What kind of data should an IT company analyse before launching a new feature?, Who should analyse data in a tech company: developers, product managers, or analysts? Why?, Can analysing too much data slow down decision-making?, What type of user feedback is most useful for improving an app: complaints or suggestions?, How should a company react to negative user feedback online?, Do users always know what they really want? Why / why not?, What can usage statistics show that surveys cannot?, Can usage statistics ever be misleading? Give an IT-related example., Which is more important for you: what users say or what usage statistics show?, If market research shows mixed results, what should a company do next?, Are mixed results more common for innovative products or simple ones? Why?, Have you ever been part of a project with mixed results? What happened?, What could be a key insight from low usage of a popular feature?, Can a small piece of data lead to a key insight? Why?, Who should decide which insight is the key one?, Is it better to roll out a feature slowly or all at once? Why?, What risks can appear when a company rolls out a feature too quickly?, Should all users get new features at the same time?, Why are early adopters important for IT companies?, What kind of users usually become early adopters?, Would you trust early adopters more than average users? Why / why not?, How can user behaviour show problems that users don’t talk about?, What user behaviour might indicate confusion or frustration?, How can companies change user behaviour without annoying users?, What is the biggest pain point for users of complex software?, Can a product have too many pain points and still succeed?, How can companies clearly identify a real pain point?, Is a data-driven decision always the best decision? Why / why not?, When should a company trust experience instead of data?, Can data-driven decisions reduce creativity in IT products?.
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