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BlogBreadcrumb SeparatorKoala in the Field: How Checkly Turns PRs into Pipeline

Koala in the Field: How Checkly Turns PRs into Pipeline

Koala in the Field: How Checkly Turns PRs into Pipeline

Checkly is a dev-centric synthetic monitoring platform that leverages an extremely popular open source project, Playwright, for browser-based monitoring. Because they also offer several scale-ready features like alerting, scheduling, geo-distributed checks, and integrated dashboards, the team wanted a way to auto-identify Playwright users most likely to benefit from these additional features.

However, Checkly wanted these conversations to feel organic—starting from a place of genuine helpfulness at exactly the right moment. That’s where Koala comes in.

The Challenge: Identifying Best Fit Playwright-Adopters

Checkly’s ideal customers are technically sophisticated organizations that value reliability and fast issue resolution. However, pinpointing these teams and determining the right moment to engage posed a challenge. Traditional outreach methods lacked the precision needed to identify best fit accounts, with genuine adoption signals.

The Solution: Leveraging Koala to Detect and Act on Playwright Signals

Checkly implemented a targeted strategy using Koala to monitor and act upon specific indicators of Playwright adoption:

1. Monitor Technical Activity: Track GitHub interactions with Playwright repositories, such as stars, forks, and pull requests. Trigger the Play on visits to Playwright-related documentation pages, indicating research and potential adoption. Exclude current customers.

Setting up Play targets and triggers

2. AI-Powered Research: Utilize Koala's AI agents to uncover additional signals, including:

  • Job postings requiring Playwright expertise.
  • Public reports of service outages or reliability issues.
  • Hiring patterns for SRE or QA roles.
Adding AI agents to add more color to every outreach message

3. Route to the right rep:

Setting up routing rules

4. Personalized Outreach: Employing Koala Coach to combine signals, historical CRM data, and designated Plays to build a comprehensive view of each account's journey. Generate hyper-tailored messages that address the specific needs and pain points of each prospect.

Koala Coach at work—pulling relevant details about the prospect from AI research and CRM data, to combine with Checkly positioning and preferred sales play.

By focusing on concrete indicators of Playwright adoption, the Checkly sales team can now stay focused on engaging prospects with exactly the right education about their company, at exactly the right time.

Implementing Your Own OS Project Monitoring Strategy

If you know of an open source alternative to your solution, you can replicate this company’s Plays by following these steps:

  1. Identify Key Adoption Signals: Determine the technical activities that indicate interest in your product or related technologies.
  2. Leverage AI for Deeper Insights: Use AI tools to uncover additional context and validate the intent behind observed signals.
  3. Integrate Historical Data: Combine current insights with past interactions to understand the full customer journey.
  4. Personalize Outreach: Craft messages that speak directly to the prospect's current challenges and objectives.

Interested in giving it a go?

Let’s build it together →


Lauren Craigie

Lauren Craigie

Head of Marketing

Case Studies

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