CROWDSOURCING OOH AUDITS:AN EXPERIMENTAL PILOT

Peter Searll

OVERVIEW

• The Wisdom of Crowds

• Crowdsourcing

• Rationale driving the experiment

• Pilot methodology

• Results

• Implications

OPENING REMARKS

• OOH media is a vital part of the African mix

• It is probably the most difficult media to measure

• Wide geographic spread

• Variety of installations and sizes

• Rise of digital displays

• Audiences

• There is ongoing innovation in this space

AUGMENTED REALITY COMES TO OOH

• Google has won a patent to add new billboards to Street View – so new OOH ads can appear in the virtual world!

• Innovative use of QR codes or other interactive devices can make advertising significantly more engaging

• iBeacons allow Mobile Apps to listen for signals from beacons in the physical world and react accordingly.

• Highly contextual, hyper-local, meaningful messages and advertisements on their smartphones.

• Is this the ultimate OOH?

• Crossover with digital media

BUT FOR NOW…..

We need cost effective, practical measurement tools that can work anywhere

THE WISDOM OF CROWDS

• Published in 2004, Surowiecki details how crowds can be harnessed to make better decisions and accomplish more than individuals

• He describes 3 main types of problems that crowds can work with:

1. Cognition

2. Co-ordination

3. Co-operation

COGNITION

• Problem solving and information processing

• Under the right circumstances, groups are remarkably intelligent, and are often smarter than the smartest people in them

• Danger of electronic herd – following the crowd like fund managers could be disastrous

• Search algorithms rely on this approach

• In research, we rely on representative samples to help solve problems – like which ad is better? Or which pack has more appeal?

CO-ORDINATION

• Harnessing the power of the group

• Crowdsourcing could be seen as an extension of this•Defined by Merriam- Webster as:

“the process of obtaining services, ideas, or content by soliciting contributions from a large group of people”

• In research, this is distinctly different to Cognition, which usually requires a representative sample

• What’s the quickest way to translate a 500 page book?Get 500 people to translate 1 page each…

Can this be applied to OOH audits?

RATIONALE FOR THE PILOT EXPERIMENT

Traditionally:

• OOH audits are complex and expensive

• Often only cover larger formats

• Relatively infrequent measurement

• Media owners only cover own sites – no aggregated perspective (SOV), questionable independence

• Not all areas / regions are included in audit

• Damaged sites can be left un-noticed for months

• Many markets lack even basic OOH data

Our pilot aimed to establish whether or not these limitations could be overcome using a crowdsourced approach

PILOT OOH CASE STUDY - ZAMBIA

PILOT OBJECTIVES

• To determine the feasibility of a crowd-sourced approach to OOH audits

• Can this be done effectively?

• Can this be done cost effectively?

KEY CHALLENGES IN OUR PILOT

1. Using non-professionals

2. Duplicate site coverage

3. Non-commercial sites (e.g. signage)

4. Linkage to specific media owners

5. Traffic counts – to assess reach

METHODOLOGY

• Using our existing panel (Amplify24), we invited applicants and selected some participants for this pilot

• We built an App that selected participants downloaded onto their phones

• Only Android

• Need to have GPS functionality

• Pilot limited to Lusaka only

DATA COLLECTION

• The App included instructions of how to conduct a brief site audit, with pictorial examples

• Participants needed to take photos and complete some high level metrics

• A total of 15 people were invited and 7 actively took part

• Fieldwork June and July 2016

ENCOURAGING DATA COLLECTION

• Participants were incentivised based on the number of accepted sites

• Defined as sites that were paid for and could be changed to have another advert / message

• Gamified with a simple ranking system

• Data costs minimised - option to upload site data when in Wi-Fi range

SIMPLE AUDIT

For each site, participants were required to take a clear photo, and the App automatically added GPS and timestamp• App ensured photos taken during audit only.

• No external pictures to be uploaded from phone or websites to limit cheating.

AUDIT OUTPUTS

Apart from the feasibility objectives, the audit aimed to provide these key metrics:

• Share of voice – by category and within category

• Number of sites – by type of installation

• OOH advert format Billboard / bus shelter / lamp post /other

• Degree of clutter - How many other advertisements are visible?

• Standout / obstructions / visibility - How likely is someone passing by to see this advertisement?

• Level of damage (if any)

These metrics are not comprehensive, but do provide insight

PILOT RESULTS

SITES AUDITED – LUSAKA GPS

A TOTAL OF 507 SITES WERE

AUDITED

(109 EXCLUDED –EITHER SIGNAGE OR

POOR QUALITY)

EXAMPLE SITE

TYPE OF SITES

65%

20%

15%

1%

Billboard

Other

Lamp Post

Bus Stop

OTHER – MOSTLY WALLS

EXAMPLES OF “OTHER” TYPES

CATEGORY SHARE OF VOICE

20%

10%

9%

9%

7%

5%

5%

5%

4%

4%

3%

3%

3%

2%

2%

2%

1%

1%

1%

1%

1%

1%

1%

Construction / Building /…

Drink - Non Alcoholic

Financial Services

Food

Political & Government

Technology/Cellphones/Gadgets

Appliances

Transport

Mobile & Internet

Services / professional

Entertainment

Cosmetics/Beauty

Retail

Education/Schools/Universities

Telecommunications

Household products

Drink - Alcoholic

Healthcare and medicine

Travel and tourism

Events

Religious

Agriculture and livestock

Other

Traditional OOH only captures a fraction of all the messaging

NON-ALCOHOLIC DRINKS GPS

NON-ALCOHOLIC DRINKS GPSCOCA-COLA VS COOLSPLASH

Coca-Cola

Coolsplash

CATEGORY EXAMPLE:NON-ALCOHOLIC DRINKSSHARE OF VOICE

Coca-Cola, 14%

Coolsplash, 12%

Apple max, 10%

Shake'n sip, 8%

Ama sip sip, 6%Pepsi, 6%

Planet drinks, 6%

American cola, 4%

Humming Bird, 4%

Reaktor, 4%

Thirsty, 4%

Aqua Savannah, 2%

Dragon, 2%

Fanta, 2%

Flamingo, 2%

Fruitree, 2%

Mountain dew, 2%

Savannah, 2%Yess drink, 2%

EFFECTIVE SHARE OF VOICE

• Not all sites are the same size, so a simple count of sites could be an unfair measure of share of voice

• To compensate for this, we propose a blended measure:number of sites x the size of each site = effective share of voice

• Standout be used as a moderating variable as well

CLUTTER TOTAL

4%

24%

21%

29%

12%

4%

3%

2%

1%

0

1

2

3

4

5

6

8

10

Nu

mb

er

of

oth

er

visi

ble

ad

vert

s

An average of 2.6 other adverts are visible from each

place

AVERAGE CLUTTER BY BRANDNON-ALCOHOLIC DRINKS

An average of 2.4 other adverts are

visible in this category.

Apple Max, Thirsty and Hummingbird should relook their

placements

5.04.5

3.23.03.03.03.0

2.42.42.3

2.02.02.02.02.02.0

1.51.01.01.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Mountain DewDragonAmerican ColaShake'n SipPlanet DrinksFruitreeFlamingoCoolsplashAqua SavannahAma Sip SipPepsiCategory averageCoca-ColaSavannahReaktorMobile CityFantaApple MaxThirstyHumming Bird

VISIBILITY / STANDOUT

84%

14%

2%

0%

Everyone

Some People

Hardly Anybody

Nobody

SOME PEOPLE…

HARDLY ANYONE…

DAMAGE

83%

13%

3%

No damage

Slightlydamaged

Badly damaged

A total of 85 sites have some damage

REACH ESTIMATION

• Using Waze (a traffic app), we can calculate the average travel time along a road from A to B (based on previous whole year’s data of users)

• Using a density algorithm, it is possible to broadly estimate the weekly traffic flow past a point

• Could be enhanced / validated by actual counts

• Accounting for bus routes

• Would differ for type of road and type of traffic (car, bus, pedestrian)

50

60

70

80

90

100

110

Average duration (mins)

Weekday average Weekend average

A

B

IMPLICATIONS

CHALLENGES & SOLUTIONS

1. Using non-professionals

2. Duplicate sites

3. Non-commercial sites

4. Linkage to media owners

5. Traffic counts

1. Describing exactly what is to be captured, providing examples and feedback on rejected sites. Verification.

2. Data needs to be thoroughly cleaned to remove these

3. Feedback and training to minimise

4. List of sites from media owners or advertisers.

5. Traffic estimates using Google Maps / Waze with sensible algorithms

BENEFITS TO ADVERTISERS

• Independent, regular site audits to ensure compliance

• Optimise placements – reduce cluttered site holdings

• Immediate notification of missing / damaged installations

• Competitive intelligence:

• Share of voice data (and spend IF rate cards available)

• Intel on competitor campaigns (location and content)

• Mapped location of own and competitor sites

BENEFITS TO THE INDUSTRY

• Independent, regular site audits for customer peace of

mind

• Immediate notification of missing / damaged installations

• Comprehensive database of all sites

• Competitive intelligence:

• Share of sites

• Mapped location of own and competitor sites

FUTURE ENHANCEMENTS

• Pre-load list of sites to link to media owner holdings• Media owner or advertisers to supply

• Augmented gamification to engage more participation• Along the lines of Pokémon Go?

• Layers of verification

• Additional metrics like SES/LSM description of each area – profiling

• Better traffic count solutions to assess cost of reach• Would require rate cards to be public

• Data linkage to media planning like Telmar

• JIC involvement

CONCLUSIONS

• Crowdsourcing could be used to conduct OOH audits on a regular basis

• And certain other research like promotion activations or price checks

• Coverage of smaller installations (and regions) easily included

• Highly scalable

• With broad participation, this is a cost effective solution (approx. 2%-3%)

HOW WISE ARE WE?

0

2000

4000

6000

8000

10000

12000

14000

16000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

Median: 2 500

Actual 1 125 – we are obviously not very wise!Only 3 guesses below 1 000 – the anchor bias was too strong!

PARTING THOUGHT

Surowiecki mentioned 3 types of problems that can be solved using the Wisdom of Crowds….

We covered Cognition and Co-ordination.

The third type is Co-operation:

We welcome feedback and collaboration to develop this approach.

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

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

peter@dashboard.co.za+27 (0)82 857 7057

Thank you!