This document discusses how to effectively use mobile marketing technology to build better customer relationships. It covers three pillars for mobile marketing - acquisition, analysis, and engagement. It provides examples of how different types of mobile users can be engaged, such as bounced, window shopping, forgetful, and churned users. Recommendations are given for targeting messages and campaigns to each user type to improve engagement and customer experience.

1. How to get the most of mobile
marketing technology
(and build a better customer relationship)
Hugh Reynolds, Co-Founder
hugh@swrve.com

4. Ubiquity

5. LOCATION
AND
ADDRESSIBLILITY
Loca-on
+
Addressability

6. TECH
ECOSYSTEM

7. Acquisition
Analysis
THREE
PILLARS
Engagement
The
three
pillars

9. Jargon

10. COMPONENTS
OF
THE
STACK

11. Iden-ty

12. Marke-ng
Database

13. Analy-cs
+
Data
Management
PlaAorm

14. ailable tools
Segmenta-on

15. Decision
Engine

16. Available
tools

17. 1177
email Push notification
/ SMS
In-App Message In app inbox
Deep-link

18. User
Experience
changes

19. iBeacon

20. A
REAL
WORLD
ANALOGY

21. Real-­‐-me
engagement

22. Private & confidential © 2014
Value
exchange

23. Private & confidential © 2014
Personaliza-on

24. Real
World
Example:
Tagged
24
• Increase
average
app
store
ra-ng
from
2.3
to
4.2
• Deliver
surveys
(driving
new
users
to
engaged
users)

25. Real
World
Example:
Gaana
:
• Drive
users
to
‘subscrip-on
only’
features
during
app
trial,
showing
inters--al
messages
promo-ng
these
features
• Drive
over
250k
users
to
new
features
• Deliver
click-­‐thru
rates
>
10%
25

26. Real
World
Example:
Space
Inch
• Target
English
Speaking,
engaged
users
who
had
progressed
beyond
level
14
and
s-ll
spend
no
money
in
game.
• Deliver
12x
ROI
and
5%
li
in
revenue
in
a
single
campaign.
26

27. DEMO

28. Private & confidential © 2014
Lets
try
this
together

29. 46%
of
18-­‐34
year
olds
name
mobile
as
‘primary
screen’
29
Nov 2011 – 14% Jun 2013 – 36%
Mobile
growth

30. “Joe
is
a
new
OpenTable
user.
The
app
was
recommended
to
him
by
a
friend.
He
starts
the
app
and
skip
through
to
the
good
stuff…
then
quickly
become
confused.
Is
the
app
free?
What
happens
when
they
book
something
–
hmm
he
reckons
he’ll
come
back
to
this
later…”
The
bounced
user

31. 31
“Joe
uses
the
app
a
lot
but
books
only
infrequently.
He
searches
and
researches
far
more
than
he
books.
Some-me
he
checks
out
availability
for
a
specific
-me
but
does
not
make
a
booking.”
The
window
shopper

32. 32
“Joe
has
missed
a
bunch
of
reserva-ons,
it’s
a
problem
for
Joe
to
remember
his
dates
but
we
don’t
want
to
bug
everyone
just
because
Joe
is
forgeAul”
The
forgeAul
diner

33. 33
“Joe
was
a
frequent
user
but
has
not
been
seen
for
quite
some
-me.
We
do
however
know
what
kinds
of
foods
Joe
likes.
We
also
know
that
he
booked
a
lot
of
meals
in
restaurants
tagged
as
Roman-c.
He’s
based
in
SF,
has
eaten
in
Café
Bas-lle
and
falls
into
our
urban
professional
segment”
The
churned
power
user

34. Private & confidential © 2014
Lets
try
this
together

35. For:
segment
2
Diners
at
the
end
of
the
meal.
Who
have
not
asked
for
check
Offer
desert
–
men-on
the
item
that’s
your
favourite
Both
say
no?
Ask
“anything
else”
and
Supply
the
Bill
Both
say
yes?
Take
order
and
deliver
Offer
coffee
to
2nd
diner
y
n
n
y
Thanks
and
“hope
to
see
you
next
-me”
Bill
over
$100
?
Offer
free
coffee
to
2nd
diner
y
n

36. Private & confidential © 2014
Bounced
Window
Shopper
ForgeAul?
Lost?

37. Engagement
TacGcs
&
RecommendaGons
37
“Joe
is
a
new
OpenTable
user.
The
app
was
recommended
to
him
by
a
friend.
He
starts
the
app
and
skip
through
to
the
good
stuff…
then
quickly
become
confused.
Is
the
app
free?
What
happens
when
they
book
something
–
hmm
he
reckons
he’ll
come
back
to
this
later…”
• IN
APP
JIT
TUTORIAL
FOR
“STALLED
USERS”
• PUSH
CAMPAIGNS
FOR
“STALLED
USERS”
• DRIVE
FIRST
BOOKING
CAMPAIGN
FOR
“NEVER
BOOKED
USERS”
• IN-­‐APP
CAMPAIGNS
/
OFFERS

38. Engagement
TacGcs
&
RecommendaGons
38
“Joe
uses
the
app
a
lot
but
books
only
infrequently.
He
searches
and
researches
far
more
than
he
books.
Some-me
he
checks
out
availability
for
a
specific
-me
but
does
not
make
a
booking.”
• RECOGNIZE
WHEN
JOE
IS
WINDOW
SHOPPING
AND
USE
REAL
TIME
IN
APP
MESSAGES
TO
INFLUENCE
HIM
TO
BOOK
HIS
TABLE
• DRIVE
REPEAT
BOOKING
BEHAVIOR
WITH
“LIGHT
BOOKING
USERS”
• IN-­‐APP
CAMPAIGNS
FOCUSING
ON
POINTS
AND
PERKS
• A/B
TEST
AND
OPTIMIZE
THE
CONTENT
• DRIVE
BOOKING
BY
SHOWING
SPECIFIC
PROMOTIONS
TO
JOE

39. Engagement
TacGcs
&
RecommendaGons
39
“Joe
has
missed
a
bunch
of
reserva-ons,
it’s
a
problem
for
Joe
to
remember
his
dates
but
we
don’t
want
to
bug
everyone
just
because
Joe
is
forgeAul”
• USE
A
PUSH
TO
REMIND
“FREQUENT
NO-­‐SHOWS”
ABOUT
UPCOMING
RESERVATIONS
• DEEPLINK
FROM
THE
PUSH
TO
THE
SPECIFIC
RESERVATION

40. Engagement
TacGcs
&
RecommendaGons
40
“Joe
was
a
frequent
user
but
has
not
been
seen
for
quite
some
-me.
We
do
however
know
what
kinds
of
foods
Joe
likes.
We
also
know
that
he
booked
a
lot
of
meals
in
restaurants
tagged
as
Roman-c.
He’s
based
in
SF,
has
eaten
in
Café
Bas-lle
and
falls
into
our
urban
professional
segment”
• REENGAGE
JOE
USING
A
COMBINATION
OF
FEATURE
AND
OFFER
PUSH
MESSAGING
• VALENTINES
DAY
PROMOTION
•
PROMOTE
PAY
WITHOUT
THE
WAIT
TO
JOE.
• TARGET
JOE
WITH
EMAILS
TAILORED
TO
HIS
OT
POINTS
BALANCE
• USE
DEEPLINK
FROM
EMAIL

41. Private & confidential © 2014
Thanks
–
hugh@swrve.com