每个人都在利用大数据，但小公司如何操纵那些通常由大公司使用的大数据呢?

虽然大数据已是游戏规则颠覆者，但中小型企业基于一个主要的劣势没能搭上这班车。缺乏充分利用新式数据技术的资源，也就无缘实施最佳的广告和销售策略。工具和大数据人才是昂贵的。诸多障碍牵制了小企业拥有全面的大数据能力，然而，抛开这一点不谈，一个好消息是小企业实际上已经利用数据很多年了。

本文由ChrisMu翻译向36大数据投稿，并经由36大数据编辑发布，原文作者HANNAH AUGUR。任何不标明来源36大数据及本文链接http://www.36dsj.com/archives/37336  均为侵权。

一个企业只有能力存储大量的信息与能够利用大数据之间有很大区别。大数据是把信息放在一起，并将过去不相连的点连接起来。这和经理与业主在作决定时经常使用的机制类似。新技术只是在更大规模上做这个事儿罢了。它允许用户从堆积如山的数据中提取信息——但小企业为了做出更好的决策并不需要PB级的数据。他们需要的是适当的工具，清晰的意图和正确的问题。

找到一个值得回答的问题

简单地说，小企业面临的第一关是大数据方面的开销。软件和工具的前期成本高（购置费），后期使用费用（雇人）也高。虽然大公司可能愿意购买最好的软件并聘请分析师搜寻数据黄金，然而这不是最具成本效益的战略。相反，小企业必须专注于精确定位哪些问题是他们想要解决的。不是跳进昂贵而且难以控制的数据湖泊，而是寻找一个值得解答的问题，并找到答案。在现实中，大数据的难点不只是技术或信息，还有逻辑和分析。你不需要高价工具或大牛团队。您需要结构化的、明智的计划和战略，以免随后陷入困境。

当你准备好时，试着咨询 IBM 的沃森分析（IBM’s Watson’s Analytics），谷歌分析（Google Analytics）或洞察力平方（Insight Squared）。

利用开源解决方案尽可能地获取数据

先别买Hadoop。有些轻量级的解决方案，成本较低，使用方便。事实上，如果一家公司一直在用分类帐格式 (Excel、 QuickBooks) 收集自己数据，那么他们应该已经有很多数据了。这些信息已经可以提供关于促销、营销活动以及销售的深层见解，拿它与外部数据比较亦将获得更多信息，然而前提是你要有正确的问题。社交媒体是一个重要的数据来源。社交数据可以帮助你洞察客户身上往往不明显的个人生活特征。除了更好地了解目标客户外，社交数据还能反应出什么原因导致网站访问量增加（或降低）——网友张贴了某类信息还是竞选之类的活动。评测民众的兴趣水平和情绪状况还可以成为竞选利器——在陷入困境前请教社交数据可能会得到一些真知灼见。

利用社交媒体数据就是要全面地360度地了解顾客。这些数据不仅包含位置和的采购清单，而是展现了一个标明兴趣、个人主张与喜好的血肉丰满的人物。深入分析社交数据可以获取更多信息，以减少客户流失率。

可以去查Hootsuite，33Acrossor，Presto，或者简单一点，用Facebook Insight 和Twitter Analytics。

做些大公司做不到的事情

大公司可能有钱，但他们缺乏迅速响应所需要的那种速度和敏捷。在实时变更和调整方面小公司做得更好（前提是要具备一些基础的软硬件）。一个大型公司可能需要首席执行官的多项批文以及一份白皮书才能推行变革，而小企业更容易在利用数据时发挥机智和直觉的作用。大数据可以洞察当前的趋势并预测，因而快速应变的能力至关重要。当趋势出现时，小企业反应迅速，及时变革，崭露头角。由此，大数据让更多中小企业成为弄潮儿，乃至潮流的缔造者。

响应问题时灵活性也至关重要。减少客户流失的关键是及时从负面数据中得到线索并予以响应。即使很小的投诉也会带来很大的负面影响。

寻找灵感?像Constant Contact和 Intuit Quickbooks 这样的工具可以帮助那些无法获取大量数据的小公司。通过比较行业内类似的数据集，小公司可以更好的认识其市场趋势。

与团队共享数据和见解

大数据带来的惊喜之一是它影响团队成员的心理。一旦数据开始露脸，形成结论，并且实施落地，整个气氛都在改变。雇员 (和雇主)（凭借大数据）能够找到更清晰的路径，更好地了解客户，他们将更明白如何做好本职工作。一个有趣的研究是审视大数据如何改变一个小公司的思维模式和能力。以往企业主和经理凭借经验以及少量的用户信息做决定，如今更好的数据意味着更好的决策和更高的参与水平。关于这项研究大家可以参考以下链接

一个重要的教训是要对数据有信心。尝试了解数据的含义是个好主意，然而数据不是万能的，比如并非总能探察到每个小细节的“why”和“how”，而且由数据揭露的事实并非总是不容置疑的。无论哪个市场、公司规模多大、甚至商业模式如何，大小企业都受惠于利用大数据。当然，首先要提出恰当的问题，并且打开思路。或许你要问该如何开始利用大数据？最好的启程可能只是Google Analytics和一大杯咖啡。

二、翻译笔记

1、Apart from giving better insight into target customers, it also highlights what posts, information or campaigns are driving traffic up (or down)。这里drive traffic指网站流量，例如：drive traffic to my web site.( 想办法让流量流向我的网页)。Drive more traffic with our SEO recommendations.(我们的网络引擎优化的推荐配置可以帮助你引流) 8 Ways to Drive Traffic to Your Site With Google+。

2、Triggering and partaking in deeper conversations leads to more information and less churn.这里的churn指客户流失。参见churn rate。

3、Hootsuite，国外一个社交媒体管理平台。HootSuite采用了Klout开发的计算互联网影响力的算法，帮助企业根据其关注者在Twitter上的影响力来分类这些关注者，让企业和品牌可以更好地与关注者进行沟通。

4、33Acrossor，社交服务广告公司。

5、Presto是Facebook开发的数据查询引擎，可对250PB以上的数据进行快速地交互式分析。

6、One important lesson to be learned is to trust the data. Trying to make sense of data is a great idea. Knowing the “why,” and “how” of every little detail could be useful; however, it can’t always be possible. The facts represented by data are not always easy to divine and, in fact, it might just be impossible sometimes.翻译成了“一个重要的教训是要对数据有信心。尝试了解数据的含义是个好主意，然而数据不是万能的，比如并非总能探察到每个小细节的“why”和“how”，而且由数据揭露的事实并非总是不容置疑的。”译者认为直译过来有些生硬，但是如此意译又造成一些信息丢失，渴望大家能多提提意见。

三、原文

Big data solustions for small businesses

Everyone is leveraging big data…but how can a small company maneuver a world of data intended for mega-companies?

While big data has proven a game changer, small and medium-sized businesses are left at a major disadvantage. Without the resources to fully leverage new data technologies, it is simply impossible to implement the best advertising and sales tactics. Tools and personnel that specialize in big data, its uses and implementation can be expensive. However, despite the many barriers holding small business from full big data capabilities there is very good news; Small businesses have actually been leveraging data for years.
There is a very large difference between what it means to use Big Data, and a company simply having the capacity to store large quantities of information. Big Data is about putting information together, and connecting dots that were not connected in the past. This is the same mechanism managers and owners regularly use when making decisions. New technology simply does this on a larger scale. It allows users to pull information from unthinkable mountains of data—but small businesses don’t need petabytes of data in order to make better decisions. What they need are appropriate tools, clear intentions and the right questions.

Find a question worth answering

The first hurdle for small businesses is, quite simply, the costs of big data. Software and tools have high up-front costs as well operational costs. While large companies may be content buying the best software and paying analysts to search out data gold, it is not the most cost effective strategy. Instead, smaller businesses must focus on pinpointing what problem they want to address. Rather than jumping into an expensive, unwieldy data lake, find a question that is worth answering, and find an answer. In reality, the very crux of big data is not just tech or information, but logic and analysis. You don’t need overpriced tools or a team of analysts in order to ask creative questions and find practical results. You do need structured, intelligent plans and strategies before jumping into the deep-end.

When you’re ready, try consulting IBM’s Watson’s Analytics, Google Analytics or Insight Squared.

Leverage open source solution to get data wherever you can

Don’t buy into Hadoop just yet. There are lightweight solutions available that cost less and are easier to leverage. In fact, if a company has been collecting its own data in a ledger format (Excel, QuickBooks), they already have a great mountain of data. This information already offers insights on promo and marketing campaigns as well as sales, and can be compared against external data for even more information—once you have the right questions. Social Media is not only an easy source of data, but an important one. These outlets give you insight into the personal lives of customers that aren’t always apparent. Apart from giving better insight into target customers, it also highlights what posts, information or campaigns are driving traffic up (or down). Gauging interest level and sentiment can also work as the backbone to a new campaign—before jumping in the deep end, consulting social data may hold some serious insights.

Leveraging social media data is all about getting the full, 360 degree view of customers. Rather than just a location and list of purchases, they become a person with fully developed interests and opinions and, well, likes. Triggering and partaking in deeper conversations leads to more information and less churn.

Check out Hootsuite, 33Acrossor, Presto or start simple with Facebook Insight and Twitter Analytics

Do what big companies can’t

Large corporations may have money, but they lack the speed and agility to respond quickly. Real-time changes and adjustments are something the little guy can excel at—when properly equipped. While a huge company may need five approvals from a CEO and a white paper to make changes, smaller businesses are able to combine data with savvy and intuition much easier. Big data lends insight into what is trending now. While it can also make predictions, the ability to implement quick changes is vital. When a trend is emerging, small businesses are just as capable (if not more capable) of making quick changes and jump on board. Rather than letting big names pave the way, big data let’s more modestly-sized companies ride (and make) the waves.

Flexibility is also important when responding to problems. Rather than letting customers slip away, taking cues from negative data and responses is key to cutting back on churn. Even small complaints paint a big picture.

Looking for inspiration? Tools like Constant Contact and Intuit Quickbooks helps smaller companies that can’t collect substantial amounts of data. By comparing their customer’s data to similar datasets from others in the industry, small companies can get a better idea of what’s trending in their market.

Share data and insights with the team

One of the biggest surprise results of big data is the way it impacts the team mentality. Once data is beginning to show up, conclusions being drawn, and responses implemented, the entire atmosphere shifts. With the ability to find a more clear path, and a better understanding of customers, employees (and employers) have a much better idea of how to do their jobs. A very interesting study delves into how big data changes the mindset and abilities of small companies. Rather than owner-managers running everything based on experience and a small pool of consumer information, better datasets meant better decisions and higher involvement levels. A great summary of the research can be found here.

One important lesson to be learned is to trust the data. Trying to make sense of data is a great idea. Knowing the “why,” and “how” of every little detail could be useful; however, it can’t always be possible. The facts represented by data are not always easy to divine and, in fact, it might just be impossible sometimes. Whatever the market, company size, or even business style, businesses big and small benefit from leveraging big data. It all begins with the right questions, and an open mind. The best place to get start might just be Google Analytics and a big cup of coffee.

四、原文引用的文章

Small Businesses Need Big Data, Too

by Christina Donnelly and Geoff Simmons

December 05, 2013

If you run a small or medium-size business, chances are you haven’t felt a need to invest in extensive customer data, relying instead on your well-honed intuition to help you hold your own against data-rich, bigger competitors. A lot of small-firm owners and managers feel that way, and in many cases they’re justifiably proud of their competitive intangibles—a gut sense of the market and the flexibility to change quickly.

What you may not realize is that investing in data and learning how to use it might be transformative for your business. In research we conducted with Gillian Armstrong of the University of Ulster and Andrew Fearne of the University of Kent, we found not only that small businesses benefited from the precision offered by customer data, but also that exposure to data encouraged owner-managers to share insights with employees and get them involved in companies’ competitive thinking.

Of course, for the smallest businesses, access to extensive consumer data can be prohibitively expensive, a point we’ll address in detail in a subsequent post. But cost isn’t the only barrier. Small firms tend to find the whole concept daunting—they know they lack the expertise and the time resources to make good use of the information. Our three-year project was designed to build awareness among small firms about the value that data could have for their businesses.

Funding from a regional UK government agency enabled us to get over the cost barrier: It allowed us to provide loyalty-card information from supermarket giant Tesco, free of charge, to seven firms in the Northern Ireland region of the UK. These companies, ranging in size from seven to 45 employees, sell such things as dairy products, baked goods, vegetables, and desserts to Tesco and another grocery chain, Sainsbury’s (we tasted some pretty amazing soups during the course of our research—a tough job, but someone has to do it).

The data, provided by analytics firm dunnhumby, covered such things as consumer life stage and lifestyle, market-basket analysis, and best-performing stores for the small firms’ products.

The formalized structure of loyalty-card data within a statistical format requires firms to take a more formalized and struc­tured approach to marketing planning—that’s a challenge for small companies. Owner-managers were encouraged to attend workshops, and one of us (Christina Donnelly), after being trained by dunnhumby, worked one-to-one with owners and managers to help them retrieve the most relevant data from the loyalty-card database and analyze the information, so that the companies could answer questions such as “How is my category performing?” “What is the most popular flavor of bread?” “What type of consumer buys a product similar to mine?”

We found that prior to being exposed to the loyalty-card data, the small businesses tended to be dominated by their owner-managers, who made decisions on the basis of their past experiences and any consumer information they could get their hands on. For example, one firm, having been asked by a retailer to produce a range of ready meals, simply looked at other products on the market and tried to imitate them. In other cases, the small firms followed guidelines laid down by the big retail buyers.

Once they were given access to loyalty-card data, most of the small firms took to it immediately. They were quick to adopt a more formalized approach to marketing planning. They were able to envision long-range innovations, rather than reacting to competitors’ or the retailers’ actions. One small-firm owner said the data had changed the company’s ideas about how to grow its consumer base. Another said, “Now we know precisely who our target consumer is.”

A yogurt maker, for example, learned by analyzing the data that older adults were a key market for its products, so when the company’s representatives visited supermarkets for in-store tastings, they no longer tried to entice younger shoppers and instead focused on older people. The tactic improved the events’ productivity.

But the small firms didn’t abandon their reliance on experience. Instead, the data complemented the owners’ and managers’ intuition, giving them new confidence.

Moreover, the data amplified the firms’ inherent entrepreneurial nature. Workplaces became more collegial: Most of the owner-managers shared the card information with their firms and encouraged employees to get involved and offer new ideas.

Big Data threatens to create a deep divide between the have-datas and the have-no-datas, with big corporations gaining advantage by crunching the numbers and small firms left to stumble in the dark. The small firms we worked with were well aware that they were at a severe disadvantage to big competitors that had the financial muscle to buy into loyalty-card data and the resources to use it.

Governments and universities can play important roles in bridging the divide, providing funds and expertise so that small firms can get access to, and learn to interpret, data. Our project is an example of a fruitful collaboration—among the University of Kent, the University of Ulster, dunnhumby, and the government funding body. The quality of the learning is important. A key reason why this project worked was the one-to-one help for the owner-managers. Data is only as good as the people who use it.

For small and medium-size firms that do manage to acquire consumer data, there’s still more work to be done: They need to be sure to encourage employees to participate in thinking about how to use the information competitively. We saw firsthand that inclusivity energizes firms, driving innovation.

From Data to Action An HBR Insight Center

•Are You Ready for a Chief Data Officer?

•Does Your Company Actually Need Data Visualization?

•Nate Silver on Finding a Mentor, Teaching Yourself Statistics, and Not Settling in Your Career

•Stop Assuming Your Data Will Bring You Riches

Christina Donnelly is an assistant professor in marketing at the National University of Ireland Maynooth, Kildare, Ireland.

Geoff Simmons is an associate professor at Queen’s University Belfast in the UK.