Mobile Concierge Services Take Consumer Data Analysis To The Next Level
Technology solutions as tools for consumer behavior data gathering, analysis, and automated online and mobile marketing have gone through a tremendous amount of development. Yet paradoxically, the next big leap forward in terms of mobile consumer insight will come from reintroducing the human factor to this tech-dominated environment.
Mobile concierge services (MCSs) are either SMS or app-based mobile services allowing you to request pretty much anything you like and a human operator will carry out everything from helping you with research through placing the order to delivery. The concept got a lot of coverage after Magic, a service reportedly put together over one weekend reported an impressive 17,000 requests in their first 48 hours of operation.
It has also just emerged that for over a year Uber has been working on its own version called Operator. And with the potential of using unoccupied cabs to deliver products, many agree Uber is onto something here.
While the potential disruption to retailers and the size of the opportunity have been well covered, no one seems to have identified the consumer behavior data goldmine MSCs are about to unlock:
A Glimpse At An MCS Enabled Future
Let’s fast forward a few years and assume that MCS are widely adopted by the mass market and became a standard shopping method:
- MCS will cannibalize a part of retailers’ traffic: Nothing unexpected. But a key disruption will stem from the consequential dent in retailers’ ability to analyze their consumers’ behavior. As retailers loose part of their traffic to MCSs, the robustness of their consumer data sample will shrink too. Subsequently, retailers’ analytics will become less accurate. So far this sounds like a typical ‘win some market share from a competitor’ story. But the sheer impact becomes apparent when we consider the way MCSs will be able to process these poached data samples.
The Real Value Of Human Operators
With every interaction, operators will be essentially conducting a one to one qualitative interview about consumer’s behavior and attitude patterns. This is an unprecedented development in analyzing m-commerce for a number of reasons:
- Emergence of non-intrusive surveying: MSCs bring the first ever form of non-intrusive surveying that includes dialogue. While marketers today say “Please give us your data, so we can guess what products you will want” the MSC marketers of tomorrow will be approached by consumers saying: “I have all this consumer data to share, can you please help me find the right product?” Operators will be relatively free to use prompt questions, coating them as ‘questions essential to satisfy the customer’.
- MCSs Will Add Lost Context To Consumer Data Analysis: Because of real time human interaction in place, the interpretation of consumer behavior data will become a lot more revealing. For example: “I don’t care much about the shoe color as long as it’s not orange” processed by a human MCS operator as ‘doesn’t like orange on shoes’, is a lot more revealing than what current analytics could offer on the subject. [“Consumer clicked on the shoe catalogue but didn’t click on different colour offerings” or “Consumer browsed all shoe colors except orange”]
Consumer Data From MCSs will be more honest and accurate: As MCS’ consumer databases grow, unprecedentedly honest and accurate data sets will emerge helping marketers shine more light on questions they have been trying to accurately answer for decades:
- How many people ask for a brand vs. product (i.e. Send me a pair of running shoes vs. Send me a pair of Nikes) and how exactly does this differ with various products?
- How purchasing patterns change with consumer’s mood or the state of hurry in which they are in?
While all these questions were subjects of surveys and studies in the past, for the first time now qualitative consumer data will be collected in real-time, during the real-life shopping experience of a consumer. In other words, Marketers will finally get to see how consumers actually think when they are shopping, instead of how they say they think in a survey environment or by leaving click traces online.
Finally, gathering data in this way will turn the ‘annoying’ consumers who end up having 20min back and forth and don’t buy anything into valuable assets providing consumer data and shining more light on reasons for not purchasing.
The convenience of having a personal shopping assistant is indisputable. Indeed, MCSs are and will be using it as one of their main unique selling points. The comeback of human factor to the technology dominated e-commerce works as a very convincing PR story for consumers. But make no mistake, creating a ‘nicer’ m-shopping experience by adding expensive humans is no free giveaway.
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