As researchers, most of us are feeling a tectonic shift under our feet. We know that consumers’ lives are rapidly evolving. We see companies scrambling to capitalize on marketplace changes by developing more agile research approaches. And, in our new social world, we have discovered that qualitative research and storytelling often does the most to drive successful business outcomes. This blog will cover three key topics related to qualitative technology:
- Why technology is taking an increasingly important role in qualitative research
- Which three technology trends have the greatest impact on our ability to drive consumer insights
- What role market researchers are going to play as access to research technology continues to be diffused in organizations
Why New Technology is Critical in Qualitative Research
First, the days of believing that all market research will be replaced by big data has long past. We know that there is an overwhelming amount of secondary and operational data that can help identify problems and opportunities in organizations. But, our success in responding to those problems and opportunities comes from determining the strategy and execution of new, innovative and creative solutions not addressed by big data. The speed of building and optimizing these new products, services and communications programs has become the focus of marketing and innovation teams. And that is where I believe qualitative technology has the potential to drastically improve business speed and impact.
The companies that have shown the most success at rapid innovation have primarily been technology companies who have embraced agile development efforts to collect the right consumer data and gain rapid team alignment at every stage of development. Because agile development typically requires in-depth learning and rapid iteration, this is driving demand for new qualitative research technologies that reduced time and complexity, and enable rapid team decisions.
Three New Qualitative Research Technologies
Here are three technologies trends creating significant change in the effectiveness of qualitative research and delivering consumer insights that propel marketing and innovation teams.
#1 Automated Micro-Targeting:
Online communities have been around for nearly two decades now, and teams that use them for testing new ideas have seen significant benefits, particularly in terms of having rapid access to a highly-targeted group of participants. But many teams have struggled implementing or sustaining online communities because of drawbacks related to cost, sample diversity, quality and bias.
Newer technologies developed by tech giants to handle big data are also providing market research technology companies’ new ways to get the speed of online communities in a way that is more flexible, cost effective and targeted. For example, some qualitative research technology companies have tapped into social media sites for recruiting. Sites like Facebook, Instagram and LinkedIn have much richer and more up-to-date data on potential research participants than traditional research panel companies collect. By tapping social media technology, companies can shorten the time to target and recruit participants from weeks to days. This creates an opportunity to supplement or replace ongoing communities with shorter term, more flexible online qualitative research that delivers Iterative Insights.
Also, organizations that have dedicated panels are building automated recruiting interfaces that tap a much more sophisticated set of data on participants. The outcome of these interfaces is rapid consumer insights studies that can be created and fielded using exactly the right target audience. With ongoing industry issues related to sample quality, some companies are even building proprietary qualitative panels that ensure participants are geo-demographically validated, vetted to be articulate and willing to engage in social media-style conversations with photos and video. A major advantage of this approach is that companies can have a mix of branded and unbranded qualitative engagement, excluding participants that might have been biased by prior discussions.
#2 Virtual-Assisted Design and Data Collection:
One of the biggest challenges of gathering online qualitative consumer insights is figuring out how to collect the right data. Do you ask people survey style questions, or have them capture video? Do you create an interactive dialog or gather private responses? How do you sequence questions to get unbiased answers? And, how do you foster high quality responses, team discussion or rapid iteration to building on ideas that are generated by the group?
Historically, all qualitative research has been “custom” research, with expert moderators taking days or weeks to build research designs. But technology is taking the work out of design, and making it faster and easier to collect high quality qualitative data. It started with qualitative tools that sequence participants through a series of video or text-based questions that were “programmed” by moderators. But it has evolved with automated technology that taps into pre-designed discussion guide templates which have been developed to maximize quality. These activities are also structured to create qualitative datasets that are easier to analyze than traditional transcripts. For example, Digsite Fill-In-The-Blank tasks allow participants to tell MadLibs style stories. The complete response can be read in paragraph form, but the individual elements of the story can also be more easily analyzed.
In addition, automated tools are eliminating manual labor of qualitative data collection and validation. State of the art platforms automatically checks quality of responses, send out reminders and rewards, checks that participants are recording videos correctly, and even identify and feature responses that are most representative of the data. With the emergence of virtual assistants and chat bots, platforms will continue to get smarter about design and data collection.
#3 Smarter Reporting Automation:
In the past, extracting consumer insights from qualitative data has been a manual process. Researchers end up with lengthy transcripts or videos to cull through, using outdated coding approaches that make team iteration and rapid decision making more difficult.
Today, qualitative platforms are starting to apply automated tagging, natural language processing, sentiment analysis and text analytics to qualitative datasets to automatically find and feature the most relevant content. They have also taken a page from Pinterest and other social media sites to make it easier for teams to share key quotes and photos while they are in the process of collecting qualitative data. Smarter interfaces are taking quotes pinned by the team along with automated text analytics and combining them to create fast and customizable reports. This improved approach to identifying and sharing key insights is making it easier for teams to make decisions and iterate solutions within a single project or community.
The Role of Market Research in Technology Adoption
So, the final question is, are we as market researchers going to be the ones driving the adoption and usage of new qualitative technology? While this seems like the obvious path, research organizations are often late adopters of new technology. After all, you could say we are in the “safety” business, trying to get consumer feedback to reduce risk before moving forward with business decisions. The challenge is, the approaches we know to be “safe” are what we did before in absence of all of this technology change.
At the same time, other departments outside of market research are finding ways to collect qualitative consumer insights on their own. Whether it is R&D teams doing immersion work in the field, usability testing teams doing user testing, social media team doing social media engagement, or customer support teams collecting voice of the customer data, organizations are being encouraged to collect more consumer insights and put it in the hands of the decision makers.
If we as market researchers don’t take the lead in showing our organizations how to be more agile, we continue to narrow our value to only large-scale studies that have limited impact on the key decisions that teams need to make week in and week out. We also have to be ready to train our teams on how to use research data and results appropriately, so they make effective use of the capabilities we bring.
With that, I’d like to encourage all of you to get out there and look how qualitative research is changing and start to plan how you can transform your internal function to tap new qualitative tools for faster and more flexible consumer insights. You can make a difference in growing informed decision making, and help organizations avoid the quality sacrifices we have seen when unsophisticated research tools are put in the hands of untrained decision makers.