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  Customer Evangelists: What Are They Worth? 

Armelini, Guillermo; Villanueva, Julián
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Word of mouth holds important implications for marketing because it influences consumer behavior and purchase decisions. It can also be more powerful than advertising as a communications tool.

For these reasons, academics as well as marketing directors would like to know how to manage word of mouth and how to determine customer referral value (CRV) for a company.

Julián Villanueva and Guillermo Armelini propose a social network-based methodology for calculating CRV, which they explain in their article, “Who Are the Customer Evangelists and What Are They Worth? A Network Model to Measure Customer Referral Value.”

The Importance of Social Surroundings
Earlier research has concluded that companies can manage social interactions among consumers by acting as a moderator and encouraging conversations among customers.

However, that strategy requires identifying the clients who get most involved in that kind of communication, and this is not an easy task.

One alternative is to aim for opinion leaders, whose influence often speeds up the spread of an innovation. But these people are not easy to identify, either.

Given these difficulties, it is a good idea to develop a method that allows one to evaluate consumer recommendation activity, regardless of what their motives might be.

The new technique described in their paper for assessing CRV does just that. Based on social network theory, it takes into account the connections that exist among different individuals. This factor is essential in informal communication, because people do not act in an isolated fashion.

This approach also allows one to understand the factors that drive recommendation activity, such as whether the link is strong or weak – i.e., if the people interacting are relatives, friends or just acquaintances.

Using an econometric model, the authors argue that CRV depends on the customer’s contribution to the process in which people around them acquire products or services, and on the economic value of each one separately.

The authors tested their model in the telecom sector, applying it to local telephone calls made over the course of nine years (1998-2007) in a small town (population of less than 4,000) in Argentina. During this time, the telecom company had more than 1,000 customers, both private individuals and businesses. The study focused on Internet services, which the company began to market in 1998. Thus, complete data were available for when each customer signed up for the service and when they dropped it.

The authors acknowledge some limitations to their model, which requires knowing the social relationships that exist between different groups of customers. Also, it is based on the influence a customer has on his or her direct contacts, not on indirect ones. Furthermore, the technique’s validity has been tested only in sectors that have a contractual relationship with their customers, such as telecom.

Factors That Influence a Recommendation
In line with earlier studies, the authors find a weak correlation between a customer’s referral value and their economic value. This confirms that companies should segment their customers and keep both factors in mind, not just the economic value, as is usually done.

Even though they find that the most valuable customers are not necessarily those who have the greatest capacity for influencing other people’s purchasing decisions, the authors do not mean to imply that recommendation potential is of no value. In fact, the power of social propagation remains a decisive factor in the acquisition of a product or service, they say.

The authors suggest that companies should strive to identify those customers who are most active when it comes to making recommendations, as they can serve to lure new ones with a minimal investment of money.

At the same time, the economic value that a customer can generate by making recommendations provides a good tool for segmenting clients in terms of their prospects for influencing others – a goal which is the dream of any marketing director.

The length of time that a customer has been using a service, and the frequency with which they use it, also have a significant and positive impact on CRV. Loyal customers generate value for a company, not just through their own individual consumption, but also by their potential for recommending it. Unlike those who signed up more recently for the service, long-standing customers are the ones more likely to influence those who are not yet customers.

Therefore, companies can target their products at this loyal customer base, sending them personalized information in which they describe new products and promotional offers. Indirectly, this could prompt this set of clients to talk more about these products to the other people they come into contact with.

The strength of the links between people in a social network is also a critical factor. Referral value is greater in groups joined by stronger bonds. People with a closer relationship – through marriage or friendship, for instance – tend to interact more frequently than those who are just acquaintances.

With this in mind, companies could study the groups that are most interconnected within the network, using social network analysis tools such as clicks or clusters, and within these groups identify the people who are most influential.

In this way, companies could launch marketing campaigns targeted directly at these customer evangelists, who might help accelerate purchases of the product.

Furthermore, the results show that people who are more connected socially are more inclined to have greater CRV.

However, physical proximity is not a significant variable: Being neighbors is not decisive when it comes to predicting the acquisition of a service.

This article is based on:  Who Are the Customer Evangelists and What Are They Worth? A Network Model to Measure Customer Referral Value
Year:  2009
Language:  English