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Finding Meaning in Mobile Behavioral Data - CASRO Webinar

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Information about Finding Meaning in Mobile Behavioral Data - CASRO Webinar
Marketing

Published on March 6, 2014

Author: ResearchNow

Source: slideshare.net

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Presented by Melanie Courtright, Roddy Knowles, and Kristin Luck from Decipher. Hosted by CASRO.
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Finding Meaning in Mobile Behavioral Data Melanie Courtright and Roddy Knowles

Can you identify this picture? 2

Notice any differences? 3

Who are we studying? What devices? 4

US Census vs. Mobile and Brand Demos Census 49% 50% Mobile 51% 50% 25% 25% 17% 20% 18% 23% 12% 15% 12% 15% 4% Male Brand Female 6% 4% 5% Less than $25K25K - $49K$50K - $74K$75K - $99K100K - $149K $ $ $150K - $199K $200K+ Gender Income Male Female < $25K $25K $49K $50K $74K $75K $99K $100K $149K $150K $199K $200K+ 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 3% 2% 2% 3% 1% 4% 4% 2% - Other 5% 7% 12% 3% 4% 5% 4% 4% 3% 5

US Census vs. Mobile and Brand Demos Census Mobile 72%73% 33% 29% 13%13% 18 - 24 Brand 18%18% 25 - 34 18%19% 35 - 44 19%20% 45 - 54 16%15% 55+ Hispanic 13%15% Caucasian Age Black 5% 6% 9% 6% Asian Other Black Asian Other Ethnicity 18-24 25-34 35-44 45-54 55+ Hispanic Caucasian 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 2% 2% 4% 4% 0% 3% 2% 2% 8% 2% Other 2% 1% 5% 7% 9% 6% 7% 4% 4% 3% 6

Who We Are Studying What We Can Control! Mobile (Mean) Web (Mean) I am only interested in major sporting events I love watching all sports Sports really don’t interest me Watching / engaging in sports is important to me There are more important things in life than sports The Olympics will increase my interest in sports I will watch the Olympics with friends and family There are more important things in the World than the Olympics 2.95 3.11 2.18 3.51 3.57 3.24 3.66 3.60 2.97 3.14 2.17 3.56 3.56 3.31 3.72 3.59 Olympics Following Methods (%) (%) Television Newspapers News website(s) Radio Sport website(s) Mobile phone apps/applications 92% 42% 33% 31% 23% 13% 91% 40% 36% 32% 25% 15% Smoking (%) (%) Everyday Some Days Not at all 15.1% 7.8% 77.1% 14.2% 6.5% 78.1% Sports / Olympics Attitudes 30K global completes, single sample source, dual mode, with each mode weighted to age, gender, income, and ethnicity. 7

What Are We Capturing 2 Primary Mobile Platforms 7 Types of Data Collected Passively Location: GPS Apps: usage Phone calls: incoming, outgoing, missed, duration Text/SMS Messages: sent, received Email: sent, received Web: URL/websites visited Camera: usage 8

What We Can Do With… Location Data (GPS) • Filter behavioral data by location • Derive location type (e.g. home, work) • Target and push surveys Considerations • Not everyone is trackable • GPS accuracy: Satellite vs. Network • Type and frequency of communication • Advanced analytics 9

What We Can Do With… App Data Considerations • Target based on apps used • Passive or “active” usage • Measure “stickiness” • Raw data allergies • Slice and dice • Capture foreground & background usage 10

What We Can Do With… Web/URL Data • Track websites/URLs visited • Aggregate – top sites by category, user Considerations • What is captured, what is delivered, and what may be lost • Time measurement • Compare website usage vs. app usage 11

What We Can Do With… Text/SMS, Email, Phone, Camera, Music Considerations • Track ingoing and outgoing communications • Music listening varies by platform • Log Camera usage • Boolean capture • Capture specific details of music played • When content is important, ask 12

What This Means for Research Behavioral data stands alone… or hand in hand with other data points On its own/ Aggregated • Key indicators and measures • Trend spotting Sliced and diced Combined with survey data • Place and time • Stated vs. actual • Demographics • Trust but verify • Attitudes and behaviors • Understand the “why” 13

Aggregated Behavioral Data Top Level Report on User Activity Data from US mobile behavioral panelists rolled into a monthly summary report 14

App Usage December Top 10 App Categories Used % Reach Communications 29 Average Number of Apps Used Per Day Social Media 155% Email 124% App Stores 4 App Categories w/ 100%+ Reach 160% 100% Music 80% Streaming Video 76% Mapping & Nav. 70% Shopping 42% 15

Website Visitation December Top 10 Most Visited Websites Top 10 Websites with the Most Unique Visits 1. google.com 1. google.com 2. facebook.com 2. facebook.com 3. amazon.com 3. amazon.com 4. wikipedia.org 4. yahoo.com 5. youtube.com 5. wikipedia.org 6. walmart.com 6. youtube.com 7. ebay.com 7. ebay.com 8. answers.yahoo.com 8. espn.go.com 9. twitter.com 9. accuweather.com 10. walmart.com 10. ups.com Designates website ranks in top 10 for most visits and unique visits. 16

Behavioral Data Alone Holiday Shopping Study As part of a broader study on holiday shopping including online and B&M shopping, mobile activity was tracked. 17

Planned and actual store visits during a two week period What respondents said and did ranked differently Top 10 store visitation ranking 70% GPS Store visitation 64% 47% 41% 35% 33% 24% 23% 22% 22% 21% 21% 20% 18% 10% 10% 9% 1 2 15 7 8% 7% 0 11 3 16 5 10 9% 3% N=5829 - Q8. Which of the following store locations are you planning to visit in the next few weeks? Please check all that apply. 18

Top 20 Apps Usage The Facebook app was used 11,004 hrs during the 12-day period (11/19-11/30) by 719 users averaging to 1.275 hrs per day (76.5 minutes). Period: Nov 19-30, 2012. Tracked websites which are in top 20 are highlighted in Blue Color. Segmented based on No of Users & Hrs used is more than 100. Default apps not considered under consideration (like Settings, Contacts etc.,) 19

Traffic Store Visits GPS Sample = 800 Total # of Visits 300 242 247 256 254 245 11/29 11/30 204 207 223 202 167 144 153 144 11/25 11/26 11/27 543 136 547 0 11/19 11/20 11/21 11/22 11/23 11/24 Mobile Websites Sample = 1150 Total # of Visits 1000 11/28 921 701 745 456 376 281 279 11/20 11/21 475 0 11/19 11/22 11/23 11/24 11/25 11/26 11/27 11/28 11/29 11/30 3221 3098 2930 2710 11/27 11/28 11/29 11/30 PC Websites Sample = 5398 Total # of Visits 7000 4969 3389 3316 5757 5404 4593 3885 3789 0 11/19 11/20 11/21 11/22 11/23 11/24 11/25 11/26 20

Behavioral & Survey Data Combined In-store Phone Usage Grocery shoppers’ phone usage was captured, verified, and contextualized. 21

Shopper Profile Greg Grocery Male, 53, Divorced Fred Meyer – April 18, 2013 Special Trip, Under 15 Minutes $14 Game, Fa cebook No Coupon Used 22

App Usage Stated and Actual Types of Apps Used Text/SMS Phone Social 31% 25% 24% Shopping/ Retail Games 21% 13% 16% 12% 14% 11% 5% Stated Actual 23

App Usage What & Why 39% 46% Call about a purchase Message about a purchase What did you buy? 24

App Usage What & Why Shopping List 83% Coupon 45% Compare Prices 41% 25

The Behavioral Data Journey 26

P1: Lost at Sea 27

P2: Learning how the data lives together 28

P3: Happy Days 29

P3b: I Love Data, Too 30

P4: Data Magic 31

P5: Elite Data Team 32

Thank you! Melanie Courtright mcourtright@researchnow.com Roddy Knowles roknowles@researchnow.com 33

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