Phishing simulation is one of the most powerful tools to measure and strengthen employee awareness.
But its effectiveness depends on a variable that is often underestimated: frequency.
The key question for every IT or Security Manager is: “What is the right rhythm to achieve results without overwhelming users?”
Industry best practices recommend scheduling multiple phishing simulations spread over time, maintaining high awareness through regular, well-structured campaigns on a semi-annual basis.
However, excessive, uncalibrated frequency can lead to habituation, frustration, or—at worst—user disengagement.
Why one-off simulations don’t work
An annual test may meet compliance requirements, but it doesn’t build a security culture.
Effective learning relies on repetition, reinforcement, and practical application — not occasional exposures.
According to the Verizon DBIR 2023, 36% of analyzed breaches involve phishing attacks, often within multi-vector scenarios where the human element plays a decisive role: clicking links, opening attachments, entering credentials.
In this context, habit makes the difference. Those who have already trained their risk awareness develop faster and more conscious response mechanisms. A one-off simulation doesn’t create this automatic response. It generates surprise. And surprise doesn’t build competence.
The frequency paradox: too little doesn’t help, too often irritates
Here lies the real operational challenge: finding the right balance.
An overly aggressive approach can:
- saturate attention
- undermine trust in the IT team
- trigger defensive or passive reactions (“it’s always just a test anyway”)
On the other hand, an insufficient pace:
- doesn’t encourage distributed learning
- doesn’t allow for continuous monitoring
- leaves entire teams or critical moments (e.g., onboarding, peak activity periods) unprotected
The concept of “phishing dwell time” — the time between the arrival of a malicious email and its identification by the user — is now central to evaluating training effectiveness.
Companies that conduct regular, targeted simulations demonstrate significantly faster reaction times compared to those with sporadic or purely formal approaches.
The point isn’t to do “more tests,” but to do them consistently, calibrated, and sustainably.
There’s no one-size-fits-all frequency: the optimal rhythm is adaptive, built on users’ risk, roles, and behavior. Better fewer, well-designed simulations than a massive, repetitive routine that ends up losing effectiveness — and meaning.
How to keep attention high (without losing buy-in)
The key to making simulations effective isn’t to “catch” users out, but to turn every test into a moment of situational learning. It’s not about catching them making mistakes, but helping them recognize risk in the real context they operate in.
A key element is the use of gamification: badges, leaderboards, symbolic rewards, and positive feedback can encourage attention without causing stress. Instead of blaming those who make mistakes, it’s better to reward those who improve, turning the experience into an opportunity for growth.
Equally important is the tone of communication. The most effective simulations use a human, credible language that’s close to the user’s daily life—without being punitive or alarmist.
The goal is for the message to be seen as helpful, not as a trap. To keep interest high, it helps to include creative elements in content design: themed campaigns, cultural references (including pop culture), targeted memes. These touches break the routine and make training more memorable.
But more than anything else, what makes the difference is immediate feedback.
A contextual message right after the mistake has a much stronger impact than theoretical training conducted weeks later. It’s at that exact moment — when the error is still fresh — that the person is most receptive and ready to change behavior.
A practical case: our approach with Albert
To tackle this problem systematically, we developed a framework based on personalized, cyclical, and intelligent simulations, integrated into our ongoing awareness program: Albert.
With Albert:
- The simulation frequency is adapted to the user’s role, risk level, and responses.
- The content evolves over time, avoiding repetition.
- Each simulation is followed by immediate, contextual micro-feedback.
- The system monitors real behavioral KPIs, providing the IT team with clear, actionable, and progressive reports.
Result: a sustainable, progressive, and measurable phishing simulation program that educates without overwhelming.
The goal isn’t to “catch out” users but to truly train them. An effective simulation isn’t meant to “spot mistakes,” but to coach those who can improve. It’s a process of distributed learning, not a disguised audit.
As an IT team or security leaders, there’s only one real goal: turning every click into a learning opportunity.
And every simulation into a step toward a more mature risk culture.
