How Intelligence Transforms End-to-End Salesforce Testing

Salesforce started as the first cloud-based CRM in 1999 and has since sprouted into a multibillion dollar ecosystem with 9M downloads across 6.7K apps in Salesforce AppExchange. From the moment a potential customer first visits a company’s website through the sales process to the customer experience, Salesforce is a constant presence. Which is why automated Salesforce testing has emerged as a critical business need. 

Complex Salesforce Apps Derail Shift-Left Testing Efforts

Despite its dominating presence in the prospective customer experience, 33% of Salesforce teams rely primarily on manual testing. The sheer complexity of Salesforce applications and workflows; shadow DOM components, integrations with other third-party applications like Marketo and Intercom, as well as highly customized workflows inhibit consistent Salesforce automated testing. What limited efficiency gains that can be made with scripted test automation frameworks are usually undone the next time any change is made and element properties change. 

Intelligence Makes Salesforce Testing a Reliable Part of Testing Strategies 

Intelligent testing is helping quality teams adapt to the challenges of automated Salesforce testing. Traditional test automation tools often rely on element IDs as the primary locator for each element. But Salesforce applications feature dynamic element IDs that are prone to rapid changes, quickly rendering ID-dependent tests irrelevant. Mabl uses Salesforce-tuned machine intelligence to collect dozens of element attributes and determines which ones are stable so tests can be updated even as some IDs change. Intelligence also enables mabl to autoheal broken tests when IDs change, minimizing the amount of time needed to maintain complex Salesforce tests. Tests become more reliable and require less maintenance, freeing quality engineers to focus on goals like increasing test coverage. 

Greater reliability improves the accuracy of automated Salesforce tests, making it easier for teams to improve quality across the prospective customer experience. Features like Intelligent Wait minimize the risk of false test failures by learning how long it takes for the application to reach the correct state. Tests will only be executed when the page is fully loaded. With autoheal and Intelligent Wait, automated tests supported by machine intelligence empower software teams to improve quality sustainably across Salesforce applications. 

Manage Quality Across the Entire Customer Experience

Salesforce applications can be embedded at every step of the customer lifecycle, complicating end-to-end testing. Many automated testing frameworks can’t move between different applications, tabs, and iframes, so testing teams are forced to rely on disparate tests to manage quality. This incomplete picture of quality makes it harder for teams to collaborate and increases the risk of defects slipping into production. 

With mabl, end-to-end tests that validate changes in downstream applications can easily be created by anyone through low-code and intelligence. All Salesforce stakeholders - including administrators, Salesforce testers and developers, and internal end-users - can develop a full understanding of quality across the prospective customer experience. With machine intelligence reducing the amount of maintenance needed for automated Salesforce tests, quality engineers can scale E2E testing through cross-functional collaboration. 

Best Practices for End-to-End Salesforce Testing

Intelligence test automation enables quality teams to build new processes across their organizations for more effective testing and more collaborative cultures of quality. Through close partnerships with our customers, the mabl team has identified best practices for building quality Salesforce testing strategies: 

1. Empower business users and developers to contribute to test creation. Low-code test creation and comprehensive reporting features means that anyone can help identify and potentially create tests for important scenarios. Having the tools to understand and support Salesforce testing enforces the value of test automation and their role in quality. 
2. Support shift-left testing by creating E2E test plans that can be run on-demand, on schedule, via CLI or triggered by CI pipeline. When possible, QE should share these plans with Salesforce administrators or developers to run whenever changes are made.
3. Improve test coverage by creating comprehensive E2E tests that cover the entire Salesforce workflow, including UI+API, PDF, and email. These tests will establish a more comprehensive view of quality gaps for more efficient Salesforce testing.  
4. Extend the value of end-to-end Salesforce tests by reusing them for performance insights. More testing earlier in the development cycle means that the entire software development organization will have a better view of quality. To build awareness around these quality insights,  connect mabl to Slack or Microsoft Teams so that notifications on performance deviations are automatically sent to the relevant teams. 

Intelligent Test Automation Empowers Quality Engineers and Developers

Salesforce applications and their growing role in software development is part of larger trends of how development itself is being transformed by third-party software. As development cycles accelerate and enterprise technology becomes more sophisticated, developers and business users alike will increasingly turn to third-party applications to embed more value in the customer experience. Quality engineers need solutions that empower them to adapt to this new, highly complex world. With machine intelligence and low-code, test automation platforms like mabl are making it easier for entire organizations to collaborate on quality, even across complex applications like Salesforce. 

Transform how your team manages quality across the customer experience with mabl’s 14 day free trial. Create and run intelligent end-to-end tests in minutes, change Salesforce testing forever.