Methodology

A methodology for quantifying the enshittification of products and services, grounded in Cory Doctorow's three-stage theory of platform decay.

The Score: 0–100

Every product receives a composite enshittification score from 0 (no evidence of decay) to 100 (fully captured platform). The score is the sum of ten dimension scores, each rated 0–10. The overall score maps to a classification:

Score RangeClassification
0–20Healthy
21–35Early Warning
36–50Actively Enshittifying
51–70Severely Enshittified
71–100Terminally Enshittified

The Ten Dimensions

Each product is evaluated across ten dimensions that capture the full spectrum of platform decay. Together they cover user experience, business relationships, governance, and competitive behavior.

  • D1
    User Value Erosion
    How much has the core product degraded for end users?
  • D2
    Business Customer Exploitation
    How does the platform treat sellers, advertisers, creators, and developers?
  • D3
    Shareholder Extraction
    To what degree is the company prioritizing shareholder value over users?
  • D4
    Lock-in & Switching Costs
    How difficult is it to leave the platform?
  • D5
    Twiddling & Algorithmic Opacity
    Does the platform make opaque, unilateral changes that affect users and business customers?
  • D6
    Dark Patterns
    Does the platform employ deceptive or manipulative design practices?
  • D7
    Advertising & Monetization Pressure
    How aggressively does the platform monetize user attention and data?
  • D8
    Competitive Conduct
    Does the platform act to eliminate competition through acquisitions, bundling, or exclusionary practices?
  • D9
    Labor & Governance
    How does the company treat its workers? Is governance structured as a check on extraction, or does it enable it?
  • D10
    Regulatory & Legal Posture
    Does the company resist, undermine, or evade regulation designed to protect users and competition?
Each dimension is scored 0–10 where 0 = no evidence of enshittification, 1–3 = mild, 4–6 = moderate, 7–9 = severe, and 10 = extreme.

Category-Specific Interpretation

The ten dimensions are universal, but what each score means varies by industry. A “7” on User Value Erosion looks very different for a social media platform (algorithmic feed manipulation) than for an airline (28-inch seat pitch) or a restaurant chain (shrinkflation). Select a category below to see how each dimension is interpreted for that industry.

Products scored with this default guide typically fall into one of these archetypes: The enshittification framework (Doctorow) describes a three-stage pattern: attract users, attract business customers, extract from everyone. Not all products follow this arc — some remain in early stages, some skip stages, and some resist the pattern entirely. Score what you find, not what the model predicts.

The Three Stages

Doctorow's model describes how platforms progress through three stages as they shift value away from users and toward shareholders. Each product is classified into the stage that best matches its current behavior.

1
No Decay
The platform is genuinely good for users, often investing at a loss to attract them. Features are generous, ads are minimal, and the product feels like it's on your side.
2
Squeezing Users, Courting Business
Users begin to be squeezed as the platform tilts toward business customers. Ads increase, algorithmic feeds replace chronological ones, and business customers get favorable terms to lock them in.
3
Harvesting Everyone
Both users and business customers are exploited. Value flows almost entirely to shareholders. The platform leverages lock-in to extract maximum rent from all sides.
Stage Classification Matrix
DimensionStage 1Stage 2Stage 3
D1. User Value ErosionLowRisingHigh
D2. Business ExploitationLowLowHigh
D3. Shareholder ExtractionLowRisingHigh
D4. Lock-in & SwitchingBuildingModerateHigh
D5. Twiddling & OpacityLowRisingHigh
D6. Dark PatternsLowModerateHigh
D7. Monetization PressureLowRisingHigh
D8. Competitive ConductModerateModerateHigh
D9. Labor & GovernanceLowRisingHigh
D10. Regulatory PostureLowModerateHigh

Evidence Standards

The framework uses a tiered system to categorize evidence by reliability. AI agents are instructed to prioritize higher-tier sources when researching each product. Automated validation checks that every dimension has at least 2 evidence items, but tier quality is not formally audited for every score.

  • T1Official filings and legal records (SEC filings, antitrust rulings, FTC actions)
  • T2Investigative journalism and leaked documents
  • T3Quantitative public data (market share, app store ratings, pricing changes, lobbying records)
  • T4Expert analysis and academic research
  • T5Aggregated user reports (forum sentiment, Glassdoor reviews, user surveys)
  • T6Individual reports and anecdotes

The intended standard: each dimension should cite at least two T1–T4 sources or three T3–T5 sources, and a score of 8+ should cite at least one T1 or T2 source. Lower-tier evidence (T5–T6) should support but not solely justify a high score. These thresholds are written into the AI agent prompts but have not been formally audited against every current score.

Transparency

This project aims to be honest about what it is and how it works.

  • Public methodology — the scoring framework is summarized on this page.
  • Cited evidence — each product page links to the sources used.
  • AI-generated analysis — the scoring framework was designed and all product analyses were generated using AI agents. The project maintainer reviews and publishes the results but does not independently verify every claim.
  • Open to correction — if you find errors or disagree with a score, email .