Why use Human Movement Data?

Business professionals have been running successful businesses for years without Human Movement Data. Recently, however, it has become a go-to for business around the globe. The question then naturally follows, why should my business use Human Movement Data? We outline below 5 reasons why using Human Movement Data can be valuable for all types of businesses. And discuss the limits of Human Movement Data.

1. Quantitatively There Is No Equal

Many businesses, tourism boards, and government entities rely on intercept surveys or “boots on the ground” visits to determine things like where visitors are from, where else they are traveling to, etc. These surveys often require hiring specialty firms to perform them. Gathering data from a significant amount of people is expensive and time consuming. Furthermore, the data returned is often unstructured, making it difficult to work with, and could potentially have some serious biases (see below).

Surveys then went digital --through email, apps or advertising. These methods allowed companies to reach hundreds of people at a very low cost. However, responses could be problematic, e.g. people answering surveys twice or giving conflicting answers, and even being “less than truthful” on items like income, age and education. One large improvement of moving to digital is that it removes the survey-taker, leading to more consistent, structured responses. This improvement comes from both:

  • Changing behaviors of the survey-taker who no longer has a human being they are trying to impress or please, potentially removing some of the biases.

  • Creating standardized responses where every answer is consistent, such as each response to a Yes/No question being answered “Yes”, not “Y” or “Yep” or other random entry.  This makes the data significantly easier to work with.

Now, since the majority of people carrying smartphones, surveying on a vast scale has becoming an option. 78% of American adults, for example, now carry smartphones. Globally, 2.1 billion people carry smartphones.  Because so many of these smartphone consumers opt into sharing their geo data, businesses can see samples of data from thousands or hundreds of thousands of visitors, creating an unparalleled quantity of data.

2. Removes Survey Biases

Human surveys are known to be subject to bias. An entire ecosystem of social scientists investigating the phenomena can be found (See: Google listing for scholarly articles on possible biases in surveys).

An overview of the top issues reveals that the majority of the issues arise when humans are involved. Some examples include:

  • Poor memory

  • Over-willingness to agree

  • Social conformity: wanting to appear similar to others or impress the question-asker

Human Movement Data, on the other hand, requires no human intervention except when a human makes the decision to opt-in to sharing their mobile location data. This then provides a data source which removes many of the biases associated with traditional surveys.

3. Provides Data When There Are No Alternatives

Companies often have customer data (CRM data) or survey data associated with their own visitors/customers. This data is invaluable and can be a key source to help determine operational plans, marketing, site selection and customer profiles. But what if you don’t have CRM data? Or an expensive intercept survey is out of your reach? Human Movement Data can provide insights because of its lack of reliance on people signing up for a loyalty program or other CRM solutions. The data provided is independent of human-operated intercept surveys. In the face of nothing else, Human Movement Data can be an incredible source of data about your customers and can be used to complement CRM data, and provide deeper insights in to your customers.

4. Allows Analysis Beyond Anecdotes

While you may think you know your own brand's visitors' habits and preferences, these thoughts are also subject to personal and environmental biases. Human Movement Data can allow improved and sometimes surprising insights into the behaviors of your customers.

5. Competitor Insights

In addition to learning more about your own customers, it is also useful to know these facts about your competitor across the street. If you can see how your visitors compare to theirs, or how your location performs in comparison to theirs, you are better equipped to attract your ideal customer base.  Human Movement Data provides the quickest and easiest way to perform competitive analysis, and is often the only alternative to traditional methods available.

The Limits of Human Movement Data

After reading the above, it might seem that Human Movement Data is the magic bullet for data analysts everywhere. And while the data can be a game-changer, it is not perfect and there are places where it cannot answer every question one may have. There are also ways where consumers of mobile location data attempt to apply insights which are not necessarily valid. Some examples:

  • Human Movement Data is a sample. It is not 100% of visitors, and it should not be treated as such. Like any sampling method, it can be subject to biases or lack of volume. For more information, take a look at articles on scale, accuracy and mobile location data sources.

  • There is no direct link between mobile observations and value of transactions. We see footfall or visitation with Human Movement Data, but no confirmation of whether or not a purchase was made. In addition, one purchase, say at a fast food restaurant, can actually have 4 devices associated with it (a family of four). Finally, not all purchasers are carrying smartphones that have opted into sharing location. That being said, there is a high degree of correlation, but this should be used directionally rather than absolutely.

  • Since Human Movement Data is intermittent, this means that not every move a device makes is captured. This is true even for “background” sources. Because of this, doing an analysis on something like frequency of visitation can be problematic. A key thing to remember is that just because a device wasn’t observed in a location, doesn’t mean the device didn’t actually visit the location. A concrete example would be a device with a ping in a Walmart 2 times in the course of a 90-day window. This could mean that the device was only in Walmart twice. However, it could also mean the device was there 4 times, but only created a geodata event 2 of the times the devices was in store.  The proper usage of the data there is to focus on the fact that the device created a ping two times within the Walmart, nothing more. Essentially, using Human Movement Data can give you a sample of your frequent visitors, but it is not an exhaustive list of your most frequent customers.