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What a Big-Data Business Model Looks Like
by R “Ray” Wang|10:00 AM December 6, 2012
The rise of big data is an exciting — if in some cases scary — development for business. Together with the complementary technology forces of social, mobile, the cloud, and unified communications, big data brings countless new opportunities for learning about customers and their wants and needs. It also brings the potential for disruption, and realignment. Organizations that truly embrace big data can create new opportunities for strategic differentiation in this era of engagement. Those that don't fully engage, or that misunderstand the opportunities, can lose out.
There are a number of new business models emerging in the big data world. In my research, I see three main approaches standing out. The first focuses on using data to create differentiated offerings. The second involves brokering this information. The third is about building networks to deliver data where it's needed, when it's needed.
一、使用数据创建差异化的产品/服务
二、扮演信息的经纪人的角色
三、建立网络，并在需要的时间和地点交付数据
Differentiation creates new experiences. For a decade or so now, we've seen technology and data bring new levels of personalization and relevance. Google's AdSense delivers advertising that's actually related to what users are looking for. Online retailers are able to offer — via FedEx, UPS, and even the U.S. Postal Service — up to the minute tracking of where your packages are. Map services from Google, Microsoft, Yahoo!, and now Apple provide information linked to where you are.
Big data offers opportunities for many more service offerings that will improve customer satisfaction and provide contextual relevance. Imagine package tracking that allows you to change the delivery address as you head from home to office. Or map-based services that link your fuel supply to availability of fueling stations. If you were low on fuel and your car spoke to your maps app, you could not only find the nearest open gas stations within a 10-mile radius, but also receive the price per gallon. I'd personally pay a few dollars a month for a contextual service that delivers the peace of mind of never running out of fuel on the road.
Brokering augments the value of information. Companies such as Bloomberg, Experian, Dun & Bradstreet already sell raw information, provide benchmarking services, and deliver analysis and insights with structured data sources. In a big data world, though, these propriety systems may struggle to keep up. Opportunities will arise for new forms of information brokering and new types of brokers that address new unstructured, often open data sources such as social media, chat streams, and video. Organizations will mash up data to create new revenue streams.
The permutations of available data will explode, leading to sub-sub specialized streams that can tell you the number of left-handed Toyota drivers who drink four cups of coffee every day but are vegan and seek a car wash during their lunch break. New players will emerge to bring these insights together and repackage them to provide relevancy and context.
For example, retailers like Amazon could sell raw information on the hottest purchase categories. Additional data on weather patterns and payment volumes from other partners could help suppliers pinpoint demand signals even more closely. These new analysis and insight streams could be created and maintained by information brokers who could sort by age, location, interest, and other categories. With endless permutations, brokers' business models would align by industries, geographies, and user roles.
Delivery networks enable the monetization of data. To be truly valuable, all this information has to be delivered into the hands of those who can use it, when they can use it. Content creators — the information providers and brokers — will seek placement and distribution in as many ways as possible.
This means, first, ample opportunities for the arms dealers — the suppliers of the technologies that make all this gathering and exchange of data possible. It also suggests a role for new marketplaces that facilitate the spot trading of insight, and deal room services that allow for private information brokering.
The most intriguing opportunities, though, may be in the creation of delivery networks where information is aggregated, exchanged, and reconstituted into newer and cleaner insight streams. Similar to the cable TV model for content delivery, these delivery networks will be the essential funnel through which information-based offerings will find their markets and be monetized.
Few organizations will have the capital to create end-to-end content delivery networks that can go from cloud to devices. Today, Amazon, Apple, Bloomberg, Google, and Microsoft show such potential, as they own the distribution chain from cloud to device and some starter content. Telecom giants such as AT&T, Verizon, Comcast, and BT have an opportunity to also provide infrastructure, however, we haven't seen significant movement to move beyond voice and data services. Big data could be their opportunity.
Meanwhile, content creators — the information providers and brokers — will likely seek placement and distribution in as many delivery networks as possible. Content relevancy will emerge as a strategic competency in delivering offers in ad networks based on the context by role, relationship, product ownership, location, time, sentiment, and even intent. For example, large wireless carriers can map traffic flows down to the cell tower. Using this data, carriers could work with display advertisers to optimize advertising rates for the most popular routes on football game days based on digital foot traffic.
There are many possible paths to monetize the big data revolution ahead. What's crucial is to have an idea of which one you want to follow. Only by understanding which business model (or models) suits your organization best can you make smart decisions on how to build, partner, or acquire your way into the next wave.
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