Last week the Wall Street Journal reported that many large retailers, after years of slashing staff in an effort to contain costs, are starting to realize they may have gone too far. While fewer workers obviously leads to lower labor costs, it can also result in missed opportunities for sales or diminishing brand loyalty among shoppers. Ever walked out of a store without buying anything because you didn’t feel like waiting in line? So have nearly 90% of US consumers, according to a survey referenced by the article. The problem isn’t unique to large retailers either; when I worked for a small pizza restaurant in college, we’d sometimes cut our delivery staff so low that we’d miss out on big orders because of excessive wait times.
Having the right level of staff on hand at the right time is obviously crucial for any organization. But how do you set that level? Believe it or not, your existing Wi-Fi network may hold the key. Instead of setting staff as a percentage of sales or based on time of day, data gleaned from Wi-Fi can allow businesses to gauge foot traffic in and around their location, and set staffing levels accordingly.
The way this works is actually pretty simple: As we move around, our phones, smartwatches, tablets and other Wi-Fi enabled devices are continually sending out short messages looking for networks we might be interested in connecting to. This happens even when we’re not actively using the device. Wi-Fi access points are listening for these types of messages, known as probes, and can respond to the interested client device with information about the network. Even if we never connect, the access point and client device exchange some limited information as long as they’re both in range of each other. Here’s where the magic happens: by keeping track of how many devices are sending out probes at any given time, we can come up with a pretty accurate guess as to the amount of foot traffic nearby. Taking it a step further, keeping track of the amount of time devices remain near the access point can yield an estimate of conversion rates. If a device (and by extension the person carrying it around) is in range for more than, say, 10 minutes, we can reasonably assume they are interacting with the business in some way, whether it’s shopping, dining, or some other interaction.
That, in a nutshell, is what’s known as Wi-Fi Presence Analytics.
So how does it help us optimize staffing levels? Well, looking at this data over time, we can identify trends and patterns like busiest hour of the day and busiest day of the week, and then schedule our staff accordingly. Let’s look at an example:
The screenshot above is a real example of this technology, with the data being collected from a wireless access point in my living room. I’m in a large multi-unit building, right next to the elevator lobby, so the AP is mostly picking up my neighbors as they come and go. We can see, though, that Friday nights seem to have more visitors than other nights of the week, particularly around 10-11pm (I’ll let you ponder the reasons behind that on your own). If I were a physical business, I could use these types of insights to optimize staff levels without dramatically increasing labor costs. For example, I might overlap shifts to have additional people on hand from 10-11pm when they’re most needed.
We can also use this to easily identify when we might be missing opportunities because we’re understaffed. Here’s a key insight from that WSJ article I referenced earlier:
After installing cameras last year, Cycle Gear Inc., a 130-store chain that sells motorcycle apparel and accessories, noticed sales dipped during the afternoon at its Orlando, Fla., store even though it was packed with shoppers.
“That told us the salespeople were overwhelmed,” said Rodger O’Keefe, a vice president. “We added two more salespeople during those hours, and sales have been up since then.”
Cycle Gear made a smart move here, but you don’t need to pour over hours of CCTV footage to gain similar insights. All we really need to do is cross reference our sales data with passerby and visitor information capture via Wi-Fi. Let’s look at another example:
Here we can see a pretty significant bump in foot traffic on April 6th and 7th. If we had data for these two days that told us sales had remained flat or even dipped, it might tell us that potential customers passed us over for the business next door because we were understaffed. It could also be that we need to work on getting customers in the door in the first place. Fortunately this same type of technology lets us cheaply and easily do some A/B testing of different marketing strategies in addition to optimizing staffing levels.
So you’re probably wondering what the catch is here. Well, the big one is that Wi-Fi access points on their own aren’t enough to gain these kinds of insights. While the APs are constantly receiving probes from nearby Wi-Fi devices, they aren’t doing the calculations necessary to turn probes and signal strengths into visitor data and human-friendly graphs like we see above. That requires an additional solution, typically delivered as a cloud service that feeds off the raw data from one or more access points. There are technical caveats as well: you’ll need business-grade access points as opposed to off-the-shelf equipment, and the placement of APs takes on a new level of importance when tracking foot traffic as opposed to merely providing connectivity to devices.
The good news is that both the cost and complexity of these solutions has come down to the point where just about any sized business can take advantage of it. The example deployment from my living room consists of just a single AP from Cisco, paired with their entry-level cloud service, and represents less than $1000 total investment. If you already have business-level equipment from a major vendor like Cisco, Ruckus, or Aruba there’s a good chance you may not need a hardware upgrade and would therefore have practically no upfront cost. Many of the big presence analytics cloud services also offer a free trial of some kind, giving businesses a chance to see exactly how the technology might benefit them.
If you think your business could benefit from a presence analytics solution, please don’t hesitate to contact us!