PROPOSITION 1: BIG DATA AND ABILITY TO OBSERVE THE POPULATION

Most consumer marketers deal with millions of customers and require ways to study and reach these customers effectively. The volume of activities is critical in such an environment. A market test for an electronic products maker may require connecting with hundreds of thousands of prospective customers, while a national launch may involve millions, and a global launch may communicate with billions. Corporate marketers deal with much smaller number of customers, but with massive variety of data. While the number of customers may be much smaller, each customer includes many decision-makers, many decision-making processes, and a variety of data sources Corporate marketers have developed ways to deal with clusters of customers, each representing a single customer, as in the case of large customers, or a homogenous group of SME customers.

Let me start with some examples of large observations for corporate marketers. Customer-facing professionals get in touch with a large number of observations about these customers. Some of these observations are very structured-revenue, billing, collections, usage, number of defects. Then, there are unstructured sources—organization charts, emails, trouble reports, Request for Proposals (RFP), Request for Information (RFI), mission statements, business plans, contracts, and so forth. Some of the information is available at client sites- contact information, organizational relationships, corporate directives shared with business partners. Social media is providing a lot more new sources of information—LinkedIn, YouTube, SlideShare, Twitter, press releases, web content, and so forth.

Another gold mine of data comes from product usage information. As this information becomes available to marketers, it can be used for mining use cases—how customers are using the products and how they differ from each other. In analyzing this data, a marketer can aggregate across employees of many customers, formulate segments, and use the segmentation information to classify customers by usage behavior. Let me give an example of a wireless telecom organization that provides service to employees of large customers. The contract may include a discounted device and service payment by the employer, and additional products and services purchased directly by the employee. Given the mobility and work-at-home provisions from most employers, many of these employees could be spending a fair amount of time working from home. What if the wireless service is not adequate at the home office? The employer may be willing to invest in a network extender product from the wireless telecom supplier, which, once added to a broadband source, can boost the wireless signal at home. The employee can use the extender to enjoy better service for all cell phones in the household, not just those that were supplied by his/her employer. The wireless telecom supplier now has a sticky customer. Even if the employee changes jobs or stops subsidizing the phone, the network extender makes it harder for him/her to switch providers. By analyzing usage and mobility information, the wireless service provider can identify employees who work from home and have poor service at home.

A corporate customer may be comprised of a large number of organizations related to each other, with the buyer-seller food chain within the corporation, and each organization in the food chain holding a different relationship with the marketer. Typically, end users, such as call center operations, sales, and so forth are supported by staff functions, and then there are supplier organizations, such as IT and procurement groups. For example, for a wireless provider like Verizon, which provides services to IBM, the end customer is a selected set of employees who use Verizon’s wireless devices. The IT infrastructure that interfaces with the wireless devices is managed by the Chief Information Officer (CIO) organization at IBM, and the purchasing operations have been outsourced to a third party. The seller must deal with end users, technology providers, and the purchasing organization, as well as the procurement organization. The corporate marketer must understand the objective across these groups and devise ways to market products to each of them. For wireless services, the relationship is even more complicated, as corporations discount the device and service costs, and often employees are customers buying the upgrade and additional services. Knowledge of the food chain is absolutely the most important aspect of corporate marketing. Corporations that focus primarily on their component in the food chain rapidly become relegated to a commodity provider role, while most of the value added and extra margins are awarded to the corporation with the best end-to-end vision of the marketplace.

CRM systems traditionally provided 360 degree views using structured data. Increasingly, they are augmenting their structured customer data with social media sources, and providing analytics driven campaign tools for corporate customers.1 Web-crawling techniques provide customer snapshots, summarizing all customer activities for a dynamic 360-degree view of an account. These views combine all significant customer activity, and may include public news, new sales, problems discovered, resolutions, and customer contact activities. This information may be available publicly or in emails, memos, IT systems, or elsewhere within the organization. Unstructured analytics tools are often used for customer research. These tools crawl through public sources, internal documents, emails, as well as structured sources to define 360 degrees view of a customer organization, covering a large number of dimensions, sources, and formulating links across these sources to facilitate account research.2 While such views are absolutely necessary for account management, marketers can benefit from the organization of this information in one place. Without the synthesis, a marketer may invest a significant amount of time collecting customer information from a variety of sources.

With product usage and other big data sources available, corporate customers can now collect much more data about their customers. While the number of customers and contracts may be small, the number of users could be much bigger. A wireless contract with a global Fortune 50 company could easily include a large number of employees. A hotel contract for corporate travel could involve thousands of employees. Can a corporate marketer use big data analytics and borrow ideas from consumer markets for organizing segmentation information, connecting with their customer base, or engaging in marketing campaigns? Would it be possible for a corporate marketer to advertise their value-added products to a corporate employee who is using a corporate contract for basic services, but could use additional services from the marketer?

 
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