Democratization of research: how technology is reshaping access to consumer research

Like free and fair elections are essential to political democracy, the democratization of research—making it readily available to non-researchers—is a cause for celebration.

However, not long ago, some research professionals viewed it differently:

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When I began as a qualitative researcher in late 2005, we were having a team lunch when one of the directors shared a story about their time as a junior researcher. The subject was ‘the most awkward market research meeting she’d ever attended.’ 

She described going to a debrief with a senior team member and their ad agency client. They’d had a generally successful, amicable presentation of findings using a new-fangled research tool (I can’t remember exactly which one).

One of the ad agency’s team members—impressed with the tool and its results—casually asked whether they could gain direct access.

The senior researcher unthinkingly retorted:

“No, sorry mate, you don’t give guns to monkeys.”

As you might imagine, the meeting concluded incredibly awkwardly, and once back in the taxi cab, my future director sat there stunned.

The senior researcher eventually reflected: 

“Yeah, I probably shouldn’t have said that monkey thing.”

Probably not. 

A few years later, I moved to the UK and was doing research for Lloyds of London. 

My colleague commented about wanting to keep the raw data private from the client due to the risk of misinterpretation.

However, the research manager replied sharply, "Yes, well. It’s our data, so we’ll do what we want with it!’”

He sure told him—and again—awkward!

(To make matters worse, we also broke this client’s dress code by failing to wear ties during the debrief—not the most successful meeting by any stretch.) 

These anecdotes illustrate protective and growingly passé attitudes towards market research data and insight—who can access what and who is responsible. 

Every industry and individual wants to safeguard their roles and responsibilities somewhat. In this sense, research professionals were not uncommon in wanting respect for their expertise, not to mention discouraging non-researchers from conducting shoddy DIY research. 

I’ve experienced instances where advertising agencies did not appreciate non-ad agency members contributing creative ideas to ad development. They took an extremely dim view of external contributions—and let you know about it. As a researcher, your job was to test their ideas, not develop your own—that was strictly ad agency turf, and they proactively defended it. I can’t imagine a cloud-based collaborative platform like Miro, which allows non-agency members to participate in creative work, being received well in the mid to late 2000s ad agency world.

In past articles, I discussed the continuous advancement of AI and how it affects those involved in research. However, besides predictive and generative AI, there has been a rapid development of 'research tech,' which refers to technology and systems used to distribute research data and insights via emerging digital technologies.

Based on my experience, this has been a net positive for researchers and non-researchers in terms of leveraging data and insights. 

It has allowed researchers to do more with the data they collect while making extracting insights far more inclusive and collaborative than in the past. 

Unlike giving power to those incapable of wielding it responsibly (as implied by that researcher’s woeful remark about monkeys and guns), today’s technology offers non-researchers access to explore what has traditionally been very difficult work, or at least outside their scope of responsibility.

Previously, access to market research insights (generating, analyzing, and leveraging them) was labor intensive and generally required the engagement of human ‘experts’ to support you. 

Running a focus group required a whole raft of people, from recruiters to physical session hosts, usually an expensive venue and catering. Then there was the drama and expense of organizing FocusVision—a notoriously fiddly, costly, and now defunct video streaming platform predating Zoom and Teams.

At the back end, you’d need audio transcriptionists before a team of researchers could analyze the findings—usually working on large sheets of A1 paper before typing it into a PowerPoint report. The process was time-consuming, labor-intensive, and expensive. 

However, the advent of digital research tools has changed all of this. Now, you can DIY participant recruitment using platforms like Askable. Zoom or Teams means you no longer need a venue, and auto transcription tools, like those offered by Dovetail, mean you have all your transcripts collected and collated the minute you finish an interview. 

With access to this range of digital and SaaS research-tech tools, a small business or research freelancer can replicate what a multi-person research agency or insight department did, generating insight in a fraction of the time for a fraction of the cost. 

Again, it’s easy to forget how painful sharing research data (especially raw, qualitative data) was until recently. 

Seven or eight years ago, I worked for a financial services provider in the UK who wanted to understand their cohort of users with large credit card balances who were only making minimum payments. 

The research involved filming respondents in their homes and using Skype to conduct online interviews with their audiences. The logistics around downloading footage from the videos, generating transcriptions, and sharing the footage at a face-to-face workshop session were incredibly stressful. 

In these situations, I wasn’t worried about my ability to create collaborative insight from the team. On the other hand, I was very concerned about the tech letting me down and preventing me from sharing raw data with workshop participants to make the most of the session. 

Now, digital platforms like Dovetail can easily share, analyze, and tag raw data and share it with the wider research team via an insights hub whenever convenient. 

Having shared, cloud-hosted content in consistent formats and settings removes all the stress-inducing technical issues associated with research content sharing, meaning everyone can get up-to-speed with relevant insight and data immediately. 

Equally, suppose you have a shared analysis session. In that case, you can host and access content from a single location in a consistent format and focus more on getting the most out of the data presented rather than worrying about the tech letting you down. 

I wish this technology existed years ago when the video camera used to broadcast footage ran out of battery, and my junior had left the charging cable in her apartment.

Traditional market research methods often involve significant financial investments—all the aspects related to running qualitative focus groups are also relevant to large-scale quantitative research, from time-consuming setup to data collection and analysis. 

Again, today's tools and platforms provide cost-effective alternatives. For example, you can write a simple survey with basic skips and filtering for free using Google Forms, where previously, you might have needed to learn how to program or code a survey. 

Similarly, the amount of data from free tools like Google Trends can greatly illuminate when addressing a research question online. For those unfamiliar, Google Trends looks at what people search for globally. It's a widely held ‘research truth’ that what people search for versus what they say they search for differs—so having access to this resource to check what respondents claim is incredibly valuable.

Aside from purely free tools, there are low-cost survey scripting tools like Survey Monkey and Qualtrics, social media analytics tools like Sprout Social, and other digital tools that allow you to gather data and insights, analyze trends, and generate insight to feed into business strategy, without breaking the bank. 

Using Qualtrics for the first time to create a relatively complex survey from scratch, without needing to write a single line of code, was a revelation for me, as I’m sure it is for non-research specialists using it for the first time.

Beyond this, the cost efficiency of a range of powerful, accessible, and low-cost (even free!) research tools is particularly beneficial for startups and smaller businesses that won’t have the financial resources for a dedicated research team or insight specialists. It also deepens the skill set and potential range of questions you can answer as an individual researcher.

When I first tried my hand at SPSS (Statistical Package for the Social Sciences), I was fumbling through Stats 101 at Otago University in Dunedin, New Zealand. And yes, this was the last millenia! I don’t recall much, aside from the baffling complexity of the software and the confusing, non-intuitive methods for importing and analyzing the data. 

I recall the long-suffering computer laboratory assistant grudgingly holding my hand through the various steps in the analysis, and I eventually scraped a pass on my paper. Little did I know that the much-loathed stats/research methods element of my psychology degree would be the most practical element once I entered the workforce! 

Now, the tools to analyze, manipulate, and visualize data are more powerful, far more intuitive, and user-friendly than they ever used to be. While you can undoubtedly export data into tools like SPSS and undertake further, more detailed analysis with it, platforms like Qualtrics have relatively powerful analytics and data visualization tools as dashboards built into the platforms themselves, meaning that, at a glance, trends and insight are observable within the data, to those who are both expert and non-expert in data analysis.

One of the common issues directed at market researchers is that the process simply takes too long. It’s unsurprising, given the number of people it once involved, each with specialized roles, handing off to each other, getting the brief, designing the methodology, and getting it signed off. 

By the time you’d collected your data, cleaned it, analyzed it, turned it into a PowerPoint report, proofed it, and waited two weeks for a window to present it to the client, the findings were either a little bit dated or the moment when they would have been really useful had passed.

Again, the tools now at a researcher’s disposal to create real-time reporting to shape real-time decision-making are unprecedented. One area where this is particularly useful is PR research, where up-to-the-minute awareness of brand perception, including what’s being said about your business—can be critical (especially in times of crisis). 

Tools like Signal AI, which collects all the media mentions for your brand or business in real-time, can be incredibly powerful. 

These tools can translate data into dashboards that illustrate your brand’s share of voice and positive/negative sentiment. Again, all of this is immediate, so you can see how unfolding events shape public perception of your business. 

Instead of waiting for a researcher to conduct a research exercise, gather all brand mentions over time, turn this into a report, and present it in days, not weeks. Then, you can make data-driven decisions right now about business-critical issues. 

Again, such tools are low-cost, cloud-based, and intuitive for a non-PR research expert, so smaller organizations without dedicated research teams can generate valuable insights in-house.

Judging by the explosion of research-tech tools shaking up the status quo and reshaping researcher roles, this shift has been a massive positive, democratizing access to research and insight while enhancing the portfolio of tools accessible to specialist researchers. Now, if only I had a tool to generate and shape my creative ideas next time I’m in front of a creative advertising agency...