Mobile Targeting Michelle Andrews Temple University Chee Wei Phang Fudan University Xueming Luo Temple University Zhang Fang Sichuan University
Mobile Targeting
Michelle AndrewsTemple University
Chee Wei PhangFudan University
Xueming LuoTemple University
Zhang FangSichuan University
Uniqueness of Mobile Technology
• Mobile Portability = Real-time Targeting• GPS, Wi-Fi, Bluetooth, iBeacon = Geo-Targeting
• Geo-Targeting + Temporal Targeting
Research Questions
(1) How do timing and location in combination affect mobile sales?
(2) What are the underlying mechanisms for these effects?
Contextual Marketing Theory
• Efforts to influence purchases must be context dependent
– Portability enables ubiquitous reach and time-sensitive offerings
? Temporal & spatial boundaries may interactively impact behavior
• Decision to attend event is function of event time and place
• Ex: web usage contexts affect revisit intentions
Kenny and Marshall 2000; Johnson 2013; Galletta et al. 2006
Field Experiment
• Large, randomized field experiment
• Text messages promoting movie tickets
• Users had not previously purchased mobile tickets
• Large city in China
• Single movie promoted
• Sent to 12,265 mobiles
SMS Message
To enjoy a movie showing this
Saturday at 4:00 pm for a reduced price, download this online ticket app to purchase
your movie tickets and select your
seat.
Variables
• Dependent
• Mobile targeting effectiveness: ticket purchase via new app
• Independent
• Temporal targeting
• Geo-targeting
Defining Temporal Targeting
• Messages sent at 2 pm
• 2 hours (Sat.), 26 hours (Fri.), 50 hours (Thurs.) before movie
• Movie time: 4 pm, Saturday
• Messages sent to mobiles located at
• Near distances: < 200 meters (from the movie theater)
• Medium distances: 200 meters < x > 500 meters
• Far distances: 500 meters < x > 2km
Defining Geo-Targeting
200m
350m
1km
Control Variables
• Theater (A, B, C, D)
• Rate plan types
• MOU (minutes used monthly)
• ARPU (monthly bill)
• SMS (amount of text messages sent and received)
• Traffic (amount of data usage)
Response Rate
• 901 of 12,265 users downloaded app and bought tickets= 7.35%
• Mobile click rates in Asia:= 0.42%
eMarketer 2012
Time0.00
0.02
0.04
0.06
0.08
0.10
0.12
Estim
ated
Mar
gina
l Mea
ns
Sam
e-da
y
Evidence: Temporal Targeting
One
-day
prio
r
Two-
day
prio
r
χ² = 9.53, p < .01
χ² = 14.68, p < .01
Mean purchase for same-day messages:• Higher than one-day prior
• Higher than two-day prior
0.00
0.02
0.04
0.06
0.08
0.10
0.12
near medium far
Estim
ated
Mar
gina
l Mea
ns
Far
Medium
Near
Evidence: Geo-Targeting
Mean purchase for proximal distances:• Higher than moderate distances
χ² = 9.20, p < .01
• Higher than far distancesχ² = 18.33, p < .01
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
Time
Estim
ated
Mar
gina
l Mea
ns
Sam
e-da
y
One
-day
prio
r
Two-
day
prio
rFar MediumNear
Sam
e-da
y
One
-day
prio
r
Two-
day
prio
r
Sam
e-da
y
One
-day
prio
r
Two-
day
prio
r
Geo- and Temporal Targeting Combined
Additional Results: Customer Scenarios• Messages sent to mobiles located in
• Residential districts
• Shopping districts
• Financial districts
0
0.05
0.1
0.15
0.2
0.25
Near Medium Far Near Medium Far
Estim
ated
Mar
gina
l Mea
ns
Sam
e-da
y
Sam
e-da
y
Sam
e-da
y
Sam
e-da
y
Sam
e-da
y
Sam
e-da
y
Sam
e-da
y
Sam
e-da
y
Sam
e-da
y
One
-day
prio
r
One
-day
prio
r
One
-day
prio
r
One
-day
prio
r
One
-day
prio
r
One
-day
prio
r
One
-day
prio
r
One
-day
prio
r
One
-day
prio
r
Two-
day
prio
r
Two-
day
prio
r
Two-
day
prio
r
Two-
day
prio
r
Two-
day
prio
r
Two-
day
prio
r
Two-
day
prio
r
Two-
day
prio
r
Two-
day
prio
r
Time
Near Medium Far
At Mall At Home At Work
Distance x Time x Customer Scenario
Geo-Targeting on same day is most effective for shoppers vs. others (χ²=5.12 & 19.07, p = .01)
Geo-Targeting’s effect diminishes over time
U-shape for far distances is robust across segments
• Mobile targeting by location and time
• Customer context matters
Geo- and Temporal Targeting Takeaway
Effectiveness Effectiveness
Time TimeNear Distance
Far Distance