网络分析法进入实体商店

    位于西雅图市的Placed公司发布报告称，今年第一季度，进入美国各大书店的人流量增加了27%。Placed公司致力于把网络上常用的营销分析法带入线下的世界。

    Placed发布的这个数据似乎有些惊人。我们很难知道这个数据到底有多准确，也不清楚它是否能吸引各大企业开始采用Placed公司的服务，不过它的确为这家公司带来了媒体的关注。说起来有点讽刺，因为Placed公司为客户提供的分析方法要比单纯计算人流量复杂得多。它的Placed Insights服务可以自动从下载这款手机应用的用户那里收集信息，从这一点上来看，Placed公司研究的人群都是主动成为研究对象的，因此样本可能不够全面。不过公司创始人兼CEO大卫•希姆否认这一点。现实中许多实体店都在统计客流量，Placed给出的数据肯定不如他们的第一手数据精确。

    尽管如此，Placed公司的技术还是很诱人的，而且很有前景——甚至可能是革命性的。虽然许多大型连锁超市和连锁餐厅也开发了一些复杂的方法，用来计算自家门店的人流量，但是Placed的独特之处在于，它还知道顾客进店之前或是离店之后会干什么。更重要的是，它还可以根据人口统计学特征对顾客群体进行划分，然后可以向实体店提供像尼尔森公司（Nielsen）和康姆斯科（comScore）公司提供给网络营销公司的那种服务。

    希姆说，营销人员可能想知道：“当麦当劳（McDonald）的顾客不在麦当劳吃饭时，他们会去哪儿吃饭？”如果说他们更喜欢去熊猫快餐（Panda Express，美国知名中餐馆——译注）或是汉堡王（Burger King），而不是去苹果蜜蜂（Applebee）餐厅，那么这就是一个有用的数据点。（Placed公司没有透露客户的名单，不过希姆表示，它的客户以大零售商、连锁餐厅和广告公司居多。）如果能知道顾客群的人口统计学特征就更有用了，比如麦当劳的西班牙裔顾客与其他顾客群相比，更喜欢吃熊猫快餐而不是苹果蜜蜂餐厅。

    这种获得、使用信息的能力可以说是史无前例的。从某些角度讲，它比那些能够通过追踪人们的上网行为获得的数据更有用，更具有启发性。市面上也有一些公司提供类似的服务，但是它们通常是通过第三方获得的数据（比如购物习惯），而且它们覆盖的地域也更广。而Placed Insights的数据是直接从消费者身上获得的，它所针对的地理位置可以精确到平方英尺。Placed Insights包含了大约1,300亿个经纬度点，而且还把它们与数以十亿计的其它数据相结合，为它所提供的任何见解提供翔实的数据支持。移动技术和大数据的这种联姻能够使营销人员接触消费者的方式得到革命性的创新，尤其是当这些消费者没有守在电脑旁边，而是在吃饭或购物的时候。

    Foot traffic at bookstores rose by 27% in the first quarter of this year, according to a report issued this week by Placed, a Seattle-based company that aims to bring Internet-like marketing analytics to the offline world.

    That seems like a surprising number. It's hard to know for sure how accurate it is, or how effectively such reports might sell companies on Placed's services, though they do help the company get media attention. It's a bit ironic, though, because the analytics Placed offers its customers are a lot more sophisticated than clunky foot-traffic counts. For its new Placed Insights service, the company automatically collects data from people who have downloaded its smartphone app, so the population that it studies is self-selected, despite protestations to the contrary by CEO and founder David Shim. It's not nearly as accurate as simply counting heads, as stores already do.

    Nevertheless, the technology is both fascinating and promising -- maybe even revolutionary. While big retailers and chain restaurants have developed sophisticated methods for measuring foot traffic within their stores, Placed also reports what customers do before they get there and after they leave. Further, it breaks down their demographic profiles and presents retailers and restaurant chains with the kinds of analytics that companies like Nielsen (NSLN) and comScore (SCOR) provide to online marketers.

    A marketer, Shim says, might want to know: "Where do McDonald's (MCD) customers go to eat when they're not at McDonald's?" If they tend to go to Panda Express or Burger King (BKW) rather than, say, Applebee's, that's a useful data point. (Placed doesn't reveal the names of its customers, but Shim says they tend to be large retailers, chain restaurants, and ad agencies.) It's even more useful to know the demographics of various customers: say, whether older, Hispanic customers of McDonald's, as opposed to other groups, tend to prefer Panda Express over Applebee's.

    The ability to gather and manipulate this kind of data is unprecedented -- in some ways, it's even more useful and revealing than the data that can be gathered by tracking people's online behaviors. Other companies provide somewhat similar services, but they gather their data (such as shopping habits) from third parties and cover wider geographical areas. Placed Insights gets it right from the source: the consumer, and the geography is measured almost down to the square foot. Placed Insights incorporates about 13 billion latitudinal/longitudinal geographical points and combines them with billions of other bits of data to produce any number of possible insights. This marriage of mobile technology and big data could revolutionize how marketers reach customers who are away from their computers, and shopping or dining.