unitQ, the leading platform empowering companies to take a user-centric, data-driven approach to improving product quality, has announced a new tool — Impact Analysis. Impact Analysis is a first-of-its-kind tool utilizing machine learning enabling organizations to surface critical product quality issues and determine the impact of fixing them.
“Impact Analysis provides our customers with new capabilities to reduce churn rates, make for happier customers and to enhance revenue streams,” says Christian Wiklund, Founder and CEO at unitQ. “Our customers improve their product quality by over 20% after using unitQ for just a month, and with every new tool we build, including Impact Analysis, we should continue to see that number rise.”
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The Impact Analysis tool is cross-functionally built to work across different teams — from support, to product, to engineering and marketing. Impact Analysis surfaces relevant user feedback parsed through proprietary artificial intelligence to identify issues blemishing the customer experience. With Impact Analysis, teams can learn what impacts fixing an issue might have on KPIs like one star reviews, support tickets, brand sentiment and more before taking action.
In addition, Impact Analysis calculates how much an organization’s unitQ Score and Internal unitQ Score could be boosted by fixing customer-surfaced issues. A unitQ Score allows companies to measure product quality against other organizations in the same industry with Apple App Store and the Google Play Store reviews. An Internal unitQ Score, meanwhile, includes the same user feedback as well as additional user feedback from social media such as Twitter, Reddit, internal support applications and a host of other sources.
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