Posted By Jennifer Dale,
Tuesday, September 17, 2019
Qual or Quant? Choosing the best method for your research study
Quantitative and qualitative research are both scientific methods for data collection and analysis. They can be applied alone, or in combination, to maximize insights.
The Basic Difference: Going Beyond What vs. Why
Quantitative research relies on large sample sizes to collect numerical data that can be mathematically analyzed for statistically significantfindings. Surveys are structured, questions are typically closed-ended, and answer choices are fixed. However, quantitative research may also include a limited number of short-answer open-ended questions to help clarify why people responded the way they did to a closed-ended question. Eye tracking, facial coding, and even Big Data fall under the umbrella of quantitative research, with computers analyzing enormous volumes of data incredibly fast.
Quantitative studies produce numerical data, which allows for statistical analysis and ultimately precise findings. The US Census is a great example of a quantitative research study – fixed and close-ended questions, an enormous sample size, a collective review of many respondents, and measured population segments.
In contrast, qualitative research seeks to understand the reasons behind the numbers, as well as what is not yet known. Sample sizes are smaller, questions are unstructured, and results more subjective. Unlike quantitative research, qualitative studies insert the researcher into the data collection process. The researcher probes responses and participants provide more detail. Qualitative data is collected through interviews, group discussions, diaries, personal observations, and a variety of other creative and ever-expanding means.
Qual studies work with textual and visual data, interpreted and analyzed for directional findings. Qualitative research studies include fluid and open-ended questions, a smaller sample size, an in-depth review of each respondent, and emerging themes.
I like to think of the difference visually, where a quant study collects specific data from a large number of people, and a qual study goes deeper to collect greater insights from a small number of people.
How to Choose
The answer to whether you proceed with quantitative or qualitative research lies in your research objective and available resources.
Why you’re doing the research
What you need to know
Your budget, staff, + schedule
How the findings will be used
Consider these possible scenarios the next time you’re stuck and don’t know which way to go:
Quant + qual can come together in other ways. A questionnaire with open-ended questions, while ultimately coded numerically, can offer a window into the unknown. Focus groups that also include poll questions or surveys can produce hard data when analyzed in total, even if the results are not statistically significant.
With good planning, quantitative and qualitative research come together like a dance, guiding the marketer’s success with every step.
I Say Hybrid, You Say Multimethod
Combining quantitative and qualitative research approaches is an ancient strategy, but the names continue to change with the times. I did a bit of research and found the following terms being used to describe that ideal combination of quantitative and qualitative research. What term do you use? And why? ;)
Posted By Bruce Peoples,
Tuesday, August 20, 2019
Updated: Tuesday, August 13, 2019
Moderating vs. Facilitating: What’s the Difference? Can You Do Both?
A few events in my career journey triggered the exploration of facilitating as a business opportunity and value-add for my clients. First was a breakout session at a QRCA conference where “facilitating” — vs. “moderating” — was brought to my attention. The second was when a client called me on a Sunday to replace his facilitator on Monday, to facilitate a session with R&D, sales, and marketing. With so little time to prepare, I trusted my instincts and experience as a moderator and let it fly… and suddenly I was a facilitator! It was a productive session — the client called me back for another session, and later to do consumer focus groups — and my curiosity was piqued to learn more.
Core Elements: The Same
I attended a three-day training session in facilitation (much like those offered at RIVA or Burke) and was pleasantly surprised to confirm that these two disciplines have much in common. The core elements of moderating and facilitating are the same: there is a gathering of people with something in common; there is a purpose behind the meeting; and there are desired outcomes. You guide the discussion in a thoughtful manner by providing structure and process.
Perhaps the biggest commonality is putting together an agenda — what we call a discussion guide — based on the client’s objectives and desired deliverables. Like a focus group discussion guide, much attention must be paid to the flow of the meeting and to the activities that will generate robust discussions.
Many of the exercises you utilize for qualitative can also be used for facilitating meetings. These might include:
Developing lists and gathering, sorting, and ranking ideas
Breaking out in small groups
Facilitated meetings are usually longer – a half day – and therefore benefit from energizing exercises interspersed throughout the session.
The Differences: Participants, Output, and Achieving Consensus
One key difference between moderating and facilitating is the participants. Focus group participants have no skin in the outcome; you will never see them again. Facilitated participants have to work with each other. A facilitated meeting may have colleagues from different functions (R&D, marketing, sales) and at different levels of authority (managers to vice presidents). When the meeting is over, they have to work together to achieve common goals. Their strategies and tactics – their jobs – might be affected by the outcome. I ask to conduct a few brief interviews of participants from different areas prior to the meeting to get a feel for the situation, personalities, motives, and issues that might arise.
Another difference is the output: in a focus group, the outputs are insights and determining their implications and developing recommendations. In a facilitated work group or work team meeting, the output is often an action plan that determines what, who, how much, and when. The action plan should be understood and agreed upon by all participants. In other words: achieve consensus, which means participants can live with the decisions that created the action plan and support them.
Two issues you’ll address more often when facilitating a work team than moderating consumers are resolving conflicts and achieving consensus. Marketing wants that new ice cream now; manufacturing can’t make it until next year. Your approach is somewhat intuitive and not much different than if moderating – but requires more attention and care. Things you’ll need to spend more time on include clarifying the issue, understanding its root causes, ensuring everyone understands the issue, brainstorming pros and cons, and ultimately utilizing techniques to rank or prioritize.
Projects and Meetings Where Facilitators Add Value
Facilitators can add value to a lot of different projects and meetings, but common types are:
Innovation: Brainstorming to create new product ideas.
Process improvement: This might include flowcharting a process, identifying roadblocks, and developing solutions to clear those roadblocks.
Strategic planning: This might include a market situation assessment, SWOT analysis, and developing the outlines of a new strategic plan.
Data Analysis: Sharing, analyzing, and assessing a lot of data from a variety of sources.
Planning and executing a new product launch: The output is often an action plan.
Implications for You
If you are a good moderator, should you seek out facilitation opportunities? Yes! You already have many of the skills, resources, and experiences to successfully facilitate work group meetings. To pump up your confidence before jumping in, seek and find some formal facilitation training. On your first projects, get a partner to help plan and execute.
Put together a one- or two-page brochure (PDF is fine) highlighting your capabilities – and this can include moderating. Then network your way to generate awareness. Many of you work with research managers at large companies. Let them know and ask them to share your capabilities with their colleagues in other functions, such as marketing, sales, R&D, or HR.
About the Author:
Prior to becoming a qualitative consultant, Bruce Peoples worked in brand management, channel, and customer marketing for several well-known brands in different industries including Hanes and Jack Daniel’s. Bruce has been a QRCA member for about a decade now and utilizes a variety of methods to help his clients solve their marketing problems, whether they be consumer or business-to-business related. Bruce was trained in moderating at RIVA and in facilitation at Leadership Strategies.
Posted By Katye Hamilton,
Tuesday, August 6, 2019
Updated: Tuesday, August 6, 2019
Qualitative Research 101 – A Guide to the Basics of Qual
Qualitative Research 101 – A Guide to the Basics of Qual
Are you new to qualitative research or want a refresher on the different styles of group discussions that typically encompass qual research? While the topics you explore in each session will vary widely, there’s a basic group structure to take into consideration before you start building your discussion guide. First, decide if your research objectives need face-to-face (F2F) solutions or if an online approach will work.
For best group dynamics, the ideal total participants is 4-6 people. Any larger and you won’t be able to hear from each participant as often or dive deep into the conversation with everyone involved. The discussion is led by a moderator and you may see an assistant or dual moderator in the room. The moderator(s) lead the group from topic to topic and encourage all to contribute.
Dyads and Triads
These are groups with only two or three participants, respectively, plus the moderator. Maybe it’s a physician, patient, and caregiver doing an appointment mock-up. Or you want to have a focused discussion with just a few consumers; three pet parents, each with a pet with a specific dietary need. The conversation is likely going to be less exploratory and more focused so you can dive into details quicker. Dyads and Triads are great when there’s a monitoring session, like website navigation or roleplaying situations.
In-Depth Interview (IDI)
A true one-on-one interview involves a moderator + respondent. The power in an IDI usually stems from the research topic at hand. Is it a sensitive subject like health care, death, financial, etc.? Or maybe it’s understanding a person’s journey – purchasing process, behavior understanding, etc. Isolating the respondent helps promote a feeling of safety in the conversation as well as creates an opportunity to explore subjects more deeply.
All three of these session types can be executed in a research facility, off-site with cameras for recording, or online with a focus group vendor. Most clients want to see and hear the conversations in real time, so they watch from what we call the “back room” which may be a physical room at a research facility or off-site, or in a virtual back room with an online provider.
There are some innovative focus group spaces that shake up the traditional, round table/conference room set-up with more relaxed or on-topic scenes. Check out Good Run Research & Recreation; they have a formal living room and bar room models (still with the one-way mirror, complete back room experience for clients) to amplify the respondent and moderator discussions.
These have a lot of names (workshop, co-creation, etc.), but the premise is pretty similar across the board. These are sessions where you bring multiple groups of people into a room together. When you have a client that wants to be highly engaged with the process, and not just an observer, you may want to tap into these models. These could be:
An internal workshop with employees from multiple departments (stakeholders) and you as the moderator facilitate the group activities and conversation.
A session where you mingle clients with the respondents for brainstorming, ideation, new product development, etc. Clients would likely be spread out among the respondent tables so they can engage directly as well as learn firsthand their experiences and ideas.
Marketing research ethnographies are never “hands-off.” In the education space, a true ethnography would have little to no engagement with the person or people you are observing; you’re meant to do just that – observe. In marketing research, we believe in the power of observation plus asking questions.
Ethnographies in MR can come in the form of in-home interviews, shop-alongs where you meet a respondent at a specified location and track their buying process, or even on-location research. The purpose is to get the respondent in a natural environment, rather than a traditional focus group setting. This is helpful when you need fewer recall answers and more in-the-moment engagement.
Other F2F Types
The list above is not meant to be exhaustive; in-person intercepts and telephone interviews can be important for your qualitative research, depending on the objectives. Is there another form of F2F that I missed? Tell me about your methodology in the comments!
Online qual solutions have expanded tremendously in terms of vendors, programs, platforms, and the types of research executions available — from desktop applications to mobile phone apps. It’s important to consider online styles when your client may have a limited budget or there’s a tight timeline that limits your travel opportunities.
Methods may vary, from text-based surveys with auto Q&A to mobile apps that track respondents’ phone patterns (the apps they open, websites they checked, etc.). Sometimes it’s important to engage and observe in a respondent’s natural habitat – their mobile device. Maybe you need to geo-ping respondents for a study when they’re near a certain location and you need photo collectors?
Communities vs. Online Bulletin Boards (OLBB)
For some, online communities are virtual hubs for long-term or continual engagement. The online community acts as a “panel” of ready respondents for your ongoing topic.
Shorter engagements are sometimes called communities or online bulletin boards. These could be as short as 2-3 days with a few dozen respondents. There are multiple engagement activities from photo collages, Q&A, group discussions, etc. OLBBs may be less flashy and more of a straight discussion thread. There could be engagement through liking/commenting on others’ posts, but the conversation itself is pretty straightforward.
Semantics aside, this type of online qual is still moderated! Through probing questions, video chats, or private messages, the moderator writes the discussion guide and engages with the respondents in the platform to promote responsiveness, details, and any follow-up questions that may arise. These tend to be a solution for more respondent engagement than in a one-time fixed setting and give respondents flexibility with their dedication since many are mobile enabled.
Since the Fall of 2017, InsightsNow’s Clean Label Enthusiasts™ is an online community which offers ongoing insights into a range of topics, providing a highly flexible research solution for quick answers.
Just like the F2F group types, you can translate that experience into a digital medium. Multiple vendors allow moderators to share their screens, their stimuli, allow for group chat, individual webcams and a client view. Doing online groups in this way helps alleviate any travel pains but does usually require more technology-adept consumers – something to consider if that may change your recruit type.
I’m specifically leaving out the topic of surveys for this blog post! While some surveys can be qualitative in nature, most of the time they still fall into the realm of quant. Qual derives part of its value from the moderated content — something we haven’t been able to solve fully in the survey space.
I hope you either learned something new with this post or gained fresh inspiration for a project you’re working on. Tell us about your qual methods in the comments!
About the Author:
Kayte Hamilton is a hybrid marketing researcher with a passion for solving complex client problems. She’s got a knack for sorting out the details while maintaining project integrity. In her free time (ha!) you will find her spending time with her dog Muffin, traveling the states, or volunteering.
Posted By Kay Corry Aubrey,
Tuesday, July 23, 2019
Updated: Tuesday, July 23, 2019
How Can Voice AI Help Qualitative Researchers?
Within three years, 50% of Web searches will be done via voice. Today almost one in four US households has access to a smart speaker such as Google Home or Alexa. Consumers are adopting voice technology faster than any other technology, including smart phones. Very soon voice artificial intelligence (AI) will become embedded in our everyday lives to the point where we may not even notice it anymore. How can qualitative researchers leverage this powerful trend?
For inspiration I spoke with four experts who are doing cool things with voice technology. They described unique ways to apply voice Artificial Intelligence (AI) that offer a preview on how this technology might transform our work as researchers. For example, consumers are shifting toward using their voice vs. their fingers to interact with technology and the Internet.
The Rise of the Talking Survey
Greg Hedges has had great success with voice-based surveys through virtual assistants such as Siri, Alexa and Google. According to him, “It’s like launching a focus group of one. People are interacting where they are most comfortable in their own home, using their own words. We’ve found that people are more spontaneous and natural when they talk vs. when they type.” Greg’s company also helps organizations integrate voice branding into their digital marketing ecosystem. Part of their expertise is redesigning a client’s SEO strategy to be phrase and question-based (vs. keyword based) to accommodate voice searches.
Ask Your Digital Twin Narrate Your Next Report
Domhnaill Hernon collaborates with artists to explore the deep connections between technology and human potential. He worked with Reeps One, a beatboxer, who fed hours of his audio recordings into Nokia’s AI machine. To their astonishment, the system returned new melodies he didn’t put in but sounded just like him. Rather than feeling threatened, the artist embraced the capability and now incorporates AI-generatedtunes into his work. Soon this technology will be widely available, and you’ll be able to produce reports in your own voice that clients can listen to just like a podcast.
It’s hard to imagine how voice technology – and AI in general – will change our world. Technology is always a double-edged sword. On one hand, AI will be used to cure disease, make societies more efficient, and redistribute wealth so humans everywhere prosper. On the other, it might lead to a hardening of the social classes and a surveillance state. In a recent episode of 60 Minutes, AI expert Kai Fu Lee said that 40% of jobs will be eliminated within 15 years due to artificial intelligence. To empower ourselves we need to understand what AI is, how it works, its capabilities and limitations.
How Voice AI Works
As with any artificial intelligence, voice technology relies on two things: having access to a huge pool of data, and algorithms that look for patterns within the data. For voice, the algorithm is called Natural Language Processing (NLP). The result can only be as good as the data that are fed into the machine. Today in North America, Voice Assistants (VA) are 95% accurate if the person speaking is a white native-born man, 80% accurate if it’s a woman, and as low as 50% accurate if the person has an accent. This is because of the socially limited group of people who contribute their data by using voice assistants - VA users tend to be early adopters, white, and highly educated.
Jen Heape notes, “Natural Language Processing (NLP) cannot deal reliably with anyone who is not a white male, and this is deeply problematic, which is why Google and Amazon are giving away so much free so they can collect more complete samples.”
The algorithms that make up NLP leverage fixed rules of language around syntax, grammar, semantics. The algorithm can be taught, “if they say this, say that” and the machine learns the pattern. This capability allows the virtual assistant to process simple prescriptive (but useful) commands such as “turn on the lights,”“play NPR,” or “order more lettuce,” because the technology has learned the vocabulary and structure of English sentences.
Can a Machine Be Conversational?
However, voice technology is still very much in its infancy. The machine has no concept of culture or social inferences. As Heape noted, “If I were to say ‘The kids just got out of school’ and the listener is in the same time zone, they’d know it’s 3 or 3:30. However, the voice technology would not be able to infer this because it lacks the data.”
Freddie Feldman leads a voice design team which creates chatbots and conversational interfaces for medical environments. According to Feldman, chat bots and voice technology in general are helpful in medical environments to get quick answers to predictable questions. “But for anything more crucial, dynamic or that requires understanding the other person’s psychology you’ll need to call someone in the end.” In theory, it’s possible that voice technology will have deeper human characteristics one day. “The technology is there. It’s just a question of someone piecing it together.”
It’s hard to imagine any machine being able to understand and integrate all the rich signals we send and receive in a conversation: the look on a person’s face, the tone of their voice, their diction, their physical posture, our perception of anger and pleasure, or what they are thinking. These elements are as essential to meaning and human connection as the words themselves. As Heape said, “VAs will never replace the human. There will always be a human pulling the lever. We decide what the machine needs to learn. VAs will remove the arduous elements. But we need a human to interpret the results and analyze it. We’re still so much at the beginning of it — we have not fed the machine.”
My feeling is there will be abundant opportunities for qualitative researchers, but – first – we need to understand the beast and what it cannot do.
Learn More about Artificial Intelligence and Voice Technology
Thank you to the experts I spoke with while researching this post:
Freddie Feldman, Voice Design Director at Wolters Kluwer Health
Jen Heape, Co-founder of Vixen Labs
Greg Hedges, VP of Emerging Experiences at RAIN agency
Domhnaill Hernon, Head of Experiments in Art and Technology at Nokia Bell Labs.
About the Author
Kay Corry Aubrey is a User Experience consultant and trainer who shows her customers how to make their products more easily understandable to ordinary people through usability testing and in-home studies. For the past few years she’s focused on products and services for older people that improve their lives, helping them remain independent and in their home. Kay sees great potential in voice-enabled products geared towards older folks. Her clients include Pillo Health, Stanley Black and Decker Futures, and the Centers for Medicare and Medicaid Services. Kay is the Luminaries Editor for the QRCA VIEWS magazine and a RIVA-certified Master Moderator and Trainer.
Posted By Isabel Aneyba,
Tuesday, June 25, 2019
Updated: Monday, June 24, 2019
Let’s Work Together: The Consumer Co-Creation Camp
While focus groups have long been a part of the innovation process, many clients have voiced their frustration about the limitations of traditional focus groups. To respond to this and other client needs, we created a methodology called Consumer Co-creation Camp. It is designed to expedite the research process while making it fun and provide a more direct connection between the client and consumers.
We had a client that decided it was time for his company to start an innovative process. This is how he requested the research: “I do not want boring focus groups, I want a fun process like a reality show, where we are looking to discover new things. I do not want to listen to top-of-mind responses, I want a deeper understanding. We want to achieve a year’s worth of research in one comprehensive study: understand the target, create product/brand concepts and evaluate those concepts”
To address this client’s broad request, we facilitated three groups simultaneously in three days to create products and brands with consumers. This process involved multiple stakeholders: the client team, the advertising agency and the consumers. We called this engaging process: The Consumer Co-creation Camp.
At the end of the fieldwork, the client stated: “We clearly know what we need to know to make this product a success in the marketplace”. How did this project provide such clarity and confidence to the client team and agency? In my view, it was the co-creation of compelling consumer-ready ideas. Three successive stages lead them to:
We wanted the participants to get to know one another first, so we asked Millennial participants to introduce themselves using a collage they created prior to the Camp. This set the stage that this process was about the Millennials and about being together. They felt appreciated while they found new friends and were free to use their own colloquial language.
During this process, our clients moved from feeling“I want to hear this and that” to “These people are interesting”” to “This is going to be big”. There was a perception shift because it was the first-time clients had a chance to see how these Millennials saw themselves.
Millennials created new concepts after testing the product. Collages helped participants to articulate their feelings because many times participants do not know how to describe their feelings and emotions. Collages were a springboard to show their feelings and it was a great equalizer, giving them all the opportunity to adapt the product and the brand to themselves. Our clients witnessed how the brand concepts matched Millennials’ needs and personal styles.
This stage motivated the clients the most. The Millennials presented their ideas directly to them, in the same room. The client team and Millennial teams had a vigorous conversation. There was ‘one voice in the room’. Consumers and clients worked in tandem focused on the unifying goal, with no barriers, mirrors or attitudes. After the final presentation, all the clients knew what the final output of the research was!
At the end of the process, three key outcomes would significantly impact product management, the brand vision, and consumer engagement.
Product Management. The global R&D and Marketing team became aligned and felt empowered to make necessary product and packaging changes.
Brand Vision. The client and ad agency gained a deeper understanding of Millennials, their needs, and shared this with the entire corporation. This understanding inspired them to create a new brand vision.
Engagement. The marketing teams learned how Millennials made friends, and this insight helped them to better engage with this target – utilizing a relevant marketing platform.
Even after the camp, the participants’ ideas were referred to constantly by the clients and the agency. Their vivid experiences allowed for crisper memories. The co-creation experience anchored the clients’ understanding on this target audience through a human connection. It was clear how the Co-Creation Camp streamlined the research process, and in the end, saved the client money and time while enhancing their understanding.
Do you believe your corporate clients would value working together with the consumers in a fun, engaging process that yields high quality insights and speedier outcomes?
If so, how can you streamline your next research project to generate compelling consumer -ready ideas? Consumer Co-creation Camp is a great alternative. When empowered and enabled by the research process our experience has shown that Millennials and Clients are happy to embrace the challenge of creating new products and services.
Isabel Aneyba is president and chief insight generator of COMARKA, an Austin, Texas research firm. COMARKA empowers marketers to develop meaningful product and brand ideas with their customers through dialogue. www.comarka.com
Posted By Janet Standen,
Tuesday, June 11, 2019
Updated: Friday, June 7, 2019
Qualitative Research with Employees – Why You Should Be Doing it
If you’re an experienced qualitative researcher and you haven’t done any employee experience research yet, perhaps it’s time you did!
First Things First
Why do I find employee qualitative so rewarding? We spend about a quarter of our life working, so if I can unearth an insight or two that can really make a difference in bettering the experience employees have in the workplace, I’m making a real contribution. By elevating the happiness of people on the job – where they spend so much time – my job seems more worthwhile and – in turn – makes me happier!
When and Why Is Qual Needed?
As is often the case, qualitative is a comfortable (and critical) companion to quantitative research. Most medium to large companies have a comprehensive annual Employee Engagement or Employee Satisfaction Survey – and each year they review the resulting data. Survey questions vary depending on the company, but they are usually around enjoyment, pride, understanding of and fit with the company vision, diversity, management performance, rewards, work/life balance, career development, and so on.
But what happens when the data show a shift or a trend, and no one is quite sure why it’s happening? Or, there’s an unexplained exodus of people; there may be gossip and rumors but no firsthand, deeper understanding about its cause. Exit interviews may or may not get to answers; by this point, the individuals leaving often don’t care enough to help make a difference for the people left behind.
And, what about all those subtle nuances of day-to-day life at work that don’t actually get captured in the big bucket questions? In order to have one standard survey that can be applied across all roles and levels in a company, the survey questions can become so bland – and we all know how dangerous it can be to include honest, open-ended answers if we think it might be possible to track it back to us. This is why qualitative is needed.
Different Roles for Qualitative
To ensure a quantitative survey will provide greatest value, its design is as critical as understanding its output. Qualitative should be used to inform the right questions included in the survey. Qualitative can be invaluable in ensuring the questions are being asked in the right way. Following the survey results, a third use of qualitative is to help explain the reasons for any negative shifts in data, ideally before employees start walking out the door.
Steering Qual. This should come first to ensure that the right questions are asked. Mini-groups are a good way to include a greater number of employees than IDIs, even if it requires some travel. Participants can be cross-functional and cross-level, at least to some degree. The conversations should be informal around key areas that matter to people. The discussion guide should be loosely designed with input from key stakeholders like Directors of Human Resources or Insights, but the moderator should be guided most by the natural direction that each group’s discussion takes. Specifically: what impacts their working environment and success every day; what really matters to people, how much it matters, why it matters. A comprehensive list of topics that impact employee happiness needs to emerge with a good understanding of the right way to think about the topic. Only then should an analysis of the output and learnings translate into a draft survey.
Tune-up Qual. This should come second. Once you have your draft survey, conduct a series of UX IDIs – where respondents think out loud as they take the survey. They need to take place with a range of people in different roles and levels. The survey can iterate throughout the interviews—but once you think it has evolved and been polished to a state of readiness for primetime, do a final 6-8 interviews to ensure it is as good as it needs to be, i.e. has comprehensive and relevant questions for all, that are asked in a clear, easy-to-understand way.
Directions Research. In this next stage, the learning becomes actionable given the benefit of a deeper understanding of the reasons behind shifts in data or behavior. IDIs or mini-groups can be considered, but ideally it’s a combination of the two. The topics up for discussion are driven by the data from the quant. Usually 5-6 topics can be covered in a 90-minute mini-group or a 30-minute IDI.
A great structure once the topics have been carefully introduced is:
What’s working well?
What’s not working so well?
What fears do you have?
What do you wish for?
There is a huge benefit in the research being recruited by an independent recruiter to allow for anonymity and to avoid manager bias of “favorites” being put forward. When moderated by an independent moderator, openness and honesty from participants is encouraged. Employees should be guaranteed anonymity during these sessions, and ideally, a note taker should scribe the session rather than recording it. Reassure individuals that their opinions and experiences will feed into an overview report of themes and that nothing will be attributed to an individual.
Suggestions for change resulting from the research can be grouped into “quick wins” ensuring employees experience the impact of their input, and “longer term challenges” to make sure some of the deeper challenges can be prioritized and tackled by management.
If you haven’t brought your qualitative skills to bear on employee happiness yet, you may want to consider adding it to your “to do” list for the future. You won’t regret it!
Janet Standen is Co-Founder of Scoot Insights, a qualitative provider specializing in helping decision-makers choose a better direction, effectively and efficiently. Her background is in innovation, business strategy and brand positioning.
Posted By Jeff Walkowski,
Tuesday, May 28, 2019
Updated: Friday, May 24, 2019
How To Create Effective Screeners
Whether you’re experienced or just breaking into qualitative research, it never hurts to review what makes a screener effective in finding just the right people for a research project. It is a questionnaire that recruiters will use to find qualified participants for the study. It is called a “screener” because it is like panning for gold—we have to sift through many people to find the nuggets (qualified people) to be invited to participate. Screeners are used by telephone recruiters, or they may be online surveys as a way to automate the recruitment process. Automation helps reduce expense by eliminating the human effort of dialing phones and talking to potential participants. Keep in mind that automated screeners still have costs associated with them – most notably programming costs which may include quota control, skip patterns, and conditional questions (all of which are typical of any online survey).
All the rules/guidelines about questionnaire construction apply to qualitative research screeners. The most effective screeners have the following characteristics:
They Are Short
If a screener is too long, participants may hang up the phone with a recruiter or simply decide to discontinue completing an online survey. Ideally, screeners have no more than 10-15 questions, or they take no longer than 5 minutes to administer (online or offline).
They Are Clear about the Purpose at the Beginning
Tell participants that it is not a sales call. Explain that we are looking for people to participate in a market research interview, but we must spend some time asking some questions to determine if they qualify.
They Do Not Provide Hints that Encourage Cheating
They include an intentionally general description of the nature of the research so as to not tip off participants to answer a particular way so that they can be invited. For example, say, “We are putting together a focus group on beverages,” instead of “We are putting together a focus group to determine what consumers think of Starbucks.”
They Include Questions Up Front that Are Easy to Answer and that Quickly Eliminate People Without Taking too Much Time
For example, if we are looking for millennial females, we will first ask about gender and age so that non-millennial males are quickly excused.
They Include Need-to-Know Questions – Not Nice-to-Know Questions
Asking nice-to-know questions lengthens the screener, can be frustrating to potential participants going through the screening process, and makes the recruitment process less efficient and possibly more expensive. Keeping the focus on questions that help determine whether a person should be invited or not is best.
They Include Intriguing Questions
Interesting questions keep survey-takers engaged. The objective is to not lose them along the way due to boredom.
They Feature Mostly Closed-End Questions
Again, this is designed to help the prospective recruit move through the process as quickly as possible. Closed-end responses also make the task easier for the recruiter (no judgment required).
They Often Include One or More of the Following Question Types
Product/service category use
If they are not users of a particular product or service, they are unlikely to be useful.
Brand(s) used more often and/or brands they would never use
If the project is about a particular brand, we probably do not want individuals who reject the brand outright (unless, of course, the purpose is to attract those who reject the brand).
Past participation in market research surveys, focus groups, and interviews
Preference is given to those who are not considered “professional” participants, so that they approach the research experience with a fresh attitude.
Employment in certain industries
We typically do not want those who are employed in advertising, public relations, or market research. In addition, we tend to rule out those who are employed in the industry that the project is about, because they may “know too much” and not represent the typical customer for the product/service.
They May Include an “Articulation” Question
Such open-end questions are used to help ensure that a participant will be able to make a meaningful contribution to the discussion. Sometimes questions are asked that pose a creativity challenge to the potential participant (e.g., “List 10 ways in which rubber bands might be used”). Ideally, however, a question that is related to the product category will be more relevant (e.g., in a study of high-end golfing equipment, potential participants might be asked to demonstrate some core knowledge of current equipment). In markets where participants may have differing levels of proficiency with the language to be used in the group (e.g., English), the recruiter may be asked to judge the ability of the potential participant to be clearly understood. This serves as an additional articulation assessment.
Jeff Walkowski is the principal of QualCore.com Inc., a consulting firm providing traditional and online qualitative research services to a wide range of industries including health care, financial services, automotive, and information services. He was schooled as a quantitative specialist and entered the industry in the 1980s as a statistician. He later discovered his talents as a moderator and evolved into a qualitative specialist by the mid-1990s.
Posted By Maria Virobik,
Tuesday, May 14, 2019
Updated: Monday, May 13, 2019
Data Visualization: 3 Ways to Make Your Qualitative Reports Pop
What Can Data Visualization Do for Us?
Data visualization—the graphical representation of information and data—can be a powerful tool in qualitative reporting. While we certainly can’t completely escape text-centric pages in our qualitative reports, graphics add visual interest and help break up the monotony of pages (or slides) of text. Done well, graphics help support qualitative findings and enable us to communicate in more interesting ways beyond words on paper (or a screen). Effective data visualization can also help readers understand concepts more quickly and easily and make information more memorable.
All the Cool Kids Are Doing it
Newspapers and other media outlets have jumped on board the data visualization bandwagon. Publications like The Washington Post, The New York Times and the Los Angeles Times employ full-time data journalists to augment their reporting. These folks take an enormous trove of data on a particular topic—for instance, the earlier start of spring in some parts of the U.S. or the confirmed U.S. measles cases by county in 2019 —and expertly slice, dice and manipulate the information into interactive graphics that communicate big ideas in an accessible and elegant way.
Data Visualization and Qual: Not a Linear Journey
Visualizing quantitative data is relatively easy. Hard numbers and percentages naturally lend themselves to visual representation. Charts, graphs and their modern equivalent—infographics—are easy to create from quant data.
Qualitative data can be harder to visualize; transforming qual data into graphics isn't as straightforward or simple. A search for “infographics and qualitative data” reveals that some people even argue that qual data can’t be turned into infographics. Take heart, however. An equal number argue that it can and provide examples to back this assertion.
But it’s not a linear journey from qualitative data to data visualization. Many of us have heard from end clients who want hard numbers or percentages included in a final report to quantify how various concepts or ideas stacked up against each other. We can explain that “qual isn't quant” until the cows come home, but clients persist in making such requests.
Instead of giving in to these requests (or refusing them outright), there is another option. We can take this as the opportunity to develop data visualization approaches that give our clients the detail they want and expect without compromising the qualitative nature of the report. A few examples follow.
Word Clouds – an Oldie but Goodie
Word clouds are a common data visualization technique in qualitative reports. Using font size (and often color), they convey magnitude of various responses, thoughts or ideas. Larger words=more popular/frequent/common. This approach works well because it’s a way to provide granular detail without showing the actual numbers behind the information.
While word clouds aren't the answer for every situation, they are a great tool, and websites for creating them abound. The PollEverywhere blog lists nine favorite word cloud generators, including Wordle and Tagxedo. A Google search for “word cloud generator” will point you to others.
Customer Journey Maps:Timelines in Disguise
Customer journey maps are another way to employ data visualization in qualitative reports. These maps are essentially timelines; a quick Google search on this term turns up many great examples that can be easily adapted to fit your particular purpose.
Here’s one example: a timeline detailing milestones in the 21st Century Conservation Service Corps history from 2010 to 2014.
The example above is organized by year, but the general format can be adapted to visualize a customer journey. Year markers become phases in the purchase journey: research, comparison, selection, purchase. The linear format allows room above and below the line for details on the individual steps consumers undertake in each phase.
Venngage is one great resource for infographic templates and tools, including many for timelines (such as the one below). They offer a couple different subscription plans. But you can peruse the templates for free, and that might be all the inspiration you need to create your own.
Bubble graphs are another idea we can borrow from data journalism. During the 2012 London Olympics, The New York Times kept a running medal count by country and visualized the data in a simple table (below). The information is clear, but the table doesn't do a great job conveying the magnitude of differences among countries.
The Times formatted the same information into a bubble graph. This approach does a much better job conveying magnitude. You can easily identify the countries that led the medal counts. Readers could hover over any circle for more detailed information, including a country’s medal count by type (gold/silver/bronze). (Visit the link below the graphic and try it for yourself!)
The same idea—sans numbers, of course—could be employed in qualitative reporting. For example, we could use a bubble graph to report the characteristics that participants want in a dog.
Readers can immediately see which characteristics were most important and which were mentioned by fewer participants. By keeping numbers out of it, the graphic remains faithful to the spirit of qualitative research.
Sky’s the Limit
These are just a few examples of how data visualization techniques can be employed to make qualitative reports more engaging and communicate findings and implications more effectively.
Here are several links to more examples; many additional resources can be found by searching data visualization:
What are your go-to data visualization techniques and tools? What works? What doesn't? If you have advice or a favorite resource to share, please leave a comment.
Maria Virobik joined QRCA in 2018 but has worked in qualitative research since 1997. After early dalliances in the advertising world, she came to her senses and has been devoted to qualitative analysis and reporting ever since. Originally from Southern California, she and her husband sold their house last year and now live a nomadic lifestyle with their two marginally obedient dogs, Lucy and Ginger Snap.
Posted By Lisa Horwich,
Tuesday, April 30, 2019
Updated: Tuesday, April 30, 2019
Why Quallies Should Care about Marketing Technology (MarTech)
The “Rise of the Machines” and how We Got Here.
When I graduated from business school back in the late ‘90s I never dreamed I would become a total tech geek…in fact, I really thought I was going to be a high-powered consultant (think McKinsey, Bain, BCG). Instead, somehow, I found myself implementing large-scale computer systems (fears of Y2K!) and then became a product manager for a small software company. My journey to tech geekdom had begun without me knowing it.
Fast forward to today. After spending much of my time working on quantitative and qualitative research for large tech companies, I can honestly say that I really love learning and studying technology.
With this in mind, about 2 years ago, a prediction from Gartner (the big technology industry research firm) caught my eye – their analyst Laura McLellan predicted that by 2017 CMOs will spend more on technology than CIOs. She was almost correct – it happened in 2016, a year ahead of schedule.
Think about it. Marketing departments are now spending more on information technology than the department that is responsible for a company’s technology infrastructure. Crazy, I know!
This has led to a proliferation of companies clamoring for a piece of this MarTech pie. From 2011 when 150 companies offered MarTech solutions, we are now in 2019 looking at over 7,000 companies competing in this space.
What is the aim of all these solutions? More importantly, what has changed with CMOs to prompt this massive investment in technology? It boils down to three main factors:
Most CMOs now share P&L responsibility. Instead of just being a “cost center,” marketing is looked on as fundamental part of revenue generation.
Marketing funds and designs the entire cross-functional customer experience (CX). If you think of CX holistically from generating awareness through post-sales feedback, it makes sense that marketing is in charge.
Finally – and arguably most importantly – with the soaring costs involved in attracting, maintaining, and growing the customer base, marketing now has to justify the ROI of their activities.
CMOs are turning to data-driven solutions that help them deeply understand every phase of the customer journey – tracking and quantifying the ROI of all marketing activities along this journey. They are also investing heavily into solutions that personalize the customer’s experience with the hope of converting these interactions into greater sales opportunities.
Technology Solutions and Their Uses
As researchers, we need to know the types of technologies where our clients are spending significant portions of their overall budgets (~30%) so we can recognize where we fit as human insight professionals. We don’t have to be experts in tech, just conversant — so when we walk in the door and our clients say they are using a new “Artificial Intelligence email optimization tool,” we understand what that is and can talk about how our services complement and augment this tool.
I’ve put together a few charts and tables outlining some of the fundamental building blocks of these solutions. Most MarTech offerings are powered by technologies such as Artificial Intelligence, Machine Learning, Business Intelligence, and Real-Time Analytics. I find it useful to see the interaction of these technologies with a chart:
To understand definitions of these technologies and common uses, this table is a quick reference (CAUTION: Tech speak ahead):
Unified customer data platforms, predictive analytics, and contextual customer journey interactions.
Any system that learns from past data to make judgments about previously unseen new data.
Optimize ad campaigns and other metrics, predict churn.
Opportunities for Quallies
Many of the technologies outlined above have inherent limitations – which I like to think of as “opportunities” for qualitative researchers. Most of the limitations center around the data – quality (how good is your data) and quantity (do you have enough of the right type of data). In addition, the other major limitation is having enough marketing content – a major bottleneck in the quest for personalized customer engagement.
Decisions are made solely on data – past and present.
Use the data as a launching point for deeper qualitative analysis.
Existing data is not predictive enough for decision-making.
Create and maintain communities focused on pinpointing predictive behavior.
Need exponentially more messaging content for personalization.
Assist in narrowing target messaging by identifying key characteristics valued by customers.
Insufficient data to train the machine/AI.
Provide personas and other descriptive metrics to help “train” algorithms.
Lack of “industry specific” attributes.
Create detailed feature lists to describe the unique features inherent to that industry.
While the ideas above are great tactical opportunities, strategically, our most important job as qualitative researchers to remind our clients how, in a world of automation, humanizing the experience of individual customers is key to authenticity.
Lisa Horwich is the founder of Pallas Research Associates, a B2B-focused research and consulting firm located in Seattle, WA. She is a self-ascribed tech geek and loves talking to developers, IT decision-makers, and CIOs. She also co-chairs the QRCA B2B SIG.
Posted By Liza Carroll,
Wednesday, April 17, 2019
Updated: Tuesday, April 16, 2019
Design Thinking – Beyond the Breakers
Depending upon the source, Design Thinking (DT) is key to innovation in everything from consumer goods to complex social systems, or it’s an overhyped workshop package. Having first been introduced to the concept at QRCA’s 2019 annual conference, and with the idea that others reading this blog might also be new to Design Thinking, I wanted to share more about it. Design Thinking is meant to place those who seek to engage in innovation – often diverse stakeholders – into an uncomfortable space. It should move people past their own biases so they can understand customers’ real needs, and design solutions that work.
The five steps of the process are most often introduced graphically on brightly colored hexagons: Empathize, Define, Ideate, Prototype, Test. Activities in the first two steps live in the problem space, and the last three are in the solutions space. People who understand the ego-threatening implications of these steps point out that practitioners must be willing to manage controlled chaos in seeking the path to making something great.
Design Thinking is demanding. Yet, it is often sold as a quick fix and its core essential stages skimmed. This is why it is disparaged by some designers and others close to it. Consultancies and companies seeking commercial success without committing to authenticity may champion superficial workshops. Some using the process try to make Design Thinking overly linear, misunderstanding the untamed nature of the creativity that lives within its DNA.
The first step – Empathize – has the most relevance to qualitative researchers — but can also be the most often snorkeled-over by those who don’t have the training or the gear to dive deep. “Empathy is hard!” notes Annette Smith in Is Design Thinking a Silver Bullet for Consumer Research. She explains what we all know better than most: “The ability to empathize without imposing your own cultural values and preconceived notions on a consumer is just not easy to do.” Add cultural difference to the equation, and empathizing is, of course, exponentially more difficult.
Jon Kolko addresses criticism of DT in his article, The Divisiveness of Design Thinking. He asserts that the real work required during the Empathy step might conceivably be exchanged for 2-hour ‘subject matter expert’ interviews; but in taking such an approach, you may only gain a scratch-the-surface understanding of the business needs at hand. Kolko also examines breakdowns that happen in the other Design Thinking steps. In summary, anyone planning to take on the enormous job of leading others through the process would have to have the ability and experience to guide people toward dramatically reframing a problem by asking more interesting questions and to facilitate rich, meaningful collaboration. I recommend reading Kolko’s article to gain a much deeper introduction to the topic than provided in most introductory articles that stick to defining the steps.
Circling back and thinking about Design Thinking’s qualitative heart, it’s interesting that just this month there was a post in the Qual Power Blog by Patricia Sunderland titled When Ethnography Becomes a Joke. In her post, she explains the difference between valuable and degraded ethnographic fieldwork, the methodology that is, as it happens, key to Design Thinking’s Step One – Empathy. Sofia Costa Alves, in her presentation Discover and Deploy Design Thinking described the careful ethnographic work that underpinned the Design Thinking activities she led with participants who were holders of diverse roles in a corporation during her facilitation experience in South America.
Being introduced to Design Thinking, what it can yield when done courageously, and also the ways in which it can be used when thinking “out of the box”, has been a wonderful learning experience. If you would like a list of resources I found valuable for gaining some understanding of Design Thinking, feel free to let me know in the comments or email me at email@example.com.
Liza Carroll is Consumer Insights Manager at RDTeam, Inc.