Can Understanding Hourly Car Traffic Flows Improve Store Traffic?

Mobility data provider Citilabs has created what it claims is the first comprehensive map of hourly traffic flow in the U.S.

Dubbed Streetlytics, the data visualization tool leverages information from billions of data points to measure and paint what Citilabs CEO Michael Clarke says is the “most complete picture of the moving population.” In addition to hourly details of where traffic is coming from and going to, it also shows traveler demographics based on derived home locations.

Asked if there is any value for either multi-location businesses or even independent small-to-medium sized businesses from Streetlytics’ hourly traffic map, Clarke emphasized that “Streetlytics is much more than an hourly traffic map.”

“It does provide the directional volume of vehicles and people moving along every street in the US by hour and type of day (weekdays, Fridays, Saturdays and Sundays), but it also tells business where those people live (and the associated demographic information such as income, size of household and many other attributes), as well as where those people are coming from and going to and why they are traveling (commuting to work, for example),” Clarke said.

Streetlytics also compiles the routes that people take, he added. So, for a business, let’s say a doughnut chain, Streetlytics can identify the road segment where you find the maximum number of the target market that does not currently drive within, say a quarter-mile, of one of their existing locations and/or their competitors.

“Nothing like that has existed until now—determining location based on the flow of the target market down the streets, not simply based on where the target market lives,” Clarke said.

In terms of who Streetlytics data, which hows the intensity of traffic volume on roadways in the continental USA by hour for an average work day, the underlying data and insights are applied today in advertising, insurance, real estate, retail, investment and new mobility solutions.

Hugh Malkin, director of Business Development, offers this explanation of the tool’s value: “Since Streetlytics provides the routes used for every vehicle trip, it is also a great base line or control to measure the impact of new technologies around smart cities on every road in the US. These averages can help businesses, startups, and governments spot anomalies in the new technologies they are testing to help them learn and get better faster.”

“Another example of how this information is important is that it tells businesses not only the number of people that pass in front of or near their location but the detailed characteristics of those travelers,” Clarke noted. “That is important information for helping business to align their product breadth, depth and assortment with the drive by population and for use when comparing against in-store transactional data.”

Smart Cities On The Road

The information from Streetlytics could help spur projects around the “smart cities” concept for businesses, tech companies or municipal planners, Clarke said.

In explaining the underlying value of Streetlytics to those constituencies, Clarke offered this analogy: If you were considering opening a restaurant, you would want to understand the market for your restaurant.

The big question you would have would be “Does the demand exist and does it match with what your restaurant will serve?”

When planners, businesses and tech companies consider where to put a road, a transit line, a bike path or, say, to initiate some kind of new mobility service or smart concept—they really have no clear understanding of the demand—how many people are going to and from every part of the city, by hour by day, Clarke said.

“Streetlytics provides a comprehensive view of travel demand. It tells a provider or planner how many people travel from say Riverdale to Tribeca, or Hoboken to Wall Street hour by hour and the characteristics of those people,” he said. “That’s valuable information for planners who want to have a clear understanding of not just where they have traffic jams or crowded subways, but where those people are coming from and going to so that solutions can be found that serves that market and alleviates the problem.”

“In the same way, it provides a clear understanding of the market for private enterprise to serve that demand with evolving mobility services – does this make sense for us to create such a service – what is the size and characteristics of the market?” You can think of many examples where Streetlytics can improve the ‘smartness’ of cities such as much more efficient ways of operating services and infrastructure on a daily basis, to where you should spend your maintenance budget to give the best bang for the buck,” Clarke said.

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How Intel’s Mobileye And Esri Plan To Make Smart Cities Into ‘Safer Cities’ For Transportation

Mapping analytics provider Esri is working with Intel’s Mobileye, a provider of advanced driver-assistance systems software, to combine the former’s location analysis and visualization with the latter’s Shield+ product to help shape transportation safety programs for “Smart Cities.

Mobileye’s Shield+ will stream road safety data retrieved from city bus fleets into Esri’s ArcGIS platform, where information such as pedestrian and cyclist detection in blindspots can be viewed on the Intel company’s Smart Mobility Dashboard.

Shield+ alerts will be updated to the dashboard in real time, providing a city-wide view of pedestrian and cyclist safety. For example, city bus drivers can receive alerts about “imminent hazards” such as a bicyclist or pedestrian coming out of a driver’s blind spot seconds before a potential collision.

“Esri is excited to collaborate with Mobileye for an offering that brings us so much closer to creating safer communities,” said Jim Young, Esri head of business development. “Making spatial data available to governments to improve safety and overall quality of life is an important step.”

Intel Mobileye’s Shield+ with Esri’s location analytics and data visualization can help buses eliminate “blind spots” and provide more traffic safety.

“Through this collaboration with Esri, we are able to provide a game-changing product to cities and mobility providers,” adds Nisso Moyal, director of business development and big data at Mobileye. “By enabling direct uploading of geospatial events from Shield+ fitted to municipal buses and the like to the Mobileye Smart Mobility Dashboard, cities will be able to anticipate and help prevent the next collision, while in general managing all of their assets much more efficiently.”

As Young and Moyal note, the Shield+ project is another way of highlighting how location data is factoring into — and shaping — the future of Smart Cities.

GeoMarketing: What Is “Shield+”?

Jim Young, Esri: I like to think of Shield+ as a set of sensors that are continuously moving around a city, collecting data. While today the sensors are focused on things like saving lives through detecting pedestrians in the street, tomorrow, these sensors could be focused on collecting, reporting, and analyzing any type of road information they collect.

Think about if a series of vehicles passed over a major pothole. If sensors are installed, this could automatically trigger a dispatch to public works in order to repair the hazard quickly. This data, or other types of data, including construction alerts, traffic or weather-related hazards, could also be fed to other vehicles in the fleet to improve awareness in the moment and be analyzed later on, to continue creating smarter cities that provide the best services for their communities.

How did this collaboration between Intel/Mobileye and Esri come about? Was there a previous connection between the two brands? 

Jim Young, Esri: The connection came about through several mutual partners through Esri’s work in Israel. While there has been some previous connection with Intel, this is the first initiative between Esri and Mobileye.

Nisso Moyal, Intel Mobileye: We are excited to work together, as this cooperation provides cities and governments with a tool to make their cities smarter and safer for road users.

Who will this collaboration serve? Municipal governments? Automotive manufacturers? Public transportation authorities? Urban planners/non-profits outside of government? Brands? All of the above (if so, is there a hierarchy?)? 

Jim Young, Esri: The initial collaboration with Shield+ will serve city planners, DoT’s, transit authorities and transportation planners.  We look forward to later iterations expanding to serve a broader customer base.

Does Mobileye’s Shield+ have any other mapping or tech partners beyond Esri? 

Nisso Moyal, Intel Mobileye: Mobileye Shield+ offers increased awareness for operators of long vehicles, and provides vital seconds to react with real-time alerts. Drivers are given an intuitive experience and fleet managers have seamless telematics integration. The system is mounted inside the vehicle’s tab with a tolltag-sized sensor on the windshield and an EyeWatch display on the dash. The Mobileye Sheild+ system uses up to four individual sensors for improved blind spot detection in urban environments. The two level warning system and minimal false alerts achieved by Mobileye assure the highest level of driver attention whenever an alert is delivered including:

  • Forward collision warning: alerts when a collision is imminent with anything ahead of the fleet vehicle;
  • Pedestrian & Cyclist Collision Warning – Alerts when a collision is imminent with a pedestrian or cyclist within the vehicle’s front danger zones;
  • Lane Departure Warning – Alerts when a lane deviation occurs without proper signal notification;
  • Headway Monitoring and Warning – Alerts when the following distance from the vehicle ahead becomes unsafe;
  • Speed Limit Indicator – Recognizes speed limit signs and alerts when the vehicle exceeds the posted limit;

Jim Young, Esri: There are telematics partners but no other mapping partners as part of the solution.

How does Esri’s visualization tools enhance Shield+?

Jim Young, Esri: Esri’s visualization tools enable the customer to see patterns beyond what a single bus can see with Mobileye vision. The technology creates a feedback loop for cities to learn and improve, by turning their existing fleet into a network of sensors that can map the areas of the city where pedestrian safety can be improved.

Shield+ in action

How do you see this collaboration aid the growth of smart cities? 

Jim Young, Esri: By attaching Mobileye sensors to existing fleets, cities can begin to lay the digital tracks for their autonomous future which will create safer roads.  The bundle allows cities to see patterns that were previously invisible. By mapping the data and events that Mobileye vision sensors see across an entire fleet, areas of the city that present a risk to pedestrians and cyclists are revealed and can be improved through improvement initiatives and more informed transportation planning.

How does “asset mapping” work within the context of this collaboration? And do you see any benefit for local businesses from this tool? 

Jim Young, Esri: The initial offering between Esri and Intel Mobileye is focused on improving safety. Future iterations that take advantage of more capabilities of Mobileye vision could benefit asset mapping and be of great benefit to other aspects of cities and local businesses.

How do you expect the project to develop? Any initial expansion plans for 2018 that you can preview? 

Jim Young, Esri: The project will initially be focused on visualizing Mobileye data on an Esri map. We plan to offer Esri customers the ability to see other map layers alongside the Mobileye data, such as transit stops, bus routes, weather and accident data, for example, for additional visualization and analysis.

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Does Location-Based Advertising Have A Viewability Problem?

Location-targeted mobile ad sales are expected to rise from $9.8 billion in 2015 to $29.5 billion by the end of 2019 — but with that rising demand comes greater expectations about ROI, attribution, and accuracy.

The issue of geo-data accuracy has always been a thorn within the great promise of location-based advertising to bridge online and offline, desktop and mobile (and we first outlined the problem here back in 2014).

Placed, which was acquired by Snap this summer to provide attribution services for Snapchat ad clients,  is the latest geo-data specialist to offer guidance on the matter of location analytics accuracy in a report, Accuracy & Bias In Ad Exchange-Derived Location Data.

The analysis for the report is gleaned from the company’s primary product, Placed Attribution, which is based on an audience of over 150 million device generated over 140 billion latitudes and longitudes on a monthly basis.

Thanks to its extensive alliances with dozens publishers, networks, and demand side platforms, including ncluding IPG MediabrandsDigitasLBiHorizon MediaTapadDataXuDrawbridge, among others, Placed’s data sources have grown to include first and third party data as well.

As Placed CEO David Shim describes it, location ad accuracy is a viewability problem.

  • Average location accuracy was 4 New York City blocks
  • Only 1 percent of locations were accurate enough to identify a store visit
  • 80 percent of bid requests with location occur when they are in-between visits, with a good portion of the visit based impressions occurring at home

“With location accuracy not in the forefront of the viewability conversation, bad players have been able to capitalize,” Shim said. “Placed’s recent research and findings arm advertisers with an understanding of the location landscape that has been missing to date, independent of media.”

The Viewability Issue

In the larger ad tech sense, viewability has been a considerable cause of mistrust between buyers (brand and agencies) and publishers. In essence, viewability refers to whether a display ad placement was seen by an actual person or if it fraudulent ad impressions were generated by the “visits” of bots.

“In the near future, marketers will require a viewability-like metric to gauge the accuracy of location used for media, targeting, attribution and analytics,” said Benjamin Bring, VP, Mobile Media Director at Ansible, in the Placed report. “To date, the siren’s song around the potential of location has been able to drive the early adoption, but scale won’t come until the industry delivers a standard verification solution.”

“Viewability in location is directly aligned with accuracy,” Shim told GeoMarketing. “In an ecosystem today, where anyone can claim any location, it is important to not take location at face value, and continually verify the source of the location.”

‘Not All Geo-Data Is Created Equal’

Among the most difficult issues for marketers who want to use location data comes down to the sourcing of that information. Those sources, or signals, can come from a variety of channels, including GPS/satellite, wifi, computer IP-addresses, cell phone towers when it comes to pinpointing the specific lat/long the device accessed. Panel-based check-in services  like Placed’s— the location-based ad equivalent of a Nielsen diary that contains what a viewer watched on TV — are another popular avenue for accessing location data.

As programmatic advertising has become mainstream, the general purpose for for location advertising is two-fold: there’s the desire to provide real-time ad targeting as well as developing a greater understanding of consumers according to the places they go that provides more actionable insights than mere demographics (age, gender, household income, etc…) can offer.

Placed also leverages a proprietary behaviorally-derived measure of store location that it calls ‘Survey Geometry.’ Similar to the store geometries that measure the outline of the building or parcel (i.e., car lot).

One of the problems with a source like bidstream data is that its not a persistent signal like wifi or GPS. Bidstream data often depends on a person opening an ad on their phone while they’re in a specific place. The publisher whose ad is opened in that moment receives the data and passes it on to the network or vendor that placed the ad. If that person who saw the placement then goes to a store that was advertised, that visit counts as being “attributed.”

Of course, a phone’s location services records signals from hundreds of places in a given day. The odds of the information being attributed coincidentally (i.e., incorrectly) is a challenge that comes with real-time data platforms.

Quality bidstream location data, like those coming directly from publishers, is generated from the mobile device native location-based services, which use a combination of GPS, wifi, and other signals. That data is then pulled by the app developer via the phone’s SDKs. The process is the same whether the app sends location data via the exchange (bidstream) or direct. Regardless of a location data’s origin, bidstream or direct from publishers, it’s important to filter data and curate sources as well as recognize and filter low-precision signals.

“Not all data is created equal,” said Joao Machado, director of Mobile at OMD, in the Placed report. “You have to be very diligent in determining the accuracy of location data coming off the exchanges.

“Quality beats scale all day long and 1st party data is the gold standard in quality of location data,”Machado added. “A horoscope app dumping location data into an SSP before landing in the exchanges is the example of what leads all of us to scratch our heads around lack of value around so much of what goes on in the market.”

As we noted above, the average location accuracy Placed found was within four blocks — and only 1 percent were able to identify a store visit. That all sounds pretty dismal and much less reliable than the image a user has when looking at their own location on a map and seeing the accuracy within 3- to 20 feet on average, according to industry sources we’ve spoken to.

While it’s a given that location accuracy is, all over the map (pardon the pun), is this a matter of the difference of location signal sources, such as GPS versus cell towers versus wifi versus bidstream data?

“It’s a combination of factors,” Shim said. “When measuring directly from the device, location signal can vary based on a number factors include environment.  This said, the primary source of location inaccuracy is bad players on the exchange that treat cell tower location the same as GPS, map IP address to latitude and longitude, or commit outright fraud by applying a latitude and longitude to a non-location based impression.”

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How Brands Can Have Authentic Conversations In ‘Smart Cities’

As interconnected rise of shared mobility and connected intelligence has led to the development of “smart cities,” major urban centers are using technology like sensors, smart lights, and digital displays to collect and analyze data. But perhaps one of the most interesting factors in the development of smart cites is the arrival of free, high-speed wifi in public urban spaces — bringing with it significant opportunities for marketers and consumers alike.

As the internet proliferates within smart cities, it’s effectively “reinventing information in a public space,” explained Colin O’Donnell, CIO at Intersection, in a session at Cannes Lions — giving brands, public service [entities], and more the opportunity to respond to how people behave in real time.

“We’re at a moment in advertising where personalization, connecting to someone’s life, is becoming more important,” O’Donnell said. “And then we have this rise in smart cities happening at the same time. That’s huge.”

For its part, Intersection has launched its LinkNYC initiative, replacing outdated phone booths in New York City and turning them into “digital kiosks” with free wifi — which can both take inputs (anonymized data) and push outputs, like real-time infrastructure updates or, yes, a brand’s message.

But now that this capability exists, the questions is: How can brands have authentic conversations in cities — without being viewed as one more interruptor during the daily commute?

  • Use the city as a conversation starter: As always, it’s crucial to focus on user experience: What is the journey that someone is on? Obviously, this can be complicated — but by using real-time data based on where users are accessing the wifi, marketers can customize messages based on time of day (is it rush hour?) or contextual location (is there a train delay nearby?) For example, Intersection ran a campaign for Miller-Coors based on LinkNYC wifi points that informed consumers near a delayed train where their closest bar serving Miller-Coors was — so they could wait out the delay with a drink rather than on a hot train platform.
  • Think outside the box: O’Donnell emphasized the need to ask, “what needs to be done [via technology in smart cities]  that can’t be done already?” This means that it doesn’t truly add value to use mass wifi to simply push out generic banner ads; instead, as in the first example, its about responding to a city’s circumstances in real time. Is this a central tourist area where someone might need help with directions? Or are there a line of locals waiting outside a bar for a concert? This makes a big difference; then use this information to think creatively about what kind of services people might want.
  • Marry geo-data to brand data: “At Intersection, our approach is about marrying the [real-time data we have] to the data a brand already has about its consumers to create something meaningful, useful, entertaining,” O’Donnell said.  “The advertising essentially has to be a product.” In other words, it takes viewing a combination of data points holistically to create messages that are more than ads; success likes in building something so interesting or informative that it adds value in and of itself — not just sells something.

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