“Location, location, location,” as the saying goes. But who knows exactly where the right location is? For retailers, real-estate developers, restaurant owners, hotel directors, and advertisers, knowing where to locate their new store, building or sign could be the difference between success and bankruptcy. This is not a decision to be taken lightly or on a whim; rather, it should be supported by data and the best one is car data.
The Olympics, for example, are a good case study for poor retail location decisions. Governments and companies typically invest large amounts of money in building infrastructure, hotels, and restaurants that will accommodate the vast number of sports fans attending the events. However, these are usually no longer in demand after the games, leaving these entities in large debts.
Location Intelligence through Data
Data can attest to the presence of crowds in certain areas, and the services they need. By understanding how many people are situated where, at which times of the day, where they came from and where they’re going to, and how long they stayed there (anonymously), intelligent assumptions can be made as to what groups of people want. This is called location intelligence data.
Accommodation and restaurants
For example, if thousands of people drive from an airport for 45 minutes, stay at a location overnight and return the next morning to the airport, it’s probable that a hotel around the corner from the airport will be in demand and successful. Such a hotel will also need a restaurant, a gift shop, a spa, and a taxi service. It will also need suppliers of linen, cleaning services, beverages, and more.
Or, if the advertisers of a mall can see that there is heavy traffic throughout a long highway up to a competing mall, their marketers can respond strategically. They might place an advertisement for their mall on an intersection on the way to the competing mall, leading back to theirs. After placing the advertisement, monitoring traffic overtime could measure campaign effectiveness.
As a third example, let’s look at a marketing research firm. Such a company can use data to track and identify market trends. For example, if delivery trucks leading to a shopping center grow in frequency, it can be assumed the center is more successful than in the past and that business is growing. However, if across the US fewer trucks deliver goods over Christmas compared to the previous year, this might be an indication of an economic slowdown approaching.
City infrastructure and society
Finally, location intelligence data can be used to improve infrastructure. If aggregate vehicle data shows how much school districts are crowded during the beginning and the end of school days, a new system from dropping off and picking up children might be implemented, or accessibility could be improved.
In the case of hospitals, crowded highways that stall newcomers for minutes or even seconds are crucial. If data shows that the ways to the hospital are congested during certain hours, a new side road might need to be paved, or an hourly restriction put in place.
Automotive data adds location intelligence value
Traffic data from connected vehicles is a new and unique valuable data layer that is now becoming available. By analyzing connected car data attributes, retailers, real-estate managers, and advertisers can understand customers’ spatial behavior better and identify the best location for businesses and operations, like strategic store placements or targeted campaigns. This layer of automotive data is enough on its own, but when added to other data parameters and existing datasets, it becomes even more powerful by adding a holistic understanding of behavioral patterns and adds extra value to optimizing locations.
To utilize this data into decision-making, car data attributes like GPS, fuel level, vehicle model, odometer, ignition on/off, and more can be integrated into existing data systems and be part of location analysis. Trip data can be presented on a map to enable analysis on its own. These options are available through Otonomo. Use data to make the smartest, most informed location decisions by implementing traffic and automotive data as part of your processes and platforms.
To learn about car data options for location analysis, contact us.
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