Hello everyone
I am developing a data visualization project using Tableau with a hotel dataset that contains booking records for city and resort type of hotels, and related data such as guest details, pricing, and cancellations, to name a few.
I have drafted 4 visualizations which will eventually be consolidated into a single dashboard.
Please visit the visualization link here.
The visualizations were developed to answer these research questions (in the same order):
Q1. How do cancellation rates differ by market segment and deposit type for City Hotel and Resort Hotel?
Q2: How do booking volume and average length of stay change throughout the year, and does the pattern differ by distribution channel and customer type?
Q3: What geographic patterns can be identified in cancellation rates across guests’ countries of origin, and what booking characteristics are associated with these patterns?
Q4: What booking profiles can be identified based on lead time and waiting-list duration, and how do they differ by room assignment, customer type, repeat-guest status, and number of special requests?
For each research question (visualization), may I request your feedback on (one or more of) based on these questions?:
A. Is the chart type appropriate? If not, could you please recommend a more appropriate one along with what measures to use?
B. Do any of the colors/color scheme need to be changed?
C. Do you recommend mark labels? If so, for all, or for high/low only?
D. Hovering over the visualization shows more details but does it look like cognitive overload? Would you recommend splitting the visualization into two or more instead?
E. Do you have (any) other feedback or best practice using data visualization principles to improve this?
Thank you very much in advance!
#Tableau Public #Tableau Desktop & Web Authoring #Best Practices #Reports & Dashboards
Your hotel booking data visualization project covers great foundational research questions, especially comparing cancellation rates across market segments and analyzing seasonal length of stay patterns. To give you constructive feedback on your draft dashboard components, your chart types for market segment comparisons and seasonal trends generally work well, though ensuring consistent color coding between city and resort hotels will help prevent visual clutter.
When presenting cancellation rates by country of origin, consider using a filled map or a sorted horizontal bar chart rather than trying to cram too many data points into a single view, as high-density hover details can sometimes lead to cognitive overload. Splitting complex geographic and lead-time distributions into smaller, focused panels will make the underlying trends much easier for your audience to digest at a glance.
Finally, to improve overall data storytelling, apply mark labels selectively to extreme high and low outliers rather than cluttering every single data point. You can also use tooltips strategically to surface guest details and special request counts on demand, keeping your primary views clean while still providing deep exploratory depth for anyone reviewing your research.