Understanding your audience isn’t just a box to check—it’s the foundation of any impactful strategy, especially in a field as dynamic as language learning. At Lingano, we strive to redefine language education, and knowing the “why” behind our learners’ choices is essential for delivering meaningful solutions.
Currently, we’re in the middle of an exciting research project to better understand our learners’ motivations, challenges, and goals. By combining quantitative surveys and qualitative interviews, we’re exploring new ways to tailor our courses and marketing strategies. Along the way, we’ve faced challenges like ensuring statistical validity, refining our sampling methods, and cleaning data for actionable insights.
This blog post dives into the what, why, and how of our ongoing research journey. Whether you’re a data scientist, an entrepreneur, or simply curious about market research, you’ll find practical takeaways here.
Why Audience Research Matters
Imagine designing a course for exam preparation, only to discover that most learners are interested in boosting their workplace confidence. That’s a costly mismatch between assumptions and reality.
At Lingano, audience research is helping us uncover the real reasons people turn to us. Questions we’re exploring include:
- Why are learners motivated to study English?
- What specific outcomes do they expect?
- How can we align our offerings with their goals while keeping the experience engaging?
But getting reliable answers isn’t as straightforward as it might seem. Ensuring accuracy requires a rigorous process, from defining sample sizes to validating findings.
Quantitative Research: Setting the Foundation
Quantitative research allows us to collect data from a broad audience, providing a high-level view of trends. For instance, we surveyed learners to identify their primary motivation for learning English:
- Work
- Study
- Migration
- International Exams
How Many Responses Are Enough?
One of the first questions we tackled was: How many responses do we need for reliable results? We turned to the Krejcie and Morgan formula, which helps determine sample size based on population size. You can learn more about this method here.
Ensuring Randomness in Sampling
Even with an ideal sample size, the quality of your data depends on how you select participants. We’ve been following guidelines for random sampling to reduce bias and ensure our results are representative of the larger audience. Check out this guide for more details.
Validating the Questionnaire
Crafting a reliable survey requires both subject-matter expertise and statistical validation. While we collaborated with content experts to refine the questions, we also ensured the survey met statistical standards for validity and reliability. If you’re designing surveys, this resource is a great place to start.
Qualitative Research: Exploring the “Why”
While quantitative surveys provide a bird’s-eye view of trends, qualitative methods like focus groups and interviews uncover the why behind the numbers.
What We’ve Learned So Far
- Learners interested in “Work” often seek more than language skills—they want confidence in professional settings, like interviews and workplace communication.
- Migrants worry not just about learning the language but about adapting to cultural norms.
- Exam-focused learners value structure but also need strategies for managing anxiety.
These insights are helping us rethink our course design, adding elements like soft skills training and stress-management tips where needed.
Cleaning and Analyzing Data
Data collection is just the beginning. Cleaning and analyzing data ensures that only valid responses inform our decisions.
- Cleaning the Data:
- Removing inconsistent or incomplete responses.
- Filtering out duplicates.
- Analyzing Statistical Significance:
- Using p-value analysis to validate findings and ensure observed trends are meaningful rather than random.
- For a practical explanation of p-value analysis, check out this resource.
Combining Both Approaches
Our research combines the strengths of quantitative and qualitative methods in a three-step process:
- Quantitative Surveys identify trends, like the prominence of “Work” as a motivation.
- Qualitative Interviews explore deeper motivations, such as confidence-building or adapting to cultural norms.
- Real-world validation through metrics like sales trends, course engagement, and learner feedback ensures findings translate into actionable improvements.
For example, based on qualitative insights, we’re experimenting with modules on professional communication and workplace etiquette. As we roll these out, we’ll track learner engagement to see if these changes drive better outcomes.
Common Challenges (and Solutions)
Will Qualitative Insights Mislead Us?
Qualitative research provides rich insights but isn’t generalizable. That’s why we use it to generate hypotheses, and then validate these hypotheses with quantitative data and real-world metrics.
Is Quantitative Data Always Reliable?
Quantitative data can mislead if poorly collected or analyzed. By following sampling best practices and analyzing statistical significance, we ensure our findings are robust and reliable.
Lessons Learned
Here’s what our ongoing research is teaching us:
- Quality Over Quantity: Good research isn’t just about gathering data—it’s about gathering the right data.
- Depth Complements Breadth: Quantitative research gives trends, while qualitative research provides human context.
- Iterate and Validate: Data isn’t static. Constantly testing and refining hypotheses leads to better decisions.
What’s Next?
We’re excited to see how our insights translate into better learner outcomes. Will modules on confidence-building boost course satisfaction? Can we address test anxiety effectively for exam-focused learners?
Our next steps involve analyzing performance metrics to validate these hypotheses and iterating on our findings.
Join the Conversation
Are you using quantitative or qualitative methods in your own projects? How do you balance breadth and depth in your research? I’d love to hear your experiences. Feel free to contact me on LinkedIn.
