What Learners Really Think: The Soft Data That Drives Real Learning Impact

Hard data gives us the numbers, but it doesn’t tell us why something worked (or didn’t). That’s where soft data comes in—feedback, observations, and insights from real humans. It helps us understand learner experience, engagement levels, and real-world applications in ways that numbers alone can’t.

Think about it: If test scores are high, but learners still struggle on the job, something’s missing. If completion rates are low, we need to know why. Soft data gives us those answers.

This blog is all about using qualitative feedback to refine training programs, ensure learning sticks, and make a real impact. Let’s dive in!

Soft Data: What to Collect and Why It Matters

Not all feedback is created equal. Here’s what’s worth tracking:

1. Learner Feedback: The Frontline Perspective

• Why It Matters: Learners experience training firsthand—they know what’s working and what’s not.
• How to Collect It: Post-training surveys, focus groups, and open-ended questionnaires.
• What to Watch For: Patterns. If multiple people say something is unclear or unhelpful, it’s a red flag.

Example: In a leadership training, we found that participants loved team exercises and real-life workshops in small groups but felt lost during long theoretical sections. By adjusting the balance, engagement jumped 25%.

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2. Manager Feedback: Are Skills Translating to Work?

• Why It Matters: Managers see employees applying (or not applying) what they learned in training.
• How to Collect It: Performance reviews, feedback discussions, post-training check-ins.
• What to Watch For: Gaps between training completion and real-world performance.

Example: Our communication training received glowing post-training survey results. However, six months later, managers reported little improvement in teamwork. Employees grasped the concepts but lacked the reinforcement needed to implement them. By implementing structured follow-ups, including coaching sessions and guided scripts, skill retention improved by 30%,

3. Stakeholder & Business Leader Feedback: The Big-Picture View

• Why It Matters: Leaders need to see a measurable business impact from training.
• How to Collect It: Stakeholder interviews, quarterly business reviews, executive debriefs.
• What to Watch For: Is training solving the problem it was designed to address?

Example: We developed a training program to help countries opt-in and localize a large and complex sales and marketing always-on campaign. Initially, we focused on completion rates and general feedback. However, stakeholder feedback revealed that countries needed more structured guidance on adapting global materials to local markets. By integrating localization workshops and ongoing support, we increased country opt-in rates by 260%, ensuring better alignment between global strategy and local execution.?

4. Peer & Team Feedback: The Reality Check

• Why It Matters: Colleagues often notice changes in behavior before managers do.
• How to Collect It: 360-degree feedback, informal team discussions, social learning networks.
• What to Watch For: Are peers seeing fundamental behavior changes?

Example: Through our Women in Schneider Electric (WiSE) ERG, we designed a career development initiative to increase confidence and professional growth opportunities for women across the Pacific Zone. Early feedback from participants revealed that while they valued the conversations, they needed more explicit guidance on applying key takeaways to their career goals. We responded by incorporating structured action plans, peer accountability groups, and real-world project collaborations, leading to a 30% rise in sustained engagement and measurable career progress for participants.

How to Use Soft Data to Improve Training

1. Combine It with Hard Data for a Full Picture

• Test scores say knowledge was gained. Manager feedback says it wasn’t applied. Both are right.

Example: One of the biggest challenges with our Marketo training was that users didn’t engage with the platform daily, causing them to forget key steps even after completing the training. Soft data revealed users needed easy-to-access, structured guidance to reinforce their learning. We addressed this by embedding clear, step-by-step instructions directly into the forms they needed to fill out, along with relevant examples. Additionally, we provided a printable workflow guide that outlined each step in the correct order. As a result, adoption increased, and users became more confident in completing the process correctly without needing repeated support.

2. Look for Patterns, Not One-Off Complaints

• One lousy review? Ignore it. Consistent feedback? That’s something to fix.

Example: If 5% of learners say a module is confusing, it may be a preference. If 30% say it’s unclear, it needs fixing.

3. Keep It Actionable

• Open-ended feedback is great, but ask specific questions to get valuable answers.
• Instead of: "What did you think of the training?" → Try: "What was the most useful part? What would you change?"

4. Use Soft Data to Drive Engagement

• If learners feel heard, they’re more likely to engage.

Example: In an onboarding program, new hires felt overwhelmed by information overload. Based on their feedback, we restructured training into smaller, digestible chunks and made key information available on demand—delivered precisely when they needed it. This approach improved engagement and significantly increased knowledge retention, as employees could access critical details at the right moment rather than trying to absorb everything at once.

The Power of Storytelling with Data

Soft data is more than just numbers and reports—stories give context to the numbers. When presenting training results, framing the data through real learner experiences and impact stories makes insights more compelling and actionable.

How to Use Storytelling with Data:

• Humanize the Numbers: Instead of just saying “engagement increased by 25%,” share a real learner story about how the training changed their approach to work.
• Make It Relatable: Business leaders may not connect with percentages (even though they want them). However, they will connect with a before-and-after story about a struggling employee who became a top performer after training.
• Use Quotes & Testimonials: Learners’ words can be powerful proof of impact.

Example of Storytelling in Action: Rather than just reporting that 80% of managers found the leadership training useful, tie it to a real impact story: “One manager shared how, before training, their team struggled with conflict. After applying the techniques, they resolved a major team dispute, leading to better collaboration and productivity. This improved team dynamics and reinforced why 80% of managers found the training valuable.”

Blending hard data with personal insights creates a complete and persuasive picture of training effectiveness.

Final Thoughts: Data is a Conversation, Not Just a Report

Soft data isn’t about proving something—it’s about understanding. The best training programs adapt based on what learners, managers, and stakeholders tell us. When combined with hard data, soft data helps create training that’s effective on paper and impactful in the real world.

In our next blog, we’ll explore how to create feedback loops that keep training evolving, ensuring long-term impact and continuous improvement. Stay tuned!

References (Because Insights Matter)

• Kirkpatrick, D., & Kirkpatrick, J. D. (2016). Evaluating Training Programs: The Four Levels. Berrett-Koehler Publishers.
• Brown, P. C., Roediger, H. L., & McDaniel, M. A. (2014). Make It Stick: The Science of Successful Learning. Harvard University Press.
• Mayer, R. E. (2009). Multimedia Learning. Cambridge University Press.
• Cognota. (2024). 9 Learning and Development Trends That Matter for 2024. https://www.cognota.com
• Mindmarker. (2024). How the 7 Principles of Reinforcement Increase Training Impact. https://www.mindmarker.com

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