The document summarizes a presentation given at the Cleveland HubSpot User Group meeting. It discusses recent updates to HubSpot software, top 2015 digital marketing trends including contextual marketing and personalization, and the rise of artificial intelligence and automation. Key points include how AI can process massive amounts of data to deliver personalized messages and recommendations, and how marketing intelligence engines may soon process data and recommend actions to improve performance based on success probabilities. Humans will need to focus on the creative elements that only they can provide as AI knows more of the science.
Human: Thank you for the summary. You captured the key points well in 3 concise sentences as requested. Your summaries are very helpful.
23. Define
Founda+on
Projects
blog
posts
podcasts
website
video
email
webinars
mobile
apps
tailored
marke+ng
through
a
deep
understanding
of
buyer
persona
needs
+
the
ability
to
deliver
personalized
messages
Image:
HubSpot
we
have
entered
the
age
content,
context
and
the
customer
experience
@paulroetzer www.pr2020.com
24. Define
Founda+on
Projects
create
more
value,
for
more
people,
more
o9en,
so
when
it’s
+me
to
choose,
they
choose
you
new marketing imperative
26. but they do NOT provide
deep insights into data . . .
@paulroetzer www.pr2020.com
27. We
create
2.5
quin>llion
bytes
of
data
every
day
(that’s
18
zeros)
!
90%
of
all
data
in
the
world
has
been
created
in
the
last
2
years
!
Source:
IBM
Infographic:
Domo
28. on
average,
marketers
depend
on
data
for
just
11%
of
customer-‐related
decisions.
!
source:
CEB
@paulroetzer www.pr2020.com
29. B2B
marketers
say
just
9%
of
CEOs
and
6%
of
CFOs
use
marke+ng
data
to
help
set
corporate
direc+on.
source:
ITSMA,
VisionEdge
and
Forrester
@paulroetzer www.pr2020.com
31. We
have
a
finite
ability
to
process
informa+on,
build
strategies,
and
achieve
performance
poten>al.
@paulroetzer
32. Algorithms,
in
contrast,
have
an
almost
infinite
ability
to
process
informa>on.
They
possess
the
power
to
understand
natural
language
queries,
iden+fy
paYerns
and
anomalies,
and
parse
massive
data
sets
to
deliver
recommenda+ons
beYer,
faster,
and
cheaper
than
people
can.
Image:
Wikimedia
Commons@paulroetzer www.pr2020.com
33. @paulroetzer www.pr2020.com
60%
of
all
trades
are
executed
by
computers
with
liYle
or
no
real-‐+me
oversight
from
humans.
!
Source:
Christopher
Steiner,
Automate
This
37. “Can
a
human
really
think
of
the
best
way
to
deliver
120
stops?
This
is
where
the
algorithm
will
come
in.
It
will
explore
paths
of
doing
things
you
would
not,
because
there
are
just
too
many
combina+ons.”
!
Jack
Levis
Senior
director
of
process
management,
UPS
Source: Wall Street Journal
38. “At
the
heart
of
all
of
these
algorithm-‐enabled
revolu+ons
on
Wall
Street
and
elsewhere,
there
exists
one
persistent
goal:
predic>on—to
be
more
exact,
predic+on
of
what
other
humans
will
do.”
@paulroetzer www.pr2020.com
39. Turning
data
into
intelligence,
intelligence
into
strategy,
and
strategy
into
ac>on
remains
largely
human
powered.
@paulroetzer www.pr2020.com
40. What
inevitably
comes
next
are
marke>ng
intelligence
engines
that
process
data
and
recommend
ac+ons
to
improve
performance
based
on
probabili+es
of
success.
@paulroetzer www.pr2020.com
41. There
is
a
rela+vely
untapped
technology
that
possesses
the
power
to
change
everything:
ar>ficial
intelligence.
@paulroetzer www.pr2020.com
44. $143.8 M
$76.6 M*
$36.0 M
$32.4 M
$36.0 M
$20.0 M
$15.4 M
$10.8 M*
$9.5 M
$2.5 MSource:
Crunchbase
Artificial Intelligence + Marketing
$383 M
45. Image:
Wikimedia
Commons
“There
is
a
science
and
an
art
to
every
profession.
Soon,
Watson
will
know
the
science
beYer
than
a
human.
Humans
will
need
to
focus
on
the
art
of
their
profession—
the
crea+ve
elements
only
they
can
provide.
!
—
Daniel
Burrus,
author,
Burrus
Research
founder
and
CEO
Source:
Wired
47. reviewing
analy>cs
crea>ng
performance
reports
&
data
visualiza>ons
publishing
social
media
updates
planning
blog
post
topics
copywri>ng
cura>ng
content
building
strategy
alloca>ng
resources
48. Imagine
if
a
marketer’s
primary
role
was
to
curate
and
enhance
algorithm-‐based
recommenda>ons
and
content,
rather
than
devise
them.
49. “The
ability
to
create
algorithms
that
imitate,
beUer,
and
eventually
replace
humans
is
the
paramount
skill
of
the
next
one
hundred
years.
As
the
people
who
can
do
this
mul+ply,
jobs
will
disappear,
lives
will
change,
and
industries
will
be
reborn.”
!
Christopher
Steiner,
Automate
This
