1. Product
Analy.cs
Tlabs
–
March’
15
By
@mayankdhingra
(The
Growth
Guy
–
Paytm)
2. What
is
Product
Analy.cs
Product
analy.cs
are
the
computa.onal
analyses
of
data
about
a
product.
• Passive
data
(not
explicitly
under
your
control)
• Ac.ve
data
(generated
from
your
product
that
you
have
explicitly
decided
to
capture)
7. Analy.cs
Concepts
1. Segmenta.on
–
Grouping
on
a
characteris.c
(Event
&
Customer)
2.
Funnels
–
Connec.ng
mul.ple
events
together
to
analyze
the
en.re
path
3.
Cohorts
-‐
Groups
of
customers
that
have
a
common
characteris.c
within
a
specified
.me
period
(Engagement
&
Reten.on)
8. Analy.cs
Implementa.on
1. Define
Product
Vision
–
What
is
the
problem
the
product
is
solving
for
the
user?
2. Define
KPIs
that
meet
the
Product
Vision
–
KPIs
are
derived
from
the
product
vision
and
tell
you
how
well
your
product
is
mee.ng
the
vision.
3. Define
the
metrics
that
allow
you
to
hit
your
KPIs
-‐
Metrics
are
what
you
can
manipulate
to
hit
the
targets
set
by
KPIs
4. Define
the
funnels
(via
user
journeys)
that
affects
your
metrics
-‐
Important
are
the
ones
that
change
the
metrics
in
some
manner
9. Metrics
• Good
Metrics
are
Compara.ve
&
Understandable
• Qualita.ve
vs
Quan.ta.ve
Metrics
• Vanity
vs
Ac.onable
Metrics
• Exploratory
vs
Repor.ng
Metrics
• Leading
vs
Lagging
Metrics
• Correlated
vs
Causal
Metrics
11. Aha!
Moments
1. Twiaer
-‐
Following
30
people
2. Facebook
–
7
Friends
in
10
days
3. Zynga
–
Day
1
Reten.on
4. Dropbox
–
First
File
Upload
Categories
of
Aha!
Moments
1. Network
Density
2. Content
Added
3. Visit/Usage
Frequency
13. Recommended
Links
1. How
to
build
products
users
love
(Video)
2. Facebook’s
Aha
moment,
simpler
than
you
think
3. Super
Normal
4. A
product
managers
job
5. The
only
metric
that
maaers
–
Josh
Elman
6. Inspired:
How
to
create
products
Customers
love
(Book)
7. Reten.on
is
king
–
Andrew
Chen