Methodology White Paper: v2.4

The Science of Integrity

The "Trust Deficit" documented by BBB National Programs represents a systemic risk for modern agencies. The Candango protocol addresses this through institutional-grade audit logic applied to the YouTube API ledger.

50%

Audience Engagement

The primary pillar of conversion. We measure the velocity of interactions relative to reach using a 30-day trailing API ledger.

25%

Content Consistency

Standardized reliability audit. We reconstruct a 12-month lifecycle to verify systemic performance vs. viral anomalies.

15%

AI Sentiment Audit

Qualitative authenticity check. Scans for bot signatures and engagement pods to verify human intent and brand safety.

10%

Market Reach

Logarithmic reach scaling. We suppress vanity metrics to curb the influence of purchased or "zombie" subscriber bases.

Bridging the Trust Deficit

Institutional assessments by BBB National Programs highlight that while influencer marketing is a $16B industry, marketplace integrity requires a "Verified Standard of Truth." Agencies typically rely on static media kits; Candango provides the independent third-party verification required to mitigate that risk.

Algorithmic Accountability

We pull raw data directly from YouTube Analytics API v2, bypassing forged screenshots and engagement pods.

Niche Standardization

We normalize engagement rates against specific sector baselines (e.g., Tech vs. Lifestyle) to ensure ROI parity.

Technical Specifications & Reasoning

Logarithmic Reach Scaling

Raw subscriber counts are highly susceptible to "Vanity Inflation." Our algorithm applies a logarithmic curve to the Reach component (10%). This rewards the first 10,000 highly-engaged subscribers more than the 1,000,000th subscriber, as the conversion potential of early-stage, focused communities is statistically higher and harder to forge.

Systemic Lifecycle Auditing

Agencies often hire based on a "Peak Performance" (a viral hit) rather than a "Sustainable Baseline." Our Consistency Pillar (25%) reconstructs 12 months of video metadata to ensure that performance is systemic. A high score requires a minimum inventory of 100 verified assets to mitigate the risk of anomalous data spikes.

Qualitative Sentiment Analysis

Raw engagement rates can be manipulated via engagement pods. Our AI Sentiment Pillar (15%) utilizes Gemini 2.5 Flash to perform a linguistic audit of comment sections, identifying "low-intent" bot patterns versus high-value human discussion. This ensures that the conversion potential is authentic.

Risk Mitigation: Velocity Penalty

The Impact of trailing inactivity

To protect agency partners from investing in "fading stars," the CII incorporates a 20% Activity Decay Multiplier. When a creator fails to maintain content velocity within a trailing 30-day window, the algorithm treats the lack of output as a loss of market relevance. This systemic safeguard ensures that institutional capital is only allocated to active, high-velocity assets.

30-Day Trailing Audit
90-Day Contextualization
Multi-Channel Verification

Proprietary Algorithmic Framework

The Candango Integrity Index is not a simple average. It is a multi-variate statistical model that weighs engagement velocity, historical reliability, and market reach through a series of proprietary coefficients adjusted specifically for niche-sector standard deviations ($\sigma$).

Core CII Calculation (v2.4)

CII = S_base + Δ_range * Σ [ (E_μ/B_baseline)*ω_e + Λ(V_inv)*ω_c + Ψ(AI_qual)*ω_s + Φ(log_10 R)*ω_r ]
Final Audit = CII * (1.0 - Γ_velocity)
where ω: Variable Weight Coefficients based on Niche σ

The Imperative of Verified Integrity

Ultimately, the Candango Integrity Index serves as the critical bridge between the raw data of the creator economy and the fiduciary responsibility of modern marketing agencies. By standardizing trust, we enable a marketplace where quality is rewarded, risk is quantified, and institutional capital can flow with confidence.