Results for “attribution”

Separate a strategy return series into declared baseline exposure and residual edge with returns-based OLS attribution, HAC inference, rolling stability, alternate-baseline sensitivity, and regime breakdowns. Use when evaluating whether backtest, out-of-sample, or live returns contain independent alpha beyond market, equal-weight, momentum, sector, or user-supplied factor returns; when explaining whether a drawdown came from baseline exposure or strategy-specific behavior; or when a strategy needs an attribution quality gate after backtesting. Do not use for holdings-based Brinson attribution, feature-level Shapley explanations, or analysis from summary metrics without a dated return series.

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Use when the user asks to "figure out where our direct traffic really comes from", "measure dark social", "add a how-did-you-hear-about-us field", or "show social drives signups without click data"; produces a share-link/UTM hygiene spec for owned share surfaces, a self-reported attribution field design that replaces an existing form field (free-text first, coded later), a GA4 direct-traffic decomposition read (deep-URL directs, mobile-app skew, private-push correlation) with every derived number hard-labeled Estimated/proxy, and a branded-search-lift proxy from GSC plus Wikipedia pageviews — the declared dark-social method behind ECHO O2. Not for paid-channel attribution reconciliation (platform-claimed vs analytics conversions) — use attribution-reconciler. 暗社交归因/直接流量分解/自报来源字段/分享链路UTM

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How to read paid media dashboards without fooling yourself. Attribution models, platform reporting quirks, multi-platform reconciliation, ROAS vs LTV horizon traps, statistical noise in performance metrics, incrementality testing, and the failure modes that produce expensive lessons. Triggers on read paid media dashboard, attribution analysis, ROAS vs LTV, multi-platform reconciliation, ad incrementality, geo holdout, conversion lift study, ghost bidding, paid media reporting, board-deck paid media metrics, blended CAC, MMM, MTA, last-click attribution. Also triggers when a marketer is about to scale, kill, or rebudget a campaign based on platform metrics, or when reconciling platform reports against warehouse revenue.

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Marketing analytics covering campaign analysis, attribution and marketing mix modeling, ROI measurement, and performance reporting. Use when analyzing campaign ROI, comparing attribution models, or optimizing budget allocation.

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Privacy-preserving ad measurement with AdAttributionKit (SKAdNetwork's successor) — install and re-engagement attribution, conversion-value strategy under crowd anonymity, and end-to-end postback testing. Use when running paid acquisition beyond Apple Ads, measuring re-engagement campaigns, designing conversion values, or migrating from SKAdNetwork.

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Measure what matters. Event tracking design, attribution modeling, funnel analysis, experimentation platforms. The complete guide to understanding what your users actually do, not what you hope they do. Good analytics is invisible until you need it. Then it's the difference between guessing and knowing. Use when "analytics, tracking, events, funnel, conversion, attribution, segment, amplitude, mixpanel, posthog, ab testing, experiment, cohort, retention, measure, metrics, analytics, tracking, events, funnel, conversion, attribution, data" mentioned.

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Reconstruct an open-source project's growth channels, key content, and stage-by-stage attribution from GitHub history and public web evidence. Use this skill when asked to research GitHub star growth, identify launch and amplification channels, explain viral milestones, find representative posts or videos, compare Product Hunt/Show HN/Reddit/KOL impact, or produce an evidence-backed OSS growth attribution report.

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Climate physics, forcing, feedback, and attribution. Covers the greenhouse effect and radiative forcing, climate sensitivity, fast and slow feedbacks, the paleoclimate record, detection and attribution science, regional climate impacts, and the distinction between weather, climate variability, and forced climate change. Use when reasoning about global warming mechanisms, interpreting temperature or CO2 records, evaluating attribution claims for extreme events, or distinguishing signal from natural variability.

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Performance measurement, attribution modeling, and marketing ROI analysis. Use when setting up tracking, analyzing campaign performance, building attribution models, or creating marketing reports.

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Estimate per-turn token attribution across 6 categories in Claude Code sessions to show where context budget is spent

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Build AI attribution systems for content sourcing. TRIGGERS - Use when user needs help with ai-attribution-system related tasks.

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Build AI marketing attribution systems. TRIGGERS - Use when user needs help with ai-attribution-analyzer related tasks.

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Profiles a threat actor by aggregating observed ATT&CK techniques into a TTP profile and comparing it against known-group technique sets to estimate similarity and candidate attribution. Activates for requests to profile a threat actor, compare observed TTPs to known groups, or estimate attribution from technique overlap.

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Gathering and documenting Salesforce marketing reporting requirements: defining KPIs, choosing an attribution model (First Touch / Last Touch / Even Distribution / Multi-Touch), selecting the right Campaign Influence configuration, and mapping business questions to report types and dashboard features. NOT for actually building the Campaign Hierarchy and CCI models - use admin/campaign-planning-and-attribution. NOT for CRM Analytics dataset and dashboard requirements - use admin/analytics-requirements-gathering.

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Campaign attribution analysis involves systematically evaluating evidence to determine which threat actor or group is responsible for a cyber operation. This skill covers collecting and weighting attr

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Use when the user asks to "figure out where our direct traffic really comes from", "measure dark social", "add a how-did-you-hear-about-us field", or "show social drives signups without click data"; produces a share-link/UTM hygiene spec for owned share surfaces, a self-reported attribution field design that replaces an existing form field (free-text first, coded later), a GA4 direct-traffic decomposition read (deep-URL directs, mobile-app skew, private-push correlation) with every derived number hard-labeled Estimated/proxy, and a branded-search-lift proxy from GSC plus Wikipedia pageviews — the declared dark-social method behind ECHO O2. Not for paid-channel attribution reconciliation (platform-claimed vs analytics conversions) — use attribution-reconciler. 暗社交归因/直接流量分解/自报来源字段/分享链路UTM

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Builds multi-touch pipeline attribution models and generates stakeholder-ready narratives from campaign performance data. Use when analyzing channel contribution to pipeline, preparing monthly/quarterly revenue reports for leadership, diagnosing pipeline misses, modeling budget reallocation scenarios, or translating raw attribution data into board-deck language. Designed for B2B SaaS demand gen teams that report on pipeline and revenue, not leads or MQLs.

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Campaign attribution analysis involves systematically evaluating evidence to determine which threat actor or group is responsible for a cyber operation. This skill covers collecting and weighting attr

The English summary is being prepared. Showing the original description.

Build AI marketing attribution systems. TRIGGERS - Use when user needs help with ai-attribution-analyzer related tasks.

The English summary is being prepared. Showing the original description.

Build AI attribution systems for content sourcing. TRIGGERS - Use when user needs help with ai-attribution-system related tasks.

The English summary is being prepared. Showing the original description.

Campaign attribution analysis involves systematically evaluating evidence to determine which threat actor or group is responsible for a cyber operation. This skill covers collecting and weighting attr

The English summary is being prepared. Showing the original description.

Multi-touch attribution analysis across marketing channels with multiple models

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Explain a trading model's prediction by ranking the input features that contributed to its signal. Returns a Markdown table and saves an attribution record with calculation settings, adding a digital signature when a signing key is available.

• Reviewing which inputs drove a trading signal
• Saving signed records of model explanations
• Reproducing rankings with the same signal and seed

Plan and validate tracking for marketing and product decisions. Define events, configure GA4 and Google Tag Manager, standardize campaign link labels, and calculate metrics using matching time periods to produce dependable measurement plans and findings.

• Design a tracking plan for signups and purchases
• Investigate missing or duplicate events
• Standardize UTM labels across campaign links