In my last few posts, I explained what in-store journey analytics is, described the basics of the technology and the data collection used, and went into some detail about its potential business uses. Throughout, and especially in that last part around business uses, I wrote on the assumption that this type of measurement is all about retail stores. After all, brick & mortar stores are the primary focus of Digital Mortar AND of nearly every company in the space. But here’s the thing, this type of measurement is broadly applicable to a wide variety of applications where customer movement though a physical environment is a part of the experience. Stadiums, malls, resorts, cruise ships, casinos, events, hospitals, retail banks, airports, train stations and even government buildings and public spaces can all benefit from understanding how physical spaces can be optimized to drive better customer or user experiences.

In these next few posts, I’m going to step outside the realm of stores and talk about the opportunities in the broader world for customer journey tracking. I’ll start by tackling some of the differences between the tracking technologies and measurement that might be appropriate in some of these areas versus retail, and then I’m going to describe specific application areas and delve a little deeper into how the technology might be used differently than in traditional retail. While the underlying measurement technology can be very similar, the type of reporting and analytics that’s useful to a stadium or resort is different than what makes sense for a mall store.

Since I’m not going to cover every application of customer journey tracking outside retail in great detail, I’ll start with some general principles of location measurement based upon industry neutral things like the size of the space and the extent to which the visitors will opt-in to wifi or use an app.

Measuring BIG Spaces versus little ones

With in-store journey tracking, you have three or four alternatives when choosing the underlying measurement collection technology. Cameras, passive wifi, opt-in wifi and bluetooth, and dedicated sniffers are all plausible solutions. With large spaces like stadiums and airports, it’s often too expensive to provide comprehensive camera coverage. It can even be too expensive to deploy custom measurement devices (like sniffers). That’s especially true in environments where the downtime and wiring costs can greatly exceed the cost of the hardware itself.

So for large spaces, wifi tracking often becomes the only realistic technology for deploying a measurement system. That’s not all bad. While out-of-the-box wifi is the least accurate measurement technology, most large spaces don’t demand fine-grained resolution. In a store, a 3 meter circle of error might place a customer in a completely different section of the store. In an airport, it’s hard to imagine it would make much difference.

Key Considerations Driven by Size of Location:

• How much measurement accuracy to do you need?
• How expensive will measurement specific equipment and installation be and is it worth the cost?
• Are there special privacy considerations for your space or audience?

Opt-in vs. Anonymous Tracking

Cameras, passive wifi and sniffers can all deliver anonymous tracking. Wifi, Bluetooth and mobile apps all provide the potential for opt-in tracking. There are significant advantages to opt-in based tracking. First, it’s more accurate. Particularly in out-of-the-box passive wifi, the changes in IoS to randomize MAC addresses have crippled straightforward measurement and made reasonably accurate customer measurement a challenge. When a user connects to your wifi or opens an app, you can locate them more frequently and more precisely and their phone identity is STABLE so you can track them over time. If your primary interest is in understanding specific customers better for your CRM, tracking over-time populations or you have significant issues with the privacy implications of anonymized passive tracking, then opt-in tracking is your best bet. However, this choice is dependent on one further fact: the extent to which your customers will opt-in. For stadiums and resorts, log-in rates are quite high. Not so much at retail banks. Which brings us to…

Key Considerations for Opt-In Based Tracking

• Will a significant segment of your audience opt-in?
• Are you primarily interested in CRM (where opt-in is critical) or in journey analytics (which can be anonymous)?

How good is the sample?

Some technologies (like camera) provide comprehensive coverage by default. Most other measurement technologies inherently take some sample. Any form of signal detection will start with a sample that includes only people with phones. That isn’t much of a sample limitation though it will exclude most smaller children. Passive methods further restrict the population to people with wifi turned on. Most estimates place the wifi-activated rate at around 80%. That’s a fairly high number and it seems unlikely that this factor introduces significant sample bias. However, when you start factoring in things like Android user or App downloader or wifi user, you’re often introducing significant reductions in sample size AND adding sample biases that may or may not be difficult to control for. App users probably aren’t a  representative sample of, for example, the likelihood of a shopper to convert in a store. But even if they are a small percentage of your total users, they are likely perfectly representative of how long people spend queuing in lines at a resort. One of the poorly understood aspects of measurement science is that the same sample can be horribly biased for some purposes but perfectly useful for others!

Key Considerations for Sampling

• Does your measurement collection system bias your measurement in important ways?
• Are people who opt-in a representative sample for your measurement purposes?

The broad characteristics that define what type of measurement system is right for your needs are, of course, determined by what questions you need to answer. I’ll take a close look at some of the business questions for specific applications like sports stadiums next time. In general, though, large facilities by their very nature need less fine-grained measurement than smaller ones. For most applications outside of retail, being able to locate a person within a 3 meter circle is perfectly adequate. And while the specific questions being answered are often quite specific to an application area, there is a broad and important divide between measurement that’s primarily focused on understanding patterns of movement and analysis that’s focused on understanding specific customers. When your most interested in traffic patterns, then samples work very well. Even highly biased samples will often serve. If, on the other hand, you’re looking to use customer journey tracking to understand specific customers or customer segments (like season-ticket holders) better, you should focus on opt-in based techniques. In those situations, identification trumps accuracy.

If you have questions about the right location-based measurement technology solution for your business, drop us a line at info@digitalmortar.com

Next up, I’ll tackle the surprisingly interesting world of stadium/arena measurement.