The document summarizes a presentation given at the MRMW Chicago conference from May 27-30, 2014. It discusses how mobile behavioral data can provide insights into web and app usage beyond just the top 10 sites/apps. It highlights differences between Android and iOS users demographically, attitudinally, and behaviorally. It also shows how engagement scoring and segment profiling of mobile data can provide customized profiles and targeting.

1. May 27-30, 2014
Congress Plaza Hotel & Convention Center
#MRMW
Organized by

2. Title Sponsor Gold Sponsors
Silver Sponsors
MRMW Chicago May 27-30, 2014 #MRMW

3. Workshop Sponsors
Association & Education Partners
Networking Reception
Sponsor
Event App
Partner
Media Partners
MRMW Chicago May 27-30, 2014 #MRMW

4. Combining Profiling and Mobile Behavioral Data
for “Easy” Insights into Web and App Usage
Beyond the Top 10
Roddy Knowles
Director of Mobile Research
@roddyknowles

5. 2
Mobile Behavioral Data
Part of the Research Toolkit

6. 3
Mobile Behavioral Data
Web
Camera SMS
Location
Phone Music
Email
Data Transmitted
Battery
Application

7. 4
Top 10
Web
82%
72%
41%
40%
27%
25%
22%
20%
18%
18%
Google
Facebook
Wikipedia
Amazon
Twitter
YouTube
Answers.Yahoo
Huffpost
Accuweather
Buzzfeed
Website Reach %
Research Now Mobile Panel, March, 2014

8. 5
Top 10
App
77%
64%
62%
64%
29%
26%
25%
24%
23%
21%
App Reach %
Facebook
Gmail
YouTube
Instagram
Pandora
Google
Candy Crush
Twitter
Groupon
Amazon
Research Now Mobile Panel, March, 2014

9. 6
App and Web
Amazon
Groupon
LinkedIn
Ebay
Instagram
Pinterest
Yelp
Target
Gamestop
Walmart
LivingSocial
CVS
App Only App and Web Web Only
1,000 2,000 3,000
Research Now Mobile Panel, March, 2013

10. 7
Parsing The Data
Demographics
OS
Engagement Scoring
Segment Profiles

11. 8
Brand
Gender Income
M F > $25K
$25K -
$49K
$50K -
$74K
$75K -
$99K
$100K -
$149K
$150K -
$199K
$200
+
Android 57% 39% 53% 56% 48% 37% 44% 23% 24%
iPhone 33% 50% 32% 37% 43% 50% 44% 63% 70%
Blackberry 3% 3% 1% 3% 4% 4% 4% 8% 4%
Windows Phone 3% 2% 2% 3% 1% 4% 4% 2% -
Other 5% 7% 12% 3% 4% 5% 4% 4% 3%
Brand
Age Ethnicity
18-24 25-34 35-44 45-54 55+
Hispa-
nic
Cauca-
sian
Black Asian Other
Android 51% 54% 54% 45% 40% 59% 42% 57% 53% 74%
iPhone 43% 42% 36% 39% 45% 28% 47% 30% 35% 19%
Blackberry 2% 1% 2% 5% 5% 5% 3% 8% - 2%
Windows Phone 2% 2% 4% 4% 0% 3% 2% 2% 8% 2%
Other 2% 1% 5% 7% 9% 6% 7% 4% 4% 3%
Does OS Matter?
Demographics

12. 9
• Devastated if phone was lost
• Important for entertainment
• Used to avoid being bored
• Researching products
• Shopping
• Purchasing products
• Play Games
• Listening to Music
• Recording Videos
… and many more!
• Comfortable around people
• Talk to lots of people at parties
• Admire people with $$$ things
• Thing I own say a lot about me
• Feel they are trendier
• New products are exciting
• Buy new & different products
• Pay more to try new products
• Particular about brands used
iOS Users More Likely To
Say They Are…
Does OS Matter?
Attitudinal and Behavioral Differences in Users

13. 10
Android Users More Likely
To Say They Are…
• Not care about brand names
• Try to keep their life simple as far as
possessions are concerned
• To watch shows or movies on TV
• Talk on their phone
• Use navigation on their phone
Differences do indeed exist
between & users –
demographically, attitudinally, and
behaviorally.
These differences are
highly relevant for researchers.
Does OS Matter?
Attitudinal and Behavioral Differences in Users

14. 11
Android and iOS Users
streaming audio
messaging
deal apps
mobile banking
news

15. 12
Parsing the Data
Engagement Scoring
Application and URL Metrics
Moderately
High
Moderately
Low
LowVery High High Very Low

16. 13
Parsing the Data
Segment Profiles
Segment Segment SegmentSegment Segment
Profiling Attributes
Segment Segment SegmentSegment Segment

17. 14
Interested in
Fashion, Food,
Entertainment
Skews female
High
engagement
Broad range
of hobbies
and interests
Moderate
engagement
Involved in
home
improvement
and home-
related
activities
High
engagement
Likes
travelling,
concerts,
outdoor
activities
Moderate
engagement
Focused on
finance &
investing
Skews male,
higher
education,
affluent
Low
engagement
Parsing the Data
Segment Profiles
Enthusiasts HomebodiesCulture Club
Interested in
Fashion, Food,
Entertainment
Skews female
High
engagement
Broad range
of hobbies
and interests
Moderate
engagement
Involved in
home
improvement
and home-
related
activities
High
engagement
Likes
travelling,
concerts,
outdoor
activities
Moderate
engagement
Focused on
finance &
investing
Skews male,
higher
education,
affluent
Low
engagement
Money
Minders
Out and
About
Enthusiasts HomebodiesCulture Club

18. 15
Segment Profiles
Heavier users of
social sites such
as Facebook,
Instagram,
Buzzfeed
Average users of
retail sites/apps
Heavier users of
Facebook,
entertainment
sites like Netflix
Average users of
shopping
sites/apps but
heavier users of
Ebay
Heavier users of
email, sports,
LinkedIn
Lighter users of
social and deal
sites/apps
Money Minders Out and AboutCulture Club

19. 16
Top 10 Tips
1. Know what is collected.
2. Determine which data points are important.
3. Understand the makeup of the panel/sample.
4. Define what you want to find, and then…
5. Dig deeper.
6. Acknowledge OS as a consideration.
7. Look at App and Web data in parallel.
8. Understand levels of engagement.
9. Creatively parse the data with profiling or
segmentation.
10. Integrate with other types of research.

20. 17
Thank You!
17
Roddy Knowles
roknowles@researchnow.com
@roddyknowles

21. Title Sponsor Gold Sponsors
Silver Sponsors
MRMW Chicago May 27-30, 2014 #MRMW

22. Workshop Sponsors
Association & Education Partners
Networking Reception
Sponsor
Event App
Partner
Media Partners
MRMW Chicago May 27-30, 2014 #MRMW

23. May 27-30, 2014
Congress Plaza Hotel & Convention Center
#MRMW
Organized by