4 MIN READ
Mixed Methods Research Explained in 7 Minutes
Research forms the backbone of many project activities. Whether you’re looking to launch a new product or want to identify a new audience to target, research will help you position yourself in the market and understand core customer pain points.
Many brands have inadvertently siloed their user testing and data analysis teams when, in reality, they should be working in tandem to uncover the context behind key patterns and trends. But they are beginning to see the limitations of having split departments and, as a result, mixed methods as a research strategy is making a comeback, particularly in the tech world. Research is now a proactive part of the UX process as teams strive to understand the core pain points of their customers and why they behave the way they do.
Big-name brands like Airbnb, Spotify, and Microsoft are all using mixed methods research to analyze user insights alongside actionable statistics to develop deeper insights across the entire customer journey.
What is Mixed Methods Research?
Mixed methods is a research strategy that collects and analyzes both quantitative and qualitative data from the same study.
- Quantitative data: focuses on collecting and analyzing numerical data to find trends and patterns (i.e. how many visitors landed on your site in one month, or how many people bought your latest product)
- Qualitative data: collects non-numerical data including experiences and opinions (i.e. why visitors decided to land on your site and how they behaved when they got there)
The idea is to mix together these two common research methods to provide deeper results and an extra layer of context around data.
It’s not enough to just run some quantitative research and some qualitative research in the same study. Instead, mixed methods research links the data together using these two methods so that it’s easier to interpret what people are doing and why they’re doing it.
For example, if you want to understand how to profitably increase website conversions, you can start by looking at the data to understand where your visitors come from, what percentage converted, and what the cost per signup was (all quantitative methods), as well as gather feedback from a popup post-signup that asked new users what nearly stopped them from signing up (qualitative). You can then take the answers from the highest converting channels (quantitative) and focus on solving their issues first (qualitative) to increase conversions in your most profitable segment.
Potential Data Sources
Quantitative data sources:
- Data tracking
- Closed questionnaires
- Secondary data
- Statistical modeling
- A/B testing
Qualitative data sources:
- User interviews
- Field notes
- Focus groups
- Open-ended questionnaires
- User/participant observation
- Session recordings
The Different Types of Mixed Methods Research
While mixed methods research always encompasses two types of data collection and analysis, the strategy can follow a couple of different processes depending on how you want to use the data you have available.
In an embedded approach, there is usually one research method that becomes the primary research method. Both types of data are collected at the same time, but the secondary research method (whether that’s quantitative or qualitative) plays a supporting role in strengthening or supplementing the results from the primary research method.
2. Convergent Parallel
Similarly to the embedded model, convergent parallel collects both types of data at the same time but analyzes them separately. When you have the results from both, you can compare them and draw conclusions based on your findings.
3. Explanatory Sequential
Quantitative data collection comes first in this model. Only when you’ve gathered your numerical data can you move on to collecting qualitative data to supplement your original findings.
4. Exploratory Sequential
On the flip side, this method collects qualitative data first before moving on to quantitative data collection.
The Benefits of Mixed Methods Research
- Enriched results: using both research methods together provides context to your studies. Quantitative data alone can dismiss the lived experiences of your customers, while solely using qualitative data can make your research difficult to generalize.
- Participant focused: mixed methods can gain a deeper understanding of your customers and it gives them a chance to voice their own opinions and experiences.
- Flexible research: combining two different research methods can give your research the kind of flexibility it wouldn’t have if it was limited to just one method.
Spotify used data tracking and a diary study to understand the behavior of its users when using the app.
“These two methods provide complementary perspectives,” says Colette Kolenda, Research Lead at Spotify. “In the diary study, we recruited participants to take part in a three-week study, where we asked them to tell us about their daily listening experiences and their reactions to the ads. For the data tracking, we asked for each participant’s consent to look at their behavioral log data that was pertinent to the listening sessions. We were able to understand their overall experience from the behavioral data and their perceived experience through the diary study.”
The Downsides of Mixed Methods Research
- Complex evaluations: using two different research methods obviously makes your research slightly more complex, especially when it comes to linking your results during analysis.
- Confusing results: if your quantitative data and qualitative data show conflicting results, it can be difficult to pinpoint how you should move forward or which data would be best to focus on.
- Increased resources: running two types of data methods (whether concurrently or not) is more time-consuming than focusing on just one. It can also require several different teams to come together to provide the data and understand the results.
When to Use Mixed Methods Research
When You Have… Insufficient Data Sources
If one method alone doesn’t get you the information you need, mixed methods can help. Quantitative data provides a broader understanding of a topic, but it doesn’t necessarily provide depth to those results–for example, quantitative data can show that people are dropping off your site at your “add-to-cart” page, but it doesn’t answer why they might be doing that.
When You Need To… Bolster Initial Results
Your analytics team might have found that conversions have increased by 30% over the past six months. That’s obviously great news, but can they explain why that might have happened? If not, weaving in some qualitative research can help provide some depth to the results so you can continue to improve your efforts.
When You Want to… Generalize Focused Findings
Your customer support tickets might show that a handful of customers are having issues using a specific feature of your product. This qualitative data is useful to know (especially why they’re having problems), but quantitative data can generalize these findings so you identify who might have a similar problem in the future.
For example, you might find through quantitative data that it’s a certain audience demographic that is having issues or that the people who are struggling the most skipped out on the demo part of your sales funnel.
Mixed Methods Research: A Step-by-Step Guide
Thinking of using the mixed methods research approach to analyze your next set of data? Here’s how you can get started.
- Determine whether mixed methods research is the right method: does the information you want to collect and analyze lend itself to a mixed methods approach?
- Choose your data collection strategy: how will you collect quantitative data? How will you collect qualitative data? For example, you might analyze your Google Analytics for quantitative data and customer support tickets for qualitative data.
- Develop questions for both types of data: put together the questions you can answer with the data (i.e. how many people navigated from X page to Y page in December 2021?).
- Collect the data: pull together the data from your different sources somewhere that you can easily see in one place.
- Analyze the data: dig into your findings either at the same time or separately.
- Solidify your findings: document what you found out from the research and what this means for you moving forward.
How to Make Mixed Methods Research Work For You
There’s an art to getting mixed methods research right if you want to maximize your results and get the information you really need to tweak and improve your product development process, your marketing activities, or your sales.
Collect Both Data Types
It’s important that you collect both quantitative and qualitative data to work with and use rigorous procedures in collecting that data. For example, it’s important to work with an appropriate (or minimum) sample size when collecting both types of data.
Focus Your Findings
It’s also important to determine the questions you want to answer with the data you have (or will have). This helps focus your findings and will make the analyzing stage much easier, especially when you have two different kinds of data to work with.
Make Data Accessible
There’s a good chance you’ll be collecting data with the help of different departments. For example, you might collect Google Analytics from the marketing team and pair that with market research from the product development team. It’s important that the data collected is available and accessible to all necessary parties to ensure that the appropriate analysis can be done.
It helps here to have a dedicated platform that can combine both quantitative and qualitative research in the same place that all key departments can access quickly and easily.
Mixed Methods Research as a Viable Data Analysis Strategy
Product devs and marketers have an unprecedented amount of data at their fingertips these days. The difficulty lies in separating this data and using it to form workable hypotheses and improve the customer journey.
As UX becomes an increasingly important part of business, it’s never been more necessary for brands to understand their customers. Mixed methods research combines qualitative and quantitative data to provide enriched insights into customer pain points, behavior, and the entire user journey.