Tag: research

Surprising Buzz Champions

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When trying to create buzz about your brand, do you choose your loyal followers or do you choose people who don’t even know much about your brand? You might be surprised by the answer. A recent research by Professor David Godes and Professor Dina Mayzlin suggests that you should choose the latter group.

Buzz

Why?

  • We tend to know or come across people who are similar to us. Therefore, the friends your loyal followers have are likely to already be your loyal follower too or at least user.
  • Loyal followers are likely to buzz about you any way. So the incremental gain from a buzz campaign based on these consumers is limited.

Run the Numbers

These researchers conducted a field study and two lab experiments, which showed significant gain by choosing non-customers as buzz agents. In fact, in the case of Rock Bottom Brewery (a restaurant), they estimated an average of $192 gain in sales brought in by each interaction from non-customer buzz agents. Pretty sizable, huh?

Before You Run Away With It

I see two potential caveats that you should consider before you take the results and apply them to your business:

  • Intuitively, it would take more to get people unfamiliar with you to buzz about you. So cost is definitely a consideration. In the Rock Bottom Brewery field study, the non-customer sample came from the BzzAgent company panel. Although both the customer group and the non-customer group were offered potential prizes from the campaign, the non-customer group may have received (or expected) additional incentive from the BzzAgent network (although it’s not explicitly stated in the article).
  • People who don’t know a brand well enough may have low credibility when spreading words about the brand. Those who consistently buzz about something they don’t really know (for their own personal gain) may eventually lose the trust of those around them.

More Information

You can hear Professor Godes and Professor Mayzlin talk about their research in this Science of Better podcast. Or if you want to read the article yourself, you can find it in the July/August 2009 issue of Marketing Science (subscription or pay-per-view required).

Word-of-Mouth or Traditional Marketing?

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Some people may disagree with what I am about to say here: online social networks bring people closer to each other. At least that is the personal impact that they have had on me.  But what does this mean for marketing?  One answer is that word-of-mouth between consumers is carrying more weight in how we choose and consume products. Whether we love or hate a product, now it is so easy to make it known to the public that we are essentially affecting the opinions of other consumers (from total strangers to close friends) every day.

Managers are often hesitant to invest in encouraging word-of-mouth, however, as its effects are notoriously difficult to measure.  This is because word-of-mouth behavior is often unobserved, and it is difficult to tease out the concurrent impact of traditional marketing.  These are the exact problems a recent article by Michael Trusov and colleagues in Journal of Marketing tried to tackle.  Entitled “Effects of Word-of-Mouth Versus Traditional Marketing: Findings from
an Internet Social Networking Site”, this article offers a clear answer to the relative effectiveness of word-of-mouth vs. traditional PR and marketing.

Word of Mouth

What did they look at?
The impact of word-of-mouth, event marketing, and media appearance on the sign-ups for an undisclosed online social network.

Some intuitive findings:
More new sign-ups resulted in more word-of-mouth; event marketing led to more media appearance, and vice versa;  word-of-mouth was not affected by previous event marketing or media appearance, however, suggesting consumers’ relatively independent opinions and actions.

Some not-so-intuitive and very important findings:
The 3-day elasticity of sign-ups with respect to word-of-mouth was .17. In layman’s terms, this means that doubling the amount of word-of-mouth increases sign-ups by 17%. The corresponding impact from event marketing and media appearance, in contrast, was only 1.7% and 2.2%. The gap became even bigger with regard to long-term effects.  In the long run, the effect of word-of-mouth is 20 times that of event marketing and 30 times that of media appearance.  While doubling event marketing or media exposure led to 1.7% and 2.6% respective increase in sign-ups in the long run, doubling word-of-mouth increases sign-ups by a full 53%. Financially, an outbound word-of-mouth referral translates into 75 cents/year increase in advertising revenue.

What does this mean for marketing practice?
Word-of-mouth is a powerful tool for customer acquisition.  With the help of more powerful tracking tools provided by social networks and websites, it is possible for managers to measure the return from word-of-mouth activities. The mathematical approach used in this article (vector autoregressive modeling) further helps tease out the impact of other marketing and PR activities so that the true effect of word-of-mouth can be accurately measured. Together, this should reduce the hesitation to incorporate word-of-mouth into a company’s overall marketing strategy. The findings from this article also provide a strong motivation to better utilize word-of-mouth channel of communication.

Cautions
Readers should be cautioned from taking the results from the above research too literally.  Two things should especially be taken into consideration.  First, the data came from an online social network.  Customers on such websites are usually highly motivated to invite their friends, and those invited by their friends are also very likely to sign up.  If we were to change the context to, say, online banking, both the level of referral and the impact of referral are likely to be lower.  Second, the word-of-mouth activities studied in this article are all organic referrals initiated by consumers themselves. If the word-of-mouth had been stimulated by the company (say, with financial incentives), the referrals may not have been considered as genuine to other consumers and therefore may not have created as strong of an effect as reported in this study.  Although these are real limitations, the findings from this study are still quite powerful indicators of word-of-mouth effect. It is a tool managers should not ignore.

Reference
Michael Trusov, Randolph E. Bucklin, and Koen Pauwels (2009), “Effects of Word-of-Mouth Versus Traditional Marketing: Findings from an Internet Social Networking Site,” Journal of Marketing, Vol. 73 (September), p.90-102.

Loyalty Programs and CRM — Insights from Marketing Science 2009 Conference

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At the INFORMS Marketing Science 2009 Conference, I presented my current research project on the effects of loyalty program expiration policy change.  For those who missed the conference, here’s a summary of what I presented. I have also included the summary of the other two research projects that were presented during the same session.

Shortening Loyalty Program Expiration Period May Not Be Bad

One of the headaches companies running loyalty programs have is the liability associated with unredeemed points in program members’ accounts. One way of reducing such liabilities is to shorten the expiration period associated with program points, as major US airlines did in 2007. However, it is possible for such a policy change to alienate existing customers. To see whether this is the case, my co-author and I analyzed data from a convenience store chain that has switched from a no-expiration policy to a monthly expiration policy. To our surprise, we found that, participation in the program has actually increased significantly since the program change. Overall in-store sales have also increased, while fuel sales remained unchanged. What we plan to do next is to see how individual consumers have adjusted their purchase behavior in reaction to the policy change. We suspect that the addition of an expiration policy imposes what we call an “expiration pressure” on consumers, as consumers are pressured into making more purchases to reach a reward threshold before the points expire. However, different consumers (e.g., those with different patronage levels) will experience the pressure differently. I’ll report more findings when we are further along with the project. For now, you can download the presentation slides. We welcome any feedback or comments you may have.

Two other researchers also presented their projects on loyalty program and customer relationship management in the same session. As these are also relevant to loyalty managers, I am summarizing them below:

Loyalty Program Increases Share of Wallet by 10%

Martin Boehm from IE Business School presented his co-authored research project on the effect of loyalty program membership on consumers’ share of wallet at an European supermarket chain. By looking at a consumer panel’s behavior before and after loyalty program enrollment, they show that the loyalty program increased share of wallet by 10%.  This lift is negatively correlated with a consumer’s original share of wallet before the program enrollment. In other words, those with a high share of wallet exprienced minimal lift, whereas those with a low share of wallet experienced the highest lift. These results echo my earlier research findings showing a similar pattern. However, their research better controls for self-selection bias (i.e., better customers are more likely to enroll in loyalty programs) and therefore provides an even stronger argument for loyalty program impact.

Email and Mail Are More Effective Customer Contact Channels…

At least in the context of auto dealership’s services. Using data from an auto dealership, Andrea Godfrey at University of California at Riverside and her co-authors compared the effectiveness of phone, mail, and email customer contact in increasing sales (in this case, service revenue).  They found that mails and emails were similarly effective in increasing sales, while phone contact was the least effective. The effects of mails and emails were both curvilinear, meaning that the effects of those contacts reach maximum after a few times and then drop after the threshold. Not surprisingly, the exact effectiveness of each contact channel on individual consumers also depends on the consumers’ channel preference.  I hope these findings will help eliminate a few annoying dinner disruptions and result in less waste of papers. But I am not so sure I like the prospect of receiving more emails either. Hmm…

Questions or comments?  If you have any questions regarding any of these research projects that I have summarized here, please feel free to let me know, and I’d be happy to answer your question or forward your question to the right author.