Bringing the Minority Report Retail Experience to Life: Big Data, IoT and Augmented Reality
We’ve been told that we are special ever since we were little, but how special are we? I challenge you to find another person in the world that is exactly like you. Such person probably doesn’t exist. So if that is the case the question is, why is our brand experience often identical to everyone else’s? Somehow, in the eyes of big brands, we are just like everyone else.
The Look-Alike Illusion
Let’s try to understand why that’s the case. If you were to find your double, how would you do it? You may start the search based on some personal attributes like, gender, age, ethnicity, etc. However, as you include more of these demographic dimensions (e.g. religion, education level, political orientation, etc.), you will discover that fewer are like you (i.e. matches you in every one of these dimension).
So the apparent similarity among consumers is merely an illusion that arises from the lack of data. We only look alike because brands don’t have enough data to distinguish us uniquely. With more data, brands can see us in 3D and recognize our uniqueness.
Every one of your customers are unique, just like you. They all have different needs, limitations and preferences. They all deserve a unique brand experience. The question is, how?
In order to personalize the experiences of your customers, brands must overcome two major challenges:
- Brands must understand their customers at a personal level. This requires huge amounts of personal and behavior data about their customers to uniquely distinguish them all, which can be difficult to obtain.
- Brands must deliver a unique experience for each customer base on the understanding of their individual preferences. This is even more challenging, because most brands operate at scale for efficiency (due to the economy of scale). Such individualized offerings are very difficult to scale.
The Digital Advantage of Big Data
Personalization is hard, because traditionally many brands don’t have enough data to understand their customers at a personal level, let alone deliver a unique experience.
Big data changes this. For the first time, brands have enough data to distinguish one customer from another. Beyond the demographic dimensions on which traditional segmentation is based, brand now have access to hundreds and thousands of social and behavior dimensions. So brands have enough data to overcome the first personalization challenge.
This is why brands like Amazon and Netflix is able to hyper-personalize (i.e. personalize to one single individual) and offer a truly unique experience to each customer. However, many brick-and-mortar retail brands seem to be lagging behind in their personalization efforts. This is not surprising, and there are good reasons for it. Digital-native brands have a huge advantage in overcoming both challenges of personalization:
- In the digital world, it is much easier to collect lots of behavior data from the consumers. Digital-native brands can easily track what product you searched, browsed, bought; what movies you rated well, what movies you watched, how much time you spent on researching a particular product, and other behavior. However, it is much more difficult for brick-and-mortar shops to obtain data on who visited the store and what items they browsed, tried on or other actions.
- Not surprisingly, it is also much easier to deliver a unique experienced in the digital world. This is because most of the digital environment is controlled by software and can be customized by data learned from a consumer’s behaviors. Everything from which product you see, to what background color is used in the e-store can all be customized by a customer’s preferences and few lines of codes. In the physical world, it would be impossible to manipulate the experience suite each and every individual.
This is one of the reason why so many companies are talking about digital transformation today. Because the digital-native enterprises are able to give their customers a much more personalized experience, they will win the long-term engagement with their customers. This not only enables them to acquire customers faster, but also retain them much more effectively. This is vital in an increasingly competitive market for people’s limited attention.
Ubiquitous Sensing via IoT
Due to the digital advantage, retail brands face serious challenges from their digital competitors. But this is all about to change. The Internet of Things (IoT) will enable a whole new level of behavior data collection like never before. When physical “things” in this world are able to communicate with each other, it offsets the advantages that digital brands have in understanding their customers. A pair of jeans on the shelf may one day know which mobile device is looking at them, which picked them up, and which actually tried them on.
Not only does IoT enable the collection of behavior data in the physical world, it also enables the collection of rich environmental metadata, which gives the context and meaning to the behavior. The metadata gives contextual cues that help brands understand why a consumer behaved the way he or she did, rather than just the fact that he or she did something.
For example, knowing that I bought a GoPro is one level of understanding, but knowing that I bought it with my niece for her birthday should completely change the way brands market future product to me. I wouldn’t see any irrelevant ads on GoPro accessories for a camera that I don’t own. Instead, an annual reminder of my niece’s upcoming birthday, and potential accessories for young women as birthday present can go much further.
Merging the digital behavior data with the physical give us a more complete 3D view of our customers. This will help us further personalize the experience of our customers at every touchpoint along their consumer journey.
The Retail Strike Back with AR
The ability to measure, track and understand customers at a personal level is only half of the battle. The other half is even more challenging for brick-and-mortar retail brands: delivering a unique experience based on their understanding of the customer’s preference. This is difficult because manipulating physical spaces and environment to meet any individual’s preference is nearly impossible. That is, until augmented reality (AR), which has been popularized by Pokemon Go.
Tomorrow’s consumers do not have to see the physical world as-is, they can overlay it with digital layers. Although it’s impossible to customize the items on a physical shelf to suite everyone’s preference, it is possible for AR to recognize items that are relevant to consumers and direct their attention to them. While it is not realistic to paint the wall of the retail space with everyone’s favorite color, AR can overlay the walls with any color or even background of a customer’s choosing.
AR provides brick-and-mortar brands with a digital layer on top of the physical world. This offsets the advantages that digital brands have in delivering a unique experience again. Just as in the purely-digital world, this digital layer is controlled by software and can be customized by code and as much preference data as consumers are comfortable providing.
Although the digital-native brands have a head start in personalization, technological innovations such as IoT and AR, will even the playing field. Eventually, every brand will have the capability to hyper-personalize their experience for everyone. Personalization is not merely a set of technologies, it is a customer-centric business strategy that recognizes the unique context of every individual customer.
Brands, digital or not, must learn to consider individual preferences in order to win customers’ long-term engagement. Besides, brands have no excuse not to provide us a personalized experience. All the required technologies already exist, for brands in both the digital and physical world. With this, perhaps one day we may have a personalized shopping experience like those in the movie Minority Report.
*This article originally appeared on CMSWire.
Michael Wu, Ph.D. is Lithium's Chief Scientist. His research includes: deriving insights from big data, understanding the behavioral economics of gamification, engaging + finding true social media influencers, developing predictive + actionable social analytics algorithms, social CRM, and using cyber anthropology + social network analysis to unravel the collective dynamics of communities + social networks.
Michael was voted a 2010 Influential Leader by CRM Magazine for his work on predictive social analytics + its application to Social CRM. He's a blogger on Lithosphere, and you can follow him @mich8elwu or Google+.
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