The enterprise software industry has moved to centerstage, supercharged by market shifts to cloud, SaaS, machine learning and AI, and even the pandemic last year. As organizations have shifted to remote work and digital demands have hit record highs, US-based enterprise technology startups raised a record $156.2 billion in funding, topping the previous record of $142.7 billion, which was set in 2018. As a result, competition in the enterprise software space has become fiercer than ever.
To differentiate their product, B2B software startups are turning to the user experience and product velocity. Product teams are under incredible pressure to rapidly introduce new features and quality assurance professionals are seeing their role expand to include delivering a flawless end-to-end experience in addition to troubleshooting code. Intelligent test automation throughout the DevOps pipeline is solving both challenges and introducing quality engineering to enterprise software startups setting themselves apart in this highly competitive field.
Friend of mabl DataRobot is an enterprise AI platform that makes it easy for organizations to leverage the power of artificial intelligence. Their platform democratizes data science by automating data analysis, giving businesses the power to prepare, build, deploy, and maintain AI-driven applications at scale. The sheer size of the DataRobot platform - over 2.18 billion data models created and counting - rendered other legacy test automation tools too labor-intensive with the excessive maintenance required or were unable to effectively test advanced features.
Like many B2B technology startups, DataRobot is constantly expanding product capabilities, frequently introducing new features and functionalities to better serve their customers. Rather than forcing teams to build a quality strategy from scratch when working on a new domain, intelligent test automation with mabl allows them to import reusable flows and customize with JavaScript snippets to quickly begin testing.
Reusable flows bundle commonly used sequences into flows that can be inserted into any test. Tests can include any number of unique and reusable flows or use a flow multiple times within a single test. To avoid tests breaking as flows are updated, mabl automatically pushes changes to all tests containing the base flow. Reusable flows reduce the time needed to create tests for frequently tested features, or for new features that need to be delivered quickly.
As soon as tests are created, however, they’re at risk of breaking from product changes, leaving testers at square one. Mabl addresses this challenge with auto-healing features that can adapt to code changes with little to no human intervention. As a part of the first training session, mabl users walk through typical customer journeys, collecting dozens of identifiers for each unique element. Every time mabl runs a test and interacts with an element, it collects attributes that it uses to find the element next time and track changes over time. mabl tracks over thirty distinct attributes, like text, CSS classes, data-test-id, and other information like location and size on the page. With these elements, mabl is trained to adapt to changes in code seamlessly, compared to other automated testing tools that would break and require a QA team member to intervene.
To thrive in a competitive field, enterprise technology startups like DataRobot need solutions that enable them to bring cutting edge products to market quickly without compromising on quality or the user experience. Advanced features like reusable flows and auto-healing are just a couple of examples of valuable capabilities that save critical time and effort while enabling QE teams to spend more time focusing on priorities like exploratory testing.
Quality engineering teams at B2B software companies are in a race to meet rising expectations for product innovation and a seamless user experience. QE teams need testing tools that allow them to quickly and easily automate tests without worrying about managing a barrage of maintenance tasks every time the product changes. With quality engineering enabled by intelligent test automation, enterprise technology companies like DataRobot are building better, more innovative products at a faster pace.
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