Data in elearning isn’t just about numbers—it’s about insights.
A strong elearning strategy uses data to improve course design, user experience, and overall engagement.
Organisations that leverage data can see improved retention, ROI, and improved training effectiveness.
The Basics
Start small by focusing on key metrics like engagement or drop-off points.
Use tools like Excel or Google Sheets to capture a few data metrics and to identify patterns.
Feedback and simple adjustments can make a big difference in outcomes.
Don’t waste time building massive dashboards and investing in huge analytics boards at the start. Identify what works and then scale.
A New Way to Look at Elearning Data
Ever found yourself staring at all your elearning data and wondering, “What else can we really do with this?”
I’ve sat in meetings with customers and It’s a question I’ve heard on several occasions.
Elearning course data is often thought of as little more than a way to tick boxes—course completions, quiz scores, logins—but something clicked when I dug a little deeper.
What if I told you that even the most basic data points could unlock powerful insights?
The Hidden Value of Elearning Data
Data is becoming increasingly available to organisations, and it’s an important asset for businesses across all fields.
But here’s the thing—having a lot of data on its own isn’t useful.
Data is only valuable if it’s analysed to gain insights. And you need to know where to start.
In many organisations, elearning data is often dismissed—completions, quiz results, logins and nothing else.
Those numbers are far more than just reports.
They’re a map, showing where your strategies are succeeding—and where they’re not.
A solid elearning strategy starts with understanding these metrics.
Beyond the Numbers: What Data Can Tell You
Take platform engagement, for example. Low engagement or users dropping off too early may not indicate a problem with the course content itself. Instead, it could point to:
- A technical issue
- A usability issue
- Poor alignment of release timing with user schedules
In fact, companies using elearning data see up to 25% higher retention rates among learners (Docebo). This suggests that understanding and responding to data can drastically improve engagement and retention.
How often do you undervalue the most basic data points? The easiest data to collect is often overlooked, yet it can be the most revealing.
How to Make Elearning Data Work for You
Here’s what I learned along the way:
1. Start Small
Don’t try to track everything at once.
Focus on just one or two key metrics—like daily user activity or drop-off points—and watch how trends start to emerge quickly.
You don’t need a complex analytics platform. Google Sheets or Excel is fine.
2. Look for Patterns
Does engagement spike in the mornings?
Does a certain group prefer video content over text (PDF, Whitepapers)?
Spotting these trends can influence everything from course design to release schedules.
Plus, 60% of organisations report enhanced ROI by personalising elearning using data insights (Training Industry).
3. Gather Feedback
Don’t assume you know the problem.
Ask questions, observe user behaviour, and challenge your assumptions.
Data doesn’t always tell the full story.
You need to get out into the business.
What is Data Analytics?
Before you start, do you know what data analytics is? Often within Leadership and Development teams will jump onto the next trend without understanding what’s involved.
Data analytics is the process of cleaning, organising, and interpreting information to produce useful insights.
It can come from both internal and external sources.
The data can be:
- Quantitative: Numbers and statistics.
- Qualitative: Images, text, and observations.
While manually analysing data is time-consuming, many data analytics tools—from spreadsheets to specialised software—can help.
These tools make it easier to spot patterns and make informed decisions.
You will probably have the data that you need but you are going to need to capture and collate it.
Be smart when you start collecting data. Manually collecting data takes time. You can automate the process.
But don’t forget you need to ensure that the quality of the data you collect is good. Your results are only as good as the quality of the data.
A Real-World Example
We were once analysing a course when we noticed a sharp drop-off halfway through. Initially, the content seemed fine.
But after taking a closer look, we realised that the course navigation was clunky, and users were disengaging as a result.
After fixing that, course completion rates shot up.
And remember, 94% of employees are more likely to stay with companies that invest in training (LinkedIn Learning).
This shows just how important it is to get things right.
Reviewing the data can provide you with critical information and insights.
Getting Started with Data Analytics
So, how can you start small with data?
- Use a simple tool like Excel to track one or two metrics, such as user activity or drop-off rates.
- Look for patterns and trends that might reveal areas to improve.
- Start with small adjustments before diving into complex dashboards or tools.
- You’ll see trends pretty quickly once you’ve started capturing data.
- Start small and you can quickly scale.
If you’ve got an LMS or an LXP you’ve got some data that you can use. Don’t dismiss the data reports. Metrics like scores, completion and time can provide insight.
If the completion rate is low, start asking questions?
Does the course work?
Have you tested it?
Ask people doing the course?
If you have low time on the system, ask why?
Do you have technical issues with people accessing the LMS?
You have to work with the data.
Why Data-Driven Decision-Making Matters
Data analytics for decision-making helps organisations move from guesswork to informed choices. Analysing past data can:
- Identify and fix inefficiencies.
- Improve resource allocation.
- Solve problems before they escalate.
For example, analysing customer behaviour can guide improvements in customer service or highlight areas for focus.
The Competitive Edge of Data Analytics
Data analytics helps businesses stay competitive by offering insights from external data such as market trends. This can:
- Identify new opportunities.
- Guide product development.
- Provide insights into performance against competitors.
The Takeaway
You don’t need to be an analytics expert to uncover actionable insights. By simply observing and digging deeper, you can improve your elearning strategy.
Whether it’s optimising course design, enhancing usability, or planning your resource allocation, data can be your most powerful tool. In fact, companies that use data analytics in their training programs can see a 50% improvement in training effectiveness (McKinsey).
So, next time you look at your platform’s metrics, ask yourself: What story is this data telling me, and how can I use it to create a better experience?
