Today I am going to discuss an exciting new area of location technology called Visitor Analytics. In my previous post, I covered how to make a Wi-Fi based solution to monitor foot traffic using RaspberryPi kit computers. The focus of this post will be on MapData Services’ Wi-Fi based Visitor Analytics offering, that brings a lot more polish to the concepts I discussed previously.
If you read the previous post, you will know that there are a lot of moving parts to a Wi-Fi analytics solution. The benefit of using a pre-packaged solution (such as the one MapData Services is offering) is that you get to jump straight into the interesting part – finding out how people are using your physical space.
MapData Services’ Visitor Analytics includes pre-configured Wi-Fi nodes, an online dashboard for viewing analytics, and a fully featured API for accessing the analytics data you collect. So you’re up and running directly after the system is set up. Some of the metrics that are listed in the dashboard include: dwell time; first time visitors; conversion (or draw rate) and many more…
For now, I will explain just a few of these pre-canned metrics, and how they can be useful to many departments in a business.
This is how long a visitor stays in a selected area, such as near the sales counter (represented as minutes), or a shelf in a particular location. Some examples of how dwell time can be useful are: determining how engaged a visitor is with your location; or, how long they have to wait to be served.
First-time detected devices (all-time) within selected time period. Some examples of how this metric can be useful include: effectiveness of a marketing campaign at driving new customers to a store; monitoring the change in customer types; and, provisioning helpful materials to new visitors.
Average percentage of visitors entering at least one zone. This metric can be used to view foot traffic that has walked past your store or venue, versus how many have actually entered.
So now I have covered the benefits of the MapData Services’ Visitor Analytics capability, and given you some examples of the metrics available. Stay tuned for the next post where I will be discussing using the Wi-Fi analytics API to produce custom reports from historical or real-time data.