Location data is one of the wonderful things we can collect in this world of connected and mobile devices. However, on their own, location data pieces are only little points on the digital map.
When you want location data to go to work for you, you need a tool for data visualizations and optimizing business outcomes. Namely: location intelligence.
Location Data and Intelligence: Today and in the Future
Carto and Hanover Research recently released their State of Location Intelligence report for 2018, which is intended to help businesses understand their location data and how to leverage it.
Because everything happens somewhere, and the number of connected devices is growing exponentially, an overwhelming number of spatial components exist within data. New methods, technology and talent will be necessary if brands want to turn these components into intelligence, and thus stay competitive.
This report found that the already critical nature of location intelligence (LI) is only going to grow in the coming years. However, there will be hurdles on the road to full implementation. Let’s see what the report found, and what it suggests for the future.
The State of Location Data
Ninety-four percent of medium and large organizations (those with 500 or more employees) collect and store location data.
While only 66 percent of executives, managers and analysts feel LI (turning the data into outcomes) is important to their success right now, 78 percent expect it to become important in the next year. Eighty-five percent expect it to be important in the next three years.
Those numbers align with planned investment, especially in small to mid-sized organizations. There, 78 percent of C-level and management respondents say they’re likely to invest in LI within one year, and 84 percent expect to invest within three years.
The Challenges of Location Intelligence
In turning location data into LI, organizations face both technological and human challenges. Employees need a better understanding of location data collection methods, and along with this come challenges of managing executive expectations and personnel staffing.
For example, executives and managers are more aware of location data collection methods (websites and web-based apps, social media, customer service interactions, etc.) than analysts are.
Executives and managers are also more aware of challenges (ensuring quality and accuracy, maneuvering privacy issues, storing data securely, etc.) than analysts are, and see LI as more important to success than do analysts.
The top overall challenges to data collection for LI adoption are ensuring data quality and accuracy (49 percent) and gathering data in real time (40 percent).
The top overall challenges to analyzing location data are extracting, cleaning and transforming data into a workable format (41 percent) and ensuring sufficient data is available for actionable analytics (38 percent).
The Future of Location Intelligence
C-level and executive survey respondents might have more familiarity with location data and LI, but they don’t necessarily understand how to implement it. Making some changes now could improve their long-term future with LI.
For example, businesses typically organize their spatial data around state, city or zip-code boundaries. Yet, more granular boundaries would provide deeper and more customized insight. One example would be Census Block Groups, which are the smallest geographical units published in Census Bureau sample data and only collected from a fraction of households.
Another area needing attention is the implementation of LI best practices. While these might be understood in theory, they aren’t necessarily happening in reality.
For example, while almost 40 percent of executives thought their companies performed crucial spatial analysis on location data, only 17 percent of data analysts confirmed this to be the case. Further, a full 42 percent of companies still use traditional business intelligence tools, rather than LI platforms, to analyze their location data.
The report wraps up by outlining three best practices your company can adopt now to secure a better future with your LI:
- Document and organize your LI process to identify missteps and develop content for sharing across the entire team.
- Ensure communication between executives and team members about challenges and opportunities to clarify the vision and how to make it reality.
- Study and apply spatial data science methods through the talents of data scientists to make your location data more effective.
Getting Started with Location Data for Advertising
Location data and intelligence can be used in many ways, and advertising is certainly one of them.
One example is how Facebook now allows businesses to build custom audiences based on customers who have already visited physical stores, and then serve them relevant ads.
Another example is seen in recent reporting from LSA Insider, which highlights how location data is used in mobile ad campaigns for improved performance.
Location data from AdWords is a way to understand how ads perform in different locations and where customers are located or have interests. Take advantage of the available targeting settings and reports to identify the geographic locations most deserving of your efforts and budget.
Back in August, we discussed using your location data to better understand your customers and improve their experiences. At the moment, location data isn’t doing all it can for advertisers due to challenges around mobile, definitions of “location” and basic understanding of location data.
However, when advertisers look to location data as an enhancement to customer profiles, and partner with the right platforms to turn that data into intelligence, this information can help to mature mobile strategies and improve customer experiences.
Location data isn’t meant to replace other data on your ads and consumers, just as location intelligence is only one component of your brand’s overall intelligence. Yet, when LI is integrated into your advertising approach, you’re defining yourself as a player in the future of advertising.