augmenting media data with mobile behaviourpamro.org/wp-content/uploads/2019/08/augmenting... ·...
TRANSCRIPT
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Augmenting Media Data with Mobile Behaviour
Peter Searll
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CONTENTS
• Intelligence
• Changing media consumption patterns
• Implications for our industry
• Rationale for this paper
• Case study
• Applications
• Conclusions
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INTELLIGENCE IS A ROUTINE OF…
..collection, collation, interpretation and dissemination of information
…it’s not a once-off task!
John Hughes-Wilson – The Puppet Masters
The Definitive Guide to Military Intelligence
www.envision.com
The application of intelligence leads us to insight & strategy
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MARKETING INTELLIGENCE SOURCES
− Tend to be source initiated
− Less structured
− Bi-polar
− Self-selection
Sentiment analysis
Interrogation (traditional research)
− Researcher initiated
− Problem focused
− Question / answer
− Sample is controlled
Motivation, satisfaction, media diaries
Spying (observation)
− “Big data”
− Systematic
− Behavioural data
Actual behaviour patterns /data mining
Tip-offs (feedback)
Applying all 3 sources provides a comprehensive consumer perspective.This paper focuses on Observation (spying) only.
Examples:
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TRADITIONAL TV VIEWERSHIP IS CHANGING
Source: Nielsen USA
• Under 50 yrs old declines• 50-64 static
• Slight growth in 65+ yrs
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THE EVIDENCE IS OVERWHELMING…
Netflix Caused 50% of U.S. TV Viewing
Drop in 2015 (Study)
UK viewers doubled amount of time spent
streaming TV in 2015
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NOT JUST USA & EUROPE
There is a proliferation of live streaming channels in Africa too…
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MOBILE STREAMING IN AFRICA
• Percentage of mobile owners currently using video or music streaming on mobile• Total across these markets is 16% - (1 in 6)
• Data courtesy of MTN - Market Performance Report Q2 2016
23%21%
20%19%19%
17%17%
15%15%
14%7%
7%5%
4%
Ghana
Zambia
Cameroon
South Africa
Rwanda
Liberia
Guinea Bissau
Uganda
Nigeria
Congo Brazzaville
Cote d'Ivoire
Guinea Conakry
Benin
Swaziland
Weighted total 16%
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The number of
mobile
broadband
connections in
Africa will climb
from 147 million
in 2014 to one
billion in 2020!
COUPLED WITH MOBILE BROADBAND EXPLOSION…
PWC, Ovum November 2015
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THE INEVITABLE… ONLY A QUESTION OF WHEN
2016 2018 When? When? When?
Broadcast Online
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PROJECTED ADSPEND GROWTH IS ASTOUNDING
• Internet spending expects a 21.7% CAGR until 2019 in SA. (Nigeria 31.6%, Kenya 16.8%)• TV at 6.2% and Radio 5.9% (CAGR)• TV spend now 5x Internet spend, down to 3.5x in 2019
Source: PWC – Entertainment and media outlook 2015-2019
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KEEPING PACE WITH CONSUMERS:INDUSTRY IMPLICATIONS
Media owners
• TV audience attrition, especially younger viewers
• Proliferation of music streaming challenges radio
• Advertising revenue share declines• Challenge to keep format relevant• Challenge to keep content relevant
Media buyers
• Also under threat, especially with programmatic buying
• Innovation to keep pace with digital channel buying as part of mix
• Media currency beyond reach and frequency (e.g. CTR – click through rates)
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KEEPING PACE WITH CONSUMERS:INDUSTRY IMPLICATIONS
Advertisers
• Cross-platform challenges for consistent messaging
• ROI metrics – easier in digital, and changing with click through rates and other metrics
• AR (augmented reality) is a game changer – allowing consumers to interact with ads
• BUT – still quite reliant on traditional media
Researchers
• How do we keep up with these challenges?
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RATIONALE FOR THIS PAPER
• Clear that media consumption is changing
• Advertisers, media owners and researchers need to keep up with the market
• Much talk of “second screen” at PAMRO 2015
• In Africa, this is often the first or only screen
• How can we measure this consumption accurately?
AND
• How can this be used to augment existing traditional media data?
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CASE STUDY: ZAMBIA
Objective: To measure and track mobile behaviour, with a specific media focus
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CASE STUDY
• We built an App that records all activity on mobile
phones / tablets
• Android only at this stage
• Very little iOS in Africa
• Respondents recruited using our existing panel in
Zambia (Amplify 24 brand)
• In return for an incentive, they downloaded the App
and gave us permission to track their device usage
Presented as proof of concept, not definitive results due to small sample size.
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METHODOLOGY
• A total of 60 respondents participated
• Once installed, the App collected usage data all the time
• Data uploaded to our servers 3 times a day – in efficient packages
• Data was collated, cleaned and analysed
• No user requirement other than installing App (and giving permission)
• If out of airtime (data) and Wi-Fi range, the App waits for signal to upload the data
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KEY METRICS COLLECTED
• Device usage:
• Websites visited (including time visited and number of times)
• Apps (including when used and time in foreground)
• Wi-Fi vs GSM data usage (uploads and downloads)
• SMS – sent and received
• Calls – made and received
• Other phone functions like settings, calendar etc.
• Demographics – from panel
Critical to clean and code this very complex data
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RESULTS – MAKING SENSE OF THE BIG DATA
© 1999-2005 Randy J Read, University of Cambridge
Probability distributions of diffraction in a crystalline structure…
Or a representation of data we received from our respondents.
Analysis requires sophisticated protocols to extract the mass of complex data
• 242 926 website visits• 402 295 App usage occasions
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SAMPLE PROFILE
Male, 76%
Female, 24%
Strong male bias
37%
53%
10%
19-25 26 – 35 36+
Light in over 36 years
Starting off with a small sample of 60 respondents, declining over time. Data collected from Sep ‘15-July ’16.While the results are not significant, the system and outputs are potent and versatile.
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WEEKLY BASIC PHONE USAGE PATTERNS
• Distribution during the week is the same for both genders – lowest on weekends.
• But… women do speak longer than men. Average female call duration is 129 seconds compared to men who average 84 seconds a call.
• Interestingly, men make more calls than women, around 3 more calls per day on average.
10%
11%
12%
13%
14%
15%
16%
17%
18%
19%
20%
Monday Tuesday Wednesday Thursday Friday Saturday Sunday
Calls and SMS by Day of week
Calls SMS
% of total volume
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THE IMPORTANCE OF WI-FI - ACCESSIBILITY
• Currently GSM accounts for 54% of data usage
• Women use Wi-Fi much more than men for downloading
GSM download48%
GSM upload6%
Wifi download30%
Wifi upload16%
Total data usage
• Cheaper data or more prevalent Wi-Fi will accelerate usage, especially VOD / streaming
• Wi-Fi hotspots are gaining traction at a rapid rate
• Critical to track how this develops over time
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WEBSITE REACH - BY CATEGORY
• Social, search and sports news are most widely accessed
• * Women seeking activism, tech / device news and adult more than men
• * Men looking out for careers and sports / sports betting more
Female Male
**
*
*
*
*
242 926 website visits in total
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WEBSITES: NEWS CATEGORY DRILL DOWNREACH & FREQUENCY
• While The Mirror has the highest reach, Zambia Watchdog has higher frequency
• Lusaka Times also has high frequency
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MIRROR EXTRACTS….MOSTLY FOOTBALL
http://www.mirror.co.uk/sport/row-zed/fifa-16-player-ratings-announced-6382404?ICID=FB_mirror_MF
http://www.mirror.co.uk/sport/football/match-reports/man-united-3-1-liverpool-6429329?ICID_mirror_MFhttp://www.mirror.co.uk/sport/football/news/liverpool-fans-launch-funding-page-6442163
http://www.mirror.co.uk/sport/football/news/louis-van-gaal-warns-anthony-6527366?ICID=FB_mirror_MFhttp://www.mirror.co.uk/sport/football/news/rafa-benitez-labels-cristiano-ronaldo-6441759?ICID_mirror_MFhttp://www.mirror.co.uk/3am/celebrity-news/liverpool-legend-steven-gerrard-admits-6394585http://www.mirror.co.uk/sport/row-zed/man-united-transfer-tool-choose-6310707http://www.mirror.co.uk/sport/row-zed/gareth-bale-scores-cheeky-goal-6374051?ICID=FB_mirror_MF
http://www.mirror.co.uk/sport/football/match-reports/man-united-3-1-liverpool-6429329?ICID_mirror_MFhttp://www.mirror.co.uk/sport/football/news/louis-van-gaal-warns-anthony-6527366?ICID=FB_mirror_MF
http://www.mirror.co.uk/sport/football/news/cristiano-ronaldo-told-real-madrid-6439575?ICID=FB_mirror_MFhttp://www.mirror.co.uk/3am/celebrity-news/liverpool-legend-steven-gerrard-admits-6394585#http://www.mirror.co.uk/sport/row-zed/man-uniteds-memphis-depay-dresses-6527564?ICID=FB_mirror_MF
http://www.mirror.co.uk/3am/celebrity-news/heidi-klum-flashes-pert-bum-6395401http://www.mirror.co.uk/sport/football/news/manchester-united-striker-anthony-martial-6482080?ICID=mirror_MF
http://www.mirror.co.uk/sport/football/news/luke-shaw-returns-manchester-united-6582607http://www.mirror.co.uk/sport/football/news/brendan-rodgers-cant-afford-liverpool-6352119
http://diply.com/visual-architecture/article/wife-insult-husband-depression-wrote-mirror-love-list
…and Heidi Klum’s bum
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SOCIAL MEDIA WEBSITES REACH
• Everyone is on Facebook
• Rate n Date and Bb Dating are more popular among women, while Slut finder and Date hot dolls are exclusively male
• Waplog has the highest combined reach among dating sites
Female Male
*
*
*
*
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FACEBOOK DRILL DOWN – SUNDAY ONLY
Versatile data and analysis enables detailed profiling by time of day / day of week
• Very similar gender usage
• Peaks before and after lunch, and around dinner time
Don’t post here!Female
Male
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FACEBOOK DRILLDOWN – WEEK VS WEEKEND
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Sunday Weekdays
Facebook uses about 100 000 weighting factors for ranking posts!Simplified:1. User affinity – relationship / connection to source2. Weight – shares, comments, likes3. Time decay
• 10am is good for weekday placements, but not on Sunday, where 3pm (or 8pm) is better!
% of visits
Time of day
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APP: REACH BY GENRE
• No surprise that Communication Apps are most widely used
• High usage of media, music and video
• Shopping Apps at 20% reach
402 295 App usage occasions in total
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APP DRILLDOWN – COMMUNICATION GENRE
• WhatsApp is the platform of choice, followed by Gmail
• Comparing the age groups, over 25’s use Messenger and Chrome more, while the youth prefer Opera Mini and Internet for Samsung Galaxy
Under 25 yrs25+ yrs
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APP DRILLDOWN:USAGE FREQUENCY & PATTERNS BY TIME OF DAY
• Simply compare Apps / website daily usage patterns • Compare different demographics
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TRACK USAGE AND SHARE OVER TIME…
15%
25%
35%
45%
55%
65% Chrome Browser - Google
Opera Mini web browser
UC Browser
0%
20%
40%
60%
80%
September October November December January February March April
VLC for Android Shazam
Google Play YouTube
Sony Ericsson Album
0%
20%
40%
60%
80%
100%
September October November December January February March
Blue Stacks
Candy Crush Saga
Plants vs. Zombies 2
Temple Run 2
Browsers
Music services
Games….etc.
Please don’t send me Candy Crush invites anymore!!
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A DAY IN THE LIFE…..
Individual / group daily usage patternsAggregated mobile perspective
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WIDE VARIETY OF DAILY USAGE…..
Great for segmentation!
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DATA VERSATILITY
•Multiple time scales available: by hour, day, week, month (or minute if really needed)
•Full usage of mobile device in perspective
•Websites and apps grouped by type / genre for full competitve profiling
•Detailed analysis of reach and frequency by any demographic at a very granular level
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KEY ADVANTAGES OF OUR APPROACH
• Tracks individuals – not specific websites / apps• Customer centric vs website centric
• Accurate, complete permission based record of actual behaviour - not diary / recall / interview based•Truly longitudinal data•No surveys required to get data – just continuous passive data collection
• Data available almost immediately – no diaries to process• Covers all websites and apps, not just the large ones
• No registration required / no tags from site owners• Does not rely on cookies (which can be deleted and don’t work on all
browsers / Apps)• Seamlessly supplemented with survey data• Scalable
• Merges easily with existing media data
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SOME APPLICATIONS
Media Owners
• Repertoire analysis – competitive context• Profile of users• Inclusion in measurement whether site is
tagged or not, or not in Top 100• Track market share
Media Buyers
• Accurate planning tool• Ability to buy across the board media• Data in familiar format
Marketers
• Better targeting • Lifestyle segmentation profiling based on
behaviour• Own customer panels
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DEVELOPMENTS
• Live reporting
• Multi-devices for respondents who use them – aggregated
• Geo-location (also enhance OOH measurement)
• User dashboards / utility to monitor their own mobile behaviour
• Links to social media profiles
• Multi-dimensional segmentation
• Survey data for uncovering motivation and customer journey mapping
• Predictive analytics
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Online
IN A NUTSHELL…
Interrogation (traditional research)
− Existing media data
Spying (observation)
− App data
Tip-offs (feedback)
Offline
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AUGMENTING TRADITIONAL MEDIA DATA
• There are many tools that conduct detailed website analytics of users and audiences, but..
• these don’t necessarily show which other sites users visit
• or App usage
• Our App data can be stand-alone or easily added to existing media sets –(matched on demographics)
• Next step is recruiting broad enough samples to ensure market coverage
• Provides a holistic and consolidated view across all websites and apps
Combined with traditional media data to provide complete media consumption:
TV, radio, print, internet and App usage
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Studio C11, Mainstream Centre, Hout Bay, 7806, Cape Town, South Africa
Tel +27 (0)21 790 1801www.dashboard.co.za
Thank you!