SaaS

End-to-End

0→1

+2k Users

Subscription management automation & bulk actions tools

Role

Solo Product designer

Duration

2 months from concept to MVP

Platform

Web Application (desktop only)

TL;DR

Context

Kurabu is a club management platform that supports the day-to-day administrative work of sports clubs.

This project solves a part of a time consuming task of clubs admins and that generates the most support requests: subscriptions’ management.

What I did

Designed a solution that adapts to each club’s pricing structure mixing automation and bulk actions. Created so that a small, mainly junior dev team can build and maintain it.

Solution’s impact

Research

Goal

Understand how clubs manage pricing, their main pain points, and how automation could improve the process. I also wanted to assess how these challenges and mistakes affect the Dev Team's workload.

Methodology

I began with a survey targeting club managers, followed by interviews with the Sales and Dev Teams. I then analysed pricing structure from clubs of various sizes to identify common patterns and key differences. Finally, I conducted a competitor analysis and audited our current product.

Insights

How clubs manage the situation

Subscriptions were managed manually or with Excel, which is time-consuming and prone to errors.
Clubs often juggle multiple databases.

Common pricing pattern

Pricing is usually fixed per bracket. Clubs want automated subscription changes based on age, especially 18.

What competitors do

None of our competitors offers a satisfying solution.

Unique pricing structures, common backbone

The factors that determine which price or plan applies to a member generally follow a core structure, with some clubs adding extra layers based on their specific needs.

Club pain points become dev team’s bottlenecks

Club pain points result in repetitive sales requests like bulk member additions, setting plan end dates, or editing plan frequency, pulling the dev team away from building new features and slowing overall product development.

Problem

Current system creates busywork for clubs and dev team

Clubs' day-to-day subscription management and mistake corrections all landed on the development team. At season start alone, this reached up to 900 update requests across all clubs.

Automations had to be customisable

The challenge was to design a system flexible enough to support diverse club needs, while remaining realistic for a small engineering team to build and maintain.

Decision

Scoping the MVP around common patterns

My goal wasn't to automate everything, but to remove the most repetitive work first. I scoped the MVP around common pricing patterns that could be translated into optional rules. Age-based changes were the most consistent pattern, while bulk actions covered frequent time-based updates, such as applying subscription start/end dates to groups of members.

Key Decisions

Kept the MVP focused on age-group rules
Added bulk actions for common tasks
Prioritized product improvement to be done before MVP implementation.

Choosing automations over AI

Pricing variations across clubs follow recognisable patterns that can be modelled as configurable rules.

AI would add unpredictability to a system where every outcome needs to be trustworthy and auditable. A rule-based system with anomaly detection was the right fit, and far easier for a small, mainly junior development team to build and maintain.

Solution

BeforeAfter

Preparing the product for automations

Before implementing the feature, I redesigned key parts of the subscription management area (“Plans” in the product) so the UI could support automation.

This improved clarity and usability, and prepared the interface to scale as automations were introduced.

Because automation impacts member communication, clubs needed clear control over which emails would be sent.

Designing a system that can scale

I designed and specified a rule builder to make automation safe and predictable.

In close collaboration with engineering, leadership, and key client clubs, I defined how rules should behave, how edge cases are handled, and what could realistically be automated.

The system was designed so new rule types could be added over time without reworking the core logic. For example, applying discounts after document validation.

Results

Validation, impact and KPIs

The feature was validated through investor pitches, client demos, and direct collaboration with sales and large club accounts to define edge case handling and rule behaviour.

While still at Kurabu, key improvements were shipped, including allowing clubs to change a subscription's billing frequency before the first invoice, which already reduced support requests and developer workload. I ensured continuity through detailed documentation, recorded walkthroughs, and handover sessions with both designers and developers.

The projected impact was estimated by the sales team for investor and client pitches. Success would be tracked through:

Ratio of subscriptions managed via automation vs bulk action vs manually
Ratio of clubs using automation vs bulk actions only vs neither, across club sizes (target: 80% adoption for 1000+ member clubs)
Number of subscription management support requests, and time spent on them (target: −70%)