How do we create learning that is relevant enough to drive behavior change at scale?

The learning industry has spent years selling personalized learning as the gold standard. However, this usually comes with the following statement as part of the “pitch”: “the right content, for the right person, at the right time, in the right way.”

It sounds compelling, right? However, this red herring also risks becoming one of L&D’s most expensive distractions.

Let’s challenge the premise: do we really need to personalize learning for every individual — or do we need to make learning meaningfully relevant to the people who need it?

Roles change, priorities shift, products evolve, markets move, confidence fluctuates, data is incomplete, inconsistent, or sitting in systems that were never designed to create a holistic picture of a learner.

Even AI works from patterns, signals, and historical data — not genuine understanding of an individual in the moment.

And yet we continue to design as though we can somehow build a perfect digital twin of every learner.

So how do we design personalized learning?

We can’t. And we don’t need to.

The pursuit of hyper-personalization can introduce enormous design, technology, and governance complexity for diminishing returns.

Instead of attempting to create thousands of individual learning journeys, organizations can use meaningful learner profiles, behavioral data, role-based needs, moments that matter, and performance signals to create experiences that feel personal without pretending they are individually bespoke.

Think precision, not perfection.

Because the future of learning won’t be “personalized for me.”

It will be: “Designed for people like me, at the moment it matters, for the behavior that needs to change.”

And that is far more scalable.

The smarter path forward is to deliver relevance at scale

Instead of treating every learner as a completely unique design problem, we can look for patterns within the population and map those patterns to performance challenges.

That means moving beyond demographics and job titles to understand what actually differentiates people in the learning experience:

• What motivates them
• What gets in their way
• What they already know
• What they struggle to apply
• Where confidence breaks down
• What they need to do differently in the moments that matter.

This is where learner personas become more than a UX exercise. Crafted properly, they become a strategic design tool.

A persona isn’t supposed to be a person. It is supposed to represent a pattern that they may recognize themselves in, and their manager and learning team can support them in changing. They are a design mechanism for turning messy human variability into usable design decisions.

That gives L&D a much more practical proposition.

Instead of:

1,000 learners → 1,000 learning journeys

we can move towards:

1,000 learners → meaningful patterns → a small number of evidence-based profiles → targeted experiences → scalable delivery

The sophistication is in creating the right personas by identifying the few differences that genuinely change the learning intervention.

Perhaps one group needs to build confidence before they can apply a skill. Another has the knowledge but struggles to translate it into behavior. Treating these learners identically may be operationally efficient, but it isn’t necessarily performance efficient.

This is where segmentation becomes powerful: not because everyone in a segment is the same, but because they share enough of a problem for us to design something that matters to them.

That gives us a useful design principle: Design for the pattern. Adapt for the person.

Research on personalized education argues that learners are dynamic: their needs and states change during the learning process, meaning that effective personalization isn’t simply about constructing a perfect profile upfront — it is about responding to meaningful changes over time.

The future isn’t hyper-personalized learning.

It is intelligently segmented learning.

The goal is not to make every learner feel like the organization built an entire program just for them. It’s to make every learner recognise why the program was built for someone like them and know what to do with it next. Optimizing performance and changing behaviour is the entire purpose.

Better data, better decisions – create stronger learning strategies

If relevance is the goal, data is the raw material.

Historically, L&D has collected data used to make fundamentally different decisions.  We now have access to more learner data than ever — but more data does not automatically mean better intelligence.

The opportunity is to move from measuring what learners did to understanding what the data tells us about capability, behavior, and performance. This is where persona-based learning becomes strategically useful. Questions such as:

• Who has the knowledge but struggles to apply it?
• Who lacks confidence rather than competence?
• And, perhaps most importantly, where are the gaps that actually matter to business performance?

Better data allows L&D to stop treating every problem as a new novel training problem and, instead, enable performance support as gaps are identified through the process of collation.

This changes the questions we ask of our data, and by doing so, we can uncover where needs differ, where barriers emerge, where behaviors or capabilities cluster, and where a standard intervention is unlikely to work equally well for everyone. Personas then provide the analytical layer between those patterns and learning design.

And because those patterns can be revisited as the organization changes, the learning ecosystem doesn’t have to be rebuilt from scratch every time the workforce, product, market, or strategy moves.

Our vision of the future is persona-based

The future isn’t about making learning more personalized. It’s about making it more intelligently relevant. At Avalere Health, we know that truly personalized learning for every individual simply isn’t achievable at scale — persona-based learning is.

By identifying the patterns that matter, organizations can create learning that is relevant enough to change behavior, scalable enough to deploy globally, and measurable enough to demonstrate impact.

It isn’t a compromise on personalization; it’s a smarter, more sustainable strategy for performance.

Discover how our learning experts can accelerate your team’s performance. Get in touch with jane.vandamme@avalerehealth.com to learn more.