Introduction

Mecca Bingo, part of The Rank Group, operates across 50+ venues in the UK, serving thousands of players through in-person experiences each week.

For many players, their journey begins at the venue, making the front desk the primary gateway into the experience.

At peak times, the front desk became a bottleneck, with staff managing all player interactions from search and registration to account support and membership access.

Queues formed quickly, delaying customers from entering sessions and reducing valuable playing time.

What began as an effort to improve the player management system quickly revealed a broader challenge across the entire entry experience.

The Problem

All entry interactions were dependent on a single staff-assisted flow.

This created pressure on staff, slowed down onboarding, and limited the system’s ability to scale during peak periods.

The issue wasn’t usability:

it was relying on a single interaction model to support every player scenario.

Supporting the entry experience

The player management system underpinned the staff-assisted path, supporting key moments across the player entry journey.

From identifying players at arrival to onboarding new customers, enabling access, and handling more complex account scenarios, the system played a central role in every interaction at the front desk.

While it supported a wide range of tasks, concentrating all of these interactions into a single staff-assisted flow created a bottleneck that struggled to scale during peak times.

The approach

Rather than focusing solely on improving the existing system, the problem was reframed around the full entry journey.

The goal was to reduce dependency on a single staff-assisted flow, while enabling faster and more flexible ways for both new and returning players to access the venue.

This led to exploring multiple paths that could operate in parallel combining staff-assisted and self-service interactions depending on the player’s needs.

To validate the approach, the focus was placed on understanding how the entry experience functioned in real-world conditions particularly during peak periods.

This meant observing how staff interacted with the system, how queues formed, and where delays occurred across the journey.

Discovery Activities.

Discovery Outcome.

The findings showed that the issue wasn’t isolated to individual tasks, but stemmed from concentrating all interactions into a single staff-assisted flow.

To improve the experience, the solution needed to support multiple entry paths that could operate in parallel and reduce pressure on the front desk.

A single, staff-dependent flow was expanded into a multi-surface experience, combining staff-assisted and self-service interactions.

This allowed players to move through the entry journey based on their needs, rather than being constrained to one path.

Following the definition of these entry paths, each journey was designed to support its specific context balancing speed, clarity, and independence depending on the level of staff involvement.

The following sections showcase how these paths were translated into focused experiences across staff-assisted and self-service interactions.

To address the bottleneck at the front desk, the entry experience was redesigned as a multi-path system, allowing players to access the venue through different journeys based on their needs.

Instead of relying on a single staff-assisted flow, the experience was expanded to include a combination of staff-assisted and self-service interactions.

This approach enabled simple, high-frequency tasks to be completed more efficiently, while still supporting more complex scenarios when staff assistance was required.

Purpose: Support staff in handling player interactions efficiently at the front desk, particularly during peak periods where speed and accuracy are critical.

Player Identification.

Improved the search experience to help staff quickly identify players using limited or partial information.

Single Sign-Up Flow.

Status: Implemented

Purpose.

Provide a faster, simplified registration path for new customers, reducing reliance on the full staff-assisted system during peak times.

Where It Fits.

This path is used when a new customer needs to be registered quickly, without going through the full Player Management workflow.

To understand the root causes behind these signals, the system was analysed from three perspectives: ecosystem context, configuration architecture, and operational workflows.

Understanding the incentive ecosystem.

Promotions were part of a broader ecosystem connecting multiple gaming products, operational teams, and platform services.

The Bonus Engine acted as the central orchestration layer coordinating incentives across the platform.

System insight.

The Bonus Engine sits at the centre of a complex ecosystem connecting multiple products, operational teams, and platform services.

Configuration decisions made within the engine directly influence player experiences, operational workflows, and compliance outcomes.

Deconstructing the configuration architecture.

The promotion setup interface was deconstructed into its underlying rule architecture.

Promotions required defining multiple interdependent parameters including mechanics, segmentation rules, deposit conditions, reward structures, and campaign timing.

Insight.

Hidden rule dependencies increased cognitive load and led to configuration errors.

Understanding the operational lifecycle.

Promotions were not static configurations but part of an operational lifecycle involving campaign launch, monitoring, investigation, and support.

Insight.

Limited visibility into promotion behaviour created operational friction and manual investigation.

Following the discovery phase, we facilitated a cross-functional workshop with product, engineering, operations, and compliance teams to define what success would look like for the redesigned system.

Addressing these challenges required improving configuration clarity, introducing better validation mechanisms, and supporting the full operational lifecycle of promotions.

Three outcome areas were identified.

Strategic direction.

The solution focused on three core improvements to the promotion configuration experience: introducing a structured configuration flow, surfacing rule dependencies and system logic, and enabling teams to confidently validate promotions before launch.

Together, these changes aimed to reduce configuration errors, improve operational visibility, and increase confidence for the teams responsible for managing promotions.

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 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.

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.

The redesign introduced several structural changes to how promotions were configured and validated. Each design decision directly addressed issues uncovered during discovery.

Mapping key discovery insights to design decisions and measurable improvements in promotion configuration.

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

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.