This project analyzes six months of yoga studio attendance and scheduling data to evaluate how effectively the studio is using its class capacity. The goal of the review is to understand where demand is strongest, where capacity is being wasted, and how class formats and instructor schedules are influencing overall performance.

The output gives studio leadership clear, data-driven visibility into where demand is being constrained, where capacity is being wasted, and what operational levers matter most.

The snapshot is based on six months of studio activity, covering:

181 total classes

2,408 total student visits

All class formats

All instructors

All time-of-day windows

The analysis focuses on three core dimensions:

Demand by class type

Demand by time of day

Instructor utilization

Across all classes, the studio averaged 63.4% seat utilization.

This means that roughly one-third of available class capacity went unused over the six-month period.

This does not suggest low interest in the studio. It indicates that demand is unevenly distributed across the schedule.

Average fill rate by time slot:

Evening: 80.8%

Midday: 48.7%

Morning: 43.8%

Evening classes operate near capacity, while morning and midday classes consistently run less than half full. This imbalance suggests that demand is being constrained during peak hours while lower-demand time slots continue to absorb fixed operating costs.

Average fill rate by format:

Vinyasa: 69%

Yin: 64%

Gentle Flow: 61%

Power Yoga: 58%

Vinyasa and Yin demonstrate the strongest demand. Power Yoga and Gentle Flow underperform relative to the rest of the schedule. This suggests the current class mix may not be optimally aligned with student preferences.

Instructor performance based on class fill rates and total students:

Maya: 69% fill rate, 623 students

Lily: 64% fill rate, 741 students

Emma: 61% fill rate, 596 students

Chris: 58% fill rate, 448 students

Maya and Lily consistently teach higher-demand classes, while Chris’s classes run with more empty seats. This pattern points to scheduling placement rather than instructor quality.

The studio has strong underlying demand, but that demand is not evenly distributed across time slots, class formats, or instructors.

High-performing classes and instructors are concentrated in limited windows, while lower-demand classes occupy capacity during less optimal times. This leads to artificial sell-outs in some areas and wasted capacity in others.

When demand and scheduling are misaligned, studios experience:

Missed revenue in peak windows

Underutilized instructors

Empty seats during low-demand periods

Lower revenue per class than the market supports

This snapshot makes those patterns visible so decisions can be made deliberately rather than by intuition.

This deliverable provides:

Objective performance visibility

Demand and capacity patterns

Instructor and class utilization insight

A clear operational baseline

It does not include schedule changes, pricing changes, or implementation. 

It is designed to support better decision-making.