Tag Archives: mall

Using Geofencing to Observe Shopper Behavior

This post was originally published on the Research Now blog.

It is widely discussed that mobile opens up incredible
opportunities for researchers. It is perhaps equally widely discussed that
mobile provides challenges for researchers ‘ especially those most reticent to
part with, let’s say, more traditional approaches. I could think of a number of
examples of this two-sided coin, but I’ll leave all of those, save one, for
future discussions.

One that the industry needs to tackle head on is the use of
geolocation for understanding shopper behavior. So much opportunity! But
logistics and analysis is so hard (for many rooted in market research)! The
notion of using geolocation itself for research is no longer new. Geofencing
has been used to target people for research for several years ‘ with the most
commonly used methodologies centered around delivering a survey to someone when
they are in a specific location or after they have left. In many cases this is
a viable approach to understanding shoppers ‘ and getting feedback close to the
point of experience.
Personally, I’m a fan of targeted and efficient research
engagements that ask people to recall their shopping behaviors before they
forget them. But I am also a fan of not having to ask what we don’t really need
to ask, for example who they are, where they shopped, and when. With this idea
in mind, and wanting to piggyback on prior years of researching Americans’
Black Friday shopping habits, we looked to explore how geofencing could be
effectively utilized to understand shoppers with minimal active engagement from
them. So, last Fall, we brainstormed with Placecast and their savvy team of
location-focused researchers on how we could shed new light onto shopping
behaviors around this critical time period for retailers.
While we did end up asking some questions directly of people,
we managed to glean a lot by matching our panelists’ location data with
existing profiling attributes. We discovered, for example, that the most
affluent Walmart shoppers came to the store on Black Friday when compared to
days leading up to and following that day.

The most affluent shoppers also proved to shop early in the
morning in the days immediately prior to and following Black Friday.
Understanding who shops where and when is crucial
to retailers and advertisers as they try to craft relevant messaging and
promotions for holiday sales. Combining geolocation data and associated
advanced analytics with known profiling attributes creates a compelling story
about shopper behavior, one that can be layered with surveys and other data
sources to provide actionable insights.

The industry has an opportunity here ‘ to use geolocation
data in a smart way and one that alleviates much of the survey burden often
placed on participants.