In the early days of Home Shopping Network (live TV, not online), we were doing some ethnographic research and started to find “physical clusters” of customers – neighbors or people who worked together. For example, one of these groups was nurses at hospitals, especially nurses who worked the night shift.
We looked for the most active member of the cluster (our “thought leader”) and asked them if they would help us with a “member get a member” program. Would they be willing to distribute discount coupons to their friends, especially ones who were not already customers? Time after time, the answer was:
“Honey, all my friends are already customers of yours”.
We launched the program anyway, because it was a pet project from upstairs – I was a junior marketer at that point so I couldn’t kill it ;) The program never, ever worked, no matter how hard we tried. It generated very few new customers while giving lots of discounts to people who were already active buyers. Basically, the cost of those discounts overwhelmed the value of the new customers generated.
Apparently a similar thing happens online with Social marketing.
As part of a WAA program that reviews academic research for WAA members, I was able to take a look at a paper titled: Firm-Created Word-of-Mouth Communication: Evidence from a Field Test by David Godes and Dina Mayzlin.
Here’s my Executive Summary:
The authors investigate the effectiveness of a firm proactively managing customer-to-customer communication. In particular, they are interested in proving how, if at all, a firm should go about effecting a meaningful word-of-mouth (WOM) communications program. This is done through two different data collection schemes: a large scale, 15 market test through BzzAgent with a client restaurant chain, and also through a controlled online experiment. The results are somewhat counterintuitive and may change the way web analysts and Marketers should be thinking about WOM and social analysis, particularly if there is a hard monetary investment in the WOM program.
Specially, the researchers are trying to answer 2 questions:
1. What kind of WOM maximizes incremental Sales?
The answer: WOM created by less loyal (not highly loyal) customers, and occurring between acquaintances (not friends). Though perhaps surprising, this result is often found in Marketing program measurement; Sales would occur anyway without the program, especially among best customers. These results demonstrate the pitfalls of not using control groups (people not exposed to the campaign) to measure Marketing effectiveness.
2. Which people are most effective at creating the WOM above?
The answer: “Opinion Leaders” or “Fans” are not as effective in spreading WOM that drives incremental Sales because these efforts are “preaching to the choir”, per #1 above. The networks that opinion leaders or fans have are likely to already know about the Product from pre-existing conversations, and spending money on creating a campaign to reach these people is ineffective because the social communication has already taken place.
In sum, if you want to invest in a WOM program that will drive Sales you would not have received anyway, you want the WOM conversations happening, as the authors say, “where none would have naturally occurred otherwise”.
The discussion of the difference between the need for a persuasive argument versus building awareness is something web analysts should keep in mind so they can make sure they understand the real needs of the Marketer or Product Manager. For products with high awareness already, what is really needed to increase Sales is persuasion of the people already aware, not more awareness. New products obviously need increased awareness.
Per this study, this persuasion versus awareness question affects the choice of who to recruit for WOM campaigns. Loyal customers are the best persuaders and are best used when the product already has high awareness. If you want to drive sales through increased awareness – the goal of many WOM campaigns online – you should be recruiting less loyal customers and encouraging them to talk not to their friends, but to their acquaintances. This approach appears to be contrary to the “opinion leader” or “fan” approach now thought of as best practices.
As is typical of academic research and testing, the paper contains an extensive review of the results of other WOM Marketing studies all the way back to the 1970’s upon which the hypothesis for this test was formulated. If you are a WAA member, you can get a copy of the peer-reviewed paper from the journal Marketing Science (other versions are floating around) with all these footnotes listing previous test sources. Instructions on how to do this are at the end of the Review.
I’m not going to post the rest of my Review on the blog. Rather, I’d like to ask some questions and get some discussion going on this topic, because I think this test and paper shines light on a fundamental flaw in the way people think about Marketing on the web. So read the rest of the Review here if you’d like, then please come back and offer your opinions on these questions:
1. Test results indicate if you’re going to maximize an investment in WOM, you should target less loyal customers talking to acqaintainces rather than loyal customers talking to their friends. Do you understand this idea? Believe in it?
2. Do you think this is an important discovery?
3. Do you think this general model – the idea that to maximize Sales, best customers should be treated differently than other customers – might apply to many different types of web / interactive marketing?
4. Will you do anything with this information? What’s first step?
Update: Prompted by the questions in Comments, I offer these additional links to previous posts. Here is a more detailed explanation of “lift” and “incremental”. Those who might want want to go “up” to a macro model for how to think about Marketing in a Social or Relationship mode should see Framework for Engagement. If you want to go “down” to analysis or execution and are interested in “How do I Measure and take Action on these Ideas”, see the Measuring Engagement Series. If you want to understand how this model integrates with the traditional offline Push model, see the Marketing Bands Series.
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