Instabug, a fictional food discovery app, conducted a survey of 300 random users about their favorite features. The survey results showed that nearly half of the users preferred online ordering as their favorite feature, with food reviews being the original main feature of the app. By analyzing the data using pie charts and bar charts, Instabug discovered a steady decline in preference for Meal Match, which could be due to bugs or UI updates. A line graph was used to plot the relationship between Meal Match fans and bug reports, showing that the appeal for Meal Match started declining at the same time that bug reports for Meal Match doubled. The analysis also highlighted the importance of gathering contextual details from other sources to piece together the full feedback story. Additionally, Instabug used the NPS survey to gather user insights in their own words, and created a stacked column to combine quantitative scores with qualitative quotes. By combining multiple data sources and visualizations, Instabug was able to gain a deeper understanding of its app performance and user experience.