Last October a New York based start-up called Placemeter won the Alpha pitch competition at the Dublin Websummit. It seemed like a fair winner considering the team has the potential to disrupt the way that we make daily decisions on what places to visit. Would you still walk for five minutes to the nearest Starbucks if you know beforehand that it will take 20 minutes before you get your cup of coffee? Would you still pay a fifty-dollar entry ticket into a club if you know beforehand that the club is almost empty? Placemeter provides real time information on how busy places are at a particular moment in time. The company uses vision algorithms to analyze video streams recorded from security-, traffic– and city cameras and turns those videos into structured data layers. If these data sources dont cover a certain area, then they use crowdsourced data collected through old smartphones suctioned to the home windows of their community members.
The insights Placemeter delivers are impressive but at the same time the data collection method being used might intimidate people and raise privacy concerns. Scanning people through surveillance cams and smartphones still sounds quit freaky to many and might even attract the attention of the NSA. Nevertheless, Co-founder and COO Florent Peyre said in a previous interview that he is not worried about privacy issues because all videos from smartphones are only saved for 24 hours and no identifiable information is even shared with Placemeter. For now, lets assume he is right and we should all prepare for a future where companies can freely use information extracted from all these millions of public data points scattered around cities. When the Placemeter team succeeds in realizing their desired future of having people check their smartphones for estimated waiting times before actually leaving the house, then regular companies should prepare for altering certain aspects of their marketing strategy. It will open the door to some innovative marketing approaches based on the real-time information they provide.
On its own Placemeter is merely a provider of real time information. To realize the true potential of the technology the team has already partnered with providers of weather forecasts data, location data, social data and data about upcoming events. All these different data sources combined make a rich big data pool used to make accurate real-time predictions on how visitor numbers will change over time. During the Websummit pitch, CEO Alexandre Winter gave a good example of how they use big data to make predictions on how many people will be at the beach during a particular part of the day. On the presentation slide this prediction was integrated with Google Maps search results. To make the beach example prediction they combine traffic data with weather forecasts, patterns in foursquare check-ins, beach related tweets, possible beach events etc. Considering most of the times you make decisions on which place to visit in advance, these predictions add a lot of value from a consumer perspective.
Now lets go back to that nightclub example I gave earlier on. I assume a large amount of people wont actually pay a fifty-dollar entrance fee knowing the place is empty, right? Instead they will use Placemeter information to check the current occupancy rates of their other favorite nightclubs and move elsewhere. Above that they can check at what time these other clubs are most likely to become busier or calmer. In most instances the upheaval caused by Placemeter will be bad news for those clubs that are already struggling to get people inside. But the clever marketers will find ways to turn this rising threat into an opportunity. Imagine seeing a real time ad being displayed on a New York nightlife app that offers the first 100 people to enter the club a 50% discount. This will help the nightclub to get that much needed initial group of people inside quickly. Nightclubs could even take it a step further and move entirely to a dynamic pricing mechanism where entrance prices go up once more people are inside. A nightclub with a capacity of 500 people could for example develop five different pricing scales for each badge of 100 visitors that enters. In the airlines industry a pricing mechanism like this has been used successfully for many years already by budget airlines. Of course nightclubs could also gather their own visitor data without Placemeter intervening, but that is not the point here. The game changer will be that the data will become publicly available across a wide variety of platforms (e.g. Yelp, Google and local deal sites) so people actually use this information to make an informed decision on where to go. If that phenomenon truly kicks in then the option of dynamic pricing might become available to a wider range of industries.
Placemeter data can also be harnessed for doing competitive analysis. Instead of spending all day counting the number of people walking in and out of your competitors stores, you will have instant access to way more accurate and reliable data on your competition. You know the real time occupancy rate of your competitors, which days of the week they are busiest and what time of the day they handle the most customers. The team even claims their technology is able to determine bounce rates. It remains a bit unclear how exactly they define a bouncing customer, but I guess those people that immediately leave the store without buying anything are being tracked. All of these competitive metrics provide a basis for new strategic insights on how to outcompete your rivals. Furthermore, with so much more competitive information up for grabs, the content of marketing messages could easily turn more intense. Imagine a local coffee shop trying to steal customers away from the neighboring Starbucks giant by pointing out the shorter waiting time for their cup of coffee. They could for example send out a tweet accompanied with a screenshot of the Placemeter forecast that looks something like this: Save 20 minutes of waiting time this #lunchbreak and give the #bestcoffee of #Midtown #Manhattan a try.
Yet another way to use Placemeter data is for estimating the number of billboard impressions. Their vision algorithms can track exactly how many people are passing by a billboard during a particular moment in time, at what speed they are passing by and if they are speeding up, slowing down or move with a constant pace. Common sense says people are more likely to actually see your ad at those places where people move slowly and/or slow down. Placemeter will make it easier to find those sweet spots for billboard ads.
Previous examples already show that Placemeter could have an impact on a wide area of businesses and I am sure there will be even more ways imaginable to use the technology. For this reason it seems remarkable that thus far the start-up only raised a rumored $143k in angel funding. Maybe VCs are still a bit concerned about privacy issues surrounding the company. Or after winning that last pitch event the team is going for a higher valuation. Of course it also remains to be seen if the startup is actually capable of reaching out to the mainstream crowd. But if they do succeed in that, then this new data source might just be a serious marketing game changer.
