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How to Maximize Your Company’s Location Data


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Download any app onto a smartphone these days and you’ll be prompted by the same question: Do you want to turn location services on?

For consumers, letting Google Maps or Waze know exactly where you are is a must — it’s the essence of why those apps exist. But have you ever wondered why other types of businesses, from grocery stores to social media platforms, want to know where their patrons are at all times?

It turns out this across-the-board drive from enterprises is not unique. According to a study by Dresner Advisory Services, more than 60% of people realize that location intelligence (LI) is a critical component of business.

So what makes LI unique?  The truth is that almost every business has a treasure trove of location data—for example, Starbucks knowing exactly where everyone with their app is right now. However, the business intelligence (BI) tools being used to process this data can only provide temporal insight or basic points on a map. LI goes a step further by answering more forward thinking questions only possible with an LI platform. Answering, for example—“where should Starbucks put its stores in the future based on user commuting patterns?” Or, “where would a billboard reach the largest number of prospective buyers early in the morning?” Instead of focusing on the now, LI seeks to answer challenges a business may face moving forward.

But performing this type of iterative spatial analysis involves so much more than just collecting the data and hoping it points an enterprise in the right direction. To get the most out of location-based services—now ubiquitous thanks to the explosion of connected devices like the internet of things, mobile phones, connected cars and social media—companies should follow a few best practices so they don’t get lost on their way to LI-driven problem solving.

Step 1: Enrich the Data

Having quality data is the first step to gaining LI insights. Companies must ensure their data is accurate and reliable, cleaning and filtering it before integrating it with other external databases. Any LI services providers should be well-versed in how to get only the best data imported or connected to a new database. Then, it’s time to enrich it—linking it with additional sources of location data, like financial, ecological and demographic measurements. To determine which sources of data to add, companies should ask themselves what they want to achieve, where their data is location and what’s the best way to aggregate their data.

Step 2: Create a Visualization

Visualizations are the foundation for interpreting LI—the baseline for how you will better understand your data. There are multiple methods to selecting how to best chart your data. Some things to consider are how much you’ll need to interact with your data to model scenarios and findings correctly, if the visualization is easy to understand (particularly important if the visualization will be interpreted by a team), and does it appropriately represent the data and findings?

Think about how the National Weather Service recently had to redesign Hurricane Harvey rain data on the fly, so it could be more easily interpreted by the public. This kind of flexibility and ease of use, where a tool scales with immediate needs, is essential.

Step 3: Analyze and Iterate

This step is what separates BI from LI. Your initial analysis, or blend of analysis methods, should be based on your company’s desired outcomes, which can come in a broad array of functionalities. By combining traditional analytics with emerging geospatial techniques, companies can create more actionable business outcomes and value from their data.

Spatial data analysis marries scientific modeling and machine learning to perform actions like identifying clusters and outliers and predicting market volatility or future consumer patterns. Database analysis works best for filtering, numeric aggregations, joins and other methods traditionally also found in BI tools. Geospatial analysis is practical for any spatial functionalities, like measuring distance, proximity or other functions often found in geographic information system (GIS) platforms.

Once you select one or a few methods, your LI dashboard should enable your team to iterate on this data. After collaborating, a business’ teams can then move onto the final step.

Step 4: Take Action

Now that you have your findings, communicating them with other stakeholders and determining a course of action is imperative to turning your LI data into concrete changes to your future business practices. Companies may even opt to develop new applications based on what they’ve learned, creating new product opportunities and streams of revenue. Or companies can identify how to increase their profit margins based on their LI insights.

The Result

Collecting LI data is just the tip of the iceberg when it comes to using that data to drive insights. Using location-based information, businesses could shift store hours to reflect when customers are actually around their business. They could gauge real estate market pricing based on projected foot traffic. They could perform geomarketing to ensure ads are placed in the right region based on its demographics, and business can make all of these choices knowing they aren’t just going on a hunch. Each of these scenarios can lead to better outcomes that would have never been possible without LI best practices.


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