Seasonal Revenue Planning

This guide explains how to build a seasonal revenue planning model for events, functions and venues in Model Reef.

You will:

  • Capture seasonality, event calendars and demand peaks across the year.

  • Link seasonal patterns to event counts, guests and pricing.

  • Connect seasonal revenue to capacity, staffing and cost models.

  • Use scenarios to test different calendars, pricing and utilisation.

Model Reef does not forecast weather or automatically create event calendars. It applies seasonality factors and event assumptions that you define.

When to use this pattern

Use this pattern when:

  • Your event and function revenue is highly seasonal.

  • You have distinct peaks such as holidays, wedding season or corporate year end.

  • Capacity and staffing must be planned around known seasonal patterns.

  • You want a clear link from the calendar to revenue and resource planning.

It can be combined with:

  • Event and Function Profitability Model

  • Staffing Rosters for Events

  • Venue Level Forecasting Pack

  • Build a Seasonality Adjusted Forecast

Architecture overview

Seasonal revenue planning uses:

  • Seasonality drivers

    • Monthly or weekly seasonality indices.

    • Event calendars with spikes for key dates.

    • Day of week and day part patterns.

  • Volume and pricing drivers

    • Events, tickets or guests per period.

    • Package and ticket prices.

    • Promotional pricing during lower demand periods.

  • Capacity and resource links

    • Venue capacity limits.

    • Staffing and roster patterns.

    • Other constraints such as noise, licence or trade hours.

  • Outputs

    • Seasonal revenue curves by venue and event type.

    • Visibility of peak periods and quieter seasons.

    • Inputs into staffing, cost and cash planning.

1

Build a seasonality index for the year

In the Data Library, create a set of seasonality drivers, for example:

  • Monthly Seasonality Index with values such as 0.8, 1.2, 1.5 for low, medium and peak months.

  • Weekly Seasonality for more detailed models.

  • Event specific multipliers for special periods such as Christmas, New Year or local festivals.

Calibrate these indices using:

  • Historical event counts and revenue by period.

  • Known booking patterns for weddings, corporate events or school holidays.

  • Qualitative knowledge from sales and operations teams.

You will use these indices to scale event and guest drivers.

2

Combine base demand with seasonality

Define base demand drivers for each venue and event type, such as:

  • Base Events per Period, for example typical events in a shoulder month.

  • Base Guests per Event.

  • Base Ticket or Package Price.

Then apply seasonality using formulas like:

  • Events per Period = Base Events × Seasonality Index.

  • Guests per Event = Base Guests × Event Specific Seasonality where applicable.

This produces realistic seasonal patterns for event volumes that then feed revenue variables.

3

Map seasonal patterns into revenue variables

Use the demand drivers from the previous step in revenue variables, such as:

  • Revenue - Weddings - Venue A.

  • Revenue - Corporate Functions - Venue B.

  • Revenue - Conferences - Venue C.

Formula examples include:

  • Revenue = Events per Period × Guests per Event × Price per Guest.

  • Revenue = Events per Period × Room Hire Fee, where capacity is not per guest.

If you use promotions or discounts in low demand periods, incorporate those as additional drivers that reduce price or increase volume in targeted windows.

4

Check capacity and operational constraints

Seasonality often interacts with capacity constraints. For each venue, add drivers for:

  • Maximum Events per Period, or per day in busy periods.

  • Maximum Guests per Event or per day.

  • Staff and rostering capacity by day and day part.

Review seasonal revenue outputs against these constraints using charts and reports. Where demand exceeds capacity, you can:

  • Increase capacity by adjusting opening hours, staffing or venue configuration.

  • Move events to different venues or dates in the plan.

  • Adjust demand assumptions downward to reflect real constraints.

This ensures seasonal revenue patterns are operationally feasible.

5

Use scenarios for calendar, pricing and utilisation strategies

Clone the base model into scenario models to test:

  • Different event calendars, such as adding or removing major events.

  • Higher or lower prices in peak and off peak periods.

  • Different strategies for smoothing demand into quieter periods.

  • Changing product mix, for example more corporate events in quieter months.

In each scenario, adjust:

  • Seasonality indices and event drivers.

  • Pricing structures and promotional assumptions.

  • Capacity and staffing assumptions if you plan operational changes.

Compare scenarios using:

  • Revenue by period and season.

  • Utilisation of capacity and staff.

  • Cashflow patterns across the year.

  • Profitability at venue and group level.

Check your work

  • Seasonality curves match historical patterns or realistic expectations.

  • Event and revenue peaks align with known dates and seasons.

  • Capacity constraints are acknowledged and not ignored by demand assumptions.

  • Scenario analysis reflects practical calendar planning options.

Troubleshooting

chevron-rightSeasonal peaks look too extreme or too flathashtag

Revisit indices by comparing with historical data and consider smoothing or capping extremes.

chevron-rightRevenue appears to exceed operational capacityhashtag

Introduce explicit capacity drivers and either cap events or adjust demand to respect them.

chevron-rightToo much effort to maintain detailed seasonalityhashtag

Use a simplified high, medium and low season structure and only apply detailed adjustments for a few key periods such as December or festival months.

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