Anjali Ahuja | Leveraging User Feedback: Combining User Research and Data Science to Measure and Improve UX

As organizations scale, user feedback becomes increasingly important to inform product decisions and measure the impact of work in UX. We get this question all the time from our product leaders- how do we know our product is improving? How…

Anjali Ahuja | Leveraging User Feedback: Combining User Research and Data Science to Measure and Improve UX

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As organizations scale, user feedback becomes increasingly important to inform product decisions and measure the impact of work in UX. We get this question all the time from our product leaders- how do we know our product is improving? How can we measure improvements in UX over time? At Salesforce, we’re building various in-app feedback mechanisms to hear directly from our users. Primary ways of consuming feedback introduced selective attention bias- product managers often only listened to very negative feedback or feedback related to a feature they own. This created a false sense of understanding of what issues there are in the product and how we can redesign elements to improve UX. By combining data science methods with user research, we’re able to generate more objective insights that feed directly into the design and planning process. The success story of in-app feedback at Salesforce proves how necessary it is for UX to collaborate openly across the company to inform design decisions and get a more holistic understanding of users. I’ll be covering a few case studies on specific UX asks at Salesforce, and how we took a multidisciplinary approach into understanding user feedback and implementing it in the product.

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