CARTO, a leading location intelligence platform, was tasked with helping a local food truck business determine where they should be placing their trucks based on revenue prediction models. To do this, they needed to build precise models based on multiple streams of data.
The Solution
Unacast, the leader in transparent, contextualized location data, worked with CARTO to provide real-time location data insights. When layered on to census data, purchase data and other sources being used in the model, these real-time foot traffic insights create a more accurate view of the activity surrounding potential sites.
The Outcome
CARTO was able to layer Unacast data into their prediction models to create the most accurate revenue and site selection predictions for their client. You can discover more details about how they built out their model here.
The Proof
Ultimately, CARTO was able to deliver the 6 sites in New York City most likely to generate the highest revenues for their client. The sites and revenues predicted were:
- Corona Park: $6,128 weekly sales average
- Penn Station: $5,975 weekly sales average
- SoHo: $5,911 weekly sales average
- Grand Central Station: $5,766 weekly sales average
- West Village: $5,234 weekly sales average
- DUMBO: $5,193 weekly sales average
Ready to find out how location data can boost your revenue?
LET'S CONNECT.
