--- name: revenue-audit description: Audit an email marketing program for revenue leaks — missing flows, dormant high-value subscribers, under-segmentation, promo gaps, stale automations — ranked by estimated $ impact version: "1.0.0" author: Cogny AI requires: cogny-mcp platforms: [klaviyo, mailchimp, rule, get-a-newsletter] user-invocable: true argument-hint: "" allowed-tools: - mcp__cogny__klaviyo__* - mcp__cogny__mailchimp__* - mcp__cogny__rule__* - mcp__cogny__get_a_newsletter__* - mcp__cogny__create_finding - mcp__cogny__write_context_node - mcp__cogny__read_context_node - WebFetch - Bash - Read - Write --- # Revenue Audit The "email growth consultant in a box." Scans your connected ESP for the revenue sitting on the table and ranks every finding by estimated dollar impact, so you know exactly what to fix first. **Requires:** Cogny MCP + a connected ESP. [Sign up](https://cogny.com) This is the skill to run once per quarter, or whenever you inherit an email program and need to know where to start. ## Usage `/revenue-audit` — full audit of the connected ESP ## Prerequisites Check Detect connected ESP. If the user has multiple connected, run against each and produce separate reports. If the ESP has no ecom integration (Rule, Get a Newsletter without ecom), the audit runs engagement-only and revenue numbers are flagged as estimated. ## Steps ### 1. Establish baseline context Pull once and reference throughout: - Total active subscribers - Average open rate + CTR (last 90 days) - Total email revenue (last 90 days, if ecom) — this is the denominator for every % impact claim - Average AOV (if ecom) - List growth rate (last 90 days) - Active flows / automations and their performance - Last 90 days of campaign sends If no ecom data, use **estimated value per subscriber per month** = (list revenue from user input OR industry benchmark $0.10–$2.00 depending on vertical). ### 2. Run the nine checks For each check, output: **finding title + estimated $ lift + evidence + recommended fix**. #### Check 1 — Missing core flows The highest-ROI flows and their typical revenue contribution in healthy ecom programs (Klaviyo benchmarks): | Flow | Typical % of email revenue | Trigger | |------|---------------------------|---------| | Welcome series | 3–7% | New subscriber | | Abandoned cart | 5–12% | Cart created, not checked out | | Browse abandonment | 1–3% | Product viewed, no cart | | Post-purchase | 2–5% | Order placed | | Winback | 1–4% | No engagement in 60-120d | | Replenishment | 2–6% (consumables only) | Predicted reorder date | | Birthday / anniversary | 0.5–2% | Date token match | | VIP / thank-you | 1–3% | Top-tier LTV crossed | For each missing or disabled flow, estimate lift: `total_email_revenue × benchmark_%` as the annualized $ left on the table. #### Check 2 — Dormant high-value subscribers Segment current active list by: - **Ever purchased** × **engaged in last 60 days** Count subscribers who have purchased at least once but haven't opened/clicked in 60+ days. Estimate: `count × avg_AOV × 3% reactivation rate × 2 orders/year = annualized recoverable revenue` #### Check 3 — Under-segmented broadcasts Scan last 90 days of campaign sends. For each campaign, check if it was sent to: - **"All subscribers" / full list** (bad default) - **A meaningful segment** (engaged, purchased, category-preference, geography) Flag any campaign sent to >80% of list where segmentation would plausibly apply. Estimate lift: `(segment_ctr - broadcast_ctr) / broadcast_ctr × revenue_of_that_campaign × number_of_similar_sends_per_year`. #### Check 4 — Promo calendar gaps Build a 90-day send calendar from actual sends. Look for: - **Weeks with zero broadcasts** (dead zones) - **Dead zones around proven peak buying windows** (BFCM, Mother's Day, back-to-school — vertical-specific) - **Over-send weeks** (>4 broadcasts to the same segment in 7 days — fatigue risk) For dead zones during peak windows, estimate: `avg revenue per send × N missing sends`. #### Check 5 — Flow decay For every active flow, check: - **Last modified date** — flag if >6 months - **Open/CTR trend** — flag if the flow's rolling 30-day rate is >20% below the flow's historical rate Recommend: refresh subject lines, update product references, re-evaluate offer. #### Check 6 — Suppression leaks Count subscribers who have: - No open in 180+ days - No click in 180+ days - No purchase in 365+ days (if ecom) Sending to these hurts deliverability. Quantify the deliverability drag: "Removing these X subscribers typically lifts overall open rate by 1-3pp on remaining list, which compounds to ~Y% revenue lift across all future sends." #### Check 7 — Post-purchase upsell / cross-sell gap (ecom only) For brands with purchase data: - Does a post-purchase flow exist? (Check 1) - Does it include category-appropriate upsell or accessory recommendations? - What's the 30-day repurchase rate? If <15%, post-purchase is underbuilt. Estimate: `customers_per_month × current_repurchase_rate_gap × avg_AOV`. #### Check 8 — List capture inference Compare list growth rate to benchmarks: - Ecom site with steady traffic: 2–5% monthly list growth is healthy - <1% monthly growth = under-capturing If growth is weak, flag: "Your site traffic (if paired with analytics MCP) vs. your list growth implies a capture rate of X%. Industry benchmark is 2-5%." Recommend: exit-intent popup, post-purchase capture, content offer gate. #### Check 9 — Over-reliance on discounting Scan subject lines and body content of broadcasts for % off / $ off / "sale" / "discount" / promo codes. If >60% of broadcasts lead with a discount: - Flag as margin leak + audience training (they wait for sales) - Recommend: content-led sends, product drops, exclusivity, early access Estimate: margin recovery = `current_margin × (promo_share_reduction × conversion_retention)`. ### 3. Rank every finding by estimated $ impact Bucket into 🔴 High (>5% of annual email revenue or >$10k/yr), 🟡 Medium ($1k–$10k/yr), 🟢 Optimization (<$1k/yr or hard to quantify). ### 4. Output ``` Revenue Audit: via Period analyzed: Total email revenue (90d): $ Implied annualized: $ Estimated annual revenue left on the table: $ (% of current) ──────────────────────────────────────────────────── 🔴 HIGH IMPACT — start here ──────────────────────────────────────────────────── 1. Missing abandoned cart flow Est. lift: $/yr (7% of email revenue benchmark) Evidence: No flow with trigger "cart created, not converted" in . Current cart sessions on connected store = /month at %. Industry abandoned-cart flow recovery ≈ 10–15%. Fix: Build 3-email cart flow (1h / 24h / 48h). I can draft this now — run /welcome-series and tell it "abandoned cart" or ask me to generate. 2. dormant high-value subscribers (LTV > $) Est. lift: $/yr Evidence: past purchasers with avg LTV $, no engagement in 60+ days. At 3% reactivation × 2 orders/year × $ AOV. Fix: Run /winback-engine for a tiered winback series. 3. ... ──────────────────────────────────────────────────── 🟡 MEDIUM IMPACT ──────────────────────────────────────────────────── 4. ... ──────────────────────────────────────────────────── 🟢 OPTIMIZATION ──────────────────────────────────────────────────── 7. ... ──────────────────────────────────────────────────── Suggested 90-day plan ──────────────────────────────────────────────────── Month 1: . Est revenue unlock: $. Month 2: . Est: $. Month 3: . Est: $. Total 90-day estimated unlock: $. ``` ### 5. Create a finding for every item Every finding in the output also becomes a `create_finding` in Cogny, so the dashboard has the same ranked list the user just saw: ```json { "title": "Missing abandoned cart flow (est. +$/yr)", "body": "", "action_type": "flow_build", "expected_outcome": "Recover 10-15% of abandoned carts", "estimated_impact_usd": , "priority": "high" } ``` ### 6. Save the audit summary Persist to context tree under `insights/email/revenue-audit/` so the next audit can show progress: - "Last audit: 2026-01-15 — identified $120k/yr unlock; 2 items now implemented." ### 7. Offer next steps ``` Next steps I can help with right now: /welcome-series — draft any missing flow /winback-engine — execute #2 (dormant high-value) /subject-line-lab — lift open rates on existing broadcasts /email-report weekly — start tracking progress against this audit Or: ask me to draft a specific flow by name. ``` ## Notes - **Benchmarks are rough.** Real uplift depends on list quality, brand, vertical, and offer. Always frame estimates as "reasonable industry range" not "guaranteed." - Don't double-count. If "missing abandoned cart" and "post-purchase gap" both hit, check that the benchmark assumptions aren't overlapping. - If the connected ESP is Get a Newsletter or Rule without ecom: run engagement-focused checks only (1, 3, 4, 5, 6, 9) and skip revenue checks (2, 7) with a note.