Marketing Metrics Dashboard & Channel Economics
Builds on Topic 9.
What you'll produce
A one-page marketing metrics dashboard for Tempo that ties your whole capstone together with numbers: a single North Star metric, the funnel/conversion and retention metrics that feed it, the channel economics (CAC vs. LTV, with the LTV > CAC check) for the channels you chose in your launch plan, an ROI / ROAS read on whether the marketing spend pays back, and an explicit call-out of the vanity metrics you'll refuse to report and why. This is the final deliverable and it proves the Topic 9 skill that separates a PMM from a poster: choosing the right numbers, doing the CAC/LTV math honestly, and being willing to ignore impressive-looking numbers that don't reflect real value. It's also the artifact a founder or hiring manager scans first — it shows you can connect positioning, launch, and funnel work to money.
Instructions
- Set one North Star metric (NSM) — the single number that best captures the real value Tempo delivers to a paying agency, not a "number-go-up" vanity metric. Define it in one precise sentence (who, doing what, how often). A good NSM moves only when customers genuinely succeed, so growing it forces you to grow retention and revenue together.
- Map the funnel/conversion metrics (AARRR), with real rates. For each stage — Acquisition → Activation → Retention → Referral → Revenue — write the metric, your current number, and the conversion rate between stages. Put a star on the worst leak you named in Deliverable 5 so the dashboard and your experiment agree.
- Add the retention block. Retention is "the king of growth," so report it on its own: logo (account) churn, net revenue retention (NRR) if you can, and the activation→retained rate. State the number that, if it slipped, would make every acquisition dollar wasted.
- Build the channel-economics table for your launch channels. Use the 2–3 channels from your GTM plan (Deliverable 3). For each, lay out spend, customers acquired, CAC, payback period, and LTV, then compute the LTV : CAC ratio and mark pass/fail against the "LTV comfortably greater than CAC" bar (rule of thumb: 3:1 or better, payback under ~12 months for SMB SaaS). Show your LTV formula so a reviewer can check it. Use the canonical price from the capstone brief — the flat $12/seat/month plan that Deliverable 3 packaged the AI feature into — so ARPA here equals seat price × average seats ($12 × ~18 ≈ $216/mo) and your LTV/CAC traces to the deal economics the whole capstone shares, not a new number invented for this page. A dashboard whose ARPA contradicts the brief's $12 plan (or any future add-on you committed to in D3) fails the coherence bar below.
- Add an ROI / ROAS line for the launch. State total launch marketing spend, the new revenue (or pipeline) you attribute to it, and the resulting return — and name the honest attribution caveat (what you can and can't prove caused it).
- Call out the vanity metrics you will not report — and why. Name at least two impressive-looking numbers (e.g., "AI feature pageviews," "total trial sign-ups ever," "social impressions") and explain, in one line each, the real metric you'd watch instead.
- Keep it to one page and make it honest. Where a number is an estimate or a benchmark rather than measured, label it
(est.). Naming what you can't yet measure scores higher than a confident-but-fake dashboard.
Worked example
(Product: Tempo — B2B time-tracking & capacity-planning SaaS for 10–50-person creative agencies, launching AI-assisted capacity forecasting. Pricing is the brief's canonical flat $12/seat/month plan (the one D3 bundled the AI forecast into); avg. paying team ≈ 18 seats ≈ $216/mo ≈ $2,592/yr. Current base: ~300 paying teams. All figures illustrative but internally consistent — and the price matches the capstone brief, D3, and D4 so the LTV/CAC math below traces straight to the GTM plan.)
North Star metric
Weekly active agencies that log a capacity forecast and bill against it — i.e., teams that don't just track hours but use Tempo to decide whether they can take the next project. Target this quarter: 210 of 300 paying teams (70%), up from 165 (55%). Why this NSM: it only rises when an agency gets the actual job-to-be-done ("can we take this project without burning the team?") — the exact value the positioning (Deliverable 2) promised. You cannot inflate it with sign-ups or pageviews; it forces activation, retention, and the AI-forecasting feature to all work.
Funnel / conversion metrics (AARRR) — monthly cohort
| Stage | Metric | Current | Step conversion |
|---|---|---|---|
| Acquisition | Website → free-trial starts | 1,000 visitors → 80 trials | 8.0% |
| Activation | Trials that connect a project + invite ≥2 teammates in week 1 | 80 → 30 activated | 37.5% ★ worst leak |
| Retention | Activated teams still active at day 30 | 30 → 24 | 80% |
| Referral | Active teams that refer another agency | 24 → 3 referring | 12.5% |
| Revenue | Activated trials → paid | 30 → 12 paid | 40% |
★ Worst leak = Activation (37.5%) — the same leak named in Deliverable 5. Most trials never connect a real project, so they never see a forecast and never hit the "aha." This is why the experiment (Deliverable 5) targets the empty first-run state, and why the AI-forecasting launch (Deliverable 3) leads with a sample-data forecast on day one.
Retention block (the foundation)
- Logo (account) churn: 2.5%/mo (~26%/yr) → keep below 3%/mo or acquisition just refills a leaky bucket.
- Net revenue retention (NRR): 104% (est.) — expansion from seat growth slightly outpaces churn; the AI feature is the lever to push this higher via an add-on.
- Activation → still-paying at 90 days: ~70% — the number that, if it slipped under ~60%, would make every channel below unprofitable regardless of CAC.
Channel economics — launch channels (LTV : CAC)
LTV formula: ARPA × gross margin ÷ monthly churn. ARPA = $216/mo (18 seats × $12/seat, the canonical flat plan); gross margin = 80%; churn = 2.5%/mo → LTV = (216 × 0.80) ÷ 0.025 = $6,912 per team. (Conservative; ignores expansion/NRR.)
| Channel (from GTM plan) | Spend | Customers | CAC | Payback | LTV | LTV : CAC | Verdict |
|---|---|---|---|---|---|---|---|
| SEO / "help-don't-sell" content (D4 piece) | $4,000 | 8 | $500 | ~2.9 mo | $6,912 | 13.8 : 1 | Pass — scale it; compounding & cheapest |
| Founder-led / warm sales (2-person team) | $6,000 | 6 | $1,000 | ~5.8 mo | $6,912 | 6.9 : 1 | Pass — high-touch, fits ACV |
| LinkedIn Ads to agency owners | $5,000 | 2 | $2,500 | ~14.5 mo | $6,912 | 2.8 : 1 | Borderline — under 3:1 & payback >12mo; keep small, re-test creative, don't scale yet |
Read: content and warm sales clear the LTV > CAC bar comfortably; don't spread thin — concentrate budget on the two winners (Topic 8). Paid LinkedIn is the watch-item, not the workhorse: at 2.8:1 it's barely above water and the payback exceeds a year, so it gets a capped test budget, not a scale-up.
ROI / ROAS — launch
- Total launch marketing spend: $15,000. New ARR attributed (16 teams × $2,592): ~$41,500 first-year revenue.
- First-year ROAS ≈ 2.8x; on LTV basis ≈ 7.4x ((16 × $6,912) ÷ $15,000).
- Honest caveat: attribution is fuzzy — warm-sales and word-of-mouth deals would partly have closed anyway, and SEO compounds after the launch window, so the true ROAS is a range, not a point. I'd report it as "≈2–3x first-year, trending up as content matures," not a false-precision single number.
Vanity metrics I will NOT report (and what I watch instead)
- "AI forecasting feature pageviews" — impressive on launch day, but a view isn't value. Watch instead: weekly active agencies that run a forecast (the NSM input).
- Total trial sign-ups ever / "cumulative sign-ups" — only goes up, hides the 37.5% activation leak. Watch instead: trial → activated → paid rates per cohort.
- LinkedIn impressions / social followers — reach without revenue; easy to buy, easy to fool yourself. Watch instead: CAC and LTV:CAC per channel.
Rubric
The app's AI scores your submission against these criteria and gives per-criterion feedback. Levels: Needs work (1) / Solid (2) / Excellent (3). Passing = every criterion at Solid or above.
- North Star reflects real value — 1: a vanity/number-go-up metric (sign-ups, pageviews) · 2: a reasonable value metric for Tempo · 3: a precise, value-capturing NSM that only rises when agencies succeed and clearly traces from the positioning.
- Funnel & conversion metrics — 1: random or missing rates · 2: covers most AARRR stages with numbers · 3: full AARRR with step-conversion rates and the worst leak marked, consistent with Deliverable 5.
- Retention reported as its own block — 1: missing or buried · 2: reports churn or a retention rate · 3: churn + a retention/NRR read and the "if this slips, acquisition is wasted" line.
- Channel economics (CAC vs. LTV) — 1: no CAC/LTV or just asserted · 2: CAC and LTV per channel with a ratio · 3: a clean table with spend→CAC→payback→LTV, a shown LTV formula, LTV:CAC ratios, and a pass/fail call against the 3:1 bar.
- ROI / ROAS with honesty — 1: missing or false-precision claim · 2: states spend, return, and a ratio · 3: ratio plus an explicit attribution caveat and a range rather than a fake point estimate.
- Vanity metrics called out — 1: none, or reports vanity metrics as wins · 2: names ≥1 vanity metric to ignore · 3: names ≥2 and pairs each with the real metric to watch instead.
- Coherence with the full capstone — 1: disconnected numbers, or an ARPA/price that contradicts the GTM plan · 2: linked to prior deliverables · 3: NSM, leak, channels, and message trace cleanly through Deliverables 1–5 into one money-grounded story — and ARPA is derived from the same seat price set in Deliverable 3, so the LTV/CAC math reconciles with the GTM and sales-enablement numbers rather than introducing a third figure.