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From YouTube: Shane and Dunk talk MQL reporting and other data
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A
All
right
great,
so,
on
the
left
hand,
side
of
what
we
have
here
is
the
sisense
chart
that
we
use
to
report
on
trials
by
segment,
and
so
you
know
what
I
do
is
just
come
in
here
update
the
dates.
Make
sure
that
it's
you
know
the
current
report
date.
So,
let's
see
where
is
the
date
on
this
scroll
down?
A
That's
ended
so
this
one
comes
back
later
today
and
looks
at
it
it's
not
a
higher
number
and
then
once
we
have
that
you
update
this
and
we'll
just
you
know,
I
tend
to
just
to
have
a
better
look
at
this.
A
I
share
the
link
and
then
just
pop
over
here
and,
and
you
know,
screen
grab
the
numbers
and
then
what
I
do
is
plug
them
into
this
chart
and
or
this
sheet
I
should
say-
and
this
runs
all
the
calculations
for
me
and
let
me
change
the
screen
size
here,
so
you
can
see
it
better.
Does
all
the
conversion
metrics
yeah.
So
what
I
can
do
is
I
pop
in
the
number
here
it
adds
up
for
the
quarter.
Total
here
tells
us
where
we're
at
for
attainment
calculates
pace.
A
What
that
number
would
look
like
if
we
you
know
continue
that
pace
through
the
end
of
the
quarter
also
calculates
you
know,
percentage
of
the
quarter
to
date,
fiscal
year
to
date-
and
I
you
know,
built
all
these
formulas
just
to
work
with
our
fiscal
year.
So
it
starts
february.
1
ends
january
31st,
and
then
you,
you
plug
in
your
goals
here
so
as
we
move
into
the
new
fiscal
year,
you'll
plug
those
in
here
and
then
that
that
will
translate
all
this
here.
A
So
you
know
divide
your
your
number
here
by
you
know
all
the
things
you
see
there,
so
it's
meant
to
be
pretty
straightforward.
You
know
these.
I
initially
added
this.
These
numbers
right
here,
not
numbers
that
are
related
to
any
reporting,
but
what
I
was
seeing
is
that
you
know,
as
you
go
into
the
next
month,
if
you
go
back
and
look
at
the
last
month,
those
numbers
change,
and
so
I
try
to
keep
them
up
for
the
current
quarter,
but
I
don't
go
all
the
way
back
for
each
quarter
at
this
point.
A
So
I'll
just
I'll
take
these
off
here
and
what
I'll
do
dunk
is.
I
will
make
you
an
owner
of
this
sheet,
so
you
can
that'd
be
great.
You
know
whatever
you
want
to
do
with
it.
Let
me
do
that
now.
Yeah.
B
Do
you
have
anything
like
when
I
look
at
this
like
one
of
the
things
as
an
example,
shane
I've
been
looking
at
is
over
the
course
of
november
december
as
an
example
prior
to
that,
our
pace
of
large
mqls
was
in
the
20
to
22
range.
I
think
the
largest
we
got
was
27.5,
but
I
did
notice
in
november
and
december
they
dropped
about
16
16
and
a
half
percent
right.
B
A
No,
I
haven't,
and
I
think
that
would
be
great
to
look
at
to
do
some
additional
modeling.
You
know
this
was
really
just
something
where
you
know
on
our
weekly
recap
calls
waking
up
on
thursday
morning
and
scrambling
trying
to
get
the
numbers
right,
making
double
checking
myself.
A
And
just
built
this
so
that
I
could
just
plug
in
one
number
and
have
everything
we
needed,
but
I
think
that
kind
of
no.
This
is.
B
A
Great
well,
are
there
any
other
questions
anything
else.
I
can
give
you
as
we
start
moving.
You
know
moving
this
around
as
far
as
what
we're
reporting
on.
A
B
Which
is
one
of
the
things
that
we've
been
looking
at
and
working
on?
Is
the
relative
performance
of
trials
versus
gated
content,
as
well
as
looking
at
trial
remarketing.
So
if
somebody
takes
a
piece
of
gated
content
and
then
they
also
take
a
trial,
you
know
what
does
that
conversion
rate
look
like
so
I'm
gonna
share
my
screen
here.
B
yeah,
it's
184.,
and
then
this
relates
to
a
larger
issue
which
is
180.,
but
the
net
net
of
that
is
just
kind
of
on
this
visual
diagram
here,
which
is
we're
looking
at
mqls
by
engagement,
which
ones
are
trial
only
which
ones
are
getting
content
only
how
many
are
actually
now
taking
both
actions
together.
So
we're
using
this
as
a
proxy
right
relative
to
whether
or
not
we
should
or
should
not
do
more
of
that
activity.
B
B
So
much
higher
I'll,
be
we're
still
talking
about
small
numbers
right
yeah,
that's
still
a
pretty
low
kind
of
a
number
set,
but
the
other
and
the
other
things
that
impact
this,
as
you
know,
is
evan's
gonna
is
in
the
process
of
rolling
out
changes
to
the
sdr
team,
where
we'll
have
a
dedicated
team
that
works
new
versus
growth,
and
so
we
believe
that
these
numbers
will
get
significantly
better.
But
I
think
our
learning
from
this
is
the
proxy
learning
from
this.
B
So
far
over
these
last
four
or
five
months
is
that
the
free
trial
plus
gated
content
as
a
set,
is
a
useful
thing
to
us
to
pursue.
The
question
is:
can
we
pursue
it
in
a
better
fashion,
leveraging
email
nurture
some
of
the
remarketing
tactics
etc,
and
we
haven't
done
as
much
of
it
right
because
it
doesn't
have
the
volume
yet,
but
I
think
it's
a
useful
nvc
test
for
us
to
to
be
able
to
answer
some
of
those
questions,
because
I've
had
that
for
a
while.
B
A
Well-
and
I
think
I
think
the
interesting
question
is
I
like
these
numbers
too,
would
be
to
maybe
break
this
out
by
segment.
You
know,
because
I
think
you
know
it
would
be
great
to
see
what
you
know
we
see
with
smb
and
large
in
particular.
I
think
mid
market
would
follow
closer
to
large,
but
would
be
my
guess
anyway,
but
yeah.
This
is
really
interesting.
B
Yeah,
the
other
thing
that
we've
been
also
looking
at
is
what
percentage
of
people
that
land
on
the
trial
page
actually
submit
the
trial,
and
so
we've
been
looking
at
the
just
through
ga
right,
the
number
of
people
that
land
on
the
the
trial
pages
versus
the
number
of
people
that
submit,
and
so
I
think
what
was
disappointing
to
me
was.
Is
we
thought
that
that
number
was
going
to
be
higher?
I
had
heard
you
know
it
should
be
in
the
50s.
B
A
Yeah,
no,
that's
what
I
would
look
at.
I
would
look
at
you
know:
self-managed
trial,
so
free
trial,
self-managed
and
just
look
at
page
views
versus
submits
on
that
page
to
come
up
that
number
yeah
the
tricky
part
there
is
always
sas.
You
know
once
we
have
the
google
tag
manager
set
up,
so
we
can
capture
those
logged
out
visitors
and
know
that
number.
I
think,
that'll
give
us
a
better
sense
of
what's
going
on
with
sas
and
I'm
wondering
if
sas
may
not
be
a
little
bit
higher.
A
B
Yep
anyway,
so
yeah
very
helpful
to
have
this
discussion
and
I
would
love
to
help
take
over
that
google
sheet
from
you,
I'm
sure
matt,
and
I
would
love
that
so.
A
Great
yeah,
so
I've
added
you
there
I'll
when
we're
done
with
the
call,
I
will
go
ahead
and
make
you
an
owner
so
that
you
can
just
take
it
over
and
and
use
it
as
you
see
fit.
You
know
double
check.
My
formulas
make
sure
they're
all
right.
I
think
they're
good,
but
you
know
oh
another
set
of
eyes
is
always
nice.
B
Yeah
you
know:
we've
got
the
upstream
from
that
too,
because
we
also
look
at
the
velocity,
so
the
inquiry
mkl
velocity
for
trial,
the
velocity
is
virtually
instantaneous
right,
but
for
other
types
of
activities,
inquired
mql
can
take
anywhere
from
two
days
up
to
about
11
days
right
to
get
somebody
to
an
mql,
oh
wow,
so
but
yeah
yeah.
B
All
that
in
the
demand,
gen
dashboard-
and
I
guess,
while
you
and
I
have
some
time
yeah
if
you're
interested
in
seeing
the
v2
of
the
demand
gen
dashboard.
This
will
also
show
you
some
other
things
that
we're
looking
at.
So
let
me
go
grab
that
tab.
There.
B
No,
we
got
a
lot
of
work
to
do
so.
Some
of
the
new
go
to
market
motions
that
we
want
to
roll
out
for
fy22.
I
got
a
mesh
and
are
working
on
an
epic
for
that
to
get
people
going
on
that
and
then,
in
addition
to
that,
we've
got.
I've
got
some
job,
family
job
descriptions
to
do
and
a
few
other
things
we're
also
looking
at
pipeline
velocity
right
now,
which
is
really
interesting
as
pipeline
shifts
right.
B
B
Here
we
go
okay,
so
I
think
you
remember,
I
showed
you
the
demand
generation
dashboards,
the
v1
that
we
really
worked
on
with
opsin
with
agnes
and
really
the
goal
was,
is
to
provide
a
core
set
of
analytics
around
of
all
of
our
paid
outbound
demand
generation
programs
and
really
get
very
detailed
like
how
are
they
performing
in
the
aggregate?
B
What's
the
velocity,
how
are
individual
campaigns
performing
overall?
What's
the
content?
What's
the
activity?
How
well
does
it
convert
so
vicky
on
dara's
team
has
been
helping
us
do
a
v2
of
this,
and
this
v2
actually
allows
us
to
look
at
a
lots
more
a
lot
more
information
right,
so
you
can
actually
in
a
more
visual
kind
of
frame
of
reference.
B
Conversion
rate
is
still
pretty
low
overall,
as
an
organization
yeah
and
part
of
that
is,
as
we
talked
about,
if,
if
less
than
one
ten
one
percent
of
your
of
your
trials
convert
to
saos,
then
that
drives
and
they
are
a
huge
percentage
of
our
total
mqls
that
drives
that
number
down.
And
so
that's
why
we're
looking
at
what
else?
Should
we
be
doing
here
to
help
that
conversion
rate?
B
So
you
know
remarketing
trials
and
content
to
users
that
are
in
the
journey
is
really
important
because
not
everybody's
going
to
respond
to
email.
The
second
thing
is:
is
having
the
sdr
team
be
able
to
focus
on.
You
know
new
first
order
deals
separate
from
growth.
B
Deals
is
also
going
to
help,
so
we
think
that's
going
to
go
up
in
both
those
categories,
but
there's
some
pretty
cool
stuff
down
below
in
the
dashboard
here,
where
you
can
actually
look
at
velocity
per
campaign
and
then
you
can
actually
do
simple
things
like
and
this
is
we
had
a
campaign
table
that
was
completely
separate,
that
you
had
to
launch
from
the
prior
demand
gen
dashboard,
but
you
can
see
okay,
where
are
we
spending
our
money
right
now
in
terms
of
campaign?
Cost
right.
So
no
surprises
here
right.
B
If
you
do
this
query
here,
you
can
see
we're
spending
a
lot
of
money
on
ci
right
over
this
period
of
time.
So
ci
is
probably
about
half
the
spend
in
total
right.
If
you
look
at
it
from
a
cost
perspective,
you'll
also
see
that
we've
been
spending
some
money
on
get
ops,
which
is
the
brown
area
not
nearly
as
big
as
the
ci
area
and
you'll
see
like
evergreen
evergreen
is
some
of
these
remarketing
costs
that
we're
talking
about
right?
B
So
that's
where
we're
kind
of
putting
that
cost
in
you'll
also
see
brand
right,
so
things
that
are
coming
in
off
of
brand.
That
would
be
as
an
example.
We
do
a
lot
of
any
kind
of
google
sem
pay-per-click
search,
engine,
marketing,
we're
doing
branded
terms,
and
so
we're
spending
money
on
branded
terms,
so
that
would
be
get
lab.
Plus
you
know.
B
Another
search
term
combined
so
but
what's
interesting
here
is,
is
that
you
can
also
say
what's
driving
inquiries,
and
if
you
look
at
this
okay
now
you
see
kind
of
we're
spending
less
on
git
ups,
it's
driving
as
much
almost
as
much
from
an
inquiry
perspective
as
we
are
getting
on
cicd.
Oh,
let's
look
at
mqls.
B
B
So
suddenly,
git
ops
is
actually
driving
almost
as
many
saos
as
ci
does
and
ci
were
spending
about
60
percent.
More
so
and
then
what
that
tells
us
is.
It
allows
us
to
look
at
that
and
say:
okay,
get
ops
right
is
actually
driving
more
opportunities
for
sales.
We
spend
quite
a
bit
more
on
ci
cd,
but
get
ops
is
more
efficient,
but
if
we
wanted
to
approve
get
ops,
we
want
to
improve
that
conversion
rate
to
mql.
B
So
what
else
can
we
do
to
improve
the
inquiry
to
mql
conversion
rate,
because
if
we
could
drive
a
volume
of
mqls
consistent
with
what
we
do
in
ci
out
of
get
ops,
we'd
have
a
lot
more
saos.
So
this
is
just
some
of
the
things
you
can
do
in
this
dashboard
and
it
gives
you
visualization.
It
also
allows
you
to
kind
of
use
some
bubble
charts
to
understand
which
tactics
really
do
the
best
job
of
driving,
inquired
mql
version
versus
conversion
versus
mql
to
sao
and
then
sao
one.
B
So
this
is
a
bunch
of
really
neat
features
that
vicki's
been
building
up
for
us
as
you
look
at
tactics
and
personas
and
lead
status.
So
even
this
one,
which
shows
executives
versus
managers
versus
practitioners
right.
So
this
actually
allows
us
to
understand
the
titles
of
the
people
and
how
they
match
to
the
campaigns.
B
B
So
that's
the
new
v2
demand,
gen
dashboard.
That
I
think
is
helping
give
us
the
additional
insights
that
we
need
to
set
up
a
successful
set
of
fy
22
go
to
market
motions.
A
Yeah
absolutely
well
in
you
know,
I
think,
looking
at
that
that
chart
right
there
at
the
top,
where
you
have
you
know,
inquiry
to
mql
to
sao
it.
Might
I
don't
just
thinking
about,
like
you
know,
quick
visual
ways
to
check
if
you
had
that
same
graph,
but
you
could
do
it
by
campaigns
and
that
way
you
can
see
what
mirrors
and
what's
different
and
then
you
know,
look
for
those
areas
of
opportunity
because
it
does
sound
like
you
know
that
that
get
ops
you
know
what
you
discovered
there.
B
Yeah
mahesh-
and
I
were
talking
about
that
on
friday-
the
other
thing
that
kind
of
you
had
that
we
didn't
have
yet
is
kind
of
the
bar
charts
or
the
meter
charts
on
how
are
we
doing
on
our
pace
right
yeah?
B
So
I
think
that's
another
part
of
this
that
we
have
to
also
improve
in
that
area.
But
I
think
this
was
a
great
mvc
too,
and
a
lot
of
work
on
this
by
vicki
and
kind
of
the
moss
reporting
team.
So.
A
That's
great
vicki
has
helped
out
a
lot
on
google
analytics
too,
so
I'm
very
excited
to
have
her
here
and
some
of
the
things
she's
helped
us
figure
out
with
bigquery
and
just
how
to
get
that
working
right.
So
that's
fantastic.
B
A
Well,
that's
you
know
we
got
to
be
able
to
drill
down
and
get
into
the
data
and
like
find
those
kind
of
inconsistencies,
areas
of
improvement.
So
that's
awesome.