Better visualizations enable better—and faster—decision-making. After spending hundreds of hours in client data, we’ve developed some charts to help us quickly understand what’s happening, and what adjustments we should make. These are a few of them.
In-Market vs. Out-of-Market Traffic | 100% Stacked Area Chart
What percent of website visitors are visiting while they’re inside our market vs. outside our market? Or what percent of revenue comes from people in those different areas? Understanding what percent of our visitors are shopping before or during their trip—and how that changes over time—can help us tailor our messaging on the website and in ads. It can also be a potential indicator of gain or loss of local search visibility.
How To Create It
Determine which regions are in-market for you. In Google Data Studio, in your Google Analytics data source, create a custom field that assigns a value of In Market or Out of Market based on the region the traffic came from. Use that field as the breakdown dimension in your 100% stacked area chart.
Bonus: Conversion Rate, $/user, $/transaction, and More
Once you’ve defined your market location dimension, you can use it for additional reports.
Multi-Year Traffic or Revenue | Line Charts With Breakdown Dimensions
Typical charts provide year-over-year comparisons, but what if last year isn’t a good baseline? For many of our traffic and revenue charts, we’ve switched to 4-year versions. It’s also possible to remove years that aren’t relevant, if you want to get rid of the noise.
How To Create It
When you create your line chart, choose a 4-year time span. Use month as the date dimension and year as the breakdown dimension. Turn off any date comparisons, since you’re creating your own comparison.
Unsold Capacity Value | Heatmap
We previously showed how to create a heatmap showing capacity utilization. While this is helpful, it can create some false positives or false negatives, if capacity was low for a given time slot. For example, if we opened just 10 seats in all of August for the Sunday 9 am time slots and filled 6 of them, it looks like we have a big problem on Sunday mornings; but we may have left 10x the revenue on the table during the 11 am Saturday slots, where we filled 80% of seats but had significantly more capacity.
For this reason, we also visualize unsold capacity value (or, unrecognized revenue).
How To Create It
See our tutorial on Visualizing Tour Capacity. Add another field to your underlying data that multiplies the unsold seats by the average seat price. In your existing pivot table or a new one, use that new field.
Paid vs. Non-Paid Traffic | 100% Stacked Area Chart
How dependent are you on paid traffic?
How To Create It
In Google Data Studio, in your Google Analytics data source, create a custom field that assigns a value of either Paid or Non-Paid based on the default channel grouping. Use this as the breakdown dimension in your 100% stacked area chart.
