Overview

This page will provide you with every-day examples of user cases.

User Cases

Regional manager

In this case, we will follow Sarah Jonson who is a regional manager for Stockholm at Fitness AB. She is trying to find out if there are any specific times during the day that their customers are working out more. She wants to see if there is any difference between gender and, she is interested in three specific age groups 20-29, 30-39, and 40-49. The period she wants to see is the first 5 months in 2022.

Sarah logs in to the BRP System and goes down to reports. She opens the report that says, “Visit hours”.She starts by selecting the year-month 2022-01 to 2022-05  in the top filter pane. Then she selects Region Stockholm. After that, she selects the three age groups 20-29, 30-39, and 40-49. Now she sees a heat map and line graph over the weekdays and hours of the day. She can now easily see that Monday to Thursday between 16:00 and 20:00 and Friday between 16:00-18:00 seem to be primetime during the week. When it comes to the weekend people seem to do more training between 09:00 and 12:00.

Open

Now Sarah wants to select one facility to see how it looks by gender for a specific gym. In the “Facility” filter pane on the left side, she selects “Body Zone Fitness Center”.

First, she sees an overview that includes all genders. She now starts by selecting “Female” in the gender filter pane. Two-time stamps have a darker blue than others meaning that females are working out more frequently on Wednesdays between 17:00-19:00. Now Sarah deselects female and then selects male instead. Here we can see that Mondays are the most popular day to workout. The most popular time is between 17:00-20:00. At last, Sarah deselects males and selects others. She can read that the gender group “Others” are working out Tuesdays between 19:00-21:00 and Thursdays between 19:00-20:00. For Sarah, this is valuable information on how to learn more about her customer’s working out sessions. To understand her customers and conclude maybe marketing campaigns etc. 

Gym owner

Learn more about gym members

Jens Larsson is a gym owner at Transform Fitness in the region “Stockholm”. He wants to follow up on his membership development last year. Jens is logged into BRP Systems and navigates to the report section and opens the “Members Report”.First of all, Jens starts by making a few selections in the filter pane on the top.

• Facility: Transform Fitness

• Region: Stockholm

When Jens has made his selection, he can now start to analyze the numbers in the report. First Jens is noticing that the member development decreased between 2020-01 to 2021-07 with the lowest point of members OB 2021-03 (3607 members). Jens can look back and see that covid-19 did affect the number of members pretty much. As the restrictions decrease and the vaccination rate increases, the members start coming back to the gym and in August/September 2021 the number of members increased by more than 200 people, Jens is very happy with that.

Open

The report also shows that the three biggest age groups that are working out at Transform Fitness are 20-29, 30-39, and 0-19. Jens can read that 36,3% is “female” and 63,5% is “male”.If Jens wants to, he can click on e.g., Female in the “Gender Distribution” pie chart to see the trend and age distribution based on females. Jens removed the female selection by clicking on the x-mark in the selected pane in the top.

Next up Jens wants to learn more about the trends of his members. Therefore, he navigates to the report called “Members Trend”.In this report, Jens can see “new and terminated memberships”. He can quickly understand that in both November 2020 and 2021 there was a high peak of members that terminated their membership. This is a valuable insight for Jens and the marketing department.  The terminated membership caught Jens’s attention and he wants to get more insight, so he navigates to the next report called “Terminated memberships”. 

Jens is curious to see what kind of members did terminate their memberships in November 2020 and 2021. To learn more about those members, Jens first needs to make some new selections. He selects in the “Year/Month” filter pane 2021-11 and 2020-11.Now Jens can start to analyze what type of members choose to terminate their membership for the selection he made. It can easily be seen that about 62% of the members that quit are male.  

Now Jens wants to learn more about his member’s behavior. He navigates to the report “Group Activities Products”.

A quick overview shows that the group activities have an occupancy of 45,3%. It’s also clear that females are more likely to participate in group activities and it’s more popular in the age 20-29. This insight is very good for Jens. If he could get more to participate, in group activities and from older age groups this will affect the occupancy and, in the end, the gym will make more money. 

Learn more about the usage of resources

Next up Jens wants to analyze how his gym instructors are doing, how much schedule time they have versus working time, and how much revenue they generate. Jens also wants to know what products are selling best to maybe adjust the range of products the gym is selling. Last of all he wants to see what type of products are booked mostly. Jens starts by making his selections.

• Facility: Transform Fitness

• Region: Stockholm

Jens navigates to the report named “Service Booking – Resource”. First, Jens gets an overview where he can see the top 10 products that are booked in the top right corner. It could be PT55 min, Squash 60 min. Second, in the right-down corner, Jens could see what kind of resources have been booked most. E.g., “Squash court 1” or “PT - Liza Wellness”. 

To the left, Jens can view tables and a pivot table of “Booking Resources” for his gym. Here he can learn about how much that is booked, compare it to last year, and see revenue for this year and compared to last year.

Jens expands the personal row and he gets a list of different resource bookings of his employees. The list could be “Group instructor”, “Cycling instructor”, “PT”, “Tennis instructor”, “Group training facility”. Jens expands the PT row and gets a list of his employees that has been booked for a PT session. He can compare the numbers for this year with last year and see how much revenue each PT has added to the gym.

Jens now navigates to the “Service Booking – Product” report. He wants to find out what products are selling best in the gym. He expands the pivot table and sees a list of his categories. Then he navigates deeper down to get more detailed information on the product level. He can see that the cafe sells a lot of soft drinks and here he can drill down more to see what products are selling and what products are not selling and maybe should be removed from the product line. When Jens clicks around a bit, he can see that they offer both PT 25 min and PT 55 min but that the first option with PT 25 min just been booked a handful of times last year. But PT 25 min is booked more frequently. This is good information to understand the customers and their behaviors when it comes to buying help from PT.

The last thing Jens wants to look at is how the usage of the resource is. How many hours are his employees scheduled and how many hours do different resources are being used? Jens navigates to the report “Service Booking – Usage” Here he will get a quick overview based on his selections. He can see “Planned time”, “Worked Time” and “Resource Usage %”.