Peak Reporting

Floristry is seasonal. Valentine’s Day, Mother’s Day, and Christmas can make or break your year. Peak reporting helps you compare these busy periods year-on-year so you can plan stock, staffing, and logistics with confidence.

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How it works

Peak reporting has two modes: predefined peaks for major holidays, and custom comparison for any dates you choose.

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Predefined peaks

Select a peak period and a year, and the system shows you everything that happened during that window — orders, revenue, products sold, customer behaviour, and more. It also compares each day against your average daily performance for the rest of the year, so you can see exactly how much busier you were. The system tracks six peak periods: Dates are pre-calculated through 2030, so you can always look ahead.

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Custom comparison

Compare any two date ranges side by side. Pick Range A and Range B — the system defaults Range B to the same dates one year earlier, but you can change it to anything. This is useful for comparing:

• This December vs last December
• A promotional week vs a normal week
• Any two periods you want to measure against each other

You can export custom comparisons as a CSV file.

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What you’ll see

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Summary cards

At the top, you get the headline numbers for your selected period:

• Total Orders — how many orders you fulfilled
• Total Sales — your revenue for the period
• Average Order Value — how much each customer spent on average
• Average Lead Time — how many days ahead customers placed their orders
• Last-Minute Orders — orders placed less than 24 hours before fulfilment

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Volume impact

This shows how much busier each day of the peak was compared to a normal day. You’ll see ratios like “2.5x busier than average” — meaning you handled two and a half times your usual daily volume. The average is calculated from the rest of the year (excluding the peak period itself), so it’s a true comparison.

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Charts and breakdowns

Peak reporting includes detailed charts across three areas: Overview

• Daily Sales & Orders — revenue and volume trends across each day of the peak
• Hourly Order Patterns — when during the day customers are placing orders (useful for staffing)
• Fulfilment Methods — how many went out for delivery vs were collected in-store
• Customer Types — new customers vs returning customers
• Order Sources — where orders came from (website, phone, walk-in, relay)
• Revenue by Customer Type — how much each customer group spent

Demand & Timing

• Popular Delivery Times — which time slots customers requested most
• Last-Minute Orders — what percentage were placed within 24 hours of fulfilment
• Lead Time Analysis — how far ahead customers ordered (days between order and delivery)

Products & Geography

• Best-Selling Products — your top products by quantity during the peak
• Revenue by Category — which product categories performed best
• Order Distribution by Price — how your orders break down across price bands (e.g., £25–50, £50–75, £75–100). Useful for understanding where your sweet spot is and whether customers are trading up
• Geographic Distribution — top postcodes by order volume, revenue, and average order value

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Forecasting

For predefined peaks, the system shows a forecast for the next year based on your historical growth. You’ll see three bars side by side:

• Previous year — what you did last time
• Current year — what you did this time
• Forecast — what the system projects for next year

This helps you plan how many stems to order, how many drivers to schedule, and how much stock to carry.

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Filtering

You can refine your peak analysis with several filters:

• Locations — view a specific shop or all locations
• Order Types — filter by gift, funeral, corporate, or event orders (defaults to gift only)
• Order Sources — filter by where orders came from
• Integrations — filter by connected platforms
• Payment Status — include or exclude unpaid orders (paid and partially paid are shown by default)
• POS Orders — include or exclude walk-in till sales

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Printing and exporting

• Print — click the print button to get a print-optimised view of the full report, with a header showing the peak name and date range
• Export — in custom comparison mode, export the daily data as a CSV file with summary metrics

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How the data is calculated

Peak reporting uses fulfilment dates, not order dates. This means an order placed on February 10 for delivery on February 14 counts as a Valentine’s Day order. Cancelled orders are always excluded. By default, only paid and partially paid orders are included — you can toggle unpaid orders on if needed. The “average day” baseline is calculated from the same year, excluding the peak period itself and applying the same filters you’ve selected.

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Common questions

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What’s next?