Why Most Activity Businesses Fly Blind

Here is a question that makes most activity business owners uncomfortable: what was your average class fill rate last term? Not a rough guess. The actual number.

If you cannot answer that immediately, you are in good company. The vast majority of children's activity providers, from swimming schools to dance academies to football clubs, make their biggest decisions based on instinct, anecdote, and whatever they can remember from the last few weeks. They know which classes feel busy and which feel quiet. They have a sense of whether bookings are up or down. But they rarely have the numbers to back it up.

This is not a criticism. When you are teaching classes, managing staff, fielding parent enquiries, and handling everything else that comes with running an activity business, sitting down to analyse spreadsheets feels like an impossible luxury. The problem is that instinct, however well-developed, leads to predictable mistakes.

You keep running a Tuesday afternoon class because it has always been there, even though it has been at 50% capacity for two terms. You set prices based on what competitors charge rather than what your costs and demand actually warrant. You spend money on Facebook adverts without knowing whether they bring in families who stay or families who try one term and disappear.

Data does not replace your expertise. It sharpens it. And the good news is that you are probably already sitting on most of the data you need.

Five Decisions Data Should Inform

You do not need to become a data scientist. You need data to help with five specific types of decision that every activity business faces regularly.

1. Pricing

Most providers set prices by looking at competitors and adding or subtracting a few pounds. This ignores the two things that actually matter: your costs and your demand.

If your Monday 4pm gymnastics class has a waitlist of 15 families and your Monday 5pm class has eight empty spaces, that is a pricing signal. The 4pm class could likely bear a modest price increase without losing families. The 5pm class might benefit from an introductory offer to fill those spaces.

Track your revenue per available session hour. This single metric tells you which time slots are generating strong returns and which are underperforming. A class that is 60% full at a higher price point might generate more revenue than one that is 90% full at a bargain rate.

2. Scheduling

Your timetable should be shaped by demand, not by habit. Data tells you which days, times, and age groups have unmet demand and which are oversupplied.

Look at your waitlist patterns. If you consistently have waitlists for under-3s on weekday mornings but empty spaces for the same age group on Saturday afternoons, that is a clear signal about what parents want and when. Look at your drop-off rates by time slot. If your 6pm Wednesday class loses 30% of participants each term while your 4pm Thursday class retains 90%, the scheduling itself may be the problem.

3. Marketing

Without data, marketing spend is guesswork. With data, every pound has a measurable return.

Track where your enquiries come from, whether that is Google search, Instagram, word of mouth, school leaflets, or something else. Then track which of those enquiries convert to enrolments, and crucially, which of those enrolments stick beyond the first term. A marketing channel that brings in 50 enquiries but only 5 long-term families is far less valuable than one that brings in 15 enquiries of which 12 become regulars.

Your cost per acquisition (total marketing spend divided by new enrolments) and customer lifetime value (average revenue per family over their entire time with you) together tell you exactly how much you can afford to spend to win a new customer.

4. Retention

Acquiring a new family costs between five and seven times more than keeping an existing one. Yet most activity businesses spend far more time and money on acquisition than retention.

Your data can tell you exactly when families are most likely to leave (the end of the first term is the highest-risk period for most providers), which classes have the best and worst retention, and whether there are patterns in the families who churn. Perhaps families who miss more than two consecutive sessions are three times more likely to cancel. That is an actionable insight: follow up after the second missed session, not after they have already gone.

5. Expansion

Opening a new venue, adding a new activity, or launching in a new area is the biggest financial risk most activity businesses take. Data turns that risk from a leap of faith into a calculated decision.

Your waitlist data tells you where demand exceeds supply. Your postcode data tells you where your current families are travelling from, and therefore where a more convenient venue might capture new demand. Your retention data by activity type tells you which offerings have the strongest long-term appeal.

From Spreadsheets to Dashboards: The Evolution

Most activity businesses go through a predictable data journey, and understanding where you are helps you take the right next step.

Stage 1: Paper and Memory

Attendance is taken on a register. Payments are tracked in a cash book or basic accounting software. The owner knows what is happening because they are present at most sessions. This works when you run fewer than ten classes a week. It falls apart the moment you grow beyond that.

Stage 2: Spreadsheets

Someone creates a spreadsheet. Then another. Then a booking spreadsheet, a payments spreadsheet, a staff rota spreadsheet, a waitlist spreadsheet. Each lives on someone's laptop or in a shared drive. They get out of sync. Nobody is quite sure which version is current. Extracting meaningful insights requires hours of manual work that nobody has time for.

Stage 3: Booking Software

You adopt a booking or management platform. Attendance, payments, and enrolments are now in one place. This is a significant step forward because the data is at least centralised and accurate. But most providers at this stage only use the software for operations, not for intelligence. They can look up an individual family's payment history, but they cannot easily see their overall retention rate or revenue trends.

Stage 4: Integrated Intelligence

This is where the real value begins. Your management platform does not just store data; it analyses it and surfaces insights proactively. Instead of asking "what is our fill rate?", the system tells you "your Tuesday classes are consistently underperforming and here is what the data suggests you do about it." AMES is built for this stage, providing daily insights, suggested actions, and risk signals without you having to run a single report.

Real Examples of Data-Driven Decisions

The Swimming School That Raised Prices and Grew

A swimming school in the Midlands had been charging the same rate for three years, afraid that any increase would drive families away. When they looked at their data, they discovered that their fill rate was 96%, they had waitlists on 80% of their classes, and their retention rate was 91%. The demand was overwhelming. They raised prices by 12% and lost fewer than 3% of families. The waitlists absorbed the few departures within weeks, and annual revenue increased by over nine percent after accounting for the small drop in numbers.

The Dance Academy That Cut a Popular Class

A dance academy ran a street dance class that was always full. It looked like their most successful offering. But when they analysed the data, they found that street dance had the lowest retention of any class: 40% of participants left after one term, and the cost of constantly replacing them through marketing was significant. They replaced the street dance slot with an additional ballet class, which had a waitlist and 88% term-on-term retention. Revenue per slot increased by 35% within two terms.

The Football Club That Found Its Best Postcode

A community football club mapped the postcodes of their participants and discovered that 60% of families were travelling from three specific areas, despite the club being located near several other residential areas. They ran a targeted leaflet campaign in those three postcodes only, at a fraction of the cost of their previous blanket marketing. The campaign generated twice the enrolments at one-third the cost.

Getting Started: What to Track From Day One

If you are not currently tracking anything systematically, start with these five metrics. They require no specialist tools, just consistent recording.

Class fill rate: How many enrolled participants versus capacity for each class, each week. This is your most fundamental health metric.
Attendance rate: Of those enrolled, how many actually attend? A class with 20 enrolled but only 12 attending has a different problem from a class with 12 enrolled and 12 attending.
New enquiries per week: How many new families contact you, and where did they hear about you? Even a simple tally with a source field gives you marketing intelligence.
Term-on-term retention: Of the families enrolled this term, how many re-enrolled last term? Express it as a percentage. This is the single strongest predictor of long-term business health.
Revenue per class per term: Total revenue from each class over a term. This tells you which classes earn their timetable slot and which do not.

Record these consistently for two terms and you will have enough data to start making genuinely informed decisions. With a platform like AMES, these metrics are calculated automatically in real time, along with trend analysis, anomaly detection, and suggested actions based on what the data reveals.

Data does not tell you what to do. It tells you what is actually happening, which is often very different from what you think is happening. The decisions are still yours, but they are built on reality rather than assumption.

Moving Forward

The gap between activity businesses that grow sustainably and those that plateau or struggle is increasingly a data gap. Not because data is magic, but because the businesses that track, measure, and respond to their numbers make fewer expensive mistakes and spot opportunities faster.

You do not need to transform overnight. Start with the five metrics above. Be consistent. Review them monthly. Within a term, you will wonder how you ever made decisions without them.