We tend to behave similar to our friends. Generally
speaking, we like the same music, wear the same clothes, share the same
hobbies, eat similar types of food, and even vote in a similar fashion. Now,
there is evidence that we even like to use the same mobile phone service.
Michael Driscoll, founder of data analytics firm Dataspora,
studied over 2.4 million customers of a major mobile carrier and found that people
have a surprisingly strong influence on the service provider of their immediate
caller network (defined as the friends and family who the person calls at least
once a month for over one minute). In
fact, Driscoll found that users who cancel service from the telecom company are
600% more likely to be within each others’ caller network, or directly
connected, than one would expect by chance. In other words, if you leave your
cell phone service provider, the chance of your friends and family also leaving
the service provider is significantly higher.
But is the contributing factor really social influence? Or
are these findings just a byproduct of the prevalence of family plans in which
entire groups of subscribers quit together?
To find out, Driscoll looked at cancellations within caller
networks one month apart since family plans customers switch carriers at the
same time. His findings suggest that
family plans only explain part of the collective behavior, and that users
within the same caller network have significant influence over one another’s
phone service provider.
Driscoll discovered that a customer is twice as likely to cancel their phone service and three times as likely to port-out their
phone service to another provider if someone within their network had canceled
or switched carriers one month earlier. For the phone service provider, this
means that a departure by a few can quickly and easily turn into a mass
migration towards a competitor’s services.
Some of this might be
explained by similar people leaving to get a new phone (like an iPhone) that is
exclusive to another carrier. But only
some of the exodus can be attributed to something positive about another
carrier – dissatisfaction with one’s current carrier is another significant contributing
Telecom companies today seem to approach customer retention
efforts reactively, often offering last-minute promotions or free upgrades to
sway customers on the cusp of cancellation. Based on Driscoll’s findings, a
supplementary and cost-effective action phone service providers could take is
to proactively offer discounts or service enhancements to customers in a recent
canceler’s caller network, especially to customers with large networks
While these exact findings are specific to the mobile
carrier and its customers, there are several lessons that all businesses can
learn about taking care of customers and customer retention.
First, take good care of your customers (especially your
best and most-connected ones). Your customers can be your biggest billboards
and will help you draw in even more customers, but they can also be your
biggest enemy and drive away both current and potential customers. To prevent
the latter, make sure you offer your customers – especially your VIPs –
exceptional customer service.
Second, try reaching out to the friends of customers you
lose. This may be done more easily for certain businesses than others since
networks within a customer base are usually not known. Companies unsure of
relationships between customers should (1) ask for or incentive customer
referrals or (2) use an outside service to determine customer social graphs and
Birds of a feather do many things together – including
leaving you for competitors.
(special thanks to Michael Hsu
for his help in writing and editing this piece)
Thanks for share your thoughts. Good post, useful information.
I just had a co-worker email me this article. As a person who entered the full time workforce just two years ago, it was great getting your perspective on which traits are retained by people who are successful. ~Cheers
Interesting analysis with a useful customer-care advice that can be applied to many other services. Insightful!
I wonder how free phones (e.g. skype) and cheap phones (e.g. digital phone) influence the cell phone market. International phone users (like myself) are surely looking for economical and convenient ways.
At&t found this many years ago with telemarketing firms.
Thanks! Interesting–but not unexpected. Nothing stronger than friends to demand cohesion in group behavior.
How much of this is explained by (1) the iPhone (which is something of a status symbol) only being offered by AT&T, and (2) reduced rates being offered when you call other mobiles on the same network?
As a recent provider-switcher at home and work, I could have told you that telecoms are overly concerned with luring new customers as opposed to retention, to the extent that often the most rational consumer decision is to switch as soon and often as possible, getting nice new equipment along the way, and that customer service dissatisfaction now spreads virally at an amazing pace.
Interesting. Everything you say about social groups is true, but I wonder about cell phones as an example. I use AT&T because the bulk of my friends are on AT&T, which means I can call them all for free. If a close friend switches, then I have to pay to talk to that person. So, there are strong financial incentives to switch to friend’s networks, in addition to social incentives. This isn’t necessarily the case for most businesses.
Chris — according to the study, it is much more #2 than #1. super interesting nevertheless.
However, technically speaking, I would not use the homophily theory (birds of a feather) to explain this phenomenon. The researchers actually did not measure to what extent people in the network are similar to each others. Rather, they discovered that those with the highest frequency of communication tend to behave similarly. So, it’s not the similarity based on some personal characteristics (like homophily theory would suggest.. people of the same age, of social status…) but it is the social network (friends, family) that influence behaviour (changing provider). Therefore I would interpret these results as a confirmation of Granovetter’s “social embeddedness” theory. People’s behaviour and social relationships depend on past relationships with the people they trust.
The power of the peer group is well known, and certainly those companies that concentrate on delivering great customer service will win in this “Digital Networking Decade”. Something the SaaS businesses would be well advised to do – Accentuate the Service.
Did the study control for people living in the same area – thus being subject to similar coverage problems which might presumably lead them to cancel with similar patterns?
While customers are the reason for a company to exist, taking care of them is also a direct operational cost as part of doing business. I think it’s important to test assumptions, measure customer behavior against the business technicals and continually iterate the customer service process for optimization.
I imagine the structure, behavior and fundamentals of the market also tend to influence the optimal customer service strategy for any business. For example, why aren’t cell phone companies more proactive in handing out deals? Is it because they can just focus on the easy customers? And when does it pay for a “customer is always right”?
Sometimes, when your team is testing for the optimal customer relations strategy, your company may initially choose an inefficient sales cycle or customer relations process. Or you may just need to fire your customers. Other times, as a customer, you really just need to get what you paid for.
an important dimension of social influence: the number of friends who leave for a competing service is less important than the percent of friends who leave for a competing service. If you wanted to define an tipping point threshold where social influence causes users to switch from Verizon to an iPhone, you’d be better off defining the threshold as a percentage of close friends who are switchers, as opposed to an absolute number.
Auren, my company has been helping mobile phone operators do better marketing by analysing this kind of data for some years now. We have found that even in markets where there is no discount for on-net calls, homophily (as the scientists call it) of network choice still applies – though it is indeed rather less. Homophily of iPhone choice is high in every market though.
Interesting article. However, I have to notice that coincidence of actions (people, switching providers simultaneously) does not necessarily mean “influence”. There are two other, equally plausible explanations: homophily (excessive similarity between friends) and confounding factors.
According to the first, one’s friends are typically very similar to him and are therefore likely to make similar decisions under similar conditions. The second means, that being friends, people are more likely to experience similar events (say, advertisements, tough economic situation, changes to quality of service).
It is extremely difficult to distinguish between the three effects. One, undoubtedly, most efficient way – randomized experiment, but this takes some planning. Another (less reliable) is matching (for instance, this recent publication: http://www.pnas.org/content/106/51/21544.short).
Therefore, what is reported in the article is evidence of clustering of decisions rather than peer influence. This would not be important, unless some conclusions would have been drawn. To claim influence and to exploit it, one has to deal with causality issues.
If payphones fail completely the blame will not fall entirely on lack of consumer demand. Part of the blame would fall on the fact that payphones simply do not work when you need them.