How Analytics Tools Can Give Digital Signage Networks Superpowers
July 7, 2023 by Dave Haynes
Low-cost sensors and easily shared and integrated data sources are taking much of the guesswork out of on-premises digital signage, making it possible to finally realize a long-held goal of putting the right messages on the right screens at just the right times.
But analytics platforms that characterize audiences and venues are not just about the timing and targeting of on-screen messaging. These technologies, when married with the right software management platforms, are informing users how a venue works, and how it should be staffed and operated. They’re also shaping and triggering on-screen content based on conditions.
Long-term analytics can establish patterns that better inform where to put digital signage displays and what’s on them, based on characteristics like foot traffic flow, demographics and time of day and week. Real-time analytics can go all the way to providing data triggers that optimize content to the audience, at that moment.
For example, QSR giant McDonald’s is using real-time analytics technology to optimize and adjust the digital pre-sell promotion displays and menu screens in its drive-thru lanes, dynamically adjusting what’s visible based on sensors and systems that can characterize ordering tendencies vehicle by vehicle. A camera-based, AI-driven based license plate reader system may pick up that a motorist entering the drive-thru tends to order specific items that include kids meals, so the menu and promotions can be optimized on the fly to highlight upsell items.
In a very different example, a large footprint mass merchandiser can look at shopper analytics and rethink where screens are going to be most optimal, but also where staff needs to be re-positioned through a day. It might be hard to know anecdotally, but analytics can show that a specific department is typically busy on weekday mornings but sees a big drop-off in the afternoon. So a store manager can shift some sales associates to other parts of the store.
And different again, an airport can use crowd analytics to monitor security screening areas – counting line lengths and density, and reporting estimated wait times on nearby digital signage displays, as well as notifying and guiding travelers when new positions open.
So just what are we talking about with analytics?
For a very long time, analytics was an analog exercise. You may recall people sitting on stools at store and mall entries, using hand-held clickers to count how many people passed by. There were elementary technology versions that used things like light beams to count traffic by recording the number of times the light beam is tripped.
These days, low-cost, low-profile sensors are providing much richer and more accurate insights. There are numerous technologies being applied, but the main ones used in digital signage involve either cameras or mobile phone sensors.
AI and Cameras – Artificial intelligence is just starting to be a mainstream discussion point in tech circles, but it has been a part of digital signage for more than a decade. Cameras mounted at digital signage displays pass their video feeds through AI-based algorithms to do near or real-time pattern detection. The technology is also called computer vision, and it is based on machine learning. These systems can analyze faces looking at a screen within a certain zone, and use the geometry of faces to indicate attributes like gender, age range and even emotion (is the viewer happy or sad?).
Vendors like Quividi have, by necessity, gone to great lengths to reinforce that what they do is anonymous and very different from facial recognition systems that can recognize specific people. Numerous projects that have included anonymous video analytics have run into controversy, or even been shut down by operators, based on public objections about consumer privacy being compromised.
Most (and probably all) of these systems marketed and used for digital signage and digital out of home advertising networks meet privacy guidelines. They don’t match captured faces against any database of faces and names, and the video feeds that pass through the software are then discarded.
Sensors – Other companies are logging smartphones that pass within defined zones, using these handheld super-computers as a proxy for people. Because the great majority of consumers go about their work and leisure days with a smartphone in a pocket, purse or hand, it’s an effective way of measuring the presence and movement of people, and characterizing things like occupancy, dwell time, unique visitors, and traffic flow.
Another company, InReality, is using a radar-based Internet of Things (IoT) sensors running computing algorithms that are designed to only detect human shapes.
As with computer vision, companies taking this approach emphasize the fully anonymous, privacy-focused nature of their platforms. The advantage of sensors is they have less of a stigma than camera-based systems that prompt detractors to raise Orwellian “Big Brother” objections and concerns.
Analytics In The Field
Here’s a range of different ways analytics are being paired and applied with digital signage technologies.
Load-Balancing Venues – A Detroit company called Waittime developed a proprietary analytics platform that uses cameras positioned around the entry and concourses of large-footprint sports and entertainment venues. The camera feeds video streams through an AI-driven system that estimates and reports on wait times for the venue’s gates, concession lines and washrooms, visually that on screens in view of ticketholders. By showing where lines are shorter
Retail Venue Performance – Analytics platforms used by retailers deliver a wide range of insights on how stores are working and performing, shifting the understanding from educated guessing to hard data. Platforms can provide tools like dashboards that visually show key performance indicators like foot traffic, engagement, dwell time and conversion rates. Systems deployed across different stores and regions can get head office operators beyond gross sales and into insights on how different stations and initiatives perform, with variations as granular as time of day.
Ad Targeting – Digital signage technologies drive the digital out of home ad market, from digital posters in malls to big LED billboards on roadways and crowded urban plazas. The tissue brand Kleenex worked with an analytics firm to pinpoint optimal locations and screens for a U.S. campaign, mashing up purchase intent and consumer spending data, location intelligence third-party cold and flu data. The analytics data precisely identified areas, within a one-mile radius, where there were higher percentages of likely buyers “experiencing cold and flu triggers.” The result was a return on ad spend almost twice the benchmark for ads in that category.
Where Analytics Are Going
Artificial intelligence has seen a massive spike in attention and understanding in the past year because of the emergence of ChatGPT, but it is a technology and sector that has been around for many years.
Numerous technologies – including the LiDAR laser imaging used for applications like autonomous vehicles – have been applied to venue and crowd analytics. But the real changes and advancements that will likely shape the future of analytics are with data integration and the large language models (LLMs) that are now driving AI toolsets.
The wide and relatively easy, but secure, access and sharing of data between different business and facility management platforms means it is far easier to track, analyze and use real-time and long-term information to inform planning and decisions, as well as trigger messaging in real-time.
LLMs like ChatGPT, driven by super-computers, can hugely streamline the development of insights and guide much more informed decisions. As computing became the backbone of industries like retail and food services, operators were sitting on a lot of data – like transactions and operating KPIs – that they could really make sense of and exploit. ChatGPT changes all of that, providing summaries, charting and whatever is requested in minutes, as opposed to months or years.
Generative AI is also empowering digital signage users to marry analytics data with hyper-targeted, dynamically-created messaging. Tools are emerging that can produce static and motion messaging on digital signage and DOOH screens, on the fly, that are tuned to attributes like geo-location or store type, and personalized to the known local characteristics of the area.
With many options available, some of them very different, it can be difficult for end-users or digital signage and pro AV solutions providers to determine what to use.
The best first step is working with a company – like Sixteen:Nine’s owners Spectrio – that has deep experience in customer engagement solutions for business, and can help assess the need, the customer and venue dynamics in play, and an optimal plan that includes a sense of outcomes and success measures.