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 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.