> ## Documentation Index > Fetch the complete documentation index at: https://docs.dacard.ai/llms.txt > Use this file to discover all available pages before exploring further. # How scoring works > Our 27-dimension scoring methodology, signal blending, and the receipts we hand back. > [!NOTE] > > We score every product across 27 dimensions in 6 functions. Each dimension lands 1-5. The composite (27-135) places you on a 5-stage maturity ladder. Connect integrations to ground the score in operational data. # How scoring works We score products by reading observable signals across **27 dimensions** in **6 functions**. Each dimension scores 1-5. Your composite (27-135) places you on a 5-stage ladder. ![Five-step scoring process: Crawl, Analyze, Score, Classify, Recommend](https://mintcdn.com/dacard/Lj-FH3-8rSmqL1t4/images/scoring-process.svg?fit=max\&auto=format\&n=Lj-FH3-8rSmqL1t4\&q=85\&s=3340d167c5fcf4dc4f2b8b89c666ab2f) ## The five steps **1. Crawl** We visit the URL and pull up to 6 pages, extracting signal from your product's public surface, docs, pricing, and UX patterns. **2. Analyze** We score each of the 27 dimensions against the rubric for each stage. Signal includes architecture tells, business model, UX patterns, and operational indicators. **3. Score** Every dimension lands a score from 1 (Foundation) to 5 (Compounding). The 27 scores sum to a composite total of 27-135. **4. Classify** The composite places you on the maturity ladder (Foundation through Compounding). **5. Recommend** We surface dimension-level reads, your strengths, your gaps, and the next move we'd take. The receipts live at `/r/{id}`. ## Five maturity stages ![Maturity ladder from Foundation (27-48) through Compounding (114-135)](https://mintcdn.com/dacard/Lj-FH3-8rSmqL1t4/images/maturity-stages.svg?fit=max\&auto=format\&n=Lj-FH3-8rSmqL1t4\&q=85\&s=d1927dc11eaad91c56182e9a45927d6e) | Stage | Score | Read | | - | - | - | | **Foundation** | 27-48 | Basics missing or absent. Capability is not yet part of the product's core. | | **Building** | 49-70 | Emerging practice, applied unevenly. Features exist; advantage doesn't. | | **Scaling** | 71-91 | Systematic, measured, repeatable. Capability is a real lever. | | **Leading** | 92-113 | Deeply integrated. Pull it out and the product breaks. | | **Compounding** | 114-135 | Capability compounds across product, data, ops, and business model. The flywheel runs itself. | ## 27 dimensions across 6 functions > **Strategy (4 dimensions)** > > **Market intelligence** - how well the team collects and synthesizes market signal > > **Decision quality** - evidence behind product and strategic decisions > > **Roadmap discipline** - how well the roadmap reflects strategic priorities and tracks outcomes > > **Competitive positioning** - clarity and defensibility of market position > **Design (4 dimensions)** > > **Research and discovery** - depth and consistency of user research > > **Prototyping speed** - how fast the team goes from idea to testable artifact > > **Experience design** - quality of interaction patterns and UX craft > > **Design-dev handoff** - efficiency and fidelity of the design-to-build handoff > **Development (4 dimensions)** > > **Architecture and systems** - depth of technical integration > > **Spec and context quality** - quality of PRDs, tickets, and context handed to builders > > **Build vs buy** - decision rigor on model and infrastructure choices > > **Delivery velocity** - speed and consistency of shipping improvements > **Intelligence (5 dimensions)** > > **Customer signal synthesis** - quality of customer feedback collection and synthesis > > **Product analytics** - depth and use of product usage data > > **Data flywheel** - whether data creates a defensible compounding advantage > > **Feedback loop quality** - whether usage data flows back to improve the product > > **Knowledge management** - how well institutional knowledge is captured, organized, and surfaced > **GTM (4 dimensions)** > > **Positioning and messaging** - clarity and resonance of market messaging > > **Launch execution** - consistency and quality of launches > > **Adoption and expansion** - how the product drives usage growth and expansion > > **Pricing and packaging** - whether pricing reflects value and supports growth > **Operations (6 dimensions)** > > **Quality and experimentation** - rigor of testing, evaluation, and quality processes > > **Team orchestration** - how the team coordinates work across people and systems > > **Process iteration** - how fast the team improves its own ways of working > > **Cost and token economics** - how the team manages inference and infrastructure costs > > **Security and compliance** - how the team manages security and compliance risk > > **Reliability and resilience** - how features handle failure and maintain availability ## Signal bars We surface scores as **signal bars** in a traffic-light system. They appear throughout the dashboard, reports, and portfolio views. | Dimension score | Color | Read | | - | - | - | | **1** (Foundation) | Red | Gap. This dimension is capping your composite. | | **2** (Building) | Amber | Developing. Targeted move pays off fast. | | **3** (Scaling) | Green | Strong. Maintain and extend. | | **4-5** (Leading / Compounding) | Green | Exceptional. Defensible capability. | ## Signal-score blending ![Surface assessment and integration signals blend into composite dimension scores](https://mintcdn.com/dacard/Lj-FH3-8rSmqL1t4/images/signal-blending.svg?fit=max\&auto=format\&n=Lj-FH3-8rSmqL1t4\&q=85\&s=1c81d33bd004fbd7af5405952ecaafe3) When you connect integrations (GitHub, Linear, PostHog, others), your scores get **signal-grounded**. We blend two sources: 1. **Surface assessment** - our read of your public surface 2. **Adapter signals** - operational ground truth from connected tools (deploy frequency, PR cycle time, sprint velocity, others) ### How we blend Each integration produces metrics mapped to specific dimensions. We convert those metrics into 1-5 signal scores using calibrated thresholds, then blend with the surface read. | Factor | Effect | | - | - | | **Signal count** | More signals, higher blending weight (5 minimum to activate, up to 0.4 weight at 20+) | | **Confidence** | High-confidence signals (from well-established adapters) carry more weight | | **Weight cap** | Adapter signal never exceeds 60% weight; surface read stays the primary input | The result: connected teams get measurably tighter scores because dimensions reflect both observable surface quality and live operational data. > [!TIP] > > Wire up GitHub and Linear first. They cover the most dimensions and produce the highest-confidence adapter signal. ## Scoring practice > **Score your own product first** > > Start with your own URL to calibrate. Then score 2-3 competitors to see where you sit. Each URL score costs 10 credits. > **Teach DAC before scoring** > > Click **Add context** before you score to drop a brief read on what your product does and who it serves. We use that to ground products with thin public surface. > **Re-score after a ship** > > Scores are point-in-time. Re-score after a major ship or quarterly to trace trajectory. We preserve score history automatically. > **Connect adapters for tighter accuracy** > > URL-only scoring leans on the public surface. Wiring GitHub, Linear, and PostHog adds operational ground truth that materially improves both accuracy and confidence. > **Share with stakeholders** > > Every score has a shareable URL at `/r/{id}`. Send it to leadership, investors, or your team without making them sign in. ## Anonymous scoring Anyone can score at [app.dacard.ai/try](https://app.dacard.ai/try) without an account. Anonymous scores are rate-limited (1 per hour per IP) and don't unlock the full report. > [!NOTE] > > When you sign up after an anonymous score, we can link the anonymous score to your new account. Your history travels with you. ## Related > **[Read your report](https://docs.dacard.ai/knowledge-base/ic-understand-report.md)** > > Walk through the report section by section. > **[Team Operations deep dive](https://docs.dacard.ai/knowledge-base/framework-maturity.md)** > > Full 27-dimension definitions and scoring rubric. > **[Connect integrations](https://docs.dacard.ai/knowledge-base/integrations.md)** > > Pull live operational signal into scoring. > **[Score your first product](https://docs.dacard.ai/knowledge-base/first-score.md)** > > Step-by-step walkthrough for first-time users. 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