frumu-ai/marketing-performance-analytics

Performance Analytics Skill

Frameworks for measuring, reporting, and optimizing marketing performance across channels and campaigns.

Key Marketing Metrics by Channel

Email Marketing

• Delivery rate: Emails delivered / emails sent (Target: 95-99%)
• Open rate: Unique opens / emails delivered (Target: 15-30%)
• Click-through rate (CTR): Unique clicks / emails delivered (Target: 2-5%)
• Unsubscribe rate: Unsubscribes / emails delivered (Target: <0.5%)
• Conversion rate: Conversions / emails delivered (Target: 1-5%)

Social Media

• Impressions: Total times content was displayed
• Reach: Unique users who saw content
• Engagement rate: (Likes + comments + shares) / reach
• Click-through rate: Link clicks / impressions
• Follower growth rate: Net new followers / total followers

Paid Advertising (Search and Social)

• Click-through rate (CTR): Clicks / impressions
• Cost per click (CPC): Total spend / clicks
• Cost per acquisition (CPA): Total spend / conversions
• Return on ad spend (ROAS): Revenue / ad spend
• Quality Score (search): Relevance rating (1-10)

SEO / Organic Search

• Organic sessions: Visits from organic search
• Keyword rankings: Position for target keywords
• Organic CTR: Clicks / impressions in search results
• Domain authority: Third-party authority score
• Backlinks: External sites linking to you

Content Marketing

• Pageviews: Total views of content pages
• Average time on page: Time spent on content pages
• Bounce rate: Single-page sessions / total sessions
• Scroll depth: How far users scroll on a page
• Lead generation: Leads attributed to content

Overall Marketing / Pipeline

• Marketing qualified leads (MQLs): Leads meeting qualification criteria
• Sales qualified leads (SQLs): MQLs accepted by sales
• MQL to SQL conversion rate: SQLs / MQLs
• Customer acquisition cost (CAC): Total marketing + sales cost / new customers
• Marketing-sourced revenue: Revenue from marketing-originated deals

Reporting Templates and Dashboards

Weekly Marketing Report

• Top 3 metrics with week-over-week change
• What worked this week (1-2 bullet points with data)
• What needs attention (1-2 bullet points with data)
• This week's priorities (3-5 action items)

Monthly Marketing Report

1. Executive summary (3-5 sentences)
2. Key metrics dashboard (MoM and target comparison)
3. Channel-by-channel performance summary
4. Campaign highlights and results
5. What worked and what did not (with hypotheses)
6. Recommendations and next month priorities

Dashboard Design Principles

• Lead with metrics that map to business objectives
• Show trends over time, not just point-in-time snapshots
• Include comparison context: prior period, target, benchmark
• Group metrics by funnel stage or business question
• Keep dashboards to one page/screen

Trend Analysis and Forecasting

Trend Identification

Look for:

1. Directional trends: consistent movement over 4+ periods
2. Inflection points: where performance changed direction
3. Seasonality: predictable patterns by day, month, or quarter
4. Anomalies: one-time spikes or drops
5. Leading indicators: metrics that predict future outcomes

Simple Forecasting Approaches

• Linear projection: extend current trend line forward
• Moving average: smooth out noise by averaging last 3-6 periods
• Year-over-year comparison: use last year's pattern adjusted for growth
• Funnel math: forecast outputs from inputs (Leads * Conversion Rate = Customers)

Attribution Modeling Basics

Common Attribution Models

• Last touch: 100% credit to last interaction
• First touch: 100% credit to first interaction
• Linear: Equal credit to all touchpoints
• Time decay: More credit to touchpoints closer to conversion
• Position-based (U-shaped): 40% first, 40% last, 20% split middle

Attribution Practical Guidance

• Start with last-touch if you have no model in place
• Compare first-touch and last-touch to understand awareness vs. conversion drivers
• Use position-based as a reasonable middle ground for B2B
• No model is perfect — use attribution directionally

Optimization Recommendations Framework

Optimization Process

1. Identify: which metrics are underperforming?
2. Diagnose: where in the funnel is the problem?
3. Hypothesize: what is causing the underperformance?
4. Prioritize: which fixes have the biggest impact with least effort?
5. Test: design an experiment to validate the hypothesis
6. Measure: did the change improve the metric?
7. Scale or iterate: roll out wins; iterate on failed tests

Prioritization Framework (Impact vs. Effort)

1. High impact, low effort: do immediately
2. High impact, high effort: plan and resource
3. Low impact, low effort: do if capacity allows
4. Low impact, high effort: deprioritize