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EMI Research Solutions is a leading online sample and quantitative research consultancy. With more than 20 years of experience operating in the market research industry, we provide you with unbiased solutions that connect you to the right sample that best fits your project and needs rather than trying to make your project fit a specific panel. We provide the highest quality, most cost-effective insights in the shortest amount of time — ensuring you get the best results for your projects. Our world-class project management team works with you as an extension of your team, providing you with a single point of contact, utilizing responsiveness, creativity, and flexibility to help you navigate any issues. Our proprietary sample management platform, SWIFT, seamlessly connects your survey with the appropriate sample audience while ensuring you get only high-quality data with our built-in data quality measures. EMI’s unique combination of expertise, knowledge, and white-glove service allows us to be the premier sample and market research consultancy — getting it done without compromise

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<h2>If you can’t trust the data from your research, what’s the point?</h2>
Most researchers are aware of numerous biases that can affect survey results. Most of us are trained to avoid or are aware of social desirability bias, <a href="https://www.greenbook.org/insights/market-research-industry/why-scoping-research-could-be-your-biggest-problem">confirmation bias</a>, leading questions and even sample bias. However, there are numerous types of sample bias and an important one is not often talked about in the online sample world, yet it can seriously impact the results and reliability of your study. The basis of sample bias stems from the fact that sample panels are different from each other and are constantly changing.
Brand key performance measures can vary a staggering amount, depending on the sample source. We’ve found that brand rating can vary by up to twenty percentage points based on sample provider selection. Twenty percent can be the difference in decisions that can have billion-dollar impacts. Some of the issues that arise from sample bias include data inconsistency, increased risk, and aggregation bias.
<h2>Data Inconsistency</h2>
Inconsistency is the enemy of tracking studies. Researchers are trying to understand whether the actions of the organization are working with their consumers. So, when there are wild swings in results wave-to-wave, especially ones researchers cannot explain, it makes it hard to compare data to previous waves.
<h2>Increased Risk</h2>
Relying too heavily on a single panel (even if you are aggregating) not only introduces bias to your study but is also dangerous. If something happens to that sample source (acquisition, bankruptcy, etc.) your study is ruined, and the data is useless with no way to replicate the study. As I said in a recent episode of our podcast, Intellicast, “when there’s an acquisition, there are always going to be changes and that includes changes to your data.”

 <div class="post-related-post">
 <h3>Related</h3>
 <h4><a href="https://www.greenbook.org/insights/focus-on-apac/is-a-sample-size-of-n1000-sufficient-for-accurate-survey-results">Is a Sample Size of N=1000 Sufficient for Accurate Survey Results?</a></h4>
 </div>
 
Even if you end up having to add more panels to complete your study or if the wrong blend is chosen, you risk incorporating sample bias. We know that sample providers significantly change over time due to changes in client demand, changes to recruiting practices, changes to how a <a href="https://www.greenbook.org/insights/tags/panels">panel</a> is managed, increased security and validation methods, and many more. These may all seem to be an improvement, and in many ways, they are, but this can affect the panel composition, the attitudes and behaviors of its members, and ultimately your data.
<h2>Aggregation Bias</h2>
If you’re already using multiple suppliers, you might think you’re safe from the risks associated with using a single source. When you use a single sample source for all of your sample, your feasibility is limited to that of your selected source. Using multiple suppliers instantly gives you better feasibility.
Most often, aggregating is done to solve feasibility problems, but it opens you up to a variety of other problems in the process. That’s because if you’re not strategically selecting those panels, you’re adding inherent bias to your research. This is where panel differences and aggregation bias come to play. Not all techniques for combining multiple panel providers are created equal.
<h2>Stacking</h2>
One method of combining panels is stacking. This form of combining sources has a panel provider add as many additional panel providers as possible to a core asset in order to achieve the required feasibility. This could mean two panels or twenty panels. When stacking, no care is given to panel makeup, respondents’ attitudes and behaviors, or panel bias.
<h2>Blending</h2>
Blending is the process of combining three or more providers, but in a more planned and intentional method, with no provider getting more than 50% of the total allocation.
I’m not sharing these issues to scare you, but rather to make sure you are fully aware of the pitfalls. However, what’s the solution? How can we best reduce sample bias? On the surface, the answer seems easy: use multiple sample providers. In fact, this might be something you’re already doing, but chances are, you aren’t doing it strategically which means it’s likely you’re making it worse. Strategic sample blending is the process of using multiple suppliers with a planned and intentional method.
<div class="su-pullquote su-pullquote-align-right gb23-iiex-pullquote-01">&#8220;Strategic sample blending is the process of using multiple suppliers with a planned and intentional method.&#8221;</div>
Blending shouldn’t be done just for blending’s sake. The key is that it should be done in a strategic manner. Customizing a blend based on a client’s needs will ensure the best results possible. If you’re not strategically selecting panels based upon attitudes and behaviors, you’re adding inherent bias to your research. Because all panels are different, they all have different attitudes and behaviors.
Remember how I said that thing about something happening to your sample source? Strategic sample blending can make it so that you don’t have to worry about those things. Panels will shift over time. Making minor adjustments allow for stability over time as panels change. If panels fall short on feasibility or need to be replaced, you already have strategically selected panels to fill in the gaps.
You don’t have to worry about biasing your sample or not knowing if changes in the data are due to differences in panels or real shifts in the market. Strategic sample blending greatly reduces risks and inconsistencies because any panel on your study can be easily replaced, and the study replicated.
This way you know your data is consistent wave to wave and changes in data are because of something the client or brand is doing, not because of the sample plan. Don’t let your research be in vain. Strategic sample blending is the premier method of online sampling and can help you improve feasibility, reduce risk, and ensure your data consistency over time. This allows you to have total trust in your data and make confident business decisions.

Researcher's know that bias can impact survey results and sample bias is often overlooked. But, what other impacts can sample bias have besides inconsistency?

Without Sample Strategy, Your Research Stands for Nothing

Editor’s Note: <a href="https://www.greenbook.org/grit">Insights That Work</a> is a showcase of how the <a href="https://www.greenbook.org/grit">GRIT</a> Top 50 Most Innovative Suppliers create solutions to some of the biggest challenges in insights today. This year&#8217;s edition provides case studies on brands like Nestle, Shell, Frito-Lay, and more.
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<h3>Challenge</h3>
Tracker studies are key for brands to understand potential changes in behavior over time. They allow organizations to observe the changes and implement strategies to address them. This can be difficult when a tracking study runs into feasibility issues, or when inconsistency in the results makes it nearly impossible to compare the data and identify trends or changes wave-to-wave.
This is the issue that our client ran into with a long-term tracking study they had been running for one of their clients, a major player in the transportation industry. Because the study had been going on for years, their feasibility was dropping and they were continuously running into reuse limits on respondents provided by their original sample providers.
The stakes for both our client and their client were huge. This was a large account for our client, and their client used this tracker as a key source of their data for making strategic business decisions. If they were to make a change in sample providers, they needed to ensure that there weren’t disruptions, and that data remained consistent compared to previous waves.
<h3>Solution</h3>
This is where EMI’s expertise shines. We started by evaluating their previous supplier. During this process, we found that all their suppliers utilized different recruiting methods, as well as had recently experienced major organizational changes including mergers, acquisitions, and internal changes. Combined, it led to differences in attitudes and behaviors of their respondents, as well as some feasibility challenges. After running a side-by-side test, we also uncovered that some of their suppliers were using third-party sample sources that were unknown to the client.
After the evaluation and testing, we implemented our patented blending methodology, IntelliBlend(r), to build a custom sample blend based on the results we uncovered, our knowledge of the sample landscape, and our Research-on-Research on the sample industry. This ensured consistent feasibility going forward while maintaining data consistency for future waves and when compared to previous waves.
<h3>Outcome</h3>
By implementing IntelliBlend on our client’s tracking study, we were able to bring greater stability and data confidence to the project. Instead of constantly worrying about feasibility wave-to-wave, we were able to provide long-term feasibility through a new group of sample providers that are blended in an intentional and controlled method.
Along with the feasibility stability, we were able to reduce the sample bias our client’s client was encountering since a majority of the sample was being provided by just one or two providers. By incorporating additional suppliers into the blend, we reduced the total amount of samples provided by each supplier, so no one supplier can vastly impact results.
Finally, we were able to improve the transparency of where the sample comes from wave-to-wave by implementing a strict policy of only sourcing proprietary sample from the providers in the blend. No longer are there issues of not knowing where some of the samples are coming from. We were able to achieve all of this, while maintaining data consistency to previous waves, delighting both our client and their client.

IntelliBlend(r) Drives Better Tracker Consistency & Stability

Editor&#8217;s Note: Sampling has always been a core concern of the survey research industry.  Without defensible sampling procedures, confidence in what we do will wither.  No wonder so much focus is placed on it, especially in light of all the technology-driven changes in how we do survey interviewing.  Brian Lamar gives us his POV on critical factors that the industry must do to improve the art and science. 
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Recently at SampleCon, a conference dedicated towards improving marketing research sampling, there was a lot of discussion around the current challenges in online sampling, including how to improve the respondent experience, new gamification techniques, tips to stop fraud, and other trends in the industry.  During one of the last presentations, however, someone asked a question that struck me. He mentioned that he has been in market research for 40 years, and the issues that were being discussed were the same issues that had been discussed 10, 20, even 35 years ago. Unfortunately, our industry is stubborn and slow to get at the heart of the issue.  
Here are the 5 things that we must do as an industry to improve sampling:
<h3>1. Create a Respondent Global ID</h3>
It’s not a well-kept secret that many respondents are members of multiple online panels – we just don’t have a quantifiable number.  If all panel companies were to adopt a global ID for their panelist that they shared across the industry, it would allow for better results since we could account for panel membership overlap and de-duplication.
Yes, most <a href="https://www.greenbook.org/market-research-firms/proprietary-panels">panel companies</a> employ some form of digital fingerprinting software to block the same device from taking multiple surveys, but with the proliferation of devices and the fact that most people have 2-4 now, what’s stopping someone from taking the same survey on different devices for different panels?
That’s why there needs to be a universal verification system as part of any respondent global ID solution.  We, as an industry, spend far too much time designing surveys to validate and verify respondents, as well as evaluating responses after the survey is submitted.  A universal verification system will give confidence to sample buyers that the data they are getting is from verified, unique respondents, as well as make us in the industry more efficient.
<h3>2. Implement a Rating System</h3>
In addition to the global ID and verification system, a standardized industry-rating system should be implemented.  This system would be two-fold, including a respondent rating component and a survey rating component to evaluate client surveys.  
With the respondent rating component, end users of the data provide an Uber-style rating of respondents.  While many Blockchain companies are developing this as part of their offering, why couldn’t this be implemented at the traditional panel level?  It could essentially be another targeting criteria for buyers, as a tool for panel companies to improve their respondents. While it may be overwhelming, it could initially simply be a binary rating: removed or not removed.
As a bonus, companies could publish the overall results so sample buyers can be more educated in their purchasing.
For the survey rating component, this would utilize the same framework as the respondent rating component, but have respondents evaluate and rate client surveys.  If the survey is longer than anticipated, it will be reflected in the ratings. If the survey is boring or irrelevant, the same would happen. We could then create benchmarks and help educate those that score poorly on how to improve the survey experience or incentivize more.
<h3>3. Better Routing / Better Profiling</h3>
With almost any survey, there are questions asked that a respondent answers over and over again.  Whether it’s demographic or profiling questions, or the same questions on different surveys that are routed to them, these are a headache for respondents.  We can fix this by passing along data on a respondent, starting with demographic data, but expanding to other areas like behavioral and attitudinal profiling data.  This will shorten surveys and LOI and make a better survey experience for the respondent. 
<h3>4. Change the Incentive Model</h3>
The current model with many panel companies is to only pay the incentive for people who complete the survey and their data is not deemed “poor quality.”  One of the most frustrating experiences for a respondent is that they invest a significant amount of time in a survey only to term out near the end, therefore receiving nothing.  This needs to change. We should be adequately compensating respondents, especially if they have been verified and willing to participate. I am not saying provide an equal incentive, but a menial incentive would go a long way. 
This isn’t a new idea either.  There are some companies that do this, and they are creating more loyal respondents and diminishing churn in their panel.
<h3>5. Be Truly Transparent</h3>
There are times where panel companies are less then forthcoming about where their sample comes from.  Sometimes it is their proprietary panel, sometimes it’s from partners or even other sources, but they may not tell their client about the other avenues. They may even try to play it off as if it is all their proprietary sample even when it isn’t.  All companies need to be completely transparent. This includes detailing your recruitment methods, your response rates, and the partners (both internal and external) utilized on any specific study. We need an extra level of transparency to help buyers.  
Here is the problem: there is no pressure on our industry’s governing bodies to push for any of these changes.  CASE, a recent industry consortium of researchers from both the client and supply side, has stated they want more information when purchasing sample, and they want to have access to more information.  We need to demand that industry associations such as The Insights Association, ESOMAR, or others step up and issue strong guidance towards best practices.
I believe that if we, as an industry, make these changes, we’ll see:
<ul>
<li style="font-weight: 400;">Respondent experience improve greatly, leading to increased response rates and reduced turnover.</li>
<li style="font-weight: 400;">Membership of online panels will grow.  We don’t know the exact number of panelists in the industry, but we know it’s not enough.  Increasing panel membership will make panels more representative while reducing the overall burden.</li>
<li style="font-weight: 400;">Quality will improve and better business decisions can be made.  This is what will drive the change. I am a strong believer that our industry can grow exponentially over the next few years, if we increase the ability for brands to make better business decisions and measure those decisions.</li>
</ul>
Let’s make sure we don’t have the same conversation 35 years from now.

5 Things the Sample Industry Must Do

I&#8217;ve been fortunate to work in research for over 20 years and have seen the industry evolve in so many ways.  I started at a small <a href="https://www.greenbook.org/market-research-companies/canada">market research company</a> in Lexington Kentucky as telephone interviewer while I was an undergrad at the University of Kentucky. Each day I came in for work, my manager would brief me on the studies that I was going to work on that day ensuring I knew the questionnaire as well as possible. We&#8217;d go through the questionnaire thoroughly, we&#8217;d role play, and she&#8217;d point out areas that the client wanted additional focus. The amount of preparation seemed like overkill to me, but I played along and occasionally would have my feedback incorporated into the questionnaire. These meetings went on for a couple of years – every single day. Every single study. And not with just me – all of us interviewers had to go through this process. I think I still have most of an utility questionnaire memorized.
Later, I managed a telephone tracking study at a different company in New York as a project manager. Like most project managers most days were very hectic with all of the different tasks that you do to support clients. About once a month I would go over to the phone center and monitor the telephone interviews. I would sit in a briefing similar to what I went through my initial role as a telephone interviewer. This briefing was at an entirely another level though. The supervisor would have an entire room full of interviewers, and they&#8217;d review the questionnaire(s) similar to what I did, only these interviewers were much more detail oriented and critical and did a very thorough QC of every study before it launched. They&#8217;d not just offer suggestions, but they&#8217;d campaign for changes and talk about how important it would be to make these changes. Each month I would receive this lengthy list of changes, and it would be frustrating to go through them and determine which suggestions were important enough to bring to the client&#8217;s attention. Typically 1-2 changes would be made, making the language more consumer (not research) friendly, more logical flow, and other improvements. Looking back on it, the process that was created long before me added a lot of value to the research.
In 2001, like most clients, this client decided to transition their research from telephone to online, including the tracking study I managed. When we initially moved the work online, we had an entire team of people review the questionnaire and offer insights on its design, keeping both new technologies in mind as well as making improvements to the respondent experience. We had internal experts discuss the advantages and disadvantages of online research, and we implemented them. We did a side by side test for over a year and were in constant communication with the client on a questionnaire/design standpoint. Rest assured, we made a lot of mistakes back then and were far from perfect. Sweepstakes as an incentive seem ridiculous nowadays. We transitioned phone surveys to online without pushing back on interview length and didn&#8217;t think long-term as much as we should have. But we had a large, diverse group of people who focused on the quality of the research as well as advocates for the respondents. Nearly all companies did back then, and the client was very involved in these discussions and decisions. They had transparency throughout the entire process that made the research more successful.
From 2001 and 2013 (when online research moved from infancy to maturity) I had a variety of positions almost exclusively in online research from project management to sales to analysis and was somewhat removed from the quality assurance processes. I know a process still existed and were important, but I wasn&#8217;t as involved. One of my current roles is to assist clients in data quality review. I review data; I review questionnaires; I review research designs at a much broader level than I did early in my career. Instead of managing or seeing 5-10 studies per week, I have the opportunity to review much more than that across a wide range of objectives and topics. Perhaps it&#8217;s the nature of this role, but I feel like the systems we, and lots of companies put in place back in my telephone and early online research days, are now non-existent. I also take a lot of surveys from non-clients as I&#8217;m a member of numerous different panels just to see what new types of innovations and research in the marketplace. According to a recent GRIT report, about half of all surveys are not designed for mobile devices, which is completely unacceptable. I can personally testify how frustrating these surveys are. Online research has made a lot of technology investments in the past few years, and many of these innovations have made improvements. But we certainly haven&#8217;t figured out how to best use this technology to improve survey design and the respondent experience – at least not yet.
I see a lot of bad research unfortunately both in my day job to evaluate data quality as well as when I take surveys in my spare time. I see screeners that are obvious for any respondent to enter the survey and even surveys without screeners entirely. I&#8217;m not sure if all researchers understand the importance of a &#8220;none of these&#8221; any longer. Respondents routinely answer the same question over and over as they&#8217;re routed from sample provider to sample provider. And this bad research isn&#8217;t from companies you would expect – they&#8217;re from names all of you have heard of: big brands or big market<a href="https://www.greenbook.org/market-research-companies/toronto-(on)"> research companies</a> along with small businesses or individuals using DIY tools.
At some point along the way, I feel like we&#8217;ve lost scrutiny over questionnaire and research design and that is the point of my writing this. A lot of other people have written similar blogs, and while nothing I say may be unique, it needs to be said over and over again until things improve. I heard someone recently say that &#8220;the market has spoken&#8221; when discussing sample and data quality meaning that clients, market <a href="https://www.greenbook.org/market-research-companies/canada">research firms</a>, and researchers have accepted lower quality in so many areas. Perhaps as an industry we have, but I feel like a lot of driving principals of research I described above are now non-existent. Do companies still have a thorough QC process? Do clients review online surveys? How many people are involved in questionnaire design? Just last week I led a round-table discussion on data quality and multiple brands admitted to not reviewing surveys and not looking at respondent-level data. Honestly, it makes me sad and if you&#8217;ve read this far you should be sad or angry as well.
Perhaps these data quality controls exist at some companies – I bet at the successful ones they do. I&#8217;d love to hear from you as data quality, and ultimately clients making better business decisions because of survey research is a goal of mine.
Having said all of this, I can&#8217;t discuss all of these challenges without a few words of advice for researchers:
<ol>
<li>I urge you to take your online surveys. All of them. Have your team take them as well. Have someone not associated with the study or even market research test it as well. I think you&#8217;ll be amazed at what you find.</li>
<li>Use technology to assist. <a href="https://www.greenbook.org/market-research-firms/survey-programming">Programming companies</a> have done a great job at implementing techniques to help with the data quality process. They can identify/flag speeders. They can summarize data quality questions. They can provide respondent scores based upon open-ended questions. Become familiar with them and utilize them!</li>
<li>Everyone else in the process should take your survey. The client shouldn&#8217;t be the only person expected to take the survey, but so should the <a href="https://www.greenbook.org/market-research-companies/united-states-of-america">market research</a> firm, the sample team, the analyst, a QC team, everyone involved. Believe me, you&#8217;ll make a lot of recommendations around LOI and mobile-design if you do this. Join a panel and take a few surveys each week and odds are, you&#8217;ll want to write a blog like this as well.</li>
<li>Know where your sample is coming from and demand transparency. Most sample providers are transparent and will answer any question, but you have to ask the question. How do they recruit? How does the survey get to the respondent? Are they ever routed? Do you prescreen? These are just a few questions you should understand about respondents to your survey.</li>
<li>Ask respondent satisfaction and feedback. Are you getting feedback from respondents about the survey design? Insights can be obtained this way as well.</li>
<li>Don&#8217;t remove yourself from the quality assurance role like I did for so many years. Regardless of where you are in the market research process, make sure you understand the quality steps throughout the entire process and ensure there are no gaps.</li>
</ol>
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6 “Back to Basics” Steps Researchers Should Practice

Editor’s Intro: For all those who said “it can’t happen here” when all the debate was taking place over the European GDPR, well, it is happening here. As Adam Dietrich very ably describes, California is once again setting the direction for the rest of the US, and other states may quickly follow. As Adam writes, this will force US researchers out of their lethargy, and spur even faster disruption, with developments like blockchain taking on greater impetus. “What, me, worry?” will not be enough of a response.
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With Europe’s implementation of its General Data Protection Regulation (GDPR), the whistleblowing around Cambridge Analytica, and Facebook CEO Mark Zuckerberg’s testimony in front of Congress, we spent a lot of time this spring talking about data collection and privacy. Media pundits, market researchers, and tech insiders alike all opined about the future of online privacy in the United States and looked to Washington to see if national legislation was on the horizon. Unfortunately, most of us may have been looking at the wrong coast.
Two weeks ago, the California Assembly and Senate passed The California Consumer Privacy Act, which Governor Jerry Brown signed into law just hours before a deadline to keep an even more aggressive version of the policy off November’s statewide ballots. The measure, which some outlets have dubbed “California’s Mini GDPR,” received opposition from The Internet Association – a lobbying group that represents the state’s major tech companies like Facebook, Google, and Uber. So, what is this bill that privacy rights groups are cheering for, but has some of the largest California employers concerned? And if you’re a market researcher that doesn’t live in California, why should you care?
The legislation is similar to Europe’s GDPR in that it will require businesses to disclose the type of data they collect on users and include details on the advertisers or other third parties with which they share data. That alone will be eye-opening for consumers, but the bill also requires companies to provide an avenue for users to opt out of their data being sold – without any degradation in services. In a watered-down version of the GDPR, the bill also gives consumers the ability to request that their personal information be deleted. Europe’s version has built-in sunset clauses that require the deletion.
While California is home to nearly 40 million residents, why does this matter outside of the Golden State? Very simply, it’s because companies don’t want to deal with the logistical nightmare of having a California policy and a “the other 49 states” policy. In 2003, when California passed the state’s Online Privacy Protection Act, requiring websites to publish the privacy policy statements whenever they collected user data, they were one of the first in the nation to do so. Being home to such a massive population, California has been setting national online privacy standards ever since.
As the research and tech world has just moved through GDPR, is this really any different? Yes and no. A lot of companies collecting data are only doing so among America’s vast and relatively wealthy consumer base. They haven’t been forced to explore compliance yet and will have to explore that burden before enforcement begins in 2020. There are also a number of organizations that have taken a different approach due to the fact that they operate globally. These organizations have taken one of two approaches: implementing different policies for the different regions they operate, or applying GDPR rules across the board, even for their North American operations. Additionally, as the legislature and tech lobby found a compromise in the drafting of the bill, it doesn’t have the same teeth as its European counterpart. For example, California’s act places the impetus for opting out and data deletion on the consumer rather than the data collector, similar to Australia’s version. Also, while the potential enforcement of fines would hurt any company’s bottom line, they’re capped at lower numbers than what we’ve seen in Europe.
Overall, there are a lot of strong provisions for consumers in this legislation and it will force American research and sample providers to update their current data protocols to a higher standard, but it isn’t all sunshine and rainbows for the research community we know today. First, due to the opt-in aspects of this bill, sample procurement will become more difficult – especially among minors under age 16, regardless of methodology. Furthermore, every branch that touches respondent data will need to create the means to delete data at the user’s request. The days of a panelist simply unsubscribing are overcome. And finally, what do we do about the major fear plaguing the industry’s lobbying arms? More legislation. Vermont looks poised to create their own bill and leading Democrats have floated the idea of a national privacy law. These overlapping entities may make the aforementioned pains of data collection even more intrusive if we’re forced to develop policies state-by-state.
Data privacy legislation will be hitting our industry over the next few years, whether we are ready for it or not. It could create a better, safer user experience and force some of the research industry’s privacy laggards to adapt. Additionally, as users come to expect more control over their data, we could see an opening for the blockchain technology that has disrupted other industries and put users in a more powerful position. Research has seen its fair share of new trends and technology, but is generally regarded as slow-moving in terms of innovation. As these data privacy laws loom, expect to see moves made by select leaders in the industry to try to get ahead.

California’s Mini GDPR and It What It Means For Market Research

One of the biggest news stories this week has been Cambridge Analytica, a political consulting firm focusing on data collection, data mining, data analysis, and strategic communications, and their questionable data collection practices with Facebook during the 2016 US presidential election. Don’t get me wrong, Facebook has a lot of questions to answer, and CEO Mark Zuckerberg is already being called to testify in Congress, but that is not the focus of this blog. The bigger question that this news has brought up is around data collection in general, and for firms that collect data – with private information or not –and how this will affect our industry.
There is already some activity to give users more ownership over their data with the coming GDPR legislation in Europe, but with the Cambridge Analytica news, I want to pose a question: Is this a new turning point in data collection?
By this, I mean, what changes in data collection rules will be created to address this? And, how will this impact how the market research industry collects data from its respondents?
<a href="https://www.greenbook.org/market-research-companies/united-arab-emirates">Market research companies</a> have been sharing data with each other for years, but the trend of appending data from third party sources to provide additional information is rapidly growing. Today, many researchers create a wider depiction of the market by combining panelist data with things such as Facebook likes, usage information from apps like Snapchat or Pandora, information from credit bureaus, and many other forms of behavioral data that most of us have agreed to share when we click through those lengthy terms and conditions without reading.
To be clear, it appears that Cambridge Analytica collected its data under the guise of “academic research” in the form of a psychological/personality test that never revealed to users that it would be used to target them and their Facebook friends regarding election campaigning. This clear breach of personal information laws and lack of disclosure is what has created the firm’s legal issues, but the parallels between academic and market research industry data collection are well-defined.
Given the high-profile nature of this Cambridge Analytica and Facebook news, there will be upcoming discussions in Washington, D.C. and statehouses around the country about potential legislation to further regulate the sharing of this type of data and information, but that might not be as crucial to researchers as addressing this topic with the general population.
At what point will consumers start refusing to share their personal data? This could compound much further than deleting a social media account. Will panelists start refusing to participate in usage tests that collect their address to ship them a product? How much trust in research remains? We’ve already seen the decades-long drop in willingness to participate in phone research, preferring to instead participate online behind a screen. Going forward, can we expect respondents to be as forthright in research about private topics such as their health or finances?
With recent breaches and misuses of data at Equifax, Ashley Madison, and now Facebook, respondents are more likely than ever to step back and examine where their data is going. Because of that, it is imperative for the many industries that rely on data collection to consider what could happen next – and enact policies to regain public trust.

Facebook and Cambridge Analytica – A Turning Point in Data Collection?

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