written by Jackie Lorch,
Many readers will be familiar with the website Kickstarter, where friends, acquaintances or complete strangers starting their own creative enterprises request help with funding: to make a music video, create an art portfolio, expand a home business. Since 2009, 4 million people have pledged funds for over 40,000 projects. Now comes a new research-related Kickstarter twist.
Federico Zannier a student at New York University is using the site to get companies to pay for access to his own personal data.
According to an article at research-live.com, Zannier has documented his online activity and other detailed information about his habits and lifestyle, and believes it has value to advertisers.
It appears he’s correct, as he has apparently exceeded his original fund-raising goal already.
For years we’ve called the people who take our surveys “respondents” – a name that signals we think of them as passive participants in the opinion process, sharing information about themselves at the bidding of the researcher. Today, people are rejecting that role, becoming increasingly savvy about the value of their opinions and expecting something in return for their data. Zannier’s project takes this to the extreme. For $2, a business can get access to a full day’s worth of his data; $5 for a week’s worth.
Would you sell information about yourself? What information? Would you pay $2 for a day’s worth of someone’s activity? Does this move herald the start of a trend? Will it soon be the norm for individuals to package and sell vital information about themselves to business?
How does this impact the research industry?
written by Pete Cape
Since online research began nearly two decades ago, rewards for survey respondents have been an integral part of the process. Several research studies have examined the impact of different reward amounts and types on response levels and panelist loyalty.
New research from SSI challenges the overall framework of how we have thought about rewards. It finds that a surprising number of respondents — even those who say they only take surveys for the reward — don’t know what reward is being offered for a particular survey they take.
These findings suggest that respondent’s reward expectations are set at the time of recruitment into a panel or community. At that point we make a deal with the respondent that they will be rewarded for their effort. But from that point forward, many panelists barely notice or remember what reward is being offered.
The conclusion from this could be that we should think more strategically and holistically about rewards. Instead of focusing on algorithms incorporating survey length or difficulty or population scarcity to set per-survey rewards, we could start to separate the survey event from the overall “membership experience”.
What would that type of rewards approach look like? Perhaps we would reinforce the reward experience by adding an additional “thank you” reward at the point of reward redemption. Or give an unexpected reward – to celebrate the respondent’s birthday, or the anniversary of their joining the community, or as a thank you a couple of days after they complete a challenging project.
We have an opportunity for some creative thinking about this important aspect of the economics of online research — because rewards clearly impact those economics in a big way. As sample providers, we must maintain large, engaged populations of respondents; while the research market is driven to get reliable opinions as economically as possible. New thinking about the strategic use of rewards could help us make progress on each of those goals.
For more details about the results from this research, contact SSI.
written by Paul Johnson,
So I was excited for the AAPOR webinar on hard-to-reach populations because I really feel like this is the hardest nut to crack in the industry. Unfortunately, I left being underwhelmed probably because of a misalignment of expectations. I came in thinking that hard-to-reach is the same as hard-to-sample so I was expecting the webinar to focus on the hard-to-sample challenges. I am grateful to Dr. Tourangeau for helping me broaden my horizon. As an employee of a sampling company, sometimes I get too focused on the hard-to-sample problem and not enough on the big picture. Still, for this post I want to focus on the hard-to-sample population and open a debate on whether or not respondent-driven sampling can actually produce good estimates that can help a company make informed decisions.
Respondent-driven sampling is a type of snowball or referral sampling. It relies not on standard probability theory, but rather on network theory to estimate the probability of being selected from the population. It makes the jump to say that it doesn’t matter where in the network you start (the seeds of the study), but as long as you map out the network you can make adjustments to account for the probability of selection inside the network. That is a large claim. Taken at face value it is hard to imagine that a convenience sample of a connected convenience sample with somehow turn into a probability sample, but the math works out in theory. Whether theory turns into practice is another issue though. Dr. Tourangeau did a great job of listing the key assumptions of the theory behind respondent-driven sampling:
- The population that connects to each other. After all, if the population doesn’t connect to each other then there is no network to examine and you are not likely to get referrals anyways. This one doesn’t concern me too much as I really believe that most of these hard to reach populations are connected in some way as the whole world become more connected. However, if you are doing respondent-driven sampling and you don’t get any referrals, you have to ask yourself: “Why am I doing respondent-driven sampling anyways?” You might need to reexamine your population or realign your incentives.
- The population is in a single network. Once again, I am not as much of a skeptic here. Even when it is shown that there are distinct clusters inside the network, there is some crossover. As an example, you can look at a picture of the some of the political networks and you will see clear clusters by party but there are still some connections between the two clusters from the people who work on both sides. http://blog.magicbeanlab.com/networkanalysis/calculating-party-affiliation-us-congress/ NOTE: that this might not be the best example because a lot of Congressman did not tweet each other, but the principal of network crossover still applies.
- Each respondent’s number of network connections needs to be known. I could see some respondent reporting error in here. Frankly though while it might not be exact it should be a close enough approximation to use for our purposes. Also in the future, as social networks develop we should be able to collect some of this data passively depending on the audience we are measuring. This seems to be a solvable problem.
- Respondent need to randomly recruit from their connections in the network. This is the one that gets me. I think that some people’s attributes will make them more likely to be referred than others. At a minimum, the type of connection (friend, family, professional) would have very different chances of being referred. Even if you instructed the respondent to randomly invite the people they know I am not a big believer in the ability of the human mind to create random numbers (our brain isn’t really wired that way in my opinion, but it is a fun topic to Google and of great importance to the computer science community). I am sure that this assumption could be relaxed as long as the probabilities of being referred were known. That is the tricky part though. How do you elicit the probability of referring each of the connections in the network that you have? I don’t have the answer here, but I do think it is an interesting challenge.
All that being said, frankly with most of my work my clients just need a “fit-for-purpose” solution. Respondent-driven sampling might just be that even if it doesn’t approach a probability sample in real life as well as in theory. Look out for my colleague Kristin Cavallaro at AAPOR conference in Boston next month to see how this type of sampling compares to traditional opt-in panel sampling. When you have budget, but you want to make intelligent solutions sometimes “good enough for government work” – or in this case maybe “good enough for non-government work” – is all you need.
written by Ati Sinaga
People outside China may not know Alibaba.com but China’s giant e-commerce company is the largest e-commerce firm in the world; bigger than eBay.com and Amazon.com combined. And according to The Economist it is now on its way to becoming the first e-commerce company handling $1 trillion USD worth of transactions in a year.
Jack Ma, a former English teacher, started Alibaba.com to connect small Chinese manufacturers and overseas buyers. He then set up Taobao.com handling consumer-to-consumer and this portal is now in the top 20 most visited websites in the world. To connect business-to-consumers, he set up another portal called Tmall.com which helps to link business to Chinese middle class consumers.
These three portals have huge customer databases that store spending behaviour of the Chinese middle class and millions of merchants. This is a massive amount of information which is still untapped and envied by marketers, including market researchers.
Alibaba’s next move is to be listed as a public company and it is expected to be bigger than Facebook’s listing last year. If all goes well, it could become one of the most valuable companies in the world.
written by Ati Sinaga
The world has witnessed India pioneering the outsourcing business a few decades ago and this business is now a significant source of foreign income to the country. Part of the success is due to the IT skills of local talent that makes people expect that India would easily tap into the internet business. But it was far beyond expectations that only 10% of residents have access to the web world. Why?
A recent article in The Economist suggests that compared to the outsourcing business, the Indian government has a higher involvement in the local internet modulation and it tends to over complicate the regulations. This problem, combined with corruption within telecom regime, says The Economist, ensures the internet industry does not move as fast as expected and it does not seem it will become resolved anytime soon.
So, where is the hope for larger segments of the Indian population to get connected with fast moving communications? Thanks to cheap smartphones and a fast wireless network, people are putting their hopes on mobile internet. Will India have another success story and lead the mobile internet? So long as government and telecoms industry work together and simplify the rules, a bright future is there.
And how would this affect the survey or data collection industry? No doubt mobile surveying is on the rise…
written by Melissa Geathers
Evolving parental roles are leading to new inroads to male insights when it comes to market research. Dad is no longer sole provider detached from his home environs with peripheral connections to his family. Today’s dads are working dads, stay-at-home dads, single parent dads and same-sex couple dads whose integral roles in their family’s lives have shifted away from the traditional definition of fatherhood. Dads are more involved in the day-to-day care of the children and household duties. Dads purchase the groceries and the products needed by their families. Modern day dads are also looking for brands and products that represent them and seek their insight as full and committed partners in their homes.
However, it appears that we as market researchers are overlooking the determined and developed dad. Family men in their 30s and 40s are missing from most of the product discussions for traditionally mommy purchased items, yet a recent Nielsen study notes that in 2012 men spent an average of $36.26 at the grocery store per trip, compared with $27.49 in 2004. As dads become more involved in the raising of their children, they have greater influence over dollars spent in the home on products and thus can be brand drivers for brands not usually associated with men.
Market researchers need to speak to dads as competent parents and not remove them from the discourse. It seems to me that the market research industry needs to do a little catching up. Market researchers need to be thinking about how moms buy, how dads buy, and how families buy, rather than focusing on one gender as the sole decision maker/purchaser/caregiver. In a society where we are constantly redefining what it means to be a family, we as market researchers need not only to be more inclusive in our search for insights, we need to be more creative in how we help dads discover brands that create a space for them that was influenced by them.