Dynamic Pricing vs Variable Pricing: What Attraction Operators Need to Know

The Great Pricing Confusion

Walk into any attraction industry conference and mention "dynamic pricing." Half the room will nod knowingly, picturing their weekend vs. weekday price tiers. The other half will think of airline-style algorithmic pricing that changes by the minute.

Both groups are talking about completely different things. And this confusion is costing operators real money.

The truth: Most attractions claiming to use "dynamic pricing" are actually using variable pricing. There's nothing wrong with variable pricing — it's a solid strategy. But calling it dynamic pricing means you're missing out on what true dynamic pricing can actually do for your revenue.

Let's clear up the confusion once and for all.

What is Variable Pricing?

Variable pricing is straightforward: you set different prices for different times or days, and those prices stay fixed until you manually change them.

Examples of variable pricing:

Weekends are $28, weekdays are $22
Holidays are $35, regular days are $25
Peak season (June-August) is $30, shoulder season is $20
Morning sessions are $18, afternoon sessions are $25

This is what most FECs, trampoline parks, and water parks do today. You might adjust these tiers once a season, maybe more frequently during busy periods. But the prices themselves are predetermined and static within each tier.

Variable pricing works because:

It's simple to implement and explain to customers
It captures some of the demand difference between busy and slow times
Customers can plan around it — they know Saturday costs more than Tuesday
Staff can quote prices without checking a system

Variable pricing leaves money on the table because:

It doesn't respond to actual demand in real-time
A rainy Saturday might command the same premium as a sunny Saturday
Sessions filling up fast pay the same as sessions struggling to sell
You're guessing at the optimal price for each tier

What is TRUE Dynamic Pricing?

True dynamic pricing uses algorithms to adjust prices continuously based on multiple real-time factors. Think airlines, hotels, and Uber.

The key difference: Instead of setting "weekend = $28" and walking away, a dynamic pricing system might price one Saturday session at $24 because it's raining and bookings are slow, while pricing another Saturday session at $34 because it's the first sunny weekend of spring and it's 80% full three days out.

Factors true dynamic pricing considers:

Time of booking: How far in advance is the customer booking? Early birds get better rates.

Historical data: What happened on this date last year? Last month? During similar conditions?

Booking curve: How fast is this session filling compared to typical patterns?

Weather forecasts: For outdoor attractions especially, weather is a massive demand driver.

Day of week and seasonality: Yes, this is part of it — but as one input among many.

Current capacity: 80% full sessions price differently than 20% full sessions.

Local events: School breaks, holidays, local festivals, competitor events.

Competitor pricing: Where available, what are similar venues charging?

The algorithm weighs all these factors simultaneously, updating prices in real-time or near-real-time to optimize for your goals (usually revenue maximization or demand smoothing).

A Real Example: Two Saturdays

Let's compare how variable pricing and dynamic pricing handle the same situation.

The scenario: A trampoline park with 100 spots per session.

Variable Pricing Approach

Saturday afternoon = $28. That's the rule. End of story.

Saturday June 15, sunny, first weekend of summer break: 100 spots sell out by Tuesday. You made $2,800. But you could have charged $35 and still sold out.
Saturday June 22, rainy, family reunion weekend: Only 60 spots sell. You made $1,680. If you'd priced at $22, maybe you'd have sold 85 spots for $1,870.

Total from two Saturdays: $4,480

Dynamic Pricing Approach

The algorithm sees different conditions:

Saturday June 15: Booking curve is steep, weather forecast is perfect, it's first weekend of summer break. Price starts at $28 and climbs to $35 as session fills.
Saturday June 22: Booking curve is flat, rain forecast, competing events in town. Price holds at $24 — but this only works if paired with marketing to drive traffic. On rainy days, people may not even visit your website, so a targeted email or social push announcing the lower rate is essential.

June 15: 100 spots at average $32 = $3,200
June 22: 80 spots at $24 = $1,920

Total from two Saturdays: $5,120

That's 14% more revenue from the same two sessions. Across a season, this adds up fast.

Is Dynamic Pricing Right for Your Park?

Here's the honest truth: Dynamic pricing is not for everyone.

Dynamic pricing optimizes your funnel — it doesn't fill it. If your main problem is that not enough people know about your park or want to visit, dynamic pricing won't help. You need marketing first.

Dynamic pricing makes sense if:

You regularly hit 70%+ capacity on peak days
You have sessions that sell out (or nearly sell out) frequently
Some days are overrun while others are empty
You have at least 12 months of booking data to analyze

Focus on marketing first if:

You struggle to fill sessions even on weekends
Peak days aren't consistently busy
Your main challenge is awareness, not pricing
You're a new venue still building an audience

Think of it this way: Dynamic pricing helps you get more value from customers you're already attracting. If you're not attracting enough customers, raising prices won't help — it'll just make empty sessions more expensive.

Best Practices That Actually Work

If you decide dynamic pricing is right for your park, follow these principles:

1. Prices Only Go Up

A customer who books two weeks in advance should always pay less than someone booking day-of. This rewards early planners and creates urgency without punishing your loyal guests.

Never drop prices below what earlier bookers paid. If someone sees their neighbor got a better deal by booking later, you've destroyed trust.

2. Full Transparency

Show customers a calendar with prices for each day. Let them see that Saturday is $32 but next Tuesday is $18. Price-sensitive families will choose the cheaper day. Families who can only visit Saturday will pay the premium. Everyone wins.

The worst thing you can do is surprise customers with higher prices after they've started booking. Lock the price once they begin checkout.

3. Give Customers Choice

Dynamic pricing isn't about extracting maximum dollars from every customer. It's about matching price-sensitive customers with lower-demand times and extracting premium from convenience-focused customers.

When a family sees "Today: $32" and "Next Saturday: $24," they're making an informed choice. Some will wait. Others will pay for convenience. Both feel good about their decision.

4. Set Floor and Ceiling Prices

You should always have minimum and maximum prices. Even on the slowest Tuesday, you probably don't want to go below $15. Even on the craziest holiday weekend, $35 might be your ceiling.

The algorithm works within your bounds. You stay in control.

Why Most "Dynamic Pricing" Systems Fail

Here's the dirty secret: Most systems that claim to offer dynamic pricing aren't really doing it right.

The Correlation Trap

System raises prices on busy days. Revenue goes up. Success, right?

Not necessarily. Busy days are busy regardless of price. If you raise prices on days that would have sold out anyway, you can't prove the price increase caused any improvement.

This is the correlation trap. Busy day + higher price + more revenue ≠ higher prices caused more revenue.

The Missing Control Group

Proper A/B testing requires a control group. At least 10-15% of your sessions should use standard pricing as a baseline, while the rest use dynamic pricing. This ensures you're not destroying your conversion rates — you need enough control data to prove the algorithm is actually working.

No other dynamic pricing system in the attractions industry does this. Some use overly simplistic algorithms — like "first 10 tickets at $15, next 10 at $17, next 10 at $19" — which isn't true dynamic pricing at all. Others are more sophisticated and incorporate multiple data points, but still don't maintain control groups to verify they're not pricing themselves out of the market. Without a baseline comparison, you'll never know if higher prices are actually increasing revenue or just killing conversions.

Conversion Rate Blindness

Revenue went up 5%? Great. But did conversion rate drop 10%? If so, you're losing long-term customers.

Good dynamic pricing tracks both revenue AND conversion. If higher prices scare away bookings, you need to know.

The "Flip the Switch" Mentality

Proper dynamic pricing implementation takes weeks, not hours. You need to:

Analyze 12+ months of historical booking data
Identify patterns and demand drivers
Configure algorithm parameters for your specific venue
Set up A/B testing infrastructure
Monitor results and iterate

Anyone selling "just turn it on" dynamic pricing is selling snake oil.

How to Implement Dynamic Pricing Properly

If you're serious about dynamic pricing, here's the roadmap:

Prerequisite: The Right Booking System

Before anything else, you need a booking system that can actually support dynamic pricing. This means:

API access to push new prices for each session in near real-time
Data feeds that provide visits, purchases, conversion rates, and booking patterns
Session-level granularity so prices can vary by specific timeslot, not just by day

Warning: Most legacy booking systems can't do this. They were built for static pricing and lack the infrastructure to support real-time price updates or granular data extraction. Even if a third-party dynamic pricing provider wanted to integrate, there's often no API to connect to. Before investing in dynamic pricing, verify that your booking system can actually support it — or be prepared to switch systems first.

Phase 1: Data Analysis (2-3 weeks)

Before touching prices, analyze your existing data:

What's your booking curve look like? How far in advance do most guests book?
Which sessions consistently sell out? Which struggle?
What external factors correlate with demand? Weather? School schedules? Local events?
What's your current price elasticity? How do bookings change when you run promotions?

You need at least 12 months of data to capture full seasonality patterns.

Phase 2: Strategy Definition (1 week)

Define your goals:

Maximize revenue per session?
Smooth demand across the week?
Fill specific underperforming sessions?
Some combination?

Your goals determine how the algorithm behaves.

Phase 3: Algorithm Configuration (1-2 weeks)

Configure the pricing rules:

Set floor and ceiling prices for each product/session type
Define which factors to include (weather? booking curve? day of week?)
Set sensitivity parameters (how quickly should prices change?)
Create A/B test groups (control vs. dynamic)

Phase 4: Soft Launch (2-4 weeks)

Start with a small percentage of sessions:

Monitor closely for issues
Compare A/B test groups
Gather customer feedback
Adjust parameters as needed

Phase 5: Full Rollout + Ongoing Optimization

Expand to all applicable sessions, but never stop optimizing:

Review results weekly
Adjust parameters based on learnings
Test new factors
Maintain control groups to ensure continued effectiveness

The Bottom Line

Variable pricing is fine. It's better than flat pricing across all days. Many successful parks use it.

But it's not dynamic pricing. And pretending it is means missing the opportunity for true algorithmic optimization.

True dynamic pricing requires:

Real-time responsiveness to multiple factors
A/B testing with control groups
Conversion rate tracking alongside revenue
Proper implementation and ongoing optimization

If you're a busy park with strong demand on peak days and underutilization on slow days, true dynamic pricing can capture 8-15% more revenue.

If you're still building your audience, save your money and focus on marketing first. Dynamic pricing optimizes a funnel — it doesn't create one.

What wakesys Does Differently

We built dynamic pricing into wakesys with these principles:

A/B testing is mandatory: We always run control groups. No more guessing whether price changes actually worked.

Conversion tracking built-in: We monitor booking completion rates alongside revenue. Higher prices that kill conversions get flagged.

Deep data analysis first: We won't flip a switch. Implementation starts with thorough analysis of your booking patterns.

Prices only go up: Early bookers always win. We never undercut previous purchasers.

Full transparency for customers: Calendar views showing prices for each day. Customer choice, not customer surprise.

Dynamic pricing is powerful, but it's not magic. It requires data, discipline, and continuous optimization. We're happy to analyze your booking patterns and tell you honestly whether dynamic pricing makes sense for your park — or whether you should focus on marketing first.

Ready to explore dynamic pricing for your park? Book a demo and we'll walk through your data together.