The ability to make more informed decisions enhances every aspect of your strategy.
Marketing wants to reach to the right customers. Operations wants to minimize wastage. Real estate wants value from your locations. Pricing wants your offering to be competitive. Finance wants strategic budgeting. From all angles, data empowers decision-makers to better understand the challenges and opportunities facing them every day.
As specialists in delivering analytics tools to enable these decisions, Trade Area Systems and Spatial.ai have joined forces to discuss Geosocial, a powerful dataset to give you the edge in 2020 and beyond.
Whether you’re looking to know your customers better or identify the optimum site for your concept, fine-tune a leasing strategy or enhance your omnichannel approach, Geosocial provides actionable data to help you drive real change while assessing the impact on your bottom-line.
How does it work?
Geosocial data capture the behaviors, interests and attitudes of communities in real time and at a geographic level. Using social platforms like Twitter, Instagram, Facebook events, Flickr, Foursquare, Yelp, and other public data platforms, Geosocial data are derived by using a machine learning algorithm to find topics of discussion that have naturally occurring relationships with one another.
Demographics and segmentation datasets focus on where people live. Workplace and employment data focus on where people work. Geosocial data help us understand where and how people play and what they do. These data are not tied specifically to where a person lives; rather, the dataset is built on their interests and the locations where they post about these interests.
Geosocial data provide additional insights to questions like:
- What do people like to do in these areas?
- Where are my top customers and where can I find more of them?
- How do the interests being shown here impact brand or retail affinity?
When we combine a real-time social dataset with more traditional and stationary datasets like demographics and psychographics, we can uncover unique and powerful insights to help distinguish between geographies that formerly looked the same.
Give me a real-world example
When you can leverage your customer data with demographic and psychographic data, and then add Geosocial data, you can better understand your customers, where they congregate, and the opportunities to serve them.
These two prospective sites for a fast-food restaurant initially appear identical based on their demographic and psychographic profiles. However, when we layer in Geosocial data, we see stark differences in behavior.
In this case, the first site has a community interested in health and fitness while the second appears to be drawn to night-life activity. If you are trying to determine where to launch a health food menu, for instance, the first location would be a much better fit.
This example provides a simple snapshot of the actionable insight provided by Geosocial data.