Introduction

The Rank Group is a FTSE-listed international gambling and entertainment company operating physical venues and digital platforms across the UK and Europe.

With over 7,700 employees and 3.1 million active customers, its internal systems support a business generating nearly £800M in annual net gaming revenue.

Promotional campaigns are a key driver of player acquisition and engagement.

These promotions were configured by employees through an internal platform known as the bonus engine.

Problem statement

Configuring promotions within the bonus engine was complex, fragmented, and difficult to validate resulting in high levels of error, slow campaign setup, and low confidence across teams.

Promotion setup required navigating multiple layers of rules, conditions, and screens, making it difficult to understand how configurations would behave once launched. As a result, teams relied heavily on manual QA to verify setups, with many issues only identified after deployment.

This led to frequent rework, inconsistent promotion behaviour, and reduced efficiency in launching campaigns.

How might we enable teams to configure promotions in a way that is clear, predictable, and validated in real-time reducing operational risk while maintaining the flexibility required for complex campaign logic?

Signals & evidence.

This challenge was grounded in a consistent set of operational signals observed across promotion configuration, validation, and campaign management workflows.

These signals suggested that the core issue was not just usability, but a lack of system clarity and predictability in how promotions were configured and validated.

While these signals highlighted the scale of the problem, they did not explain its root causes.

A structured discovery phase was conducted to break down how promotions were configured, validated, and managed across teams.

The Bonus Engine was used by multiple internal teams to configure and manage promotional campaigns across the digital platform.

To understand the problem, discovery focused on three areas: how teams configured promotions, how the system interpreted configuration logic, and how promotions were managed across their lifecycle.

This involved working across a globally distributed organisation, leading a structured discovery phase that combined user interviews, workflow analysis, and cross-functional workshops with teams in London, Gibraltar, Mauritius, and Cape Town.

Discovery activities.

The discovery phase combined qualitative research, workflow analysis, and system-level investigation to understand both user behaviour and underlying system logic.

These activities focused on where errors occurred, how promotion rules were interpreted, when validation took place, and how teams interacted across the lifecycle.

Discovery Outcome.

The findings showed the issue was not usability, but how the system was structured and understood across teams.

A gap between expected behaviour and system logic led to inconsistent outcomes and low confidence.

To address this, structured artefacts were created across three dimensions: the incentive ecosystem, configuration architecture, and operational lifecycle.

Understanding the incentive ecosystem.

Created to address: lack of a shared understanding of how promotions function across the player journey.

What it does: through a series of cross-functional workshops, the incentive ecosystem was mapped to define how promotions should behave from player entry points through to reward outcomes.

This aligned stakeholders around:

• The intended flow of incentives

• How different promotion types interact

• The relationship between player behaviour and reward logic

Deconstructing the configuration architecture.

Created to address: complex and opaque rule structures that made promotion setup difficult to understand and scale.

What it does: the existing configuration model was broken down to understand how rules, conditions, triggers, and rewards were structured.

This enabled the creation of a clearer configuration framework that:

• Defined how components should be structured

• Clarified relationships between elements

• Improved predictability in how promotions are built

Understanding the operational lifecycle.

Created to address: lack of visibility across the full promotion lifecycle, from creation to closure.

What it does: based on user interviews and workshops, the end-to-end lifecycle of a promotion was mapped from initial setup through validation, launch, monitoring, and closure.

This made visible:

• Key stages where errors occurred

• Points of handoff between teams

• Gaps in validation and ownership

Strategic direction.

This established a structured and predictable foundation for configuring promotions, reducing uncertainty and enabling teams to operate with confidence.

Discovery showed that promotion configuration was difficult to understand because rule dependencies were hidden, configuration decisions were scattered across a large form, and validation relied heavily on manual QA.

The redesign focused on making system behaviour visible while guiding teams through a structured configuration workflow.

Campaign overview.

Promotion management begins in the operational dashboard, where teams can view active and scheduled campaigns.

A card-based layout surfaces key campaign details such as reward type, status, and activation windows, making promotions easier to scan.

The interface was designed to support rapid scanning rather than deep data inspection.

Dashboard layout direction.

During exploration, both card and list layouts were considered. Cards provided clearer visual hierarchy, while a list view offered a more compact table format for managing large numbers of campaigns.

The card layout became the primary experience, with a list view toggle planned for future iterations.

Card layout direction + list view

Discovery revealed that many dependencies between configuration fields were hidden, making promotion behaviour difficult to predict.

To address this, validation behaviour was mapped using a validation logic matrix, defining how the system should respond to rule conflicts, missing dependencies, and risky configurations.

Configuring promotion rules.

Promotion setup was redesigned as a structured configuration flow.

Instead of a single dense form, the new experience guides teams through the key stages of promotion setup such as eligibility conditions, deposit requirements, reward configuration, and wagering rules.

This structure reduces cognitive load by allowing teams to focus on one decision at a time.

Dynamic reward configuration.

The rewards section adapts dynamically based on inputs defined earlier in the configuration process.

Selections such as reward type, eligibility rules, and deposit conditions automatically adjust the available reward parameters.

Preventative safeguards.

To prevent configuration errors.

The interface disables incompatible options and hides fields that are not relevant to the selected promotion type.

Advisory feedback.

Where configurations may introduce risk.

The system provides warning messages highlighting potential issues without blocking progress.

This allows teams to understand rule conflicts while maintaining flexibility.

Confident validation.

Before activating a campaign.

Teams review the full promotion configuration in a structured confirmation layer.

The validation screen displays key promotion details including eligibility rules, reward structure, deposit conditions, wagering requirements, and campaign timing.

This final step allows teams to verify that the promotion behaves as expected before launch.

Impact

The redesigned configuration experience improved both usability and operational efficiency across the teams responsible for managing promotions.

Improvements were measured against the success metrics defined during the discovery workshop.

Improving clarity and reducing cognitive load during promotion setup was a key objective of the redesign.

These improvements reflected the impact of the structured configuration flow, clearer rule dependencies, and dynamic configuration behaviour.

The redesign also reduced the operational overhead required to create and manage promotions.

By preventing configuration errors earlier in the workflow, teams were able to launch campaigns with greater confidence and fewer manual interventions.

Because promotions control financial incentives, improving governance and reducing configuration risk was critical.

The introduction of validation logic and confirmation layers helped ensure that promotions were configured correctly before going live.

By making promotion logic visible and guiding teams through a structured configuration workflow, the redesign transformed promotion setup from a complex, error-prone process into a predictable system teams could confidently operate.