Understanding how mobile device users navigate real-world environments allows companies to adapt their business strategies to changing consumer behaviors. With more companies interested in leveraging insights from location data, it is important to understand exactly how this data can be used successfully and responsibly to inform key business and marketing decisions.
Companies primarily seek to use mobile device location data to help find answers to important questions about the changing behavior of consumers. Some examples include:
What is the average “dwell time” for devices at specific locations?
How do we know if devices were actually at a location or just passing by?
What times are the most and least popular for devices to visit specific locations?
How do I create more effective advertising campaigns based on footfall?
How do I measure the efficiency of cross-channel marketing campaigns?
Limitations Of Location Data
Let’s look at a hypothetical scenario. A company wants to understand which customers are visiting their busy, urban, retail stores but runs into difficulty extracting insights from messy location data. The challenge in drawing conclusions from mobile device location data is that the company is unsure which signals located near their stores are actually visiting customers and which are people just passing by on busy surrounding streets. Using unrefined location data signals, it is nearly impossible to determine which signals represent store visits.
Understanding Messy Location Data
Mobile device location data can be disorganized, unintuitive, and even potentially fraudulent. In order to draw meaningful insights from messy location data, we need intelligent algorithms and technologies to appropriately contextualize the data. The main steps necessary to appropriately filter and extract insights are 1) to understand the movements of device location signals over a period of time and 2) to analyze those patterns to understand how those devices navigate through the real-world.
Factual’s Activity Detection
Factual’s Activity Detection technology provides companies with the ability to draw meaningful insights from mobile device data. Factual uses this technology to analyze how mobile users navigate their real-world environments, including patterns in how long they spend at locations (dwell time) and by detecting travel modes indicated by device movement (walking, biking, driving) during different activities. This technology is built on top of Factual’s Observation Graph dataset (200+ million monthly mobile devices across 27 countries) and is incorporated within Factual’s different products.
There are 3 key steps to how Factual’s Activity Detection works:
Identify groups of location signals from mobile devices over a period of time
Analyze patterns in these signals to determine activity type
Determine when to attach devices to a Factual Global Places (130MM POIs in 52 countries) location using Factual’s Place Attachment technology
At a high level, Activity Detection helps Factual determine a more accurate place attachment and better understand how mobile users navigate the real-world.
Real-World Application of Activity Detection
If we apply Activity Detection to the hypothetical scenario above, we see a more intuitive picture of device travel patterns and behavior, including, but not limited to:
Dwell time analysis showing where people spend a substantial amount of time, allowing companies to further engage consumers in these locations
Popular times analysis showing which areas are more dense during certain hours and when people migrate from one area to another over the day
Travel mode analysis showing the different travel modes, allowing businesses to optimize for traffic flows & better meet the needs of their customer
Factual’s Activity Detection technology uses innovative algorithms to solve complex business problems, derive insights from unorganized location data, and provide immense value to Factual’s clients whose problems require a more nuanced analysis of mobile device location data.
For more information on Activity Detection, Observation Graph and how you can tap into the power of location data, contact a Factual location data expert.