> For the complete documentation index, see [llms.txt](https://docs.podplay.app/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.podplay.app/owners-playbook/analytics/insights-page/insights-categories.md). # Insights Categories Every dashboard in PodPlay Insights, grouped by theme, with what the report shows and the operating decision it helps you make. Dashboards are named by type: DASH is a multi-panel dashboard, TS a time series, HM a heatmap, HISTO a histogram, CAL a calendar view, and T a raw data table you can export. ### Overview tab The at-a-glance health check for your Club. The KPI row surfaces the numbers you check first: total revenue, court utilization, average revenue per hour used, average revenue per visitor, refunds, cash, Members, active Memberships, and total and new Customers, each with its change vs. the prior period. Below, a revenue trend line and breakdowns of revenue by source and by Member vs. Non-member show where the money is coming from. * KPI Overview \[M36]: Headline KPIs, revenue over time, and revenue breakdowns by source and by Member status. Informs whether the business is up or down this period, and which lever (utilization, pricing, Events, Membership, or Customer acquisition) to look at next.
### Revenue tab Where revenue comes from, how it is trending, and how efficiently you convert capacity into dollars. The theme moves from lifetime value down to the day-and-hour level of granularity, so you can act on strategy and optimize your calendar. * CLTV Inputs \[D7]: The building blocks of Customer lifetime value (Reservations, hours, visitors, visits, and the average revenue per visit and per visitor) as a time series. Informs what an average Customer is worth over time, whether value per Customer is rising or eroding, and what a Club should be willing to pay to acquire a Customer. * Revs by Day vs Hour and Period \[D5]: Two heatmaps, revenue by day-of-week by hour, and revenue by day-of-week by period. Informs exactly which days, times, and periods generate revenue, so you can time pricing, promotions, and programming to lift yield. * New / Existing Customers Revs \[D8]: Revenue from new vs. existing Customers over a chosen period. Informs whether growth is coming from winning new Customers or deepening existing relationships, and whether a campaign moved the number. * Revs Per & Utilization – Mvg Ave \[D18]: Moving-average revenue-per (court/slot) and utilization with their KPIs. Informs the underlying yield and utilization trend, smoothed of day-to-day noise. * Power Promos \[D23]: Every Promo Code ranked by use, with discount value, booking value, revenue, and number of users. Informs which promotions drive incremental revenue versus which quietly give away margin. * Revs & Utilization \[D32]: A filterable table of revenue and utilization across many variables. A raw, exportable base for your own revenue and utilization analysis. ### Occupancy tab How full your courts are, by time, by location, and against the revenue they produce. Occupancy is the operator's core efficiency metric: empty court-hours are inventory you can never sell again. * Capacity Utilization by Time Slot \[D2]: A heatmap of court utilization by hour-of-day by day-of-week. Informs your true peak and off-peak windows, where to add price incentives or programming to fill demand troughs. * Capacity Utilization by Location \[D1]: A time series of court utilization by location. Informs utilization trends and seasonality, the impact of new openings, and how locations compare. * Utilization & Revs Per \[D34]: Utilization alongside revenue-per (court, hour, and hour used) over time. Informs whether you are converting the capacity you fill into an improving revenue yield. ### Customers tab Who your Customers are, how often they come back, and which of them drive the business. Customers is the deepest theme in Insights: retention curves, demographic mix, and a ranked view of your most valuable players. * Return Rate within Window \[D3]: The share of Customers who return from their nth to their (n+1)th Reservation, as a time series. Informs how sticky your Customers are, how retention climbs with each visit, and whether an incentive or campaign moved the needle. * Time to Next Reservation \[D4]: A histogram of how long Customers take to book their next visit. Informs repeat-behavior benchmarks and the right moment to prompt a win-back. * Locations per Customer \[M41]: How many distinct locations Customers visit, and users per location. Informs cross-location behavior, valuable for multi-site operators gauging how Members move between Clubs. * Age Range Revs / Users / Ressies \[D12]: Customers, Reservations, and revenue broken out by age band. Informs which demographics are most valuable, so you can target programming and marketing. * Spend by Cohort \[D13]: Casual, core, and power-user cohorts over time. Informs the power-law of spend at your Club and whether your core and power tiers are growing. * Power Users \[D19]: Your top Customers ranked by lifetime revenue. Informs who your best Customers are, so you can protect them and build a profile of your ideal Customer. * New / Existing Customers \[D6]: New vs. existing Customer counts over a chosen period. Informs the acquisition-vs-retention mix behind your growth. * New / Existing Customers – Mvg Ave \[D16]: A moving-average view of the new-vs-existing Customer mix, the same trend smoothed for a cleaner read. * New / Existing Customers Ressies \[D9]: New vs. existing Customers by Reservations over time. Informs whether new or returning Customers are driving booking volume. * Customers \[D33]: A holistic, exportable table of every Customer Profile. A raw base for CRM work, segmentation, and analysis outside Insights. ### Memberships tab The health of your recurring-revenue base: how Memberships are growing, what Members are worth, and where they churn. For Clubs building predictable revenue, this is the theme to watch. * Membership Dynamics \[D14]: A Membership overview with current Members, net change, and new vs. lost Memberships over time by type. Informs whether your Membership base is growing or shrinking, which plans are gaining, and where churn is coming from. * Members / Non-Members Revs \[D21]: Member vs. Non-member revenue over time. Informs your revenue mix against target, and how much of the business rides on recurring Members. * Ave Spend per Customer (Member / Non-Member) \[D15]: Average spend per Customer, grouped by Member vs. Non-member. Informs the dollar value of converting a Non-member into a Member, the case for your Membership push. * Membership Payments \[D27]: An exportable table of all Membership purchases. A raw base for reconciling and analyzing recurring revenue outside Insights. * List of Members \[D20]: An exportable table of current Members. A working roster for outreach, renewals, and segmentation. ### Events, Programs & Classes tab How your programmed revenue performs across Clinics, Leagues, Open Play, Tournaments, private Events, and classes. Events are often the highest-margin use of an off-peak court; this theme shows which ones fill and which do not. * Events, Programs and Classes \[D22]: An Events overview with revenue, average fill rate, signups, and totals by type, over time and by location. Informs which Event types perform, at which locations, so you can program to fill capacity and grow the highest-return formats. * Event Fill Rate \[D30]: A calendar view of fill rate per Event. Informs which specific Events are under-filled and need a promotional push, or should be cut. * Lesson & Clinic Detail \[D28]: An extensive, exportable table of lessons and Clinics. A raw base for Coaching, scheduling, and payout analysis. * Customer Activity & Events \[D29]: An extensive, exportable table of Customer activity and Event signups. A detailed record for participation analysis and outreach. ### Replays tab How your Members use video Replay, the capability that turns a Reservation into an experience worth coming back for. Replay adoption is a leading indicator of engagement and a revenue line in its own right. * % Ressies with Replays \[D24]: The share of Reservations that capture a Replay, over time. Informs how quickly Replay is being adopted. * Ave Replays for Ressies with Replays \[D26]: The average number of Replays for Reservations that capture at least one. Informs the capture habits of your Replay users, a direct input to how you monetize the feature. * Free / Not Free Replays \[D25]: Total, free, and paid Replays over time. Informs Replay usage and whether, and how much, you are monetizing Replays versus giving them away. ### Coaching tab The revenue and lifetime-value impact of Coaching. Coached Customers behave differently; this theme quantifies exactly how much. * Coached / Non-Coached Customers Revs \[D35]: Revenue by coached vs. non-coached Customers, with the lift in average revenue and lifetime value. Informs how much Coaching raises Customer value, the business case for investing in your Coaching program. ### On the roadmap Two more themes are visible in the Insights navigation and will populate as their reporting comes online: * **Shop tab**: reporting for retail and pro-shop revenue. * **Food & Beverage tab**: reporting for F\&B revenue lines. --- # Agent Instructions This documentation is published with GitBook. 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