Digital Marketing Analytics Guide
Overview
This skill guides the agent through proper digital marketing measurement,
attribution modeling, customer analytics, and campaign optimization. It covers
the full customer journey from awareness through retention, ensuring
methodologically sound measurement and privacy-compliant data practices.
When to Use
Use this skill when the user wants to:
- Set up or evaluate marketing attribution models
- Calculate and predict customer lifetime value (CLV/LTV)
- Measure campaign ROI/ROAS with incrementality testing
- Optimize SEO/SEM strategy with proper keyword research
- Design email marketing campaigns with deliverability best practices
Decision Tree
IF measuring marketing channel effectiveness:
IF the goal is real-time campaign optimization:
→ Use multi-touch attribution (MTA) with model awareness
→ WARN: No single attribution model is "correct" — always report
multiple models (last-click, linear, time-decay, data-driven)
→ Acknowledge model bias: last-click overvalues bottom-funnel,
first-click overvalues top-funnel
ELIF the goal is strategic budget allocation:
→ Use Marketing Mix Modeling (MMM) with adstock/carryover effects
→ Model diminishing returns via Hill functions or log transforms
→ Account for cross-channel synergy and interaction effects
ELIF the goal is causal impact measurement:
→ Use incrementality testing (geo experiments, holdout groups)
→ This is the gold standard for establishing causal lift
IF calculating customer value:
IF contractual business (subscription, SaaS):
→ Use survival models with discount rate and time horizon
→ Define churn operationally (cancellation, non-renewal)
ELIF non-contractual business (e-commerce, retail):
→ Use probabilistic models (BG/NBD for frequency, Gamma-Gamma
for monetary value)
→ Define inactivity window threshold with justification
→ Account for recency, frequency, and monetary value (RFM)
IF optimizing search:
IF organic search (SEO):
→ Ensure technical SEO fundamentals (crawlability, indexation,
Core Web Vitals — LCP, CLS, INP)
→ Address E-E-A-T (Experience, Expertise, Authoritativeness,
Trustworthiness) and topical authority
→ Keyword research: balance search volume with user intent
(informational, transactional, navigational) and difficulty
ELIF paid search (SEM/PPC):
→ Evaluate bidding strategies: manual CPC vs. tCPA vs. tROAS
→ Consider quality score optimization alongside bid management
→ Track cost per click (CPC) and ROAS as primary efficiency metrics
Guardrails
- REFUSE to recommend last-click attribution as the correct or only model.
Always present model assumptions and limitations.
- REFUSE to calculate CLV as simply "average revenue × average lifespan"
without specifying a probabilistic or contractual model framework.
- WARN if marketing KPIs are vanity metrics (followers, likes, impressions)
not tied to business outcomes (revenue, profit, LTV). Marketing measurement
should ladder up to north star metrics with clear alignment to business OKRs.
- WARN if tracking is discussed without addressing privacy compliance
(GDPR, CCPA, iOS ATT, cookieless measurement). First-party data strategy
and consent management are non-negotiable.
- MUST NOT recommend purchasing email lists. Always require opt-in consent
and proper list hygiene (bounce removal, suppression lists, re-engagement
campaigns for inactive subscribers).
- MUST NOT ignore deliverability — SPF, DKIM, and DMARC authentication
are table stakes for email marketing.
Attribution Model Comparison
| Model |
Bias |
Best For |
| Last-click |
Overvalues bottom-funnel (branded search) |
Quick directional signal |
| First-click |
Overvalues top-funnel (display, social) |
Awareness campaign eval |
| Linear |
Dilutes across all touchpoints |
Even-handed but naive |
| Time-decay |
Overweights recent touches |
Conversion-focused |
| Data-driven |
Requires significant data volume |
Best available observational model |
| Incrementality |
Gold standard — causal |
Strategic decisions |
Privacy & Compliance
All digital marketing measurement must account for:
- GDPR (EU) and CCPA/CPRA (California) consent requirements
- iOS 14+ ATT framework limiting IDFA availability
- The shift from third-party cookies to first-party data strategies
- Server-side tracking (Conversion API / CAPI) as complement to pixel-based
- Cookie consent banners and their impact on data completeness
- Privacy Sandbox proposals (Topics API, Attribution Reporting API)
Tracking Infrastructure
- Use UTM parameters consistently for campaign attribution
- Implement tag management (Google Tag Manager) for governance
- Consider server-side tracking for reliability and privacy compliance
- Set up proper conversion tracking with defined conversion windows
- Use event-based measurement (GA4 paradigm) over pageview-based
Ad Tech & Programmatic
When working with programmatic advertising:
- Understand auction mechanics: first-price auctions require bid shading
- Set frequency caps to prevent ad fatigue and wasted spend
- Monitor viewability (MRC standard: 50% pixels, 1+ second) and
invalid traffic (IVT) to ensure ad verification
- Evaluate brand safety controls alongside performance metrics
Email Marketing Best Practices
- Prioritize deliverability: authenticate with SPF, DKIM, DMARC
- Practice list hygiene: remove hard bounces, re-engage or sunset
inactive subscribers, honor unsubscribes promptly
- Personalization should use behavioral signals (purchase history,
browsing behavior, engagement patterns, lifecycle stage) — not just
dynamic name insertion
- Segment by engagement level, lifecycle stage, and purchase behavior
Content & SEO Strategy
- Build topical authority through pillar-cluster content architecture
- Focus on E-E-A-T signals: demonstrate real experience, expertise,
authoritativeness, and trustworthiness
- Prioritize user experience and helpful content over keyword density
- Address Core Web Vitals: LCP, CLS, INP for page experience
Customer Analytics
- Segmentation: Use data-driven methods (RFM scoring, k-means clustering
with silhouette validation) rather than arbitrary thresholds
- Cohort analysis: Normalize by initial cohort size and control for
seasonality effects across time periods
- Churn modeling: Define churn criteria operationally; use recency-based
thresholds for non-contractual settings
Edge Cases
- Small advertisers: May not have enough conversion volume for
data-driven attribution — fall back to rules-based with caveats
- Cross-device journeys: Acknowledge deterministic matching gaps;
probabilistic identity graphs are incomplete
- Offline conversions: Store visits, phone calls require modeling
or direct integration (store visit conversions, call tracking)
- View-through attribution: High inflation risk in cookieless
environments — require incrementality validation
Escape Hatch
Experienced marketers can override guardrails by explicitly stating:
"I acknowledge [specific guardrail] and am proceeding because [justification]."
References
For detailed methodology guides, see the references/ directory.
1---2name: good-marketing-skill3description: A comprehensive digital marketing analytics skill that guides proper attribution modeling, customer analytics, and campaign measurement with privacy compliance.4---56# Digital Marketing Analytics Guide78## Overview910This skill guides the agent through proper digital marketing measurement,11attribution modeling, customer analytics, and campaign optimization. It covers12the full customer journey from awareness through retention, ensuring13methodologically sound measurement and privacy-compliant data practices.1415## When to Use1617Use this skill when the user wants to:18- Set up or evaluate marketing attribution models19- Calculate and predict customer lifetime value (CLV/LTV)20- Measure campaign ROI/ROAS with incrementality testing21- Optimize SEO/SEM strategy with proper keyword research22- Design email marketing campaigns with deliverability best practices2324## Decision Tree2526```27IF measuring marketing channel effectiveness:28 IF the goal is real-time campaign optimization:29 → Use multi-touch attribution (MTA) with model awareness30 → WARN: No single attribution model is "correct" — always report31 multiple models (last-click, linear, time-decay, data-driven)32 → Acknowledge model bias: last-click overvalues bottom-funnel,33 first-click overvalues top-funnel34 ELIF the goal is strategic budget allocation:35 → Use Marketing Mix Modeling (MMM) with adstock/carryover effects36 → Model diminishing returns via Hill functions or log transforms37 → Account for cross-channel synergy and interaction effects38 ELIF the goal is causal impact measurement:39 → Use incrementality testing (geo experiments, holdout groups)40 → This is the gold standard for establishing causal lift4142IF calculating customer value:43 IF contractual business (subscription, SaaS):44 → Use survival models with discount rate and time horizon45 → Define churn operationally (cancellation, non-renewal)46 ELIF non-contractual business (e-commerce, retail):47 → Use probabilistic models (BG/NBD for frequency, Gamma-Gamma48 for monetary value)49 → Define inactivity window threshold with justification50 → Account for recency, frequency, and monetary value (RFM)5152IF optimizing search:53 IF organic search (SEO):54 → Ensure technical SEO fundamentals (crawlability, indexation,55 Core Web Vitals — LCP, CLS, INP)56 → Address E-E-A-T (Experience, Expertise, Authoritativeness,57 Trustworthiness) and topical authority58 → Keyword research: balance search volume with user intent59 (informational, transactional, navigational) and difficulty60 ELIF paid search (SEM/PPC):61 → Evaluate bidding strategies: manual CPC vs. tCPA vs. tROAS62 → Consider quality score optimization alongside bid management63 → Track cost per click (CPC) and ROAS as primary efficiency metrics64```6566## Guardrails6768- **REFUSE** to recommend last-click attribution as the correct or only model.69 Always present model assumptions and limitations.70- **REFUSE** to calculate CLV as simply "average revenue × average lifespan"71 without specifying a probabilistic or contractual model framework.72- **WARN** if marketing KPIs are vanity metrics (followers, likes, impressions)73 not tied to business outcomes (revenue, profit, LTV). Marketing measurement74 should ladder up to north star metrics with clear alignment to business OKRs.75- **WARN** if tracking is discussed without addressing privacy compliance76 (GDPR, CCPA, iOS ATT, cookieless measurement). First-party data strategy77 and consent management are non-negotiable.78- **MUST NOT** recommend purchasing email lists. Always require opt-in consent79 and proper list hygiene (bounce removal, suppression lists, re-engagement80 campaigns for inactive subscribers).81- **MUST NOT** ignore deliverability — SPF, DKIM, and DMARC authentication82 are table stakes for email marketing.8384## Attribution Model Comparison8586| Model | Bias | Best For |87|-------|------|----------|88| Last-click | Overvalues bottom-funnel (branded search) | Quick directional signal |89| First-click | Overvalues top-funnel (display, social) | Awareness campaign eval |90| Linear | Dilutes across all touchpoints | Even-handed but naive |91| Time-decay | Overweights recent touches | Conversion-focused |92| Data-driven | Requires significant data volume | Best available observational model |93| Incrementality | Gold standard — causal | Strategic decisions |9495## Privacy & Compliance9697All digital marketing measurement must account for:98- **GDPR** (EU) and **CCPA/CPRA** (California) consent requirements99- **iOS 14+ ATT** framework limiting IDFA availability100- The shift from third-party cookies to first-party data strategies101- Server-side tracking (Conversion API / CAPI) as complement to pixel-based102- Cookie consent banners and their impact on data completeness103- Privacy Sandbox proposals (Topics API, Attribution Reporting API)104105## Tracking Infrastructure106107- Use **UTM parameters** consistently for campaign attribution108- Implement **tag management** (Google Tag Manager) for governance109- Consider **server-side tracking** for reliability and privacy compliance110- Set up proper **conversion tracking** with defined conversion windows111- Use **event-based measurement** (GA4 paradigm) over pageview-based112113## Ad Tech & Programmatic114115When working with programmatic advertising:116- Understand auction mechanics: first-price auctions require bid shading117- Set **frequency caps** to prevent ad fatigue and wasted spend118- Monitor **viewability** (MRC standard: 50% pixels, 1+ second) and119 **invalid traffic** (IVT) to ensure ad verification120- Evaluate **brand safety** controls alongside performance metrics121122## Email Marketing Best Practices123124- Prioritize **deliverability**: authenticate with SPF, DKIM, DMARC125- Practice **list hygiene**: remove hard bounces, re-engage or sunset126 inactive subscribers, honor unsubscribes promptly127- **Personalization** should use behavioral signals (purchase history,128 browsing behavior, engagement patterns, lifecycle stage) — not just129 dynamic name insertion130- Segment by engagement level, lifecycle stage, and purchase behavior131132## Content & SEO Strategy133134- Build **topical authority** through pillar-cluster content architecture135- Focus on **E-E-A-T** signals: demonstrate real experience, expertise,136 authoritativeness, and trustworthiness137- Prioritize **user experience** and helpful content over keyword density138- Address **Core Web Vitals**: LCP, CLS, INP for page experience139140## Customer Analytics141142- **Segmentation**: Use data-driven methods (RFM scoring, k-means clustering143 with silhouette validation) rather than arbitrary thresholds144- **Cohort analysis**: Normalize by initial cohort size and control for145 seasonality effects across time periods146- **Churn modeling**: Define churn criteria operationally; use recency-based147 thresholds for non-contractual settings148149## Edge Cases150151- **Small advertisers**: May not have enough conversion volume for152 data-driven attribution — fall back to rules-based with caveats153- **Cross-device journeys**: Acknowledge deterministic matching gaps;154 probabilistic identity graphs are incomplete155- **Offline conversions**: Store visits, phone calls require modeling156 or direct integration (store visit conversions, call tracking)157- **View-through attribution**: High inflation risk in cookieless158 environments — require incrementality validation159160## Escape Hatch161162Experienced marketers can override guardrails by explicitly stating:163"I acknowledge [specific guardrail] and am proceeding because [justification]."164165## References166167For detailed methodology guides, see the `references/` directory.