Traditionally, retailers have leveraged demographic data and socio-economic indicators for analyzing and forecasting sales. While this approach was adequate five or 10 years ago, it no longer offers substantive information for sales projections, pricing, merchandising, or competitive intelligence. This is why leveraging vehicle traffic data is key for many retail organizations.
However, not all datasets are created equal. For years, the retail industry has relied on annual average daily traffic (AADT), but that data source has lived passed its usefulness. While it may be sufficient for store site selection, it’s not for operational analytics. The new standard for today and the future is detailed historical traffic (DHT). It leverages a more timely, more accurate, and higher frequency source: probe data. .
Road sensors and connected vehicles, in addition to geo-enabled mobile devices, have created more data that’s specific to local traffic volume by time of day and day of the week. With the emergence of road traffic analytics, retailers can now have a more complete understanding of consumer behavior at a hyper-local level within 48 hours of occurrence.
In this webinar, you’ll learn about traffic analytics solutions, and we’ll provide guidance about the necessary geospatial data requirements that will support the development of business intelligence dashboards for brand and marketing managers.
Key takeaways from this webinar:
- We’ll show the difference between the various types of traffic data.
- We’ll demonstrate the methods for location-based traffic patterns analysis.
- How traffic data can be leveraged to make better informed merchandising and marketing decisions on an individual store level.
- The role traffic data can play in the optimization of omnichannel services such as BOPIS and curbside pickup.
