To Know Your Consumer, Follow the Tracks on Networks

Consumers have always been searching for peers with whom to share opinions and information on common interests and products. The growing diffusion of social media has greatly magnified the scale of the phenomenon, by allowing web users to develop the habit of sharing experiences of all sorts, including consumer experience. The trend toward the socialization of experience generates an unprecedented mass of information, which is theoretically available to firms that wish to know their clients in almost intimate depth. Given users' propensity to share content and collectively build ever thicker information tapestries, companies need to find a way for the yarn to become unspun, so that all this information is transformed into learning opportunities to devise actions of personalization and individualization that can reach extreme forms of customization.

This is the essence of CRM 2.0 (Customer Relations Management), aka Social CRM, which is understood as a business strategy and philosophy geared to obtain in-depth information on customers through statistical inference methods and the actual involvement of consumers on social platforms. According to Gartner, this will lead companies to perform 90% of their customer service activities via social media by 2020. Consumers who had a positive experience with companies on social media are much more likely (four times the average) to recommend a company's products and spend on average 30% more than other customers.

Today, what could be a capital of data is a fragmented and unstructured mess: the sedimentation of social media data keeps progressing blindly, without being incorporated into traditional market research.

It is thus fundamental for companies to equip themselves with social analytics tools, and invest significant resources in the analysis of data reports, their selective circulation within the company, as well as use them in supporting managerial decisions in related areas and operations. The challenge for companies is not only to think how to best capture more and more fine-grained customer information, and develop predictive models of consumer behavior based on statistical inference, but also to understand where to stop in the digging of personal information about individual customers, since extreme personalization of communication and value proposition could well pose a real threat to privacy.

Vodafone, for instance, has launched a project to analyze more in depth individual users beyond profiling based on the traffic of individual SIM cards. It studies interactions between clusters of individuals connected to each other by the very services provided by the mobile phone operator. The operation was conducted on 10 million users and 15 million SIM cards. The average community turned out to be composed by about 7 SIM users (not necessarily Vodaphone's). The most intriguing aspect is being able to find out and manage the role played by each member in the network. This way, companies can ascertain who the trendsetters are, i.e. those who are early adopters of a product or service and educate other less tech-oriented users in their communities. Through this kind of analysis, companies can tell the clients who act as bridges between the various communities, and who can thus be useful in the search for potential new clients.

With such an information explosion leaving a fallout of huge amounts of data, the question is whether marketing managers will be able to go beyond themselves to design product offers and personalized messages that mirror the tracks left by each of us on social media.