Google Tracking How Busy Places are by Looking at Location Histories

 

Getting Ducks in a Row
Getting Ducks in a Row

Google Maps helps people navigate from place to place.

In order for it to work effectively, it’s helpful if it can track the location of the device that someone may be using to help them navigate.

It’s interesting how Google tracks your location. I’ve noticed that after I take a photo near a business, Google will sometimes ask if I would like to upload that photo to the business listing for that business. Sometimes the photos aren’t relevant to the business I’ve taken them near, such as a photo of an Agave Plant that I took near a Seaside Market in Cardiff-by-the-Sea, California.

Google seems to like the idea of saving location history for people who might search for different types of businesses, and a recent patent that I wrote about described how Google might start using distances from a location history as a ranking signal (as opposed to a static distance from a desktop computer.) I wrote about that in Google to Use Distance from Mobile Location History for Ranking in Local Search.

If you think about Google tracking individuals’ location histories in a different way, how else can that tracking history be useful to people? You may have noticed that Google now sometimes shows how busy a place might be a different points in the day. That is from tracked location history aggregated. I saw someone ask about this in Twitter today, and it set me trying to find a patent from Google that described the details of how Google might be tracking how busy different businesses might be. I found one.

The patent I found tells us that it is about:

The present disclosure relates generally to determining a latency period at a user destination, and more particularly to methods and systems that rely on user-location history, such as fine-grained user location data, to determine the latency period at a destination of a user. The present disclosure also relates to using latency period data in a variety of applications, including generation of a shopping route for a user.

Google is tracking how busy different businesses are based upon those user locations.

busy-times-pizza-google

It tells us that being able to provide someone with planning details about a shopping trip can be useful, such as how long the trip to a business might be, as well as how long they might spend there. If someone asks for a chain business, knowing how busy the location is can also be helpful to a user, and the process described in this patent attempts to answer that problem as well. I hadn’t thought of how helpful it could be in the context of chain businesses until I read the patent:

While knowing the travel time and distance to a location is often helpful to a user, the user is left without knowing how busy the nearest location is or whether other, nearby locations are less busy. For example, the user does not know whether visiting a chain location that is slightly further away—but less busy or less crowded—may take less time overall than visiting the chain location that is nearby. Thus, based on travel time to the destination alone, the user may spend more time traveling to and visiting the nearest location than the user would if traveling to and visiting a location that is further away. And in some instances, a user may not care how long it takes to get to a point-of-interest. Rather, the user may desire only to know how long the wait is at a particular point-of-interest or how long it will take the user to pass through the point-of-interest, such as through a checkout line at a retailer. In addition to knowing how long a trip will take, in certain instances a user may wish to know the fastest route or alternate routes. For example, a user with a specific shopping list may desire the best route (or alternate routes) for obtaining the products on the shopping list.

Other information that might be provided include things like wait times at restaurants and how long it is taking people to check out at grocery stores,

Interestingly, fine-grained location history tracked could include the user device in a checkout line at a grocery store, or at the entrance area of a restaurant, or in a line at an amusement park. So, times spent waiting to buy groceries or waiting to be served a meal or time spend waiting for a ride could be reported to others who might consider going to that grocery store, or restaurant or amusement park. Mobile location information history looks like it could be useful.