Measuring Digital Signage Networks - Quividi
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"Measuring Digital Signage Networks and Using Metrics to Optimize Your Impact" was presented by Olivier Duizabo, CEO, Quividi, at BroadSign's European Client Summit in London England on June 24, 2013.
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Measuring Digital Signage Networks - Quividi
- 1. Measuring digital signage networks and using metrics to optimize your impact Olivier Duizabo, CEO, Quividi BroadSign Conference London, June 24th 2013 1
- 2. Agenda • Why measure? • How to measure? • What do you get? • Who’s doing it? • What’s next? 2
- 3. >> Why? How? What? Who? What’s next? Why measure? • Learn what works and what doesn’t Get solid evidence to base your growth upon • Optimize locations Identify places where people pay most attention • Fine-tune your content Know what’s attractive to your key targets • Value your airtime Monetize your screen with proven audience data • Make Digital Signage a trusted media Demonstrate ROI 3
- 4. >> Why? How? What? Who? What’s next? Why automated measurement with face detection? • Precise Passive/unbiased method, 1/10th sec. precision • Exhaustive Measure all of the audience, 24/7 • Real-time Get audience data early on, use it on the fly • Easy to deploy Add the software to your player + a webcam (or IP cam) and you’re done • Competitive wrt. standard methods Costs a fraction of traditional methods 4
- 5. >> Why? How? What? Who? What’s next? Why Quividi? 5 • Industry pioneer since 2006 • 2Bn faces detected, 6000+ locations • The largest customer base with 150 screen networks measured across 35 countries
- 6. Why? >> How? What? Who? What’s next? How does the solution work? 6 A video analysis software running on your digital signage player and webcam, placed on or below your screen, that: • Counts faces turned toward camera Face detection – not nor eye tracking • Classifies viewers by demographics Based on facial traits (hair, skin, chin, etc) • Tracks head movements Knows when a person is looking or not, counts him as one as long as in the field of view • Models movement in scenery Isolates human silhouettes • Uploads data to a back-office server
- 7. Why? >> How? What? Who? What’s next? Demonstration 7
- 8. Why? >> How? What? Who? What’s next? How does it protect privacy & data integrity? • No human seeing any image • No video recorded • No face recognition 8 Video Stream Local SW (local automated processing) Encrypted Audience Data Private Online Back-office Charts Real time audience description made available to CMS • Data redundancy checks • Alerts on anomaly • Rights management per data 3rd party data (eg Proof of Perf reports)
- 9. Why? >> How? What? Who? What’s next? How to deploy it? • Start with a pilot Learn, compare, experience, challenge • Take time to analyze the data • Define objectives Areas of focus, strategic use of audience data, team organization, processes • Plan deployment on next roll out Large economies of scale if integrated into new design • Or build panel Appoint 3rd party to select representative screens and certify your extrapolated data 9
- 10. Why? How? >> What? Who? What’s next? What metrics do you get? 10 Globally # of Opportunities To See # of Viewers Conversion ratio viewers / OTS Average Unit of Audience new industry trading currency For each viewer Dwell (presence) time Attention (gaze) time Gender (male / female) Age class (0-8 / 8-35 / 35-65 / 65+) # of gazes In real time All of the above + Position Distance Currently watching or not
- 11. Why? How? >> What? Who? What’s next? What you get: overviews 11Data courtesy of www.media-reciprocity.com
- 12. Why? How? >> What? Who? What’s next? What you get: insight on peculiar days 12Data courtesy of JR Rail and Ocean Outdoor
- 13. Why? How? >> What? Who? What’s next? What you get: understanding demographic differences 13Data courtesy of Green Room Retail
- 14. Why? How? >> What? Who? What’s next? Media Media Viewer Count Media Runtime (Mean) Play Count Media Runtime (Total) Media Viewers / hour runtime Media #140 10 860 139 sec. 3 019 116:34:01 93,2 Media #436 9 712 383 sec. 766 81:29:38 119,2 Media #336 6 289 115 sec. 1 530 48:52:30 128,7 Media #344 5 694 46 sec. 1 534 19:36:04 290,5 Media #432 5 477 342 sec. 674 64:01:48 85,5 Media #435 5 379 414 sec. 404 46:27:36 115,8 Media #351 4 406 113 sec. 1 468 46:04:44 95,6 Media #6 4 217 94 sec. 2 167 56:34:58 74,5 Media #420 3 454 51 sec. 1 523 21:34:33 160,1 Media #431 2 964 38 sec. 1 513 15:58:14 185,6 Media #348 2 726 91 sec. 1 458 36:51:18 74,0 Media #398 2 656 66 sec. 276 5:03:36 524,9 Media #353 2 509 35 sec. 1 466 14:15:10 176,0 Media #434 2 418 37 sec. 1 036 10:38:52 227,1 Media #402 2 019 60 sec. 252 4:12:00 480,7 What you get: ad campaigns comparisons 14 Media Media Viewer Count Media Runtime (Mean) Play Count Media Runtime (Total) Media Viewers / hour runtime Media #140 10 860 139 sec. 3 019 116:34:01 93,2 Media #436 9 712 383 sec. 766 81:29:38 119,2 Media #336 6 289 115 sec. 1 530 48:52:30 128,7 Media #344 5 694 46 sec. 1 534 19:36:04 290,5 Media #432 5 477 342 sec. 674 64:01:48 85,5 Media #435 5 379 414 sec. 404 46:27:36 115,8 Media #351 4 406 113 sec. 1 468 46:04:44 95,6 Media #6 4 217 94 sec. 2 167 56:34:58 74,5 Media #420 3 454 51 sec. 1 523 21:34:33 160,1 Media #431 2 964 38 sec. 1 513 15:58:14 185,6 Media #348 2 726 91 sec. 1 458 36:51:18 74,0 Media #398 2 656 66 sec. 276 5:03:36 524,9 Media #353 2 509 35 sec. 1 466 14:15:10 176,0 Media #434 2 418 37 sec. 1 036 10:38:52 227,1 Media #402 2 019 60 sec. 252 4:12:00 480,7
- 15. Why? How? What? >> Who? What’s next? Who’s doing it: Amscreen • 6,000 screens across 8 countries in Europe, Africa & Middle East, mostly in gas station stores • Uses audience data to raise CPM and justify ad rates • Announced 100% equipment with Quividi and a standard webcam 15 "It’s revolutionary not because the technology hasn’t been used before but because of the *study’s+ sheer scale and size, and because it’s a permanent, rather than temporary, installation. It’s a positive initiative." Carolyn Nugent, head of digital, Kinetic April 8th 2013
- 16. Why? How? What? >> Who? What’s next? Who’s doing it: Ocean Outdoors • Specialist of large outdoor digital screens in the UK • High definition cameras to track tens of persons at once • Real-time analytics to identify majority gender and target content accordingly • Automated campaign reports with proven audience, by crossing audience data with a proof of performance reports 16
- 17. Why? How? What? Who? >> What’s next? What to do with audience data? • Gain insight by building knowledge at the macro and micro level • Introduce new business models (e.g. pay per view) • Introduce adaptive loops, depending on – Demographics – Behavior – Nb of viewers – Position • Benchmark your network 17 17
- 18. Why? How? What? Who? >> What’s next? The 2012 DOOH Audience Report • Published by the Ministry of New Media, based on Quividi data • A sample of 69 networks • Average week over 6 months • 18 venue types x screen placements 18 Venue type 3D screen High impact Long dwell time Wander by Window screen Global Banking X X Bar restaurant X X Pharmacies X X X Small store X X X X X Superstore X X X X Transportation hub X X X X Global X X X X X X
- 19. Why? How? What? Who? >> What’s next? Typical learning from the Audience Report • 4.4 seconds of attention time globally – Range varies from 1.5 to 9.6 seconds • Long dwell time screens in banks – 447 viewers per day – 8.3 sec of attention time – 42% conversion ratio – Daily AUA of 220 • The older people get, the more attentive 19 0 20 40 60 80 100 120 Attention time Dwell time
- 20. Why? How? What? Who? >> What’s next? What to expect in the future? • Standardization DP-AA guidelines, Methodologies, Media planning software • Embedding Preloaded players, CMS, screens with built-in cameras • More sensors / more insight Global behavior on the premises, frequency of visit/look, hand pick of product… • Integration with other data set Purchases, predictive analysis… 20
Hinweis der Redaktion
- Quividi has customers across 35 countries – in many different venues (malls, hypermarkets, superstores, boutiques, restaurants, transportation networks, gas stations, business centers, etc). making it the clear leader in automated audience measurement.
- Webcam can be any webcam, or more high end IP cameras (for instance with long zooms).Quividi is no eye tracking solution (can’t guarantee if viewers have seen a specific point); rather, it’ll count how many people and how long people were exposed to a certain Point of Interest (here: a screen).The tracking makes sure that a person is counted as one, as long as it stays in the field of view of the camera.The classification extracts image features from the head that are then hierarchized to cluster the face into predefined groups.Simultaneously, the system learns what’s fixed and what’s moving in the scene. It analyses the movement and compares it human silhouette movements.Data can be kept locally (it hardly takes more than 10Mb per month), or uploaded every 30 minutes to the Quividi Back-office
- Video is sent to a local machine for real-time processing. No human sees the image (except at setup time)VidiReports turns image into audience data + saves some monitoring info and uploads this regularly into an online serverUsers access the back-office with their credentials and can’t see data from other clients. Rights make it possible to set who can admin/see what dataOne last use of VidiReports is to pass a live description of the audience to the local CMS player for it to adapt content
- Our recommendation is to start with a pilot. That’s where you can learn about the techno, compare vendors, experience their efficiency and challenge them to your very needs. 3 months and at least 15 screens is generally what we recommend. Once you have all that data, you should sit down with your vendor and analyze the first received metricAt this stage you’ll be able to define a plan and allocate an organization to it.You could either decide to deploy the solution on your all of your future screens: by embedding cameras and going volume, the cost for this audience measurement plaform becomes a low percent of your total deployment cost and can reap in benefits rapidly.Alternatively, you can select a few representative screens to serve as a panel. To have your data recognized, you’ll want to work with research companies on that front.
- OTS = by-passersAUA: this is basically the number of persons, over a given period, which could have seen for sure a clip within a loop. It is computed by dividing the global dwell time of all viewers by the duration of an average loop. More info on http://www.quividi.com/news/090109/pressrelease. Real time data is to be used with applications needing to react to the audience (e.g. change content if a child is standing on a peculiar spot for more than X seconds)
- Data coming with authorization from partner MediaReciprocity (a screen network in office business centers, in the south of France)The chart illustratesCombined metricsRankingsNotable differences between screen: the Atrium screen at the entrance of the building has more viewers but with much fewer dwell/attention times vs screen above elevatorsData displayed By location and aggregatedCould also be grouped (eg all screens above elevators vs all those in corridors)
- Tokyo on March 11th. Just after the tsunami stroke (3:46PM local time), live video was shown in the subway. People started looking longer, and at the same time many people returned home earlierLondon Eat Street (within Westfield Center) on Valentine Day 2013: after 6PM, boys realize they need to rush to grab some present for their girlfriend
- There are clear differences in the behavior of demographic groups: some are more attentive to a specific content Some groups rather show up at certain moments in the day
- Eventually, we want to know which content is the most seen. We can do this whatever the software, provided it can export playlogsThe media in this table are ranked by nb of viewers.However, media viewer count doesn’t mean much without the context of its duration and number of times each media was played.In that case, Media 398 is the most efficientThis analysis could have been done on a specific demographic group.It could also serve to deliver automated reports for a specific ad campaign, just after it ended airing, much like on the Internet.
- Amscreen is the leader in Europe, both in terms of # of screens, # of countries covered (8 and growing) and thought leadership.The key data points for them is nb of viewers, dwell time and conversion ratio.With good data on all fronts, Amscreen has been using that data to raise substantially it profile with big media planners and announcers.We could have mentioned PilotTV as well, which now has over 2000 screens measured in Taiwan in McDonalds, 7 Eleven, Family Mart stores, etc.
- even large screens (60m²!) can be measured (ie we can use HD cams + track tens of people at once) the network operator here utilizes the technology to the most (triggering + campaign reports per clip) Quividi integrates with well known CMS
- Data provides a strong asset to build your competitive advantage uponIf you don’t measure, you can’t improve; Quividi provides information at many different level You can use the data to introduce new biz models You can use it to target specific messages, as we’ve seen with Ocean. Others are doing it on the simultaneous # of viewers, their position, their behavior (eg whether they are staying long, looking away, etc)At last, with data you can start comparing the various locations and sites within your network, but also your complete network with similar ones
- Speaking of benchmark, Quividi will be releasing a complete report this summer 2013 that highlights some key data coming from 69 different networks which have contributed data.Not all « cells » will be covered, but it’s the first audience benchmark to ever be published.
- Here are some of the sneak preview of what you’ll get in that report
- Standardization: much like in other media, there is a need for a standardization here. The DP-AA (US trade association, with sibblings in Europe) has worked on the AUA concept as the industry “trading currency”. There are also initiatives on methodologies (e.g. extrapolations) and trading software that are evolving to integrate such audience data to make trading DS campaigns more fluid. Audience measurement software will come preloaded in the future on players, within CMS software and in all-in-one screensQuividi is working with BroadSign to make this a reality shortly. The industry is evolving towards 3D sensors providing more info on movement, but also with other type of sensors providing insight on visitors habitsFace recognition however, is likely to remain un-tolerated by shoppers in the years to come and banned by data protection agencies With audience measurement, Digital Signage comes into the age of Big Data. Mixing that data with other will provide new opportunities for network owners and advertisers