Augmenting Media Data with Mobile Behaviour

Peter Searll

CONTENTS

• Intelligence

• Changing media consumption patterns

• Implications for our industry

• Rationale for this paper

• Case study

• Applications

• Conclusions

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

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:

TRADITIONAL TV VIEWERSHIP IS CHANGING

Source: Nielsen USA

• Under 50 yrs old declines• 50-64 static

• Slight growth in 65+ yrs

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

NOT JUST USA & EUROPE

There is a proliferation of live streaming channels in Africa too…

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%

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

THE INEVITABLE… ONLY A QUESTION OF WHEN

2016 2018 When? When? When?

Broadcast Online

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

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)

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?

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?

CASE STUDY: ZAMBIA

Objective: To measure and track mobile behaviour, with a specific media focus

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.

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

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

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

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.

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

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

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

WEBSITES: NEWS CATEGORY DRILL DOWNREACH & FREQUENCY

• While The Mirror has the highest reach, Zambia Watchdog has higher frequency

• Lusaka Times also has high frequency

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

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

*

*

*

*

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

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

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

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

APP DRILLDOWN:USAGE FREQUENCY & PATTERNS BY TIME OF DAY

• Simply compare Apps / website daily usage patterns • Compare different demographics

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!!

A DAY IN THE LIFE…..

Individual / group daily usage patternsAggregated mobile perspective

WIDE VARIETY OF DAILY USAGE…..

Great for segmentation!

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

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

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

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

Online

IN A NUTSHELL…

Interrogation (traditional research)

− Existing media data

Spying (observation)

− App data

Tip-offs (feedback)

Offline

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

Studio C11, Mainstream Centre, Hout Bay, 7806, Cape Town, South Africa

Tel +27 (0)21 790 1801www.dashboard.co.za

Thank you!