Automated QA Testing from Live User Data Fully automated, high-coverage end-to-end QA engineering as a software product.SaaS Machine Learning
👍 “The global quality management software (QMS) market is anticipated to reach $13.94B by 2025, compared with $6.34B in 2016. This growth is mainly driven by the increasing expectations of consumers in a more and more competitive market.” Source.
👍What is interesting with the QA software (Quality Assurance) market, is that it was a very “enterprise” one (costly software, complex to install and use), but in the past decade it went toward a democratization with better products which are less expensive and available for an increasing number of businesses (for 🐭and 🐰 and not only for 🐘and 🐳). After the Cloud wave, the AI wave will reinforce this trend: better and less expensive QA products.
👍To be honest, what I really like about ProdPerfect is its concept based on the use of live data around real user behavior to automate QA testing. Traditionally QA tests are prepared and run by human agents. It’s not only a difficult job, but it’s also very hard for QA teams to cover all types of tests and user behavior. Automation in this case makes a ton of sense to improve testing coverage as well as to make QA agents’ life better (very good use case for ML imo).
👎My main concern is around competition. As I mentioned in the market section, the past decade has seen the rise of better QA software, such as RainforestQA or Tricentis, which rode the “SaaS wave”. These companies are well positioned to add a machine learning / automation component to their existing product (they are already doing it). They have also accumulated customer data that gives them a head start.