The Go Game  ·  Head of Product & Design

Event Manager Dashboard

Nov 2020 - July 2023

Transformed a white-glove, services-heavy operation into a scalable self-serve product platform: one dashboard that absorbed the operational complexity.

TL;DR: Transformation & Impact

Key Outcomes

  • 2× event capacity: automation removed the ops bottleneck
  • +12% rebooking rate from a smoother customer journey
  • 34% reduction in customer setup time
  • One unified dashboard replaced spreadsheets, docs, DMs, and disconnected tools
  • Used by Fortune 500 companies (Google, Facebook, Amazon)

What Changed

Spreadsheets, docs, and DMsOne unified dashboard
Only senior staff ran complex eventsClear workflows by role
Heroic manual coordinationRepeatable automated execution
Weak customer setup portal34% faster self-serve setup

Context

The Go Game is a team-building and corporate events company that pivoted to hybrid (virtual + in-person) experiences during COVID. The company had built a successful events business serving Fortune 500 clients including Google, Facebook, and Amazon.

As Head of Product & Design, I owned the entire product organization. My job was to turn a professional services company into a scalable software platform. That meant productizing institutional knowledge and manual processes that had built up over years.

Challenge

Revenue demand exceeded operational capacity. Growth was capped by how much work humans could personally handle:

  • Disconnected tooling: Core workflows were spread across many disconnected tools, held together by spreadsheets, docs, and DMs.
  • Knowledge in people's heads: Every event required heroic manual coordination, and only senior staff could safely run complex events.
  • High error risk during live execution: Manual handoffs meant dropped balls, missed reminders, and coordination failures in front of clients.
  • Weak customer-facing configuration portal: Ops absorbed setup work that customers could have done themselves.

What I Did

1

Designed for Real Surfaces, Not Job Titles

Customers booking events, internal ops coordinators, and hosts running events live each needed a different control layer. Progressive disclosure by role kept each surface simple without hiding the underlying system.

2

Unified the System Instead of Adding Tools

Core workflows were spread across many disconnected tools, and critical knowledge lived in people's heads. Replacing them with one control surface cut context switching and error risk during live execution.

Tradeoff: Chose depth over breadth: focused on most-used workflows rather than full parity with every tool.

3

Automated the Highest-Frequency Pain

Focused automation on the work humans repeated every single event, not edge cases. That is what removed the ops bottleneck and doubled event capacity.

Tradeoff: Low-usage, high-complexity event types stayed manual longer.

Impact & Results

Ops stopped relying on ad-hoc docs and DMs to run events, errors dropped during live execution, and setup got faster with less senior oversight. The second-order effects mattered just as much: lower marginal cost per event, services teams shifted from glue work to higher-value tasks, and self-serve became viable for more customers.

Event Capacity

+12%

Rebooking Rate

-34%

Customer Setup Time

Event Manager Dashboard

The Go Game Event Management Dashboard

Event Management Dashboard: one control surface for customers, ops coordinators, and hosts

Event Manager Dashboard system architecture diagram

System architecture: how the Event Manager Dashboard connected all upstream booking flows and downstream delivery tools

Key Takeaways

Pull Revenue-Visible Features Earlier

The ops wins were real but invisible to buyers. Customer-facing improvements moved rebooking and deserved earlier slots on the roadmap.

Push Back on Low-Usage, High-Complexity Event Types

A small set of rare event formats consumed outsized build and support effort. Saying no sooner would have freed capacity for the workflows that ran every week.

Delay Hierarchy Models Until Usage Patterns Are Proven

Formalizing structure before real usage data locks it in too early. Ship flat, watch how people actually work, then model it.

Next Case Study

IMVU

IMVU Mobile Launch