unit-economics

Perform a bottoms-up unit economics decomposition for the company named in the user's request. If no ticker or company is provided, ask for one before proceeding. **Before starting, read `../data-access.md` for data access methods and `../design-system.md` for formatting conventions.** Follow the data access detection logic and design system throughout this skill. Follow these steps: ## 1. Company Lookup Look up the company by ticker using `discover_companies`. Capture: - `company_id` - `latest_calendar_quarter` — anchor for all period calculations below (see `../data-access.md` Section 1.5) - `latest_fiscal_quarter` - Firm name for report attribution (default: "Daloopa") — see `../data-access.md` Section 4.5 ## 2. Series Discovery & Business Archetype Detection Cast a wide net to discover ALL available series for this company. Search with multiple keyword sets to maximize coverage: - Financial: "revenue", "income", "profit", "margin", "eps", "cost" - Operating KPIs: "subscriber", "user", "customer", "unit", "arpu", "retention", "churn" - Segment/Product: "segment", "product", "service", "geographic" - Business-specific: "store", "gmv", "order", "booking", "backlog", "premium", "loan", "aum", "room", "seat", "bed", "acreage" Collect all unique series IDs. Read every series name and description returned. **This is how you learn what kind of business this is and what unit-level KPIs Daloopa tracks for it.** Based on series availability, classify the business into one of these archetypes (or a hybrid). This classification drives the entire report structure: | If you find series like... | Archetype | Unit = | |---|---|---| | ARR, MRR, net dollar retention, customers, ACV, churn, CAC, LTV | **SaaS / Subscription** | Customer or subscription | | Store count, same-store sales, AUV, restaurant-level margin, new openings | **Unit-based retail / Restaurant** | Store or unit | | GMV, take rate, orders, AOV, active buyers/sellers | **Marketplace / E-commerce** | Order or transaction | | Subscribers, ARPU, churn, content spend per sub | **Consumer subscription (media/streaming)** | Subscriber | | Premiums written, loss ratio, combined ratio, policies in force | **Insurance** | Policy | | NIM, loans, deposits, provision for credit losses, NCOs | **Banking / Lending** | Loan or account | | ASP, units shipped, cost per unit, gross margin per unit | **Hardware / Manufacturing** | Unit shipped | | AUM, management fee rate, performance fees, fund flows | **Asset Management** | Dollar of AUM | | Revenue per available room (RevPAR), occupancy, ADR | **Hospitality / Lodging** | Room night | | RPM, RASM, CASM, load factor, ASMs | **Airlines / Transportation** | Available seat mile | | Revenue per user, DAU, MAU, ARPU, engagement | **Digital platform / Advertising** | User | | Beds, admissions, revenue per admission, case mix | **Healthcare facilities** | Admission or bed | | Acreage, production per acre, realized price per unit | **Commodity / E&P** | Unit of production | If the business is a hybrid or doesn't fit neatly, construct a custom framework from the available series. The archetype is a starting guide, not a constraint. **Edge cases:** - **Diversified / multi-segment companies**: Pick the largest or most analytically interesting segment for primary analysis. Note other segments briefly. If the user specifies a segment, focus there. - **Pre-revenue / early-stage companies**: Focus on burn rate per unit of growth, cash efficiency, and path to unit profitability. - **Financial companies (banks, insurance, asset managers)**: These have specialized unit economics. For banks, the "unit" is a dollar of assets — focus on NIM, fee income/assets, efficiency ratio, credit costs. For insurance, focus on the combined ratio decomposition. Don't force a SaaS or retail framework onto financials. - **Companies with no obvious unit-level KPIs in Daloopa**: Fall back to a margin bridge / operating leverage analysis using standard income statement data. Decompose revenue into whatever sub-components are available (segment, geography, product line) and analyze profitability at that level. Note the limitation. - **Companies that stopped disclosing unit data**: Some major companies (e.g., Apple post-2018) no longer report unit shipments or ASPs. If unit-level data is not available, adapt to the highest-resolution decomposition the data supports (e.g., segment revenue × segment margin). Clearly flag the data gap and explain what proxy you used. Do not fabricate unit estimates. ## 3. Unit Economics Data Pull Calculate 10 quarters backward from `latest_calendar_quarter`. Pull all archetype-relevant series identified in Step 2 for those periods, plus standard financials: - Revenue (total and segment) - COGS / cost of revenue - Gross profit - Operating income - Net income - All operating KPIs relevant to the detected archetype **Derived metrics** (calculate from pulled data, label each as "(calc.)" and show formulas): - Revenue per unit (Revenue / units) - Gross margin per unit - Contribution margin per unit (if variable costs are available) - Unit growth rate (QoQ and YoY) - Revenue per unit growth rate (QoQ and YoY) - Any archetype-specific derived metrics (e.g., CAC payback = CAC / (ARPU × gross margin), LTV/CAC, 4-wall margin, take rate, combined ratio) ## 4. Qualitative Research Search SEC filings for context on the unit economics. Use archetype-specific search terms: - **SaaS**: Try "net dollar retention", "customer acquisition cost"; fallback to "expansion", "churn", "upsell" - **Restaurant/Retail**: Try "average unit volume", "restaurant-level margin"; fallback to "same-store", "new unit", "unit opening" - **Marketplace**: Try "take rate", "gross merchandise value"; fallback to "active buyers", "order volume", "monetization" - **Hardware/Manufacturing**: Try "average selling price", "units shipped"; fallback to "ASP", "volume", "mix" - **Insurance**: Try "combined ratio", "loss ratio"; fallback to "underwriting", "premium", "policy" - **Banking**: Try "net interest margin", "provision"; fallback to "loan growth", "credit quality", "efficiency" - **Digital platform**: Try "average revenue per user", "monthly active users"; fallback to "engagement", "monetization", "ARPU" - **General (all archetypes)**: Try "unit economics", "pricing"; fallback to "profitability", "margin", "per unit" Extract management commentary on pricing, retention, expansion, new unit openings, margin levers, etc. with document citations. ## 5. Analysis & Report Synthesis **Section 1: Business Model & Unit Definition (brief)** - 2-3 sentence description of what the "unit" is for this business - Why this decomposition matters for understanding the company's economics - What the revenue build-up looks like: units × revenue-per-unit, or equivalent **Section 2: Revenue Decomposition** - Show the bottoms-up revenue build: how units × price/rate × utilization (or equivalent) bridges to reported revenue - Table: quarterly history (10 quarters) showing each component - Highlight which lever is driving growth: volume vs. price vs. mix - Include growth rates (YoY) as sub-rows beneath each metric **Section 3: Unit-Level Profitability** The core of the report. Show margin/profitability at the unit level over time: - For SaaS: gross margin per customer, CAC payback period, LTV/CAC ratio - For restaurants: 4-wall EBITDA margin, new unit payback, cash-on-cash return - For marketplace: contribution margin per order, after accounting for fulfillment/transaction costs - For insurance: loss ratio + expense ratio = combined ratio per policy - For hardware: gross margin per unit, cost per unit breakdown - Adapt to whatever the business actually is - Table: historical trend with period-over-period change - Explicitly call out whether unit economics are improving or deteriorating and by how much **Section 4: Cohort / Vintage Analysis (if data supports it)** - For subscription businesses: net retention curves, expansion vs. contraction - For unit-based businesses: same-store vs. new-store contribution, unit maturation - For lending: vintage loss curves, seasoning - If insufficient data for true cohort analysis, note this and substitute with proxy analysis (e.g., new customer growth rate vs. retention rate implies cohort behavior) **Section 5: Scalability & Operating Leverage** - How do unit economics change as the business scales? - Fixed cost absorption: which costs are truly fixed vs. variable per unit? - Show operating leverage by plotting revenue growth vs. cost growth - Incremental margins: are they expanding or compressing as the business grows? **Section 6: Key Drivers & What to Watch** This is the most analytically valuable section. Based on the data, identify: - **The 3-5 metrics that matter most** for this company's unit economics, ranked by sensitivity / impact - For each metric: current level, historical range, direction of travel, and what would cause it to inflect - **Bull case drivers**: what would improve unit economics (e.g., pricing power, mix shift to higher-margin products, operating leverage kicking in, retention improving) - **Bear case risks**: what would deteriorate unit economics (e.g., competitive pricing pressure, rising CAC, input cost inflation, regulatory impact on take rates) - Connect each driver to its P&L impact: "a 100bps improvement in net retention would add ~$X to ARR" or "each new store generates ~$Xm in 4-wall EBITDA in year 2" **Section 7: Summary Assessment** - 3-4 sentence verdict on the health and trajectory of the company's unit economics - Is this a business with improving, stable, or deteriorating unit economics? - What is the single most important thing to monitor going forward? **Analytical standards:** - **Three-layer density**: every data point should have context (vs. prior period, vs. peers if known) and an implication (what it means for the investment case) - **Show your math**: when you derive a metric (e.g., implied CAC = S&M expense / new customers added), show the calculation explicitly so the reader can verify - **Flag data gaps**: if a key metric for the archetype isn't available in Daloopa's data, say so explicitly and explain what proxy you used or why the analysis is limited - **No generic filler**: if you don't have data to support a section, skip it or shorten it. Never pad with boilerplate - **Source everything**: every number should be traceable. Use Daloopa source citations per the design system conventions - **Prefer rates and ratios over absolutes**: unit economics are about efficiency, not scale. Lead with margins, returns, and per-unit metrics. Include absolutes as context ## 6. Charts Use `infra/chart_generator.py` for charts. Include at minimum: 1. A **revenue decomposition chart** (waterfall or time-series showing units × price → revenue) 2. A **unit profitability trend chart** (time-series showing the key unit margin metric over time) 3. Additional charts as warranted by the archetype (e.g., net retention waterfall for SaaS, same-store sales trend for restaurants, take rate trend for marketplaces) **All charts must be embedded in the HTML as base64 data URIs** (e.g., `<img src="data:image/png;base64,...">`) so the report is fully self-contained with no external file dependencies. After generating each chart PNG, read the file and convert to base64 for embedding. Do not use relative `<img src="filename.png">` paths. If chart_generator.py is unavailable, embed simple inline SVG charts directly in the HTML. ## 7. Save Report Save to `reports/{TICKER}_unit_economics.html` using the HTML report template from `../design-system.md`. Write the full analysis as styled HTML with the design system CSS inlined. This is the final deliverable — no intermediate markdown step needed. Structure the report with these sections: ``` <h1>{Company Name} ({TICKER}) — Unit Economics Analysis</h1> <p>Generated: {date}</p> <h2>Summary</h2> {2-3 sentences: What is the "unit"? Are unit economics improving or deteriorating? Key takeaway.} <h2>Business Model & Unit Definition</h2> {Section 1 content} <h2>Revenue Decomposition</h2> <table> | Component | Q(-9) | Q(-8) | ... | Q(latest) | {Units, revenue per unit, revenue — with Daloopa citations and YoY growth sub-rows} </table> {Commentary on volume vs. price drivers} <h2>Unit-Level Profitability</h2> <table> | Metric | Q(-9) | Q(-8) | ... | Q(latest) | {Archetype-specific unit margins — with Daloopa citations} </table> {Commentary on unit economics trajectory} <h2>Cohort / Vintage Analysis</h2> {Section 4 content, or note if insufficient data} <h2>Scalability & Operating Leverage</h2> <table> | Metric | Q(-9) | Q(-8) | ... | Q(latest) | {Revenue growth vs cost growth, incremental margins} </table> {Operating leverage assessment} <h2>Key Drivers & What to Watch</h2> {Ranked drivers with sensitivity analysis and bull/bear scenarios} <h2>Summary Assessment</h2> {3-4 sentence verdict} ``` All financial figures must use Daloopa citation format: `<a href="https://daloopa.com/src/{fundamental_id}">$X.XX million</a>` Tell the user where the HTML report was saved. Highlight the 2-3 most important findings about the company's unit economics and what they signal for the investment case.