(This post is a summary of an independent project completed at Harvard Business School. Click here for the complete paper. The Burberry example is purely hypothetical.)
Apple's iBeacon, a location positioning system based on Bluetooth low energy technology, made the use of consumers' location in companies' marketing activities more prevalent. However, most documented uses of iBeacon and other similar systems have been focused on pushing marketing and sales promotions to consumers. Besides this, retailers have otherwise played a passive role, waiting for consumers to act on the promotional offers.
But imagine the scenario where consumers' location data is used to notify sales staff instead of pushing potentially annoying and irrelevant promotions to consumers:
You are on your way to your favorite luxury clothing retailer, Burberry, to buy a gift for your significant other's birthday. As you enter the Burberry store, your smartphone informs the Burberry sales staff (via their iPads) that you are in the store.
Upon notification, the sales staff can see your past Burberry purchases online and in-store and your interests based on your activity on Burberry.com (e.g. Burberry items you viewed, items in your online Burberry shopping cart, etc.). From this information, the sales staff noticed that you were viewing products under "Gifts for Him/Her."
The sales staff member greets you by name, introduces him/herself, and says that based on the information in your Burberry profile, you're searching for a gift for someone and asks if s/he can help you with recommendations.
After selecting the gift for your significant other, the sales staff tells you that the newest version of the scarf you purchased last year just arrived and asks if you want to view it. In addition, the sales staff invites you to an invitational-only Burberry event next Friday.
In a generalized version of the above scenario, luxury retailers' sales staff can use the knowledge that a high value customer is in the store, in combination with data on the customer's historical shopping behavior, to provide an enhanced in-store experience. In turn, this could lead to opportunities to cross-sell, up-sell, or simply increase the size of the customer's purchase basket. However, can concerns over privacy be a showstopper? Past research have shown that consumers are willing to give up information in return for personalized online services, but few have looked at this topic from an in-store perspective.
Preliminary data from a survey of ~200 consumers showed that while there are similarities in the results between consumers' sensitivity towards on- and off-line privacy, there are also differences as well. Like their online counterparts, respondents' answers showed that past negative experiences led to lower willingness to share and higher concerns about sharing their information. Furthermore, respondents' frequency of mobile shopping, retailers' use of trust-building mechanisms (i.e. transparent data collection policies and third party privacy safeguards), and the perceived value of the personalized services all led to increased comfort with sharing information.
However, unlike in the online realm, traditional trust-building mechanisms were not sufficient to mitigate respondents' concerns in sharing their personally identifiable information. It appears that only personal experience with the retailer (e.g. having made a previous purchase) decreased respondents' concerns, and increased their willingness, in sharing their personal information. Male respondents also tended towards having lower concerns and higher willingness to share in return for personalized experiences. Regardless of gender, these results suggest that retailers that require personally identifiable information need to begin by focusing on generating consumers' trust through first time purchases or other types of trust-building interactions prior to offering any personalization based on other data sources.
As retailers move towards refreshing their POS systems and unifying their commerce platforms they need to consider the data architecture required to support in-store personalized services and the IT infrastructure needed to ameliorate consumers' privacy concerns. Not all their customers will share the same level of sensitivity towards their information, and even within an individual that sensitivity will vary across different types of information. Responsive retailers that develop the flexibility to adapt to each customer's privacy sensitivity will be better situated to capture and deliver value to customers who want the personalized service and avoid the negative PR backlash from those who don't.