Retail Analytics: Who Owns The Data?

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At AirTight Networks, we talk a lot of SMAC (Social, Mobile, Analytics, Cloud). Together these forces have come together to significantly impact and radically change various markets. It’s not hard to wax eloquent about SMAC for long periods of time, but in this article, I want to focus only on the Analytics piece – that numerical, statistical, miracle whip that drives business decisions.

Analytics Data: Type and Collection

In the SMAC model using Wi-Fi as the Mobile piece, data is collected from Wi-Fi access points. The analytics data itself generally falls into one of two categories: 1) Presence, and 2) Opt-in.

Presence Analytics
Presence Analytics is, as it sounds, focused around whether the client device is on-location (“present”) and whether it is inside or outside a boundary (e.g. a store front). This type of data is device-specific (MAC Address), independent from the user of a device (contains no user-identifying information), and therefore anonymous. It is collected by using Access Points (APs) to scan the air and to gather MAC addresses (which only a hashed representation thereof is stored). Presence Analytics can be used for a variety of things, but some examples might include:

  • Understanding total foot traffic (e.g. how many visitors came to your location)
  • Understanding capture rate of visitor traffic (e.g. which visitors came inside your store front and which ones stayed outside)
  • Understanding dwell time (e.g. visit duration) either inside or outside your location

AirTight Presence Analytics

The same capability that enables Presence Analytics also enables similar functions like Loyalty Analytics. Examples of this might be:

  • Understanding visitor frequency (how often do they come to see you?)
  • Understanding visit recency (when was the last time they came to see you?)
  • Understanding repeat visitor information (how many times have they come to this location over a period of time?)

Analytics: Unique visitors

Opt-in Analytics
Opt-in Analytics are obtained through a process whereby a person uses his/her mobile device to willingly engage the wireless infrastructure (and associated back-end systems). The typical scenario involves the use of a Captive Web Portal (CWP) to display terms and conditions and to allow the user to authenticate (log in) using one or more methods, such as:

  • Phone Number with SMS verification
  • Social Media integration (e.g. Facebook, Twitter, Google+, or LinkedIn login APIs)
  • Guestbook function where the user fills out a web form

Regardless of the process, the user is agreeing to the use policy in order to obtain a benefit, which is most often free Wi-Fi access, promotional coupons, location services, or perhaps all of these and more. The use policy allows the infrastructure to collect a specific amount of the user’s personal information that is determined by the user at the time of authentication.

Other Types of Analytics

Of course, all of those are just simple examples, but to be honest, analytics can get pretty sophisticated. Consider other types of relevant data, such as Engagement Analytics and Wi-Fi Usage Analytics.

Engagement Analytics 
Engagement Analytics might, for example, consist of:

  • Conversion and Bounce Rates (Did they come inside or stay outside? Did they use the Wi-Fi while in the store? Did they buy anything while in the store?)
  • Social Media Wi-Fi Authentication Visitor Logs (Who are they?)
  • Social Media Wi-Fi Authentication Demographics (How old? Male/Female? Where do they live?)

Engagement Analytics

Engagement Analytics allow the organization owner to pair up the device (which is identified with Presence Analytics capabilities) with the user of the device (which is possible because of Opt-in capabilities) and then tie those capabilities into back-end systems such as their CRM. That CRM system could then be used, in conjunction with the wireless infrastructure system and analytics engine, to:

  • Identify and locate a user’s device when it arrives on-location
  • Understand the owner of the device’s habits and desires (e.g. purchasing habits/desires if in retail)
  • Push context-relevant, location-relevant, and personalized content to the user in a timely fashion
  • Provide an entertaining experience while on-location

It might sound space-age, but it’s the holy grail of the retail market right now, and other markets will likely follow suit when retail has proven that it can be done well, end-to-end.

Wi-Fi Usage Analytics might, for example, consist of:

  • Device Types
  • Data Traffic
  • Session Duration

Having access to data such as average session duration may allow a quick service restaurant (QSR) to make a decision about how to configure their Wi-Fi infrastructure system. Some Wi-Fi infrastructure systems have a “black out timer” that imposes a no-use time after a configured period of use time. This type of data may help a coffee shop decide on whether to write their new mobile app for iOS or Android first. It may allow a financial services firm to decide on whether to upgrade their Internet backhaul pipe or apply protocol filtering to block peer-to-peer file sharing applications. There are 101 uses for Wi-Fi Usage Analytics.

All that rich data is just waiting to be mined for business-transforming information that can be easily organized into useful formats and compared across locations, and can help you decide on marketing spend and business expansion. All you need to get started is the right Wi-Fi solution.

Analytics Data Ownership

“Houston, we have a problem.” Yeah, that’s you when you find out that you don’t own the data…

“Say what? That doesn’t sound right…are you sure? Wait…where’s my contract! What do you MEAN I don’t own the data?” Yep, that’s you again…quickly growing worried and agitated since you’re the one who recommended the Wi-Fi vendor who’s either holding onto your analytics data awaiting ridiculous additional monthly fees or who has an analytics business partner who’s trying to perform unnatural acts with your wallet while the Wi-Fi vendor keeps you distracted.

“But it’s my system! It should be MY data! These are MY customers for crying out loud…who else’s data would it be?”

Oh, don’t worry… your analytics vendor has you covered. They can fix you up for… $_______ per AP per year. Or as my man Alan Jackson might say, “But don’t be downhearted, I can fix it for you, Sonny; It won’t take too long, it’ll just take money.”

Of course, if you buy AirTight Networks Wi-Fi and analytics, YOU own the data.

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Devin Akin

Devin Akin

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Comments

  1. says

    I feel like some analytics providers are worried that if they don’t “own” the data customers will somehow jump ship. But we still need the technology to process, organize, and analyze that information—but if I want the raw numbers they should be mine to take whenever I want!

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