
How It Started
Complex tasks with no room for error are prime candidates for automation. When GrowthRunner reached out to automate their entire analytics process, we jumped at the chance to showcase what bespoke tools can do. GrowthRunner is the expert analytics tracking agency founded by Nitesh Sharoff. They specialize in advanced analytics and tracking for iconic brands including Wagamama and Net-a-Porter. Their core business revolves around auditing analytics setups - integral to their lead generation, day-to-day implementations, and billable hours.Understanding the Problem
These audits require specialists to meticulously comb through client sites, reviewing tracking events, checking each payload and implementation. The process was error-prone and monotonous, highly specialized with numerous edge cases, critical to their business model (a misimplementation can cost clients hundreds of thousands), and time-consuming, limiting their scalability.Building the Solution
I created a custom DevTools extension that reduced their auditing and implementation time by 90%, automating monotonous tasks and improving overall efficiency. The automation works by leveraging Chrome’s Recording API to capture user journeys, building a dataLayer listener that plays back recorded actions, simulating typical user journeys and navigation, capturing screenshots and timestamps for documentation, and matching actual events against expected events to provide analytics health snapshots.The Technical Build
I built this using Plasmo.com as the web extension framework, React with Tailwind CSS for the DevTools interface, IndexedDB for local storage, and Chrome’s DevTools and Recording APIs. The main technical challenges were significant. DataLayer tracking required monitoring changes before, during, and after code execution in the DevTools window. Cross-context communication needed heavy use of main world JavaScript injection to enable communication between the client window and the isolated world of Chrome extension development. The Chrome Recording API integration was complex to implement for accurate capture and replay.What We Built
The extension is custom-built for GrowthRunner’s specific workflow. It includes an analytics dataLayer observer that tracks and categorizes all events automatically, captures user actions like clicks and text inputs, extends the Chrome Recording API for auditing and playback, and generates automated reports with screenshots and timestamps.How Fast I Delivered It
I delivered the MVP in 10 days. The total project timeline was 14 days including sales and iterations. It went to production in 2 weeks.The Results
The efficiency gains were dramatic. We achieved a 90% reduction in auditing time, reducing tasks from multiple hours to minutes. Team capacity increased from 1 audit per day to 10 audits per day per team member - a 10x increase in throughput. The business impact extended beyond time savings. GrowthRunner freed up expert team members for high-value strategic work, reduced error rates in analytics implementations, accelerated their pitch-to-delivery cycle, and enabled scaling without proportional headcount increase.What We Learned
Bespoke automation tools can transform specialized workflows. Even complex, edge-case-heavy processes can be automated effectively when you understand the domain deeply enough. Two weeks of development can deliver months of time savings. The ROI on focused automation is staggering when you target the right pain points. Custom DevTools extensions are powerful for technical service businesses. They integrate seamlessly into existing workflows and provide capabilities web apps can’t match.Frequently Asked Questions
How did you achieve 90% time reduction in analytics auditing?
How did you achieve 90% time reduction in analytics auditing?
Could this approach work for other technical audits?
Could this approach work for other technical audits?
What makes a Chrome DevTools extension different from a web app?
What makes a Chrome DevTools extension different from a web app?
How complex was the technical implementation?
How complex was the technical implementation?
What was the business impact beyond time savings?
What was the business impact beyond time savings?
How did you handle the complexity of different analytics setups?
How did you handle the complexity of different analytics setups?
Could this be turned into a SaaS product?
Could this be turned into a SaaS product?
What ongoing maintenance does a tool like this require?
What ongoing maintenance does a tool like this require?