With 10to8 you have the ability to run reports. These reports are packed with information about your organization(s).
You're able to view this information in the form of graphs, making it easy to view and digest the analytics presented to you. Graphs help you to notice trends and patterns as well as areas in need of attention, and enable you to set and track goals.
This guide explains specifically how to use 10to8's Export Events function to create graphs. For a more general guide on running reports, click here.
SECTIONS:
Waiting Times by Location and Service
How to Create Graphs
To get started, head to 'Reports' > 'Export Events'.
Set a name for the report you'd like to run, and select the date range and the organizations you'd like the report to apply to. Tick all of the desired boxes under 'Fields to include in the report' to ensure that all of the information you're looking for is processed in the report.
To create and include graphs in your report, under the 'Analytics to include in export' section you'll need to select 'Waiting Times by Location and Service' or 'DNAs by Location and Service'.
Then, click 'Run this report'.
Your report will begin generating within the 'Downloads' folder, where you'll be able to track its progress. Your report will continue generating even if you leave the page.
Once your report is complete, the 'Download' button will change from grey to turquoise. Click on it to download and open the file.
Once you've opened the file, use the tabs at the bottom of the spreadsheet to navigate through the different pages of the report.
Waiting Times by Location and Service
The graphs in this type of report detail the time lapse between the booking being made and taking place. This information is particularly useful if you're looking to reduce waiting times.
All data included in the report will be exported into the graph.
See below for some screenshots of example graphs generated by this type of report.
Note: different locations are shown within the graph by colored lines. The more locations your business uses, the more colored lines you'll see.
This example graph shows that approximately 20% of online/phone bookings were created on the same day that they took place, and 50% of the other appointments (which were not assigned to a location) took place more than 28 days after they were booked.
This graph shows the same information as the one above. This graph, however, includes information from the most recent week included in the report.
Again, this graph shows the same type of data, this time using the information from the penultimate week included in the report.
This graph (found in the last tab at the bottom of the spreadsheet) shows how many appointments in the last 60 days were booked and took place within 1 working day.
DNAs by Location and Service
DNAs (or did not attend) may also be known as FTAs (failed to attend) or no-shows. These can be a drain on your organization, so it's crucial to be able to track them and subsequently reduce them.
The graphs generated in this type of report can help you with this. These graphs will display your arrivals and DNAs together in a comparative view.
See below for some screenshots of example graphs generated by this type of report.
The first example graph displays the number of appointments that took place each day, and how many of them were DNAs. Green represents total bookings, whilst red represents DNAs.
This view makes it easy to see whether there are particular days of the month with higher DNA rates.
This graph displays a weekly view of bookings and DNAs, along with clearly labeled DNA percentages.
This graph shows the same information again but in a monthly view. This is useful for looking at a broader range of data.
This slightly different graph displays the total number of bookings by day of the week, along with the number of DNAs that occurred on each day. This information is useful for determining whether certain days suffer significantly more DNAs than others.
This graph displays the number of bookings made alongside waiting times over a specific date range. Ideally, you'd want your bookings to steadily increase and the waiting times to steadily decrease.
This graph shows a weekly view of bookings and the location at which they took place. This information is useful for determining whether certain premises require additional attention, staff, funding or maintenance.
This graph shows you which locations suffer from the most/least DNAs. Locations are color-coded underneath the graph's x-axis.
This graph allows you to compare how many appointments were booked daily at each of your locations. This makes it easy to interpret your most popular locations.
This graph displays the waiting times between appointments being booked and taking place, and at which location appointments took place.
This graph displays an average of waiting times by location.
Troubleshooting
My graphs are blank. What should I do?
Try clicking 'File' > 'Open with Google Sheets'. Alternatively, press F9 on your keyboard to recalculate the cells in the spreadsheet.
The y-axis of the graph shows a date instead of a number. How can I change this?
Click 'Edit chart' in the top-right-hand corner of the graph, and tick the checkbox labeled 'Aggregate'.
Need More Help?
We hope this guide has been useful! If you have any questions, don't hesitate to reach out to our support team who will be more than happy to help.