Carrier Achieves Continuous Quality and World-Class Test Automation Practice with Copado

The Challenge

Manufacturing a Growing Testing Backlog

Carrier is no small operation. As a global enterprise managing Salesforce Sales Cloud, Service Cloud, and Experience Cloud — alongside SAP ERP integrations and mobile applications — the stakes for quality are high and the surface area for testing is vast.

When Deepak Sharma joined Carrier as Salesforce QA Architect, most testing activities were still performed manually. The team had an established QA process supporting Carrier's Salesforce ecosystem, with 10 to 15 QA professionals working across multiple delivery pods. As the Salesforce footprint and release scope continued to grow, Carrier identified an opportunity to expand test automation and make regression testing more scalable and efficient. 

"Most of the testing was manual," recalls Deepak Sharma, Salesforce QA Architect – EDPS at Carrier. "It was a time-consuming activity — from setting up the test plan, test strategy and test matrix to executing the tests, recording results, categorizing outcomes and validating exit criteria. We saw a clear opportunity to automate these repetitive activities and allow the team to focus more on higher-value quality activities." 

The scale of regression testing made automation increasingly important. With monthly releases and a regression suite of 150–200 test cases per pod, QA engineers were responsible for executing a significant volume of tests within tight release timelines. At 10–15 minutes per test case, completing the full regression cycle alongside day-to-day QA responsibilities required considerable effort. 

As the Salesforce ecosystem evolved, the regression suite continued to grow by approximately 10–20% with each release. This increasing volume created a clear need for a scalable approach that could expand test coverage without proportionally increasing execution effort. 

Release timelines also required the team to continuously prioritize testing based on risk and business impact. When development timelines changed or release scope increased, the team had to focus execution on the highest-priority scenarios within the available window. This reinforced the value of automation as a way to increase regression coverage, improve execution consistency and provide faster feedback during releases.

The Solution

Scaling Carrier's Quality Engineering Practice with Low-Code Automation

When Deepak joined Carrier, his first assignment was clear: evaluate the market and find the right automation tool. He came with deep experience in Selenium and Playwright — but he was looking for something different. "I come from a hardcore automation background — Selenium, years of it," says Deepak. "But I realized that low-code, no-code is something that helps everyone contribute to automation and make it a huge success. Even a person without a technical background can learn the tool and make things work."

After a rigorous proof-of-concept comparing tools across dimensions of maintainability, scalability, cost, and Salesforce-specific capability, Carrier selected Copado Robotic Testing (CRT) based on its crucial functionalities: 

• QWord-based scripting: Human-readable keywords that non-technical QA engineers could learn and use independently
• Zero setup friction: No drivers, no IDE, no executable files. Just a URL and a browser
• Salesforce-native libraries: Dedicated commands like Get ID that abstract complex Salesforce interactions into simple, readable steps
• Parallel execution: The ability to run up to 40 test cases simultaneously, multiplying team capacity without adding headcount
• Mobile testing support: Coverage for Carrier's Go mobile app alongside web and Salesforce environments

"The way Copado has been designed — with human-readable QWords — everyone can understand it regardless of their background,” mentions Sharma. “If you have a coding background, it's icing on the cake. If you don't, you can still learn it and make it work."

Testing Automation Rollout

Carrier partnered with Copado Professional Services for a month-long onboarding and training program. All 10 team members became Copado-certified. From there, Deepak structured the rollout pod by pod — establishing shared keyword libraries, a common folder structure, a Git repository for script versioning, and a team guideline document that stayed open on every engineer's second screen.

The team started small — prioritizing P1 test cases, building confidence with quick wins, then progressively tackling longer, more complex scenarios. Week by week, month by month, the numbers climbed. "Those initial small wins with Copado Robotic Testing were giving us confidence," reflects Deepak. "It was boosting our morale and making us happy that yes — we are progressing."

Scaling Test Automation with Copado Explorer and TestAgent

As the team matured, Carrier adopted Copado Explorer to streamline bug documentation and exploratory testing. Previously, manual testers spent significant time taking screenshots, organizing them in folders, and assembling them into reports one by one.

"Now, whatever you're clicking on — Copado Explorer captures it. Wherever you're typing — it captures the field name and the value. And it puts the screenshot right there," says Deepak. "Explorer is saving us 70–75% of the time we used to spend on documentation."

Carrier also embraced TestAgent, Copado's AI-powered assistant embedded within CRT. For the Carrier team it became an indispensable daily companion.

The Outcome

Success in Numbers

The transformation at Carrier was not incremental — it was exponential. In the first five months of scripting, the team automated 500 test cases. By the end of 2025, they had built 1,200 automated scripts in a single year. Today, 80–90% of Carrier's core Salesforce processes are fully automated, with the remaining 10–20% representing the current sprint — automated in parallel with active development.

But the most striking proof point came from a multi-country regression project. Carrier needed to validate the same 400+ test cases across 12 global instances — the same functionality, deployed for different locales. Manually, a single resource would need 15 days per instance. For 12 instances, that was simply not possible.

Through parallel run, we are running those 400+ test cases at the same time for all 12 countries," says Deepak. "All 5000 test cases are getting executed in just 3 days. There cannot be a better example than this.

As Carrier's Salesforce footprint expanded, scaling regression testing across multiple instances became increasingly important. With Copado, the team has expanded automation across all 12 instances and can now execute approximately 5,000 test cases in just three days—enabling broader coverage, faster feedback, and significantly greater testing capacity.

With CRT running 40 parallel executions, those same 300-400 test cases that consumed 3 days of human effort now run unattended, freeing each QA engineer to focus entirely on new script development, exploratory testing, and strategic quality work.

Automation has significantly reduced the effort required during release windows, enabling the team to identify issues earlier and focus more on higher-value quality activities. By reducing repetitive testing and documentation effort, Copado has helped each QA engineer reclaim an estimated 6–9 weeks of productive capacity annually. That capacity is now being reinvested in continuously expanding and enhancing our 1,200+ automated script library.

Automation testing with Copado has made a significant difference to our release cycles,” says Deepak. “It helps us identify issues earlier, makes debugging more efficient, and accelerates the design and development of new automation scripts. Most importantly, it gives the team more capacity to focus on higher-value quality activities while maintaining better balance during releases.

Team morale has followed. Tools like TestAgent and Explorer have removed the tedious parts of the job such as manual data entry, repetitive execution, screenshot assembly, freeing the team to focus on the high-value detective work that QA engineers actually enjoy. And the time savings with TestAgent is measurable:

• The team saves 40–50% of their time searching documentation or learning new features
• Today there’s a 70%+ reduction in debugging time
• Faster script generation by learning from existing robot file patterns

The Future

From Sprint Planning to System Planning

For Deepak and the Carrier QA team, the journey with Copado is far from over. The next chapter is about moving beyond automation at the test level — and building intelligence into the entire quality lifecycle.

Carrier's near-term goal is to achieve 90%+ automation coverage across all core Salesforce business processes and then expand beyond Salesforce entirely, bringing CRT's capabilities to platforms like Shopify as the business grows.

The team plans to move beyond traditional scripting by integrating Copado Explorer for rapid exploratory sessions and leaning further into TestAgent for a stable, maintainable, and AI-assisted test framework. The goal: shift QA engineers from script writers to strategic quality architects.

Testing Agentforce with CRT

Perhaps the most forward-looking initiative is Carrier's work at the intersection of Agentforce and Copado Robotic Testing. Carrier’s QA team is already building internal Agentforce agents and they're using CRT to validate them.

"I want to bridge the gap between AI reasoning and action by using CRT to execute the agent's outputs," says Deepak. "Testing an AI agent with CRT is a brand-new frontier for us. I'm excited to dive into the learning curve of how these two powerful tools can work together to close the loop from idea to automated execution."

Using CRT's AI evaluation libraries, which assess agent faithfulness, hallucination rates, and response specificity, Carrier can measure prompt quality and agent reliability with precision. In one example, a precisely engineered prompt scored 90% on CRT's responsiveness scale, versus 70% for a generic prompt. That difference is now a measurable quality signal.

"The more precise you make your prompt, the more favorable the result," says Deepak. "CRT is letting me know when I need to refine my instructions — and that's where it's helping us even to test an agent."

With the ability to test with certainty and implement quality at scale, without mitigating risk, the future is clear: a fully automated, AI-augmented quality pipeline — from requirement to release — where Carrier's QA team spends less time on repetition and more time on the strategic, creative work that drives real business value.