Goalhanger Analytics Dashboard Template for Tracking Subscriber Revenue

Hook: Stop guessing your podcast subscription revenue — model it like Goalhanger

Creators and publishers building paid podcast products often face the same pain: you can measure downloads, but converting listeners into predictable revenue is messy. You need a repeatable place to test pricing, track subscriber metrics, and forecast revenue without rebuilding spreadsheets every quarter. This article ships you exactly that — a Goalhanger Analytics Dashboard spreadsheet template prefilled with metrics, formulas, and 2026 benchmarks so you can model subscription growth in minutes.

Why this matters in 2026

Subscription monetization for podcasts matured fast after 2023. By late 2025 and early 2026, networks like Goalhanger demonstrated scale — Goalhanger exceeded 250,000 paying subscribers, generating roughly £15m/year in subscriber income (Press Gazette).

That milestone changed the conversation: subscriptions are no longer a fringe experiment but a strategic business line. At the same time, platform fragmentation, rising first-party data importance, and higher customer acquisition costs (CAC) make careful financial modeling essential.

Use this template to:

• Convert listener KPIs into reliable revenue forecasts
• Test pricing, free-to-paid conversion, and churn scenarios
• Compare your performance to Goalhanger-level benchmarks

What’s in the Goalhanger Analytics Dashboard template

The downloadable spreadsheet is built for Google Sheets and Excel. It’s organized into three sections so teams can get insights quickly:

1. Inputs & Assumptions — price tiers, trial lengths, conversion assumptions, CAC, platform fees, gross margin
2. Metrics Engine — monthly cohort calculus, churn, ARPU, LTV, MRR/ARR, CAC payback, cohort LTV curves
3. Dashboard & Scenarios — visual KPIs, scenario compare (baseline/optimistic/pessimistic), and a benchmarking panel including Goalhanger figures

Prefilled benchmark examples (use these to sanity check)

• Goalhanger benchmark: 250,000 subscribers; ~£60/year average revenue per subscriber (ARPS); ~£15M annual subscriber income (Press Gazette)
• Typical 2026 emerging-network ranges (industry observations): conversion from free listeners to paid: 0.5%–3%; monthly churn: 3%–7%; ARPU monthly: £3–£7
• Platform fees: Apple/Spotify revenue share or hosting fees vary. Default input: platform cut 10%–30%; payment processing: 2.9% + £0.30

How to use the template — step-by-step

Step 1 — Enter real inputs for your show(s)

Open the Inputs sheet and fill the following fields (all are prefilled with sensible defaults):

• Starting subscribers (current paying base)
• Monthly listener pool or active audience
• Price tiers (monthly and annual pricing)
• Conversion rates (free→trial, trial→paid, organic paid conversion)
• CAC (channel-level: social, email, paid ads)
• Monthly churn and cohort retention assumptions
• Platform & processing fees and estimated gross margin

Step 2 — Understand the formulas under the hood

Key calculations are visible on the Metrics Engine sheet so you can audit or adapt them.

• MRR = sum(payment_amount * active_subscribers_monthly)
• ARR = MRR * 12 (or compute annual payments separately)
• ARPU = MRR / total_active_subscribers
• Monthly churn = churn_rate (input) — used to decay cohorts
• LTV (months) = 1 / churn_rate; LTV (currency) = ARPU_monthly * (1 / churn_rate)
• CAC payback months = CAC / (ARPU_monthly * gross_margin)

Example: if ARPU monthly = £5 and monthly churn = 5% (0.05), then LTV months = 20 and LTV = £100.

Step 3 — Run scenarios & compare against Goalhanger

The Dashboard page includes three scenario columns (Baseline / Optimistic / Pessimistic). Change conversion or churn in each to model outcomes over 24–60 months.

Use the included Goalhanger benchmark block to answer: What scale would my show need to reach Goalhanger’s subscriber revenue? The template computes a percentage-of-Goalhanger metric automatically:

• Subscriber gap = Goalhanger_subscribers - my_current_subscribers
• Revenue gap = Goalhanger_ARR - my_projected_ARR

Practical worksheets you’ll find inside

Cohort engine

Each monthly cohort is seeded by new paid signups; retention is applied month-on-month to produce a cohort lifecycle table. This gives you a waterfall view of live subscribers per cohort and allows precise LTV by cohort.

Sensitivity matrix

Test small changes in conversion and churn and the template shows impact on ARR and cumulative revenue. This is fast A/B budgeting: what if conversion +0.5% or churn -1ppt?

Channel ROI

Assign CAC and conversion to channels (paid social, organic, email). The template calculates payback and ROI per channel so you can prioritize spend.

Benchmarks & KPIs

The Dashboard highlights essential KPIs at a glance:

• Active subscribers
• MRR / ARR
• ARPU
• Monthly churn
• LTV
• CAC payback months

Advanced strategies included — 2026-ready

The template is built for the trends shaping podcast subscriptions in 2026. It includes toggles and fields to model these advanced moves:

• Tiered pricing & bundling — model multiple tiers and bundle discounts (e.g., annual + premium content + Discord access)
• Dynamic pricing experiments — simulate A/B tests and price elasticity by cohort
• Live event & merchandise revenue — add non-subscription income to calculate customer lifetime value holistically
• First-party data value — estimate uplift from email-exclusive offers and community initiatives (Discord, Slack)
• Platform risk — input scenario for platform policy or fee changes (e.g., 10–30% fee swings)

Monte Carlo-style stress test (optional)

If you want uncertainty baked into forecasts, the template offers a Monte Carlo-esque sheet that randomizes churn and conversion across simulations using a normal distribution. In Google Sheets, the placeholder formula is:

=NORMINV(RAND(), mean, stdev)

Run 1,000 simulations to produce a probability distribution of ARR outcomes. This is especially helpful if you’re pitching investors or planning budgets under uncertainty.

Case study: Model Goalhanger-style scale from 10k to 250k

Walkthrough: you’re at 10,000 subscribers and want to project what it takes to reach Goalhanger’s 250,000 mark over 5 years. We’ll use conservative inputs.

1. Starting subscribers: 10,000
2. ARPU annual: £60 equivalent to £5/month
3. Monthly churn: 4% (0.04)
4. Monthly acquisition (net new before churn): modeled via conversion & CAC

Key results the template will compute:

• Required average monthly net additions to reach 250k in 60 months: the model shows you need ~4,000 net adds/month (depends on churn and retention improvements)
• Marketing spend estimate: if CAC = £25, then 4,000 new paid adds × £25 × 60 months is significant — the channel ROI panel helps optimize CAC by channel
• Revenue at scale: 250k × £60 = £15M/yr (matches the reported Goalhanger estimate)

Use the scenario comparator to test how lowering churn to 3% or increasing ARPU via add-ons reduces the required marketing spend drastically. This is where the template turns strategy into numbers you can act on.

How to interpret LTV and churn in 2026

In a post-cookie, first-party-data era, retention matters more than ever. LTV is not just a formula — it’s a behavioral reflection of product value.

• Reduce churn — focus on retention experiments: early-access episodes, member communities, live events, and exclusive newsletters.
• Increase ARPU — test annual plans with discounts, premium tiers, cross-show bundles.
• Measure cohort LTV — newer cohorts often perform differently; optimize onboarding experiences for new subscribers to increase long-term LTV.

Integrations & export options

The template is intentionally format-agnostic to fit into modern creator stacks.

• Google Sheets: live collaboration, simple formulas, and Add-on compatibility (BigQuery, Supermetrics)
• Excel: full feature parity for corporate finance teams
• CSV export: import cohorts into BI tools or Airtable
• API sync tips: map your subscription platform (Patreon, Supercast, Apple, Spotify) exports into the Inputs sheet monthly to keep the model live

Quick wins you can do in the first 30 days

1. Import last 12 months of subscribers and revenue into the Inputs sheet
2. Run baseline scenario to compute current payback months and LTV
3. Test a churn reduction of 1ppt — see how it affects ARR and payback
4. Identify 1 high-ROI acquisition channel from the Channel ROI sheet and increase spend by 10% as an experiment
5. Set up a weekly dashboard email with the Dashboard KPIs to keep the team focused

Common pitfalls and how the template helps you avoid them

• Over-optimistic retention — the cohort engine forces you to model actual month-on-month decay, not a flat ARR growth number.
• Mixing annual & monthly without adjusting ARPU — the template separates annual and monthly payments so ARPU is accurate.
• Ignoring platform fees — fee toggles let you stress-test scenarios where platform takes more cut or changes terms.

What success looks like — sample KPIs to track weekly

• New paid trials this week
• Trial-to-paid conversion (7-day and 30-day)
• Active subscribers (monthly snapshot)
• MRR change week-on-week
• Churn rate (cohort and aggregate)
• CAC and payback months (channel-specific)

2026 trends you should bake into your modeling

• Bundling and cross-show subscriptions are increasing ARPU for networks — model bundles as separate tiers with discount elasticity.
• Community monetization (Discord/Slack/Telegram) contributes to retention — add small retention uplift % for community-driven cohorts.
• AI personalization drives engagement — conservatively model 0.5–1ppt retention improvements if you plan personalized content or recommendations.
• Regulatory & platform risk — include a shock scenario (e.g., platform fee +10%) to measure downside.

Final checklist before you share forecasts with stakeholders

• Inputs validated by finance (pricing, fees, taxes)
• Sensitivity analysis attached (best/worst cases)
• Channel attribution method documented for CAC
• Assumptions page exported and saved for audit trails

“Numbers are persuasive — but only when assumptions are transparent.” Use the template to make assumptions explicit and decisions measurable.

Download and next steps

Ready to stop guessing and start modeling? Download the free Goalhanger Analytics Dashboard spreadsheet template (Google Sheets + Excel). It includes prefilled benchmarks, example scenarios, and a step-by-step user guide so you can plug in your data and produce investor-ready forecasts.

Once you have it, here are three immediate actions:

1. Import your last 12 months of subscriber and revenue exports
2. Run the Baseline, Optimistic, and Pessimistic scenarios to align the team on targets
3. Schedule a monthly review to iterate tactics that lower churn and lift ARPU

Call to action

Download the Goalhanger Analytics Dashboard template now and run your first 12-month forecast in under an hour. If you want a bespoke version for multi-show networks or a live sync setup with your subscription platform, reach out for a template customization session.

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