon
Valley
the
technical
hub
that
it
is.
A
combination
of
these
rankings
along
with
my
secondary
research
yields
that
New
York,
NY
in
the
United
States
of
America
is
the
next
Silicon
Valley.
As
a
market
research
professional,
my
advice
to
private
investors
and
venture
capitalists
would
be
to
strongly
consider
investing
in
regions
like
New
York
and
Seattle
if
they
wish
to
invest
in
the
United
States.
However,
with
the
availability
of
low
cost
and
skilled
working
professionals
in
Bangalore,
it
would
be
extremely
unwise
to
not
consider
it
as
an
option.
For
engineers
and
working
professionals
who
want
to
place
themselves
in
a
region
with
future
potential,
Seattle,
WA
is
a
very
good
option
considering
its
proximity
and
ties
to
the
already
well
established
Silicon
Valley.
In
a
short
period
of
time
and
with
limited
resources,
I
was
able
to
reach
out
to
respondents
primarily
based
out
of
either
the
United
States
or
India.
This
may
or
may
not
have
led
to
some
amount
of
bias
in
the
responses
gathered
as
part
of
this
survey.
In
order
to
better
understand
the
situation
from
a
global
perspective,
it
would
be
great
if
this
survey
can
be
done
on
a
more
global
scale.
This
would
help
in
figuring
out
which
other
regions
have
the
technical
expertise
and
the
eco
system
for
nurturing
another
Silicon
Valley.
13. 13
APPENDICES
APPENDIX
A:
REFERENCE
LIST
[1] Alex
Kazaks,
Eric
Kutcher,
and
Michael
Uhl.
“How
should
you
tap
into
Silicon
Valley?”
McKinsey.
Internet:
http://www.mckinsey.com/business-‐functions/business-‐technology/our-‐insights/how-‐
should-‐you-‐tap-‐into-‐silicon-‐valley,
September
2015.
[2] Vara,
Vauhini.
“How
Utah
Became
The
Next
Silicon
Valley.”
The
New
Yorker.
Internet:
http://www.newyorker.com/business/currency/utah-‐became-‐next-‐silicon-‐valley,
February
3,
2015.
[3] “Does
Your
City
Have
What
It
Takes
To
Become
The
Next
Silicon
Valley?”
Free
Enterprise.
Internet:
https://www.freeenterprise.com/the-‐next-‐silicon-‐valley/,
June
6,
2016.
[4] Dahad,
Nitin.
“Is
France
on
track
to
become
the
Silicon
Valley
of
Europe?”
The
Next
Silicon
Valley.
Internet:
http://www.thenextsiliconvalley.com/2016/06/02/7522-‐is-‐france-‐on-‐track-‐to-‐become-‐
the-‐silicon-‐valley-‐of-‐europe/,
June
2,
2016.
[5] Lemonade,
Make.
“NZ
and
Vietnam
to
focus
on
joint
technology
trade
growth”
Scoop.
Internet:
http://www.scoop.co.nz/stories/BU1606/S00008/nz-‐and-‐vietnam-‐to-‐focus-‐on-‐joint-‐technology-‐
trade-‐growth.htm,
June
1,
2016.
[6] Athwal,
Nav.
“5
Cities
Poised
To
Be
The
Next
Silicon
Valley
Tech
Hub”.
Forbes.
Internet:
http://www.forbes.com/sites/navathwal/2015/02/12/5-‐markets-‐poised-‐to-‐be-‐the-‐next-‐silicon-‐
valley-‐for-‐real-‐estate/2/#7e0085a4bb22,
February
12,
2015.
[7]
Andrews,
Greg.
“Austin
Texas
has
what
it
takes
to
be
the
next
silicon
valley”.
Accenture
Consulting.
Internet:
https://www.accenture.com/us-‐en/insight-‐highlights-‐communications-‐
austin-‐texas-‐next-‐silicon-‐valley.
2016.
[8] Forrest,
Conner.
“10
top
startup
hubs
outside
of
Silicon
Valley
and
the
US”.
TechRepublic.
Internet:
http://www.techrepublic.com/article/10-‐top-‐startup-‐hubs-‐outside-‐of-‐silicon-‐valley-‐and-‐
the-‐us/.
February
19,
2015
[9] Kirk,
Chris
and
Oremus,
Will.
“A
World
Map
of
All
the
Next
Silicon
Valleys”.
Slate.
Internet:http://www.slate.com/articles/technology/the_next_silicon_valley/2013/12/all_the_nex
t_silicon_valleys_a_world_map_of_aspiring_tech_hubs.html,
December
19,
2013
[10] Alfaro,
Lyanne.
“The
20
hottest
startup
hubs
in
the
world”.
Business
Insider.
Internet:
http://www.businessinsider.com/the-‐20-‐hottest-‐startup-‐hubs-‐in-‐the-‐world-‐2015-‐7,
July
30,
2015.