Atlas9 Revenue & Booking Dashboard

15-min slot-level bookings · monthly revenue · ticket mix · P&L revenue crosswalk · comps treatment

Date Range (applies to all sections)

Quick:

1. Monthly Attendance + Revenue

Monthly Revenue & Attendance

Bars = realized revenue across all Rezdy orders (card + cash + invoice + ACH/wire) — tickets, catering, rentals, gift vouchers, annual passes. Line = visit pax only (catering / rental pax isn't real attendance). Gap between bars and line is your B2B / non-visit revenue.

Average Realized $ per Visit (monthly)

All-orders realized revenue ÷ visit pax, per month. Climbs in B2B-heavy months (catering / rental dollars without proportional visits) and drops with discount-heavy weeks (Half Off Tuesday, promo events).

2. Ticket Revenue by Type

Tickets by Tier (monthly, stacked)

Per-tier ticket counts from int_rezdy_ticket_tiers. Z-scoped to person-bearing products (`is_visit OR is_pass`). Annual passes are shown separately below since they're tracked as a product, not a tier.

Realized $ per ticket by tier

Face value ÷ tickets for the selected range. Hero / Senior / Child / WYN County all carry built-in discounts vs. Regular. Special-Event tiers (Prom, CINEMORPHIA, NYE) command a premium.

Ticket Tier Summary Table

Selected date range. Regular = standard adult; Hero = military/first-responder/EMS; WYN County = Wyandotte County resident discount.

3. Revenue by Rezdy Product Bucket

How Rezdy organizes revenue (what these buckets mean)

Every Rezdy order is assigned to a single bucket based on its primary (highest-value) line item, with a tie-breaker that prefers Catering / Rental / Event lines over Add-on lines. Each bucket is a grouping of Rezdy products that share a sales pattern:

Two notable May 2026 orders worth flagging:

Monthly Revenue by Bucket (stacked)

Realized $ per month by primary-product bucket. Catering / Annual Passes / Gift Vouchers are anchored to order date (no Rezdy fulfilment date); Facility Rentals use the rental date.

Bucket-by-Month Table ($ realized)

Selected date range. Empty cells = no revenue in that bucket that month.

4. Comps & Discount Treatment

How discounts and comps flow through the warehouse

Rezdy distinguishes three different mechanisms for "below face value" tickets. Each one is recorded differently in the data:

So when leadership asks "how are comps recorded?":

Monthly Discount Spend by Type

Dollar value of comps + offsets each month. Helps see when promo campaigns ran (peaks in Free / Promo) and the steady drumbeat of voucher redemptions.

All-time Payment Method Mix

Across the full date range. Refunds shown as negative.

Comps Detail Table

Order & $ counts per discount type, by month. Realized $ = money Rezdy actually received that month (card + cash + invoice + ACH/wire). It's after promo/voucher offsets and excludes refunds. Free / Promo / Voucher columns are the discount amount applied off face value — not part of realized $.

5. Promo Code Usage

Which promo codes ran each month

Promo codes are multi-use marketing codes (vs single-use vouchers). The table shows every code that had at least one redemption in the selected range. Heavy spend on a code in a single month usually maps to a one-off promotion or B2B partner block.

Promo Code Usage by Month

Stacked bars: total discount $ per code, per month. Hover for code names.

Promo Code Detail Table

Rows = month × code. Sorted by month, then by $ within month. Each row shows redemption count and discount $.

6. Slot-Level Booking Patterns

Bookings by 15-minute slot

Live from BigQuery (marts.fct_bookings with the standard visit filter — is_visit=TRUE, status != 'Cancelled', past fulfilment only). Data through .

Scheduling cadence changed in April 2026. Pre-April bookings used 20-min slots (:00 / :20 / :40); April onward uses 15-min slots (:00 / :15 / :30 / :45). Every fulfillment time is snapped to the nearest 15-min mark in this view, so legacy :20 renders as :15 and legacy :40 as :45 — a 5-min quantization but visually consistent across the whole period.

Bookings by 15-Minute Slot

Total bookings per timeslot in selected range

Avg Bookings per Slot: Weekday vs Weekend

Average per day, normalized by days in selected range

Stacked by Day of Week

Which days fill which slots

Heatmap: Day of Week x Slot

Color intensity = booking count per 15-min slot

Heatmap: Month x Slot

Monthly patterns at slot-level detail

7. Food & Beverage

Per-guest spend & Splice Bros / Concession / Speakeasy split

Not currently answerable from this dashboard. F&B revenue lives in Clover, not in the Rezdy-derived Atlas9 warehouse. The only F&B-adjacent dollars that surface here are the Rezdy Drink Tickets and Alcohol Tab add-ons (rolled up in Operational Add-on above) — those represent pre-purchased drink credits, not actual bar/concession revenue.

To break out Splice Bros vs Concession Stand vs Speakeasy per-guest spend, the next data pipe to build is Clover → BigQuery:

Once that exists, this section becomes a real chart: per-guest spend by revenue center, attach rate vs ticket sales, and same-day pairing with attendance.

Data source: atlas9-data BigQuery warehouse. Slot & tier: marts.fct_bookings + marts.int_rezdy_ticket_tiers. Revenue: marts.int_rezdy_order_payments. Buckets: order-level primary-line attribution against marts.dim_product flag taxonomy. Discounts: payment-type buckets in int_rezdy_order_payments. F&B (Clover) not yet in warehouse.
Dashboard built: . Data through .