Blue Hill Apteligent Mobile Retail and Retail Banking Webinar

Building Effective & Profitable

2016
New 18 page mobile retail shopping report based on research
conducted by Blue Hill Research utilizing Apteligent-provided global
mobile app and mobile platform data

2016
A
B C
• Mobile device types and behaviors
• Operating system platforms and long/short term behaviors: adoption rates, app
load rates, crash rates, abandonment rates
• App latency and responsiveness, data error rates
• Age Groups (Millennials, Gen Xers, Baby
Boomers)
• Mobile App Preferences and Desires
• Mobile Device Choices
• Actions each age group is likely to take
collectively and separately based on
mobile shopping app qualities and
attributes
• Mobile device types and behaviors
• Operating system platforms and long/short
term behaviors: adoption rates, app load
rates, crash rates, abandonment rates
• App latency and responsiveness, data error
rates
• Geolocation-based behaviors

Effective & Profitable
All Data Sets are Critical for Successful Mobile
Analysis
The data and information contained within each circle or within the
intersection of any two circles is insufficient to build highly effective
and desirable mobile retail shopping apps
All Data Sets are Critical to Evaluate Mobile Behaviors
It is critical for retailers to evaluate all internal user demographic and
app behavior and performance data with global user demographics
and aggregate global mobile app and mobile platform behaviors
The Highly Successful Mobile Retail
Shopping App Exists at the Intersection of All
Data Sets
Global Retail
Mobile User
Demographics
Retailer User
Demographics
& Mobile
Shopping App
Behaviors
Aggregate
Global Mobile
Ecosystem
Behaviors

M-Commerce Apps
The Intersection of User and Mobile
App Ecosystems

Retail Mobile User Demographics
It’s Mostly a Young Person’s Game
216
Do you shop and make purchases and/or do shopping research
through downloaded mobile store apps if they are available?
76%
54%
41%
32%
24%
46%
59%
68%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Older Baby Boomer (59+)
Younger Baby Boomer (51-58)
Gen X
Millennial
Percentage of Respondents
Yes
No
Source: Blue Hill Research and Apteligent, January 2016

2016
Approximately what percentage of your shopping and shopping
research is done through mobile apps?
22%
32%
50%
61%
45%
47%
33%
28%20%
13% 14%
7%12% 7% 3%
4%1% 1% 1%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Millennial Gen X Younger Baby Boomer
(51-58)
PercentageofRespondents
I do not use Mobile Shopping Apps 25% or less 50% 75% 100%
65% of Millennials &
60% of Gen Xers Do
25% to 50% of Their
Shopping via Mobile
Devices –
TODAY!

2016
If a shopping app is a delight and highly effective, I will
recommend it
12%
16%
26%
44%
4%
10%
6%
11%
14%
22%
20%
14%
34%
24%
26%
13%
36%
28%
21%
19%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Millennial
Gen X
Scale of 1 to 10, 9 & 10 Being “Most Likely”
1-2 3-4 5-6 7-8 9-10

2016
If a shopping app is a delight and highly effective, I will increase
my mobile shopping
14%
20%
30%
46%
7%
13%
8%
13%
18%
28%
19%
18%
30%
22%
24%
11%
32%
17%
19%
12%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Millennials
Gen X
Scale of 1 to 10, 9 & 10 Being “Most Likely”
1-2 3-4 5-6 7-8 9-10

Millennials are the Key to Retail’s Mobile Future
2016
Millennial Actions Retail Leaders Benefit Retail Laggards Suffer
70% of Millennials will likely or
very likely recommend highly
delightful mobile shopping
apps and experiences
Retail leaders continue to gain
visibility and mobile market
share at the expense of
competitors
Inherent loyalty makes it
nearly impossible for retail
laggards to engage or re-
engage consumers
62% of Millennials will likely or
very likely increase their
mobile-based shopping and
consequently their mobile
retail dollar spend
Retail leaders can reasonably
anticipate both continued
audience and - most important
- continued top line revenue
growth via mobile apps
The gap between retail leaders
and laggards will dangerously
widen for laggards and will put
their businesses at significant
short and long term risk

Retailers must view the experiences their mobile shopping apps deliver to Millennials
within the context of traditional brand attributes – trust, competence, good will, quality,
transaction satisfaction and security, to name but a few…
Millennials are unique among all age groups in
that they fully embody living most aspects of
their lives through their mobile devices…as they
become the “older” next generation in a few
short years, mobility will necessarily drive the
entire retail value chain
Millennials are the Key to Retail’s Mobile Future
©2016 Blue Hill Research. All Rights Reserved.

Great Apps are the Foundation of Retail Mobility
Mobile Shopping Apps - Crashes and Poor App Response, All Age
Groups (Scale of 1 to 10, 10 Being “Most Likely Action”)
6.62
5.91
4.41
4.04 3.99
3.62 3.49
0
1
2
3
4
5
6
7
If a shopping app
operates slowly
and causes
excessive
waiting, I will
uninstall it
If a shopping app
completely
crashes, I will
immediately
uninstall it
If an app runs
slowly or
misbehaves in
other ways, I will
socially share
with my personal
network of peers
If an app runs
slowly or
misbehaves in
other ways, I will
write a negative
review
If a shopping app
crashes, I will
write a negative
review that
details my
experience
If a shopping app
lacks features I
highly desire, I
will write a
critical review
If an app runs
slowly or
misbehaves in
other ways, I will
socially share
over networks
App crashes, poor performance and
poor mobile shopping experiences
reflect directly on retailers’ global
brand attributes and will
significantly harm the retail brand

Great Apps are the Foundation of Retail Mobility
Mobile Shopping Apps - Desired and Critical Features, All Age
Groups (Scale of 1 to 10, 10 Being “Most Desired”)
7.62
7.13 6.84 6.75 6.46 6.37 6.23 5.96
0
1
2
3
4
5
6
7
8
9
Ability to easily
edit my cart
Crisp, fast app
behavior
Easy ability to
switch views
between
shopping and
my cart
Rich overall
experience (as
good as
website)
Quality hi-res
images
Ease of
reviewing new
products and
prices
Easy ability to
receive and
manage
coupons and
other loyalty
awards directly
within my app
Ability of the
shopping app
to interact
directly within
an actual store
Highly positive mobile experiences will
drive brand loyalty and the desire of
mobile shoppers – regardless of their
age groups, but Millennials in particular
– to recommend not only the mobile
shopping apps but the retail brands
behind the apps as well

Effective & Profitable M-
Commerce Apps
App Ecosystems

The Aggregate Global Retail Ecosystem
The Larger Mobile Shopping App Ecosystem
Key Mobile Ecosystem Metrics & Data for Visualization & Analysis
• Long and short term mobile operating system behaviors
– OS crash rates
– OS adoption and abandonment rates
– OS and app latency rates (a function of both internal app design and
wireless carrier services)
– Data error rates
• Geolocation-based app uploads and operating system usage
• Mobile app upload rates – all apps and specific apps (e.g. shopping apps)
• Mobile app upload rates by operating system and/or device types
• Mobile app abandonment rates
NOTE: All presented data is for Android and iOS. Windows Phone, Windows 10,
BlackBerry OS and all other mobile operating systems data is available as well.

Android App Crash and Abandonment Rates
Total Android Daily Average Users (in millions) by Crash Rate
Buckets, December 2015
0
5
10
15
20
25
30
35
40
45
0.25 0.5 0.75 1 1.5 2 2.5 3 3.5 4 4.5 5
TotalAndroidDailyAverageUsers
Daily Crash Rate Buckets
All Apps
Shopping Apps
Android users are highly tolerant of app
crash rates that do not exceed an average
of .25% per day. When crash rates double
to .5% just over a third of Android users
continue their tolerance. Beyond that you
lose your audience.
Shopping app users show similar
patterns at .25% but usage drops
dramatically beyond this.

iOS App Crash and Abandonment Rates
Total iOS Daily Average Users (in millions) by Crash Buckets,
December 2015
0
2
4
6
8
10
12
0.25 0.5 0.75 1 1.5 2 2.5 3 3.5 4 4.5 5
TotaliOSDailyAverageUsers
Daily Crash Rate Buckets
All Apps
Shopping Apps
Apple users are perhaps surprisingly
more tolerant of app crash rates
than Android users.
This strongly suggests that Apple
users will provide retailers a small
window of opportunity to
understand that their app crash rates
are unacceptable and a small
window of opportunity to fix them.

Comparative iOS and Android Crash Rates
Crash Rate by OS Version
0
0.5
1
1.5
2
2.5
3
3.5
4
4.55/1/2014
6/1/2014
7/1/2014
8/1/2014
9/1/2014
10/1/2014
11/1/2014
12/1/2014
1/1/2015
2/1/2015
3/1/2015
4/1/2015
5/1/2015
6/1/2015
7/1/2015
8/1/2015
9/1/2015
10/1/2015
11/1/2015
12/1/2015
CrashRate
Timeline by Month, 5/1/2014 - 12/31/2015
iOS 7
iOS 8
iOS 9
All Android
Android has made
significant strides
towards providing a
stable OS. However,
the release of iOS 9
ensures Apple of
continued bragging
rights to stability.

App Loads and OS Adoption Rates: Android
Percentage of Total App Loads by OS Version - Android
0
20
40
60
80
100
120
PercentageofAppLoads
Android 4
Anfroid 5
Android 6
Android users are not
quick to upgrade to the
latest versions of the OS.
Android v5 took six
months to slowly
overtake v4. The
recently released v6 will
take longer to gain any
non-trivial market share.

App Loads and OS Adoption Rates: iOS
Percentage of Total App Loads by OS Version - iOS
0
10
20
30
40
50
60
70
80
90
100
iOS 7
iOS 8
iOS 9
Adoption rates for new
versions of iOS are
remarkably different than
Android’s. Adoption of new
releases of iOS is rapid –
Apple is not fibbing!
Crossover happens within a
matter of 4 to 6 weeks.
Should retailers care about
this in 2016?

App Loads and Device Adoption Rates: Samsung
Percentage of Total App Loads by Samsung Android Device
0
10
20
30
40
50
605/1/2014
6/1/2014
7/1/2014
8/1/2014
9/1/2014
10/1/2014
11/1/2014
12/1/2014
1/1/2015
2/1/2015
3/1/2015
4/1/2015
5/1/2015
6/1/2015
7/1/2015
8/1/2015
9/1/2015
10/1/2015
11/1/2015
12/1/2015
Samsung Galaxy S5
Samsung Galaxy S6
Samsung Galaxy S6 Edge
Samsung Galaxy S6 Edge+
All Samsung devices
As of December 31,
2015 Samsung Galaxy S5
devices still dominate
overall Samsung device
usage. Samsung Edge
devices have clearly not
gained any traction.
Should retailers care
about this in 2016?

App Loads and Device Adoption Rates: Apple
Percentage of Total App Loads by Apple iOS Device
0
10
20
30
40
50
60
70
80
90
1005/1/2014
6/1/2014
7/1/2014
8/1/2014
9/1/2014
10/1/2014
11/1/2014
12/1/2014
1/1/2015
2/1/2015
3/1/2015
4/1/2015
5/1/2015
6/1/2015
7/1/2015
8/1/2015
9/1/2015
10/1/2015
11/1/2015
12/1/2015
iPhone 5
iPhone 6
iPhone 6 Plus
iPhone 6S
iPhone 6S Plus
All Apple Devices
As with iOS itself Apple users
are relatively quick to upgrade
to new devices. iPhone 6 users
surpassed all iPhone 5 users
just before the holiday
shopping season kicked in. Big
screens now dominate the
iPhone landscape.
Should retailers care in 2016?

Geolocation Insights: Android Network Traffic

Geolocation Insights: iOS Network Traffic

App Latency for Shopping Apps: Android
Number of Android Shopping Apps per Latency Bucket
2
20
14
8
5
1
0
5
10
15
20
25
100 200 300 400 500 600
NumberofAndroidApps
Latency Buckets (in Milliseconds)

App Latency for Shopping Apps: iOS
Number of iOS Lifestyle and Shopping Apps per Latency Bucket
6
24
21
29
4 4 5
1 1
0
5
10
15
20
25
30
35
200 300 400 500 600 700 800 900 1000
NumberofAndroidApps
Latency Buckets (in Milliseconds)

Lifestyle and Shopping App Adoption Rates: iOS
Percentage of iOS App Loads, Lifestyle and Shopping Apps
0
2
4
6
8
10
12
App Store Lifestyle Category
App Store Shopping Category
Lifestyle + Shopping
Mobile shopping apps
matter a great deal.
Following Apple’s
creation of a pure
shopping category App
Store shopping app
uploads clearly spiked
during the 2015 holiday
shopping season.

Shopping App Adoption Rates: Android
Percentage of Android App Loads, Shopping Apps
0
10
20
30
40
50
60
70
80
Android shopping apps spiked
non-trivially in the latter half of
2015. In Android’s case the
spike occurred well ahead of
the holiday shopping season.
Why?
Additional correlations are
needed to answer the
question. Is it related to the
release of Galaxy S6 devices?

What’s Missing?
Global mobile demographics and
mobile app/platform metrics
provide the critical framework for
how retail teams – especially LOB
and marketing teams – need to
strategically and tactically invest
their resources and think about
both today and tomorrow.
But…the far greater value for this
analysis requires visualizations and
analysis of the same data
presented here customized for
every individual retailer’s mobile
ecosystem and measured against
the global aggregate mobile data.

Know Your Data…Know Your Mobile Shopping Apps!
How do your specific mobile shopping apps compare to and perform
against aggregate market behavior – both over time and for specific
(e.g. holiday) segments of time? Do they…
• Honestly outperform – creating strategic advantages
• Maintain an average performance – tactically ok but strategically
harmful
• Underperform – creating both strategic and tactical
disadvantages that will very likely lead to business failure
It’s impossible to know without specifically capturing the consumer and
mobile metrics data shown here specific to any given retailer
Effective & Profitable M-Commerce Apps
Some Quick Conclusions
M-Commerce Apps
App Ecosystems

01 02 03 04
All age groups are vital to
retail but Millennials are
already today’s most active
and proactive retail group
Meet the needs of all age
groups but cater most
specifically to Millennial
demands…today
A retailer’s mobile shopping
apps are the foundation for
the entire retail value chain
Know Your Data…Know Your Mobile Shopping Apps!

The Fundamental Mobile Retail Truth
“The Intersection of User and Mobile
App Ecosystems” isn’t a slogan – it’s
the necessary real world strategy to
retail success.
A deep understanding of both short
and long term aggregate global and
local mobile ecosystem behaviors and
their interactions is the bedrock on
which the foundation of retail mobile
apps must be built.

THANK
Phone: +1 (617) 624-3600
Contact Sales: sales@bluehillresearch.com
Contact Research: research@bluehillresearch.com
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