NEW: Dwell time distribution

How long do your visitors spend at your attraction? It’s a tricky part of the visitor experience to measure. And yet, it’s one of the most important – understanding the duration of the visitor’s time onsite and investigating its correlations – such as visitor satisfaction, ticket price elasticity and average revenue – will help your organization cater for a premium visitor experience. Dwell times are a clear indicator of the visitor’s perception of value for money and likelihood to convert onsite with a commercial or membership transaction.

Luckily, we don’t need to stalk visitors with a stopwatch in hand to find out this valuable insight. By using your existing WiFi infrastructure to annonymously track devices, Dexibit can analyze your visitor dwell times and provide interesting new ways of looking at this data. Recently, we’ve provided a number of enhancements to how we do this.

Slicing

Dexibit provides three ways to look at dwell times:

  • Dwell times per visitor, across the site overall (see visualizations 41, 96)
  • Dwell times per level, for each level in your venue (see visualizations 73, 97)
  • Dwell times per zone, for each zone in your venue (see visualizations 74, 98)

Depending on how your presence integration has configured, if you have multiple access points from your WiFi network in one space (such as an atrium), these may be grouped together into a single zone. If your venue is an outdoor campus, a level may refer to an outdoor plan area within the wider site.

Use the calendar controls to investigate how dwell times change, for example during various exhibitions or holidays.

Distribution

In addition to a running average, it is also interesting to look at how these numbers are comprised. Understanding how your visitors’ experiences are clustered helps with designing for those needs, for example, when it comes to the level of interpretation in an exhibition, or whether various parts of the venue need more seating options.

For the venue and each of its levels and zones, Dexibit provides a breakdown of dwell time distributions, so you can investigate walk throughs versus extended visits and everything in between.

Cleaning

WiFi data is notoriously messy and noisy, and most WiFi vendors either don’t directly report dwell times, or measure it incorrectly in terms of the device’s connection time. As part of the data pipeline, Dexibit cleans and transforms your data once it is ingested, in order to provide insightful analytics, including treatments for dwell times – no matter your WiFi vendor.

As part of this data cleansing, we look for and exclude passersby, fixed equipment and permanent staff from the raw data, so these  do not distort your metrics – as your network might pick up everything from someone walking past the front door through to the signal that your point of sale system emits. You’ll also find Dexibit always expresses presence insights as a percentage rather than in the number of unique devices, given these will only represent a sample of your visitation (usually upwards of 90%) as not all visitors carry a device.