Tuesday, March 18, 2008
So what makes Peanut Labs’ panel different from other online panels? All respondents are recruited directly from multiple social networking sites using non-monetary rewards. According to Peanut Labs website, there are 2.8 million respondents in their panel across 72 social networks and online user reach is up to 12 million.
With huge concerns around professional survey takers and panel overlap in online research (as noted in this Quirks Article), the idea of having non-monetary rewards is a big selling point. Instead of money, respondents are paid in virtual currency according to their social network. For example respondents on Facebook can earn a currency called “munny” for their virtual pets at (fluff)friends. Respondents earn 100 “munny” for their first survey, 200 “munny” for each new survey they complete, and 40 “munny” for being pre-screened out of a survey ($1 USD = 200 “munny”). This method is considerably cheaper than paying respondents actual money and marketers can therefore offer higher incentives to not only respondents that finish survey but also to those who do not qualify. The logic behind this is people will make “munny” regardless of qualifying for the survey, and will consequently be more likely to answer questions honestly.
At first, I sit back and think “Wow, this is pretty amazing.” Most of our concerns as online quantitative researchers could be solved (or at least this is a good start). Then I begin to think about my own personal social networking habits. I am currently a member of Facebook, Myspace, Ringo and LinkedIn. Most of my friends and colleagues are also members of multiple social networking sites. Some are also members of panels such as E-Rewards and Greenfield Online. In addition to being members of multiple sites, we also use multiple email addresses when logging into these sites. This makes it considerably easier for respondents to misrepresent themselves and brings up concerns on the issue of respondent duplication.
Take this scenario for example: A respondent signs up to take surveys through multiple social network sites by using different email addresses on each site, how will a client be able to have confidence in the sample and know that a respondent did not take the same survey three times on three different social networks (especially if the target for a survey is a niche market)?
I believe utilizing social networks and offering non-monetary incentives is a great step toward eliminating some online research woes, but until respondents can be verified and duplication is eliminated across panels, social networks, etc. can anyone really say that one is more reliable than the other? What are your thoughts?
Monday, March 10, 2008
The other day I witnessed a study being conducted at a local movie theater in which a slew of research rules were being violated: preset answers were being suggested by the moderator, exact wording was being modified and recorded however the moderator deemed appropriate, and at one point, two respondents’ answers were compiled to fill a single survey (just to name a few).
When methodologies aren’t used correctly, research data deteriorates. Implementing invalid research data more than likely yields poor results. Getting poor results, in this case is a result of methodology malpractice NOT the research field in general. However, since many marketers are unaware of the importance of the methodology chosen and how it will influence the gathered data, they leave behind not only their poorly predicted results and their budget for research, but also a cloud of unmerited doubt around whether research really works or not.
To make matters worse, we also have a surge of people who like to not only criticize the industry but do so poorly with flawed, illogical arguments and often offer no solution in return. Seth Godin attempts to argue that “our personal outlook is a lousy indicator of what works for anyone else” in his post titled “How do I persuade you?”
Here’s the main problem with this question and the rest of his post: the definition of the word “you.” Now, I hate to get all Bill Clinton-y here but I do think this is a very valid point in this context. Godin specifically labels the population to which he is referring as “human beings.” Could he be more right in this context? I don’t think anyone is arguing that the entire human race makes decisions in the same way or even in a similar manner. Decision processes don’t transcend across the entire world’s population, or even the US for that matter.
What I think many would argue is that when you limit that population down to a specific demographic, whether it’s based on geography, age, sex, and/or what brand they purchase, you may be able to narrow this defined population’s decision making process down to a common thread.
Now, John Windsor’s comment in response to Godin’s post somewhat validates my perspective but perhaps needs a bit of sustenance to back it up. Yes, “we need to listen to those we hope to influence, and then adapt our approach accordingly,” but again, to regurgitate Windsor’s original question, “Now what?” There are a couple questions you need to be sure you are answering correctly before you “adapt your approach accordingly.” They are:
- What is it you want to hear about?
- What is the most efficient/accurate way to listen to it?
All of the previously listed problems above could be solved by recognizing the inherent relationship between these two questions. Determining which methodology will be the most accurate and efficient all depends on what you are trying to hear. Common desired results include pain points, reactions to a new design, or how satisfied people are with
So, if you are looking to do research in the near future but are not completely sure which methodology would be the best way to go about gathering your desired results, please ask and find out to so we can fight research methodology abuse and bring it to an end.
Monday, March 3, 2008
Have you thought about how many free (or near free) products and services you use in a day? Here are just a few examples.
- Google – nearly all services used by consumers are free – from email to Picasa to GOOG-411.
- News – you can’t even count the number of websites that give news away for free. Now there is an ongoing rise of *paper*-based newspapers and magazines distributing news for free too.
- Web-based services – there’s everything from financial services to diet plans available.
For an impressive round-up of free (or near free) products and services in many categories check out this trend report from trendwatching.com: FREE LOVE.
Chris Anderson sums up this phenomenon of free in his article “Free! Why $0.00 Is the Future of Business” in Wired Magazine and also explains it in an interview with Ad Age. The cost of goods is becoming cheaper, and digital technology is experiencing this on a grand scale. As technology advances and bandwidth, storage, and processing power continue to increase (often for less than last year’s model), the cost of supporting additional users becomes more and more marginal.
Why would you offer something for free? Because money isn’t the only scarcity in an economy. So is attention (as Seth Godin points out). And, in a world where consumers have reached their saturation point, free gets attention. Free allows consumers to skip the cost-benefit analysis in terms of money. You still have to make a worthwhile offer though, because if you waste their attention and time, then consumers will be just as angry as if you had wasted their money.
As marketers, we instinctively understand some of this “value of free” – cross-subsidies, loss leaders or encouraging a first trial or purchase by offering a sample. As we forage into an increasingly digital world and costs move towards zero, we are challenged to explore new business models. My humble opinion is that this seems to work with online business models. Offering a service for free = more users on the site = more advertisers willing to buy in. Or offer a free version of a web-based service and a premium for-pay version that has more features, and the pay supports the free. There are overhead costs for servers, development, etc., but they are spread over thousands or even millions of users. So when you divide it out, the cost to support one more user is negligible.
Offline, this concept of free seems harder to grasp. Tangible freebies are costly to produce and distribute, and lots of marginal costs total to one big cost. The question becomes, how do we not only make up these costs, but *profit* from them? There are some companies that are out there working on this conundrum to offer their products and services for free or near free. For example, here’s how Ryanair offers near free air travel. The pie chart does a great job explaining how Ryanair meets the costs of their flights, but I have some issues with it and especially the explanation below it.
- Cut costs – this point makes sense to me. Boarding and disembarking from the tarmac and going to less-popular airports are smart moves to keep expenses down.
- Ramp up the ancillary fees – this irritates me. I do not want to be charged for using my credit card or checking my luggage or wanting a drink. And $3.50 for a bottle of water is an obscenity that’s mostly reserved for sporting events and theme parks. A fair question is do they really think that people aren’t going to realize where the profit is coming from and stop drinking the water? After all, they won’t fly out of the country for more than $100 so why in the world would they pay almost $4 for 12 ounces of water?
- Offset losses with higher fares – I suppose all airlines do this to some degree, charging a higher price for popular flight days. However, if the consumer is price conscious, and comes to Ryanair looking for a $20 flight, how often are they going to choose to fly on the more expensive days? Just from a mathematical standpoint, if 30% of your airline is ‘expensive’ and the remaining 70% is ‘average’. That high end 30% has to support a portion of average flights twice its size for the airline to profit. Which begs the question of how long do you feel you can pull a fast one on the high end customers?
What are your thoughts? Is $0.00 the future of business? What freebie models do you know that work? Which ones don’t seem to work?