Posts tagged 商业模式
麦肯锡:十大tech-enable商业发展趋势
Aug 5th
Tech-enabled business,这个词最近很红。
到底什么才tech-enabled business(粗粗翻译的意思是IT支持下的商业模式)?什么才是最被看好的呢?
麦肯锡季刊的这篇文章给出了Top 10,原文点这里:
- Trend 1: Distributed cocreation moves into the mainstream
- Trend 2: Making the network the organization
- Trend 3: Collaboration at scale
- Trend 4: The growing ‘Internet of Things’
- Trend 5: Experimentation and big data
- Trend 6: Wiring for a sustainable world
- Trend 7: Imagining anything as a service
- Trend 8: The age of the multisided business model
- Trend 9: Innovating from the bottom of the pyramid
- Trend 10: Producing public good on the grid
每个理念的分析之后还给出了相关书籍阅读的参考!希望大家一起找到下一个金矿。
T
1. Distributed cocreation moves into the mainstream
分布式协作的先驱就是wikipedia和开源软件的开发者们了。而现在这样的互动模式渐渐成为business practice的主流了。
公司们以此来降低服务用户的成本和扩大范围。比如host一个客户服务的社区,有经验的客户还可以直接给新手们些建议。据估计,用户社区在处理一个问题的成本比传统的call centre低10%。
公司们还以此来做口碑营销( word-of-mouth marketing)。比如宝洁的 P&G’s Vocalpoint network of influential mothers。
Facebook甚至利用社区的力量来完成产品开发,最近30万名用户被招募来将facebook翻译成70种语言——翻译成法语竟然只花了1天时间。.
Further reading:
Jacques Bughin, Michael Chui, and Brad Johnson, “The next step in open innovation,” mckinseyquarterly.com, June 2008.
Michael Chui, Andy Miller, and Roger P. Roberts, “Six ways to make Web 2.0 work,” mckinseyquarterly.com, February 2009.
Josh Bernoff and Charlene Li, Groundswell: Winning in a World Transformed by Social Technologies, first edition, Cambridge, MA: Harvard Business School Press, 2008.
Clay Shirky, Here Comes Everybody: The Power of Organizing Without Organizations, reprint edition, New York, NY: Penguin, 2009.
2. Making the network the organization
让组织成为一张开放的网,在组织内部能够打破地域、部门、业务的边界;在组织外部,让非雇员也为组织做出贡献——这一现象被称为“tapping into a world of talent.”——比如利用互联网技术使得公司的研发部门可以access全世界的专家。
组织的结构正在剧烈的变化、升级。
Dow Chemical就自己建立了一个talent的network,将以前的雇员,比如退休人员都囊括进来。
Amazon.com的Mechanical Turk就是一个在线的labor market;Innocentive 和Zooppa则利用企业外部的资源来为企业提供内容服务。
从长远来看,网络式的组织将不再关注工人们的归属问题,而关注一项任务的协力执行。
Further reading:
Thomas W. Malone, The Future of Work: How the New Order of Business Will Shape Your Organization, Your Management Style, and Your Life, illustrated edition, Cambridge, MA: Harvard Business Press, 2004.
Lowell L. Bryan and Claudia I. Joyce, Mobilizing Minds: Creating Wealth from Talent in the 21st-Century Organization, New York, NY: McGraw-Hill, 2007.
Albert-Laszlo Barabasi, Linked: How Everything is Connected to Everything Else and What It Means for Business, Science, and Everyday Life, New York, NY: Plume, 2009.
3. Collaboration at scale
Across many economies, the number of people who undertake knowledge work has grown much more quickly than the number of production or transactions workers. Knowledge workers typically are paid more than others, so increasing their productivity is critical. As a result, there is broad interest in collaboration technologies that promise to improve these workers’ efficiency and effectiveness. While the body of knowledge around the best use of such technologies is still developing, a number of companies have conducted experiments, as we see in the rapid growth rates of video and Web conferencing, expected to top 20 percent annually during the next few years.
At one high-tech enterprise, the sales force became a crucible for testing collaboration tools. The company’s sales model relied on extensive travel, which had led to high costs, burned-out employees, and difficulty in scaling operations. The leadership therefore decided to deploy collaboration tools (including video conferencing and shared electronic workspaces, which allow people in different locations to work with the same document simultaneously), and it reinforced the changes with a sharp reduction in travel budgets. The savings on travel were four times the company’s technology investment. Customer contacts per salesperson rose by 45 percent, while 80 percent of the sales staff reported higher productivity and a better lifestyle.
In another instance, the US intelligence community made wikis, documents, and blogs available to analysts across agencies (with appropriate security controls, of course). The result was a greater exchange of information within and among agencies and faster access to expertise in the intelligence community. Engineering company Bechtel established a centralized, open-collaboration database of design and engineering information to support global projects. Engineers starting new ones found that the database, which contained up to 25 percent of the material they needed, lowered launch costs and sped up times to completion.
Despite such successes, many companies err in the belief that technology by itself will foster increased collaboration. For technology to be effective, organizations first need a better understanding of how knowledge work actually takes place. A good starting point is to map the informal pathways through which information travels, how employees interact, and where wasteful bottlenecks lie.
In the longer term, collaboration will be a vital component of what has been termed “organizational capital.”5 The next leap forward in the productivity of knowledge workers will come from interactive technologies combined with complementary investments in process innovations and training. Strategic choices, such as whether to extend collaboration networks to customers and suppliers, will be important.
Further reading:
Andrew McAfee, Enterprise 2.0: New Collaborative Tools for Your Organization’s Toughest Challenges, first edition, Cambridge, MA: Harvard Business School Press, 2009.
Erik Brynjolfsson and Adam Saunders, Wired for Innovation: How Information Technology is Reshaping the Economy, Cambridge, MA: The MIT Press, 2009.
James Manyika, Kara Sprague, and Lareina Yee, “Using technology to improve workforce collaboration,” What Matters, October 27, 2009.
Wolf Richter, David Bray, and William Dutton, “Cultivating the value of networked individuals,” in Jonathan Foster, Collaborative Information Behavior: User Engagement and Communication Sharing, Hershey, PA: IGI Global.
4. The growing ‘Internet of Things’
The adoption of RFID (radio-frequency identification) and related technologies was the basis of a trend we first recognized as “expanding the frontiers of automation.” But these methods are rudimentary compared with what emerges when assets themselves become elements of an information system, with the ability to capture, compute, communicate, and collaborate around information—something that has come to be known as the “Internet of Things.” Embedded with sensors, actuators, and communications capabilities, such objects will soon be able to absorb and transmit information on a massive scale and, in some cases, to adapt and react to changes in the environment automatically. These “smart” assets can make processes more efficient, give products new capabilities, and spark novel business models. 6
Auto insurers in Europe and the United States are testing these waters with offers to install sensors in customers’ vehicles. The result is new pricing models that base charges for risk on driving behavior rather than on a driver’s demographic characteristics. Luxury-auto manufacturers are equipping vehicles with networked sensors that can automatically take evasive action when accidents are about to happen. In medicine, sensors embedded in or worn by patients continuously report changes in health conditions to physicians, who can adjust treatments when necessary. Sensors in manufacturing lines for products as diverse as computer chips and pulp and paper take detailed readings on process conditions and automatically make adjustments to reduce waste, downtime, and costly human interventions.
As standards for safety and interoperability begin to emerge, some core technologies for the Internet of Things are becoming more widely available. The range of possible applications and their business impact have yet to be fully explored, however. Applications that improve process and energy efficiency (see trend number six, “Wiring for a sustainable world,” later in this article) may be good starting points for trials, since the number of successful installations in these areas is growing. For more complex applications, however, laboratory experiments, small-scale pilots, and partnerships with early technology adopters may be more fruitful, less risky approaches.
Further reading:
Michael Chui, Markus Löffler, and Roger Roberts, “The Internet of Things,” mckinseyquarterly.com, March 2010.
Hal R. Varian, Computer Mediated Transactions, Ely Lecture to the American Economics Association, Atlanta, GA, January 3, 2010.
Bernhard Boser, Joe Kahn, and Kris Pister, “Smart dust: Wireless networks of millimeter-scale sensor nodes,” Electronics Research Laboratory Research Summary, 1999.
Peter Lucas, “The trillion-node network,” Maya Design, March 1999.
5. Experimentation and big data
Could the enterprise become a full-time laboratory? What if you could analyze every transaction, capture insights from every customer interaction, and didn’t have to wait for months to get data from the field? What if . . . ? Data are flooding in at rates never seen before—doubling every 18 months—as a result of greater access to customer data from public, proprietary, and purchased sources, as well as new information gathered from Web communities and newly deployed smart assets. These trends are broadly known as “big data.” Technology for capturing and analyzing information is widely available at ever-lower price points. But many companies are taking data use to new levels, using IT to support rigorous, constant business experimentation that guides decisions and to test new products, business models, and innovations in customer experience. In some cases, the new approaches help companies make decisions in real time. This trend has the potential to drive a radical transformation in research, innovation, and marketing.
Web-based companies, such as Amazon.com, eBay, and Google, have been early leaders, testing factors that drive performance—from where to place buttons on a Web page to the sequence of content displayed—to determine what will increase sales and user engagement. Financial institutions are active experimenters as well. Capital One, which was early to the game, continues to refine its methods for segmenting credit card customers and for tailoring products to individual risk profiles. According to Nigel Morris, one of Capital One’s cofounders, the company’s multifunctional teams of financial analysts, IT specialists, and marketers conduct more than 65,000 tests each year, experimenting with combinations of market segments and new products.
Companies selling physical products are also using big data for rigorous experimentation. The ability to marshal customer data has kept Tesco, for example, in the ranks of leading UK grocers. This brick-and-mortar retailer gathers transaction data on its ten million customers through a loyalty card program. It then uses the information to analyze new business opportunities—for example, how to create the most effective promotions for specific customer segments—and to inform decisions on pricing, promotions, and shelf allocation. The online grocer Fresh Direct shrinks reaction times even further: it adjusts prices and promotions daily or even more frequently, based on data feeds from online transactions, visits by consumers to its Web site, and customer service interactions. Other companies too are mining data from social networks in real time. Ford Motor, PepsiCo, and Southwest Airlines, for instance, analyze consumer postings about them on social-media sites such as Facebook and Twitter to gauge the immediate impact of their marketing campaigns and to understand how consumer sentiment about their brands is changing.
Using experimentation and big data as essential components of management decision making requires new capabilities, as well as organizational and cultural change. Most companies are far from accessing all the available data. Some haven’t even mastered the technologies needed to capture and analyze the valuable information they can access. More commonly, they don’t have the right talent and processes to design experiments and extract business value from big data, which require changes in the way many executives now make decisions: trusting instincts and experience over experimentation and rigorous analysis. To get managers at all echelons to accept the value of experimentation, senior leaders must buy into a “test and learn” mind-set and then serve as role models for their teams.
Further reading:
Stefan Thomke, “Enlightened experimentation: The new imperative for innovation,” Harvard Business Review, February 2001, Volume 79, Number 2, pp. 66–75.
Stephen Baker, The Numerati, reprint edition, New York, NY: Mariner Books, 2009.
Thomas H. Davenport, Jeanne G. Harris, and Robert Morison, Analytics at Work: Smarter Decisions, Better Results, Cambridge, MA: Harvard Business Press, 2010.
David Bollier, The Promise and Peril of Big Data, The Aspen Institute, 2010.
Janaki Akella, Timo Kubach, Markus Löffler, and Uwe Schmid, “Data-driven management: Bringing more science into management,” McKinsey Technology Initiative white paper.
“Economist special report: The data deluge,” the Economist, February 25, 2010.
6. Wiring for a sustainable world
Even as regulatory frameworks continue to evolve, environmental stewardship and sustainability clearly are C-level agenda topics. What’s more, sustainability is fast becoming an important corporate-performance metric—one that stakeholders, outside influencers, and even financial markets have begun to track. Information technology plays a dual role in this debate: it is both a significant source of environmental emissions and a key enabler of many strategies to mitigate environmental damage. At present, information technology’s share of the world’s environmental footprint is growing because of the ever-increasing demand for IT capacity and services. Electricity produced to power the world’s data centers generates greenhouse gases on the scale of countries such as Argentina or the Netherlands, and these emissions could increase fourfold by 2020. McKinsey research has shown, however, that the use of IT in areas such as smart power grids, efficient buildings, and better logistics planning could eliminate five times the carbon emissions that the IT industry produces.
Companies are now taking the first steps to reduce the environmental impact of their IT. For instance, businesses are adopting “green data center” technologies to reduce sharply the energy demand of the ever-multiplying numbers of servers needed to cope with data generated by trends such as distributed cocreation and the Internet of Things (described earlier in this article). Such technologies include virtualization software (which enables the more efficient allocation of software across servers) to decrease the number of servers needed for operations, the cooling of data centers with ambient air to cut energy consumption, and inexpensive, renewable hydroelectric power (which of course requires locating data centers in places where it is available). Meanwhile, IT manufacturers are organizing programs to collect and recycle hazardous electronics, diverting them from the waste stream.
IT’s bigger role, however, lies in its ability to reduce environmental stress from broader corporate and economic activities. In a significant push, for example, utilities around the world are deploying smart meters that can help customers shift electricity usage away from peak periods and thereby reduce the amount of power generated by inefficient and costly peak-load facilities. Smart grids can also improve the efficiency of the transmission and distribution of energy and, when coupled with energy storage facilities, could store electricity generated by renewable-energy technologies, such as solar and wind. Likewise, smart buildings embedded with IT that monitors and optimizes energy use could be one of the most important ways of reducing energy consumption in developed economies. And powerful analytic software that improves logistics and routing for planes, trains, and trucks is already reducing the transportation industry’s environmental footprint.
Within the enterprise, both leaders and key functional players must understand sustainability’s growing importance to broader goals. Management systems that build the constant improvement of resource use into an organization’s processes and strategies will raise its standing with external stakeholders while also helping the bottom line.
Further reading:
Smart 2020: Enabling the low carbon economy in the information age, The Climate Group, 2009.
Giulio Boccaletti, Markus Löffler, and Jeremy M. Oppenheim, “How IT can cut carbon emissions,” mckinseyquarterly.com, October 2008.
William Forrest, James M. Kaplan, and Noah Kindler, “Data centers: How to cut carbon emissions and costs,” mckinseyquarterly.com, November 2008.
7. Imagining anything as a service
Technology now enables companies to monitor, measure, customize, and bill for asset use at a much more fine-grained level than ever before. Asset owners can therefore create services around what have traditionally been sold as products. Business-to-business (B2B) customers like these service offerings because they allow companies to purchase units of a service and to account for them as a variable cost rather than undertake large capital investments. Consumers also like this “paying only for what you use” model, which helps them avoid large expenditures, as well as the hassles of buying and maintaining a product.
In the IT industry, the growth of “cloud computing” (accessing computer resources provided through networks rather than running software or storing data on a local computer) exemplifies this shift. Consumer acceptance of Web-based cloud services for everything from e-mail to video is of course becoming universal, and companies are following suit. Software as a service (SaaS), which enables organizations to access services such as customer relationship management, is growing at a 17 percent annual rate. The biotechnology company Genentech, for example, uses Google Apps for e-mail and to create documents and spreadsheets, bypassing capital investments in servers and software licenses. This development has created a wave of computing capabilities delivered as a service, including infrastructure, platform, applications, and content. And vendors are competing, with innovation and new business models, to match the needs of different customers.
Beyond the IT industry, many urban consumers are drawn to the idea of buying transportation services by the hour rather than purchasing autos. City CarShare and ZipCar were first movers in this market, but established car rental companies, spurred by annual growth rates of 25 percent, are also entering it. Similarly, jet engine manufacturers have made physical assets a platform for delivering units of thrust billed as a service.
A number of companies are employing technology to market salable services from business capabilities they first developed for their own purposes. That’s a trend we previously described as “unbundled production.” More deals are unfolding as companies move to disaggregate and make money from corporate value chains. British Airways and GE, for instance, have spun off their successful business-process-outsourcing businesses, based in India, as separate corporations.
Business leaders should be alert to opportunities for transforming product offerings into services, because their competitors will undoubtedly be exploring these avenues. In this disruptive view of assets, physical and intellectual capital combine to create platforms for a new array of service offerings. But innovating in services, where the end user is an integral part of the system, requires a mind-set fundamentally different from the one involved in designing products.
Further reading:
Nicholas Carr, The Big Switch: Rewiring the World, from Edison to Google, reprint edition, New York, NY: W. W. Norton & Company, 2009.
IBM and University of Cambridge, “Succeeding through service innovation: A service perspective for education, research, business and government,” Cambridge Service Science, Management, and Engineering Symposium, Cambridge, July 14–15, 2007.
Peter Mell and Tim Grance, “The NIST definition of cloud computing,” Version 15, October 7, 2009.
8. The age of the multisided business model
Multisided business models create value through interactions among multiple players rather than traditional one-on-one transactions or information exchanges. In the media industry, advertising is a classic example of how these models work. Newspapers, magazines, and television stations offer content to their audiences while generating a significant portion of their revenues from third parties: advertisers. Other revenue, often through subscriptions, comes directly from consumers. More recently, this advertising-supported model has proliferated on the Internet, underwriting Web content sites, as well as services such as search and e-mail (see trend number seven, “Imagining anything as a service,” earlier in this article). It is now spreading to new markets, such as enterprise software: Spiceworks offers IT-management applications to 950,000 users at no cost, while it collects advertising from B2B companies that want access to IT professionals.
Technology is propagating new, equally powerful forms of multisided business models. In some information businesses, for example, data gathered from one set of users generate revenue when the business charges a separate set of customers for information services based on that data. Take Sermo, an online community of physicians who join (free of charge) to pose questions to other members, participate in discussion groups, and read medical articles. Third parties such as pharmaceutical companies, health care organizations, financial institutions, and government bodies pay for access to the anonymous interactions and polls of Sermo’s members.
As more people migrate to online activities, network effects can magnify the value of multisided business models. The “freemium” model is a case in point: a group of customers gets free services supported by those who pay a premium for special use. Flickr (online storage of photos), Pandora (online music), and Skype (online communication) not only use this kind of cross-subsidization but also demonstrate the leveraging effect of networks—the greater the number of free users, the more valuable the service becomes for all customers. Pandora harnesses the massive amounts of data from its free users to refine its music recommendations. All Flickr users benefit from a larger photo-posting community, all Skype members from an expanded universe of people with whom to connect.
Other companies find that when their core business is part of a network, valuable data (sometimes called “exhaust data”) are generated as a by-product. MasterCard, for instance, has built an advisory unit based on data the company gathers from its core credit card business: it analyzes consumer purchasing patterns and sells aggregated findings to merchants and others that want a better reading on buying trends. CHEP, a logistics-services provider, captures data on a significant portion of the transportation volume of the fastest-moving consumer goods and is now building a transportation-management business to take advantage of this visibility.
Not all companies, of course, could benefit from multisided models. But for those that can, a good starting point for testing them is to take inventory of all the data in a company’s businesses (including data flowing from customer interactions) and then ask, “Who might find this information valuable?” Another provocative thought: “What would happen if we provided our product or service free of charge?” or—more important, perhaps—“What if a competitor did so?” The responses should provide indications of the opportunities for disruption, as well as of vulnerabilities.
Further reading:
Chris Anderson, Free: How Today’s Smartest Businesses Profit by Giving Something for Nothing, New York, NY: Hyperion, 2009.
Annabelle Gawer ed., Platforms, Markets and Innovation, Cheltenham, UK: Edward Elgar Publishing, 2010.
David S. Evans, Andrei Hagiu, and Richard Schmalensee, Invisible Engines: How Software Platforms Drive Innovation and Transform Industries, Cambridge, MA: The MIT Press, 2006.
9. Innovating from the bottom of the pyramid
The adoption of technology is a global phenomenon, and the intensity of its usage is particularly impressive in emerging markets. Our research has shown that disruptive business models arise when technology combines with extreme market conditions, such as customer demand for very low price points, poor infrastructure, hard-to-access suppliers, and low cost curves for talent. With an economic recovery beginning to take hold in some parts of the world, high rates of growth have resumed in many developing nations, and we’re seeing companies built around the new models emerging as global players. Many multinationals, meanwhile, are only starting to think about developing markets as wellsprings of technology-enabled innovation rather than as traditional manufacturing hubs.
In parts of rural Africa, for instance, traditional retail-banking models have difficulty taking root. Consumers have low incomes and often lack the standard documentation (such as ID cards or even addresses) required to open bank accounts. But Safaricom, a telecom provider, offers banking services to eight million Africans through its M-PESA mobile-phone service (M stands for “mobile,” pesa is Swahili for “money”). Safaricom allows a network of shops and gas stations that sell telecommunications airtime to load virtual cash onto cell phones as well.
In China, another technology-based model brings order to the vast, highly dispersed strata of smaller manufacturing facilities. Many small businesses around the world have difficulty finding Chinese manufacturers to meet specific needs. Some of these manufacturers are located in remote areas, and their capabilities can vary widely. Alibaba, China’s leading B2B exchange, with more than 30 million members, helps members share data on their manufacturing services with potential customers and handles online payments and other transactions. Its network, in effect, offers Chinese manufacturing capacity as a service, enabling small businesses anywhere in the world to identify suppliers quickly and scale up rapidly to meet demand.
Hundreds of companies are now appearing on the global scene from emerging markets, with offerings ranging from a low-cost bespoke tutoring service to the remote monitoring of sophisticated air-conditioning systems around the world. For most global incumbents, these represent a new type of competitor: they are not only challenging the dominant players’ growth plans in developing markets but also exporting their extreme models to developed ones. To respond, global players must plug into the local networks of entrepreneurs, fast-growing businesses, suppliers, investors, and influencers spawning such disruptions. Some global companies, such as GE, are locating research centers in these cauldrons of creativity to spur their own innovations there. Others, such as Philips and SAP, are now investing in local companies to nurture new, innovative products for export that complement their core businesses.
Further reading:
Jeffrey R. Immelt, Vijay Govindarajan, and Chris Trimble, “How GE is disrupting itself,” Harvard Business Review, October 2009, Volume 87, Number 10, pp. 56–65.
“Special report on innovation in emerging markets: The world turned upside down,” the Economist, April 15, 2010.
C. K. Prahalad, The Fortune at the Bottom of the Pyramid: Eradicating Poverty Through Profits, fifth edition, Philadelphia, PA: Wharton School Publishing, July 2009.
10. Producing public good on the grid
The role of governments in shaping global economic policy will expand in coming years.7 Technology will be an important factor in this evolution by facilitating the creation of new types of public goods while helping to manage them more effectively. This last trend is broad in scope and draws upon many of the other trends described above.
Take the challenges of rising urbanization. About half of the world’s people now live in urban areas, and that share is projected to rise to 70 percent by 2050. Creative public policies that incorporate new technologies could help ease the economic and social strains of population density. “Wired” cities might be one approach. London, Singapore, and Stockholm have used smart assets to manage traffic congestion in their urban cores, and many cities throughout the world are deploying these technologies to improve the reliability and predictability of mass-transit systems. Sensors in buses and trains provide transportation planners with real-time status reports to optimize routing and give riders tools to adjust their commuting plans.
Similarly, networked smart water grids will be critical to address the need for clean water. Embedded sensors can not only ensure that the water flowing through systems is uncontaminated and safe to drink but also sense leaks. And effective metering and billing for water ensures that the appropriate incentives are in place for efficient usage.8
Technology can also improve the delivery and effectiveness of many public services. Law-enforcement agencies are using smart assets—video cameras and data analytics—to create maps that define high-crime zones and direct additional police resources to them. Cloud computing and collaboration technologies can improve educational services, giving young and adult students alike access to low-cost content, online instructors, and communities of fellow learners. Through the Web, governments are improving access to many other services, such as tax filing, vehicle registration, benefits administration, and employment services. Public policy also stands to become more transparent and effective thanks to a number of new open-data initiatives. At the UK Web site FixMyStreet.com, for example, citizens report, view, and discuss local problems, such as graffiti and the illegal dumping of waste, and interact with local officials who provide updates on actions to solve them.
Exploiting technology’s full potential in the public sphere means reimagining the way public goods are created, delivered, and managed. Setting out a bold vision for what a wired, smart community could accomplish is a starting point for setting strategy. Putting that vision in place requires forward-thinking yet prudent leadership that sets milestones, adopts flexible test-and-learn methods, and measures success. Inertia hobbles many public organizations, so leaders must craft incentives tailored to public projects and embrace novel, unfamiliar collaborations among governments, technology providers, other businesses, nongovernmental organizations, and citizens.
Further reading:
Jason Baumgarten and Michael Chui, “E-government 2.0,” mckinseyquarterly.com, July 2009.
Bas Boorsma and Wolfgang Wagner, “Connected urban development: Innovation for sustainability,” NATOA Journal, Winter 2007, Volume 15, Number 4, pp. 5–9.
O’Reilly Radar Government 2.0 (radar.oreilly.com)
Connected Urban Development (connectedurbandevelopment.org)
Building a smarter planet (asmarterplanet.com)
The pace of technology and business change will only accelerate, and the impact of the trends above will broaden and deepen. For some organizations, they will unlock significant competitive advantages; for others, dealing with the disruption they bring will be a major challenge. Our broad message is that organizations should incorporate an understanding of the trends into their strategic thinking to help identify new market opportunities, invent new ways of doing business, and compete with an ever-growing number of innovative rivals.
About the Authors
Jacques Bughin is a director in McKinsey’s Brussels office; Michael Chui is a senior fellow of the McKinsey Global Institute; James Manyika is a director in the San Francisco office and a director of the McKinsey Global Institute.
The authors wish to acknowledge the important contributions of our colleague Angela Hung Byers.
Notes
1 James M. Manyika, Roger P. Roberts, and Kara L. Sprague, “Eight business technology trends to watch,” mckinseyquarterly.com, December 2007.
2 Two of the original eight trends merged to form a megatrend around distributed cocreation. We also identified three additional trends centered on the relationship between technology and emerging markets, environmental sustainability, and public goods.
3 A full summary of survey results will be available on mckinseyquarterly.com in September 2010.
4 “How companies are benefiting from Web 2.0: McKinsey Global Survey Results,” mckinseyquarterly.com, September 2009.
5 Erik Brynjolfsson and Adam Saunders, Wired for Innovation: How Information Technology is Reshaping the Economy, Cambridge, MA: The MIT Press, 2009.
6 Hal Varian explores some of these themes, along with the effects associated with “experimentation and big data” (described later in this article), in his 2010 American Economics Association lecture cited in this section’s Further reading.
7 Peter Bisson, Elizabeth Stephenson, and S. Patrick Viguerie, “Global forces: An introduction,” mckinseyquarterly.com, June 2010.
8 Peter Bisson, Elizabeth Stephenson, and S. Patrick Viguerie, “Pricing the planet,” mckinseyquarterly.com, June 2010.
原文地址:
名为Promoted tweets的广告平台:twitter今起滚滚财源开阀
Apr 14th
Twitter联合创始人比兹·斯通(Biz Stone)4月13日在公司博客上撰文称,Twitter今天将发布Promoted Tweets广告平台。
这个最近估值达10亿美元和筹集了巨额风险投资的红人twitter终于要让估值变现了。广告客户和用户多年来一直等待twitter在广告模式上作出决定,现在滚滚财源真的近了。
4月13日twitter上的广告就会开始滚动出现,约2%~10%的twitter用户会看到他们。第一批的广告主一共有10家:星巴克(Starbucks)、百思买(Best Buy)、维珍(Virgin America)、Bravo、红牛(Red Bull)和索尼(Sony Pictures)
垂涎已久的大公司
纽约时报昨天就发了预告文章(原文地址:http://www.nytimes.com/2010/04/13/technology/internet/13twitter.html?src=busln),并拿星巴克为例做了分析。
企业们现在都疯狂的想利用social media来营销,但是web2.0就是一锅乱哄哄、吵嚷不断的粥。星巴克官方会经常在twitter上发布一些促销信息,比如今天哪家哪家店送点心,哪家店打折了之类。但是一条消息刚发一秒可能就石沉大海,永无浮出水面的日子了,即使用户在搜索“Starbucks”都不再能看到这些促销推,因为可能千万个用户在发“下了班Starbucks聊聊”之类的推。
对于企业的这类需求,Promoted Tweets广告平台就能满足了,它能保证发布的信息被特别显示和标注,插入即时会话流,并不被淹没。
但用户搜索的关键词是被某个广告主买下的,那么广告推广信息就会出现在搜索结果的头部,而普通关键词的搜索结果是按照tweets的发布时间来排序的,没有人工干预。另外,用户把鼠标移到广告推上时,这条推会显示为醒目的黄色。
但是用户的反馈会是什么?
本人来说,我听到Promoted tweets之后,微微笑了下,然后打了个大问号。
看Huffingtonpost上贴了一张截图:
Y说:“所以我从现在开始屏蔽红牛、百思买、索尼……广告仍会出现吗?”
Twitter的发展之路
根据comScore的数据,Twitter.com今年3月的唯一身份访问者达到2.23亿 ,而一年前这个数字为52万4千 。并且这2亿多的用户还不包括数百万通过第三方应用如TweetDeck和Tweetie来使用tweet服务的用户。
但是 Twitter 在如何把用户变现的推进上,一直不疾不徐。创始人Evan Williams 和Biz Stone一直希望能够学习Google的盈利模式:先创造一种服务,让人们都使用它,然后再考虑如何赚钱。
而在Promoted Tweets广告平台计划宣布前, Twitter的营收仅仅靠提供google 和微软等巨头搜索twitter上内容的授权许可。因此这个广告平台可以说是 Twitter在自身重大商业模式决策上跨出的第一步。
Twitter创始人Biz Stone宣布Promoted Tweets的博文中文翻译
过去几年中,我们一直坚持引入一种传统的网络广告模式,因为我们希望在盈利以前优化价值。信息的公开交换为相像的个人、组织和公司创造了机遇,而我们也在这种交换中实现了价值,并计划以有意义的、恰当的方式来增强这种价值。
我们对放慢商业化步伐的顽固坚持已经令一些Twitter观察者感到失望,而我们持这种思索再三的立场是为了把用户放在第一位、增强现有价值以及创造利润。
我们希望,在今天我们推出名为“Promoted Tweets”的服务时,用户将与我们一样充满热情。这种非传统的服务易于使用,对Twitter来说意义重大。在今天召开的AdAge Digital会议上,我们的首席运营官迪克·科斯特洛(Dick Costolo)将透露这种备受期待的服务的细节。而在明天的“Chirp开发者大会”上,科斯特洛和我们无所畏惧的领导者埃文·威廉姆斯(Evan Williams)将进一步讨论这种应用及其对Twitter的生态系统来说意味着什么。
今天的公告我们已经等了很久,现在终于能与用户一起分享,我们为此感到激动。在这一项目成熟后,我们将会透露更多信息;而在其成长过程中,我们将学到很多。
问:你们推出的是什么产品?什么是“Promoted Tweets”?第一批的广告主是谁?
答:我们推出了第一阶段的“Promoted Tweets”平台。我们拥有多家创新的广告合作伙伴,包括百思买、Bravo、红牛、索尼影业、星巴克和美国维珍航空,未来还将宣布更多的合作伙伴。 “Promoted Tweets”是企业和其他机构希望向用户群体展示的普通Twitter消息。
问:用户将会看到什么?正常的推会受影响吗?
答:你将会在Twitter.com搜索结果页面的最上方看见由我们广告合作伙伴发布的Twitter消息。我们认为,“Promoted Tweets”将会与你产生共鸣。我们会尝试了解这些消息是否与用户产生共鸣,并停止展示无法与用户产生共鸣的消息。“Promoted Tweets”将会带有明显的“Promoted”标记,表示这是由广告主付费的。不过在所有其他方面,这些消息只是普通的Twitter消息。对于关注某一品牌的用户而言,这些消息将会有组织地出现在消息流上。“Promoted Tweets”将拥有普通Twitter消息的所有功能,包括回复、转发和收藏。在搜索结果页面上同时只会出现一条“Promoted Tweets”。
问:你提到第一阶段,那么你们未来还有什么计划?
答:在我们开始未来的阶段之前,我们希望更好的了解“Promoted Tweets”是否适合用户,以及该功能的用户体验和广告主价值。一旦这些全部完成,我们计划允许“Promoted Tweets”出现在Twitter客户端和其他合作伙伴的产品中。此外,“Promoted Tweets”将不仅仅出现在Twitter搜索中,还将以对用户有用的方式出现在用户的消息流中。
问:这是不是你所说的,我们将会喜欢,并且非常出色的产品?
答:总体而言我们对这一平台感到兴奋,此外我们还需要强调这一平台的几个方面。由于所有“Promoted Tweets”都是有组织的Twitter消息,因此在这一平台上不会出现与Twitter整体不和谐的单条广告。这与传统的搜索广告,以及近期的社交网络广告不同。“Promoted Tweets”将是具有时效性的。与任何其他Twitter消息类似,用户和“Promoted Tweets”之间的实时联系将提供与用户相关的即时信息。
“Promoted Tweets”和普通Twitter消息有一个最主要的不同。“Promoted Tweets”必须符合更高的标准,即必须能使用户产生共鸣。这意味着,如果用户不与某条“Promoted Tweets”互动,例如回复、收藏或转发,那么这条消息将会消失。
问:还有其他可以介绍的吗?
答:这是一个新的产品,我们希望它变得更好。我们很高兴你能使用这一产品,并希望获得你的反馈。
ebay的中国生意:B2C带来的第二春
Mar 5th
太多跨国企业饮恨中国的故事,失利者卷土重来的案例却少之又少。
eBay中国或许算一个。
这个中国电子商务最著名的搁浅者正迅速变身为强劲增长的代名词:连续三年,eBay中国实现年均近100%的业绩增长,其2009年的卖家交易金额扩大至7亿美元,是少数在经济危机中逆势高速增长的在华跨国企业之一。
而ebay的这波增长可以归结在一个词“B2C”。
eBay中国之所以能够迅速“复活”,就在于其扬长避短、定位跨国交易的战略充分发挥了eBay全球平台的优势。
Ebay助力B2C的生意
过去几年,基于中国制造的跨国小额交易表现抢眼,已成为中国互联网市场增长最快的细分领域之一,尤其是全球性经济危机的爆发,更促使大量遭遇出口困境的中国工厂和商家开始尝试跨国B2C业务。这为eBay平台提供了一个拥趸群体,并反过来ebay助力这一市场更迅速膨胀。
ebay是一个拥有全球3亿多买家的超级平台,其主要用户来自于美国等电子商务环境成熟的国家,本身代表着巨大的在线消费能力;同 时,eBay旗下的贝宝支付工具可以支持120多个国家和地区、20多种货币的在线支付,在全球电子商务交易支付环节的地位深入人心。这两点是任何中国本土电子商务平台短期内无法突破的竞争壁垒。更为重要的是,与难以接受付费模式的本土C2C卖家不同,跨国卖家更容易接受eBay通行全球的商品收费规则,这让深陷易趣亏损泥潭的eBay中国在“断腕”之后,反而找到了最适合自己的盈利模式。
走出低谷并驱除失败诅咒的eBay中国相信他们已经走在正确的道路上,而且未来潜力无限。“跨国交易甚至还谈不上起飞,现在刚刚滑上飞机跑道。”eBay大中华区及南亚区总裁廖光宇说。
重塑规则
在看似光明的前景背后,这家跨国公司在中国的涅磐故事并非看上去那么轻松。
在2007年初eBay中国重整,将易趣转手 TOM后,eBay在中国保留了B2C业务。因为即使是在与淘宝的全面交战失利时,其跨国B2C交易就已表现出强劲的增长。在重整后,原易趣的忠实卖家普遍感到失望和灰心,除了部分转向淘宝,有过eBay跨国交易经验的卖家大多随eBay转战香港站。但在最初的“搬家”动荡期,卖家们很难得到eBay的贴心服务,遇到问题只能打电话给香港的客服,也很少能被满意地解决。
沿着这条令人沮丧的路径发展,eBay不过是在滑向更远的失败。但此时的eBay全球策略发生了一些改变,悄然为eBay中国区业务的重新上路埋下种子。
2007 年中,执掌eBay10年的惠特曼急流勇退,将首席执行官让位给约翰·多纳霍(John Donahoe),后者就此开始了备受争议的平台改革。为了与亚马逊和其它电子商务平台竞争,多纳霍致力于将eBay塑造成一家超级购物中心,而不是继续 依赖eBay传统的旧货竞价拍卖模式。这一改革的典型做法是,降低卖家在eBay上发布产品的费用门槛,以吸引那些大卖家,并鼓励他们以固定价格销售产 品。
一些卖家指责这些政策破坏了eBay传统文化,并且抛弃了依赖拍卖模式的小卖家。比如,卖家必须付出比以往更多的沟通成本,交易成功后 也要付给eBay更多的费用。但eBay显然并不打算改变这些政策,其背后的逻辑很简单:如果卖家不能提供令买家满意的产品和服务,那将是双输的格局。多 纳霍同时也是坚定的买家至上主义者,过去两三年里他对eBay的许多修改都旨在提高买家体验和满意度,其中包括建立复杂的卖家服务评价体系(DSR)。
这 种向B2C业务的倾斜,暗合了中国市场的特点。中国卖家靠近成本低廉的商品产地,而且可以提供多样化的产品。很多国外的采购商发现,他们可以与中国卖家合 作,在线采购更便宜更丰富的商品。但是,挑战也先天存在:物流成本高且速度慢。eBay平台上70%以上的交易都采用了免运费模式,这就要求卖家所选择的 物流方式必须有足够的竞争力,这恰恰是中国卖家最大的弱点所在。
eBay的策略是与第三方物流比如美国邮政和中国邮政合作,协助卖家得到更好的服务;另一种方法是鼓励大卖家使用海外仓储服务,提前将货放到海外仓库,实现事实上的同城发货或本国交易,而且成本不见得增加多少。
多 纳霍数次宣称,将优先发展中国的跨国B2C贸易业务。为此,这家曾被认为本地化严重滞后的跨国公司开始“讨好”中国卖家。措施包括:逐渐建立本地化的客户 服务热线,为大卖家提供贴身的客户经理服务,甚至由eBay的销售人员直接跑客户,为中国卖家提供货源。目前,eBay中国的本地客服已达1000多人, 每个VIP卖家都拥有一个客户经理可以进行直接沟通。而eBay的销售部门则通过与一些大卖家的合作,培养了中国的eBay销售助理群体,这个新的职业类 似于电子商务服务托管商,帮助那些没有经验的大商家在eBay上进行销售。
这些改变恰逢其时。在错失了中国C2C业务的迅速膨胀期后,卖掉易趣独立运营的eBay中国区反而抓住了跨国B2C爆发的时机。其2009年半年报显示,跨国B2C业务已占传统拍卖业务的六成。
不过,多位eBay中国卖家均担心,随着越来越多追求销量的大卖家拥入eBay平台,卖家的平均利润会因此而摊薄。
对 此,廖光宇回应道,eBay平台上买家的数量还是会保持增长,目前eBay正在开拓印度、俄罗斯、南非、印尼等新兴市场,这些市场的买家拥有足够的消费潜 力。另一方面,以中国卖家打交道最多的美国市场为例,即使作为在线购物最发达的国家,美国人用于线上的消费比例也仅约7%,从线下到线上的消费转移空间依 然很大。
不仅是成长性的问题,与最初进入中国的境遇类似,eBay也正在遭受意料之中的挑战,比如亚马逊。与eBay相比,亚马逊在争取小 卖家方面提供了更为人性化的服务,商家只需将商品发给亚马逊公司,剩下的交易过程可以由亚马逊公司全盘操作。尽管中国卖家要登陆亚马逊依然面临不少现实障 碍,比如跨国贸易的物流速度,但亚马逊咄咄逼人的进攻姿态某种程度上迫使eBay必须做出改变。eBay在中国的老对手阿里巴巴也开始发力,借推出“全球 速卖通”服务与eBay争夺跨国B2C贸易客户。
1月27日,eBay有所应对,其再次调整了其收费政策,对于大卖家,eBay商店阶梯式 的收费系统只向其收取每月每件上架物品最低3美分的服务费,相当于把当前的收费标准调低了90%。而对于一直抱怨受到歧视的小卖家,eBay也表示将取消 一美元以下的拍卖商品的上架费,允许用户每月免费上架100件物品,这是此前数量的数倍。
在不少卖家看来,eBay最大的对手依然是其自 己。1月中旬,eBay邀请了200多位中国超级卖家在上海聚会,并为其中的佼佼者颁奖。会议结束时后,一位卖家表示自己略感失落,因为eBay中国最大 的卖家年销售额也就1000多万美金,“在我的想象中,这个金额应该更大。”他说。
Craigslist模式在中国如何复制?中国特色的差异化在哪里?
Mar 1st

像大多数回国投身互联网创业的人一样,赶集网创始人杨浩涌在2004年底的打算,是把自己当时用得正顺手的网站Craigslist 复制到中国去。这个网站类似于无需预先登录的BBS,用户能在上面发帖买卖二手货、交友、租房子、找工作,杨浩涌就曾用它卖掉了自己的吉他和沙发。虽然这个类似BBS的网站极其简单,但当时的用户数和访问量都已经很大。仅靠向每条招聘信息收费几十美元,当时其年收入就已经过千万美元。
现在来看,杨浩涌的确幸运地赌对了一个好方向。如今在全美的手机搜索中,排名第一的不是Google,而是Craigslist这家分类信息网站。虽然这个技术简单的网站基本都是文本信息,但按所有英文网站的浏览量排名,它排名第7位。
像大多数“复制者”一样,杨浩涌也做足了适应中国本地市场的功夫,但结果依然让人意外。
据调查机构AIMGroup估计,Craigslist2009年的营收额超过1亿美元,其他更乐观的研究机构则估计是3亿。但这家美国的著名网站只有 40多名员工,办公楼仅是一栋3层楼的公寓。而在北京中关村软件园的华夏科技大厦里,赶集网已经占据了半层楼的空间,两大间办公区里坐着300来名员工。 杨浩涌对《第一财经周刊》称,赶集网去年的收入已经达到上千万人民币。
但也仅仅是这上千万人民币。
人们爱上Craigslist是因为这个网站的信息足够多和有效
在创业气氛浓厚的硅谷,杨浩涌此前的4年间也雄心勃勃地组过团队、写过数次商业计划书、见过VC,但通常在一次见面后VC们就了无音讯。但当他这次拿着复制Craigslist的点子去找风险投资人时,投资人第一次表现出了兴趣,并建议他赶紧回国,着手这个需要的启动资金并不高的项目。
拿着从朋友那儿凑来的10万美金,杨浩涌在2004年12月底回到北京。在美国呆了5年,“对中国互联网一点儿都不懂”的杨浩涌最开始几乎原原本本地把 Craigslist搬了过来,这个网站一开张就有北京、上海、广州3个城市分站,还有包括交友、票务在内的8个类别。但按照杨每个月花5万、先坚持16 个月的预算计划,这家资金紧张的小公司这时只有10个员工,只能匀出两个人在各个网站论坛上发“我在赶集网租到了房子/卖掉了电视”之类的推广帖。人力有限而目标太多,导致每个类别的推广力度都不够,都只有少量帖子,访问量增长缓慢。
原本以为自己是市场首入者的杨浩涌发现,当时不仅已经有一家叫做“站台”的分类信息网站做得不错,而且新浪和eBay都正在进入这个领域。杨浩涌的赶集网在2005年2月正式上线后不过一两个月,与它面貌相似的网站就已经多达两三千家。
这正是赶集与作为分类信息网站鼻祖的Craigslist所处环境最大的不同。1995年成立后,Craigslist在头5年内一直没有收入,也就没有看到商业利益,也没有继而跟进的模仿者与其争抢用户。但杨浩涌却无法以不徐不疾的态度来经营赶集,他必须考虑如何超过一大批同类型的对手,抢先把人气的雪球滚起来。
作为Craigslist资深用户的杨浩涌琢磨,人们之所以爱上Craigslist,是因为他们想干某件事时,这个网站的这类信息足够多和有效。杨浩涌此后开始只把人力投在人气最旺的三个类别:租房、二手、交友。
赶集网和Craigslist:不一样的推广方式
这个“爱玩儿”的耶鲁毕业生也颇有机智,他在国内读大学期间,就干过组旅游团、包电影院卖票之类的事情。他并未像Craigslist的创始人Craig 那样,靠免费发送由自己列出的旧金山吃喝玩乐信息来慢慢积累人气。考虑到潜在用户多在小区和高校里,杨浩涌带着员工,从海淀到朝阳,给小区居民发放背后带有在周围修电器、搬家等服务电话的宣传卡,给高校每间宿舍派送背后印有空白课表的宣传单,用这种老式办法一个区域一个区域地扫荡过去。
这类做法见效明显,杨浩涌发现,每发完一千张宣传单,赶集网的新访问者就会增加数百个。由于这类走街串巷的事情只能在北京做,杨浩涌干脆把精力集中在北京,而在上海和广州网站发帖推广的事情停了下来。
半年以后,这些做法带来的效果已经很明显。虽然赶集网的总访问量在分类信息网站中并非最大,但其北京地区的用户访问量则是稳居第一。杨浩涌的逻辑—再花同样多的钱,赶集网就能把这个成绩复制到下一城市—也打动了不少VC。这对赶集网至关重要,因为当它打算扩展到全国时,有多少钱、能投入多少广告,几乎等同于能引来多少新用户。
赶集网:与Google的合作使之成名
当时,恰巧Google正打算进入中国市场,但中国政府彼时还不允许外资公司拥有ICP(互联网内容提供商)牌照,Google因此需要一个中国合作伙伴。杨浩涌在Google工作的两个朋友,也是赶集网最初的两个筹资人,很快就为两方搭上了线。Google和这名在硅谷工作过的耶鲁毕业生聊得很投机,2006年初,双方成立了一家叫做谷翔的合资公司,运营Google.cn域名。赶集网则可每年从这家合资公司的收益中分得一部分。
这使得赶集网再无生死之虞,所得资金不仅足够维持运营,而且能做更多推广,更意外的好处是,它因Google而获得了一定的知名度。2006年,赶集进入了上海、广州和深圳三个一线城市。每进入一个新城市,赶集都先在这个城市的地方网站上遍洒广告,再跟踪访问量源自什么网站,逐步在半年后收缩为仅在少数效果好的媒体上投广告。此后两年,它投放广告的城市渐次增至前十大、前二十大的城市,每月推广费也增至几十万,开设分站但未作推广的城市则达200多个。
在这个短期内无钱可挣的行业里,绝大多数分类信息网站则由于缺乏资金和推广而荒芜。如今,全国性的分类信息网站已经不到10家。
更多垃圾,更多人工
除了推广费用更高外,在中国进行这门生意的艰难之处在于,所需的人力成本也更多。
赶集和Craigslist的用户们的共通之处在于,他们最在乎的事情就是信息是否足够多,以及真实有效。以租房为例,除了上赶集、58 同城这种网站外,期盼找到个人房源的人们还愿意在水木清华BBS的租房版、豆瓣的租房小组这种连朝阳区海淀区都不分的地方,一页一页地翻找帖子,就是因为中介更少、信息更真实。
这件事情是如此重要,以至于Craigslist的创始人Craig将CEO职务转任他人,自己作为一名专职客服人员,每天花8小时以上的时间,和另外4个客户服务代表把商业广告和恶意信息一一删除。
但杨浩涌就没那么好命。以租房信息为例,在美国,成为一名房产经纪人意味着他有远高于个人租房者的信誉,因而没有人愿意冒充个人。但在中国,房产中介们向来口碑不佳,并且因为要收中介费而招人讨厌,他们因而更愿意冒充个人发帖。而且,发布招聘信息,向应聘者先收几百块报名费,而后消失得无影无踪的骗子,在中国也更多。
由于发帖量与自己的生计紧密相连,中国虚假信息发布者的手段也更加高明。赶集网最初上线时,为了去除虚假信息,开发了通过电话号码识别中介和商家的系统。而后中介们开始每月都买一串不同的电话号码,再做呼叫转移,转到自己的手机上。当赶集通过检测同一IP地址的发帖数量,以辨认中介时,中介们又有新办法:所有人先把帖子内容敲好,然后拔掉网线,再由一个人发令,同时插上网线、把帖子发出去—通过钻赶集此前每两分钟才对IP地址扫描一次的漏洞,这批帖子得以同时鱼贯而入。
比Craigslist晚成立10年的赶集网渴望新的帖子,因而并不删除房产中介广告一类的商家信息。但即便仅删除冒充个人的虚假信息,以及骗子们的恶意信息,赶集网的审帖队伍也多达四十多人,而不是四五个人。
发现这类漏洞多只能靠客服接听用户的反馈电话。客服们每天都会把这类漏洞转交给产品经理—能做多少改进、减少多少投诉,就是对产品经理的考核标准。在赶集网开始销售置顶帖位置后,除了必须查验商家的证照外,如果有骗子成为赶集的客户,拉来这笔单子的销售则会被罚没奖金,一名被发现协助客户伪造证件、当时销售额在全公司排名前三的销售员甚至被开除。杨浩涌在网络安全厂商Juniper工作过的背景,以及对技术的看重多少帮了些忙,这使赶集能更多地靠计算机识别恶意信息,而非人力,“不然我们审帖子的编辑就不是40人,而是400人了。”
在中国,销售员是必需的
而在销售环节,更好的技术也帮不了什么忙。但与至今都没有销售员,靠客户自动打钱上门的Craigslist不同,在中国,中小商家对成本更为计较。刚入行一年多的搬家师傅古道光称,为了自己的帖子能在赶集网上排得更靠前,他一年下来花掉了2000多块,相当于他年收入1/10,是他去年最为心疼的一笔花销。如果不是赶集网的销售连连给他打电话,他下不定投钱的决心。
在中国,所有从企业用户处获取收入的成功网站,比如百度、阿里巴巴,甚至赶集的前合作方、在国外并无销售代理的Google,都已经证实,生意额必须靠销售员拉动。杨浩涌承认,自己也梦想像Craigslist那样坐地收钱,但明白这在中国并不现实。深知这一点的他在2009年底才慢腾腾地推出了客户自助缴费系统,这比这家网站招聘第一个销售的时间晚了一年多。
赶集网在2007年招聘了几名销售员,开始尝试销售。一年后,认为自己的流量和用户数已经足够大,也证实了从房产、招聘、生活服务上确实能招来客户后,赶集网招聘了20多名销售,并在一年后扩展到近40人。
2009年上半年找到新的风险投资后,赶集网打算快速扩张,来证明自己的投资价值。但投资蓝驰创投提醒杨浩涌,快速增加人手常会带来危机。对每单生意只有几百块的赶集网来说,每一点销售额的增加都伴随着人力成本的增长。杨浩涌称一个老手能创造的销售额,通常是新人的3到4倍。
自称是个“技术派”的杨浩涌并不长于销售。在快速扩招销售员之前,他先从阿里巴巴挖来了“诚信通”产品线华北区销售总监周广印。周广印发现,赶集此前的销售多靠个人努力,但缺乏经验分享的机制和习惯。他要求老销售把自己的经验记录成文,并打算从中找出培训讲师;新销售除了会接受一整个星期的销售技巧和产品知识培训外,此后每天早晚各有15分钟和半小时的时间,用来分享经验。这种做法颇有成效,根据赶集网2009年销售额同比增长10倍的速度来看,其销售额的增长与其人数的增加速度相仿。
但近200名销售中,仅北京市场员工就占去了一大半。杨浩涌打算未来发展代理商,来解决销售员太多的问题,但至少在北京、上海、广州、深圳4个一线城市,赶集网将像大多数互联网公司一样,自己做直销。
这意味着赶集网将招入更多的销售员。在其现有的办公楼下,赶集网又新租下半层写字楼。这两个还搭着粉刷墙壁的木梯、看不出有什么特点的房间,已经有了与其楼上的单元的相似之处,就是阔大。





最近评论