frumu-ai 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
- Executive summary (3-5 sentences)
- Key metrics dashboard (MoM and target comparison)
- Channel-by-channel performance summary
- Campaign highlights and results
- What worked and what did not (with hypotheses)
- 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:
- Directional trends: consistent movement over 4+ periods
- Inflection points: where performance changed direction
- Seasonality: predictable patterns by day, month, or quarter
- Anomalies: one-time spikes or drops
- 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
- Identify: which metrics are underperforming?
- Diagnose: where in the funnel is the problem?
- Hypothesize: what is causing the underperformance?
- Prioritize: which fixes have the biggest impact with least effort?
- Test: design an experiment to validate the hypothesis
- Measure: did the change improve the metric?
- Scale or iterate: roll out wins; iterate on failed tests
Prioritization Framework (Impact vs. Effort)
- High impact, low effort: do immediately
- High impact, high effort: plan and resource
- Low impact, low effort: do if capacity allows
- Low impact, high effort: deprioritize