By: Ori Konstantin

Sense360 is a market research company that helps the largest food service and retail companies in the world use data to make consistently great decisions. Our platform helps brands understand consumer behavior so they can better understand their customers, their competitors, and the marketplace. For example, a restaurant could use our platform to help determine what type of menu consumers enjoy the most.

Transparency is one of the core foundations on which we’ve built Sense360, and for that reason, we want to do a deeper dive into exactly what data we collect and why we collect it.  It is of course no secret that our data is used for two very specific purposes: 1) to analyze foot traffic data and anonymized consumer transaction data to create research and reports for our customers, and 2) To analyze survey responses to provide the same reports, which in some cases contain de-identified survey responses. With that said, let’s dive deeper into what types of data feed our market research and why they are collected. In order to better understand what’s driving real-world behavior, the main three types of data we collect from users are: 

  1. The places people visit (which we infer from a variety of types of information)
  2. Survey responses   
  3. The list of apps installed on a phone (currently Android only)

The three types of data are integrated into different reports, dashboards and custom studies to answer questions that businesses face every day. Sometimes we also power those products with trends we notice in data we receive about individual users from third parties. For example, a customer might share information with us about which users of their app made purchases on a particular day, we may receive similar insights from other partners.  

It is important to note that Sense360 shares de-identified survey responses at the individual level, and that all our other data is shared with customers only in and anonymized and aggregated format. So, for example, we might tell that customer that 30% of the users that purchased from them on a particular day had visited a competitor in the preceding 30 days. We will never sell a user profile or any other data element linkable to an individual user, as it doesn’t align with our privacy guidelines. When we conduct a survey on behalf of a customer, we may share individual survey responses with the customer, but we first remove information that would permit the customer to identify the individual.

Sometimes an app publisher will engage us to collect device-specific data in the publisher’s app, and although we provide this data and some related analysis to that publisher in device-specific form, it’s the publisher’s own data, so this is not like a sale. You can read much more about how we think about privacy here: Sense360 Privacy.

In order to collect the above three main data types, we partner with a network of almost 100 mobile apps across both iOS and Android. We help improve the experiences in these apps in a variety of different ways such as enabling user surveys, enabling user rewards, reducing the need for advertising by paying the app developer, and powering analytics to help apps better understand their consumer base (for example, helping a coupon app understand which brands would be the most relevant to provide coupons for).  In exchange for helping improve the app experience, we collect data and share it with customers and partners  in two ways only: 1) individual de-identified survey responses, and 2) in an aggregate and anonymous form for all other data points. 

We leverage this network of apps to understand the places people visit by collecting GPS and other sensor data such as barometer, accelerometer, and nearby wifi networks. All of this information is collected for the sole purpose of understanding where a person is visiting (the first of the three data types listed above). For most people, it’s quite clear how GPS can help detect where a person is visiting, but you might want to hear more about how we could use other sensors. To help illustrate, I’ll walk through a few examples of some of the specific data components that we might use to determine location:

    1. Barometer: A barometer is used to measure atmospheric pressure and is present on many phones. Phones typically contain a barometer because if you are able to measure the atmospheric pressure near a device and know the general location of that device, you can determine with a high degree of accuracy the elevation of that device. This is important for your phone because when you need to use your GPS to get an accurate location reading, your phone needs to connect with several satellites in the sky and understanding your elevation allows the phone to more quickly connect to those satellites. In other words, when you open up a mapping app on your phone and see the phone go from a rough location to an exact location, the barometer helps make that action occur quickly. Sense360 also uses the barometer to understand your elevation for a similar purpose, which is to better understand the place you are visiting. For example, there could a case where a user appears to be at a 70 story high rise in New York City, and the elevation helps us understand if they are potentially at work near the 70th floor or visiting a coffee shop located on the 1st floor.
    2. Accelerometer: The accelerometer is present on nearly every modern smartphone, with one of the primary use cases being that it helps the phone determine if you are holding it in a portrait (vertical) or landscape (horizontal) position. Sense360 uses the accelerometer in a manner similar to how almost all popular mapping apps use it, which is to understand the activity of the user, such as if they are walking, driving or stationary. Understanding the activity of the user allows us to better determine if they’re actually at that coffee shop on the 1st floor having a coffee or if they’re simply standing outside waiting for the bus to arrive.
    3. Nearby Wi-Fi networks: If we repeatedly detect a particular Wi-Fi network at a particular location, then our system can tell that any device that senses that Wi-Fi network must be near that location, even if the device can’t directly detect the location through GPS. This also helps us determine device location more accurately, even when GPS signals are available. For example, we may be able to measure the relative strength of multiple Wi-Fi networks to triangulate a precise location even when GPS is off.  


We also may collect a variety of other technical data to help determine location and to associate the information with a particular device.

The second main data type we collect is survey responses, powered by the survey module available in our SDK (Sense360 software that our app partners and some of our customers build into their apps). We send surveys directly to users, sometimes in exchange for points, monetary payouts, and other rewards. These surveys are used to directly influence the decisions of some of the largest brands in the world, so it’s an opportunity for users in our network to have a huge impact on the brands they know and love. For example, some of the questions we’ll send to our network include:

  1. What do you think of the price and taste of new items available on a menu?
  2. Do you think different elements of the store experience should be changed such as cleanliness or location?

The final main data type we collect is the list of installed apps on a device, which currently is collected only on Android devices. We are able to see the list of apps installed on a phone at any given time, but no data is collected about the usage of those apps (except for a handful of apps that use Sense360 technology to power core app functionality, such as speed detection). This data is only analyzed in an aggregated manner. Brands want to optimize the user experience by investing in their digital apps, and they utilize Sense360 to better learn about the impact different apps have on user behavior and how to better guide their efforts. As an example, a fast food brand may use our data after releasing a major update to the app store to see if users that have their app are visiting their restaurants at an increased rate. Another use case would be to understand what the most popular apps are, so that they can better understand what types of digital experiences users are enjoying most.

While each of our data types helps in a different way, all of the data we collect at Sense360 shares the common goal of helping brands optimize their user experience. If you have any questions, please don’t hesitate to email me at [email protected].