Changes to consumer shopping behaviour wrought by the technology revolution are obvious and everywhere; a corollary effect is the ability of consumer researchers working for shopping centres and retailers to study consumers in new ways, and hopefully improve the shopping experience as a result. Changes to consumer research methods range from the humble, to the elegantly complex. One example at the humble end of the continuum is the replacement of pens and clipboards with wirelessly connec
ted digital devices in conducting shopping centre exit surveys, another is the replacement of expensive telephone surveys with more flexible online panels.
A little more interesting perhaps is the use of social media instead of traditional forms of research to guide shopping centre tenant mix decisions.
At least one crowdsourcing platform has been created, at which a shopping centre operator can post the details of a project and request ideas from the local community.
People simply log onto the site, submit their ideas for tenants, and vote on those proposed by other contributors.
This approach to obtaining tenant mix ideas is useful for shopping centres in all lifecycle stages, from pre-development to mature project.
Even a successful centre that is 100 per cent occupied can use this input on a regular basis to keep the pulse of the local community and learn about new concepts.
The practice is not yet in widespread use, but it is intuitively appealing. Consumers may have seen retailers or other kinds of businesses that went below the radar of the shopping centre leasing staff.
Besides, publicly seeking input in this way is a good means of enhancing community engagement.
Crowdsourcing – like any means of seeking direct public input into a commercial project – has some shortcomings that need to be acknowledged.
Not all consumer suggestions will be viable or optimal from an economic standpoint. The business model of a given retailer may not be suited to operating out of the particular shopping centre, or it may just not be a good fit for the other tenants.
Mobile
Other technology driven changes to consumer research are based on mobile technology. They are more far reaching in their implications, but not as far along in terms of adoption. They are often grouped under the general term ‘mobile analytics’.
The ubiquitous use of mobile devices has made it possible to monitor the movements of consumers as they pass through public spaces such as shopping centres and retail stores.
Each mobile phone broadcasts a unique signal called a MAC address that can be recorded by wi-fi or bluetooth equipment.
If the information about how consumers are actually using the centre can be in some way be aggregated, it can provide valuable input into decisions about tenant co-location and configuration of shopping centre space.
The familiar shopping centre heat map can be derived from summation of mobile phone MAC signals. The map shows the movement of people around a shopping centre with varying concentrations of shoppers depicted in a continuum of colors.
Mobile analytics is a sophisticated means of obtaining information that has been traditionally gathered in shopping centre exit surveys, such as trip frequency, stores visited, and time spent in various locations in the centre.
It can also be used analogously in the interior of a store to understand shopper flow patterns, conversion rates, strengths and weaknesses in merchandise adjacencies, and other factors.
For shopping centres, mobile analytics has advantages and disadvantages when compared with more conventional consumer research such as exit surveys.
The key advantages are:
It captures actual behaviour, rather than relying on the imperfect memories and reporting capabilities of the consumers themselves
It captures more data because it is monitoring everyone in the centre carrying a switched on mobile phone, rather than just a small sample of people interviewed at the exits
It is ongoing so long as the sensors are operating, rather than a one off survey
It does not require customers to spend time submitting to the interview process.
The technology uses only the phone’s unique signal – the MAC address – which includes no information about the identity or personal characteristics of the phone user.
This confers automatic protection of privacy, but at the same time, places a limit on the usefulness of the technology – it can count people and track their movements, but offers no insight into what kinds of people they are or what motivates their behavior.
Nonetheless, mobile analytics is an exciting emerging area of technology with useful applications to shopping centre research, particularly if it is supplemented by, and linked to, data gathered by other means, such as sales and consumer profiling.
Alternatives
If mobile analytics is not to your taste, perhaps you will like something simpler, like HappyOrNot, a system developed by a Finnish company of the same name.
HappyOrNot is a small display of four buttons mounted on movable pedestals that can be placed in strategic locations in your shopping centre or retail store.
Each of the buttons has an emoticon corresponding to ‘very happy’, ‘a bit happy’, ‘a bit unhappy’, or ‘very unhappy’. The customer hits the button that corresponds to his or her feeling about the shopping experience.
Responses are aggregated, segmented by time of day, location, and other variables, and sent on to the centre or store management.
Sure it’s simple, but there’s more to it than providing information to management about where and when it might be doing well or poorly. It also sends out a message to consumers in a fun way that your centre or store genuinely cares about what you think.
HappyOrNot may provide a bit of a gee-up to staff too. There’s quite a few execs in the retail industry who would welcome a good lever to do that.
Michael Baker is principal of Baker Consulting and can be reached at michael@mbaker-retail.com and www.mbaker-retail.com.