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Performance Report

AnthropicOfficialPublished by Anthropic

  • Skill
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  • Business and productivity
  • Apache-2.0
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From the author

Build a marketing performance report with key metrics, trend analysis, wins and misses, and prioritized optimization recommendations. Use when wrapping a campaign, when preparing weekly, monthly, or quarterly channel summaries for stakeholders, or when you need data translated into an executive summary with next-period priorities.
— the description by Anthropic

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The performance-report skill transforms raw marketing data into structured, professional reports suitable for stakeholders. It supports various reporting scopes, including specific campaigns, individual channels, content performance, or overall marketing summaries. By incorporating trend analysis, attribution insights, and a prioritized optimization framework, it helps teams move from data collection to strategic decision-making.

What it does

  • Generates executive summaries with headline metrics and trend indicators.
  • Creates structured dashboards comparing current performance against targets and prior periods.
  • Provides channel-specific metric analysis for email, social, paid, SEO, and content.
  • Identifies performance trends, inflection points, and seasonal patterns.
  • Prioritizes optimization recommendations using a high-impact/low-effort matrix.
  • Suggests next-period priorities and testing experiments based on findings.

When to use it

  • When wrapping up a marketing campaign to evaluate its success.
  • When preparing recurring weekly, monthly, or quarterly channel summaries.
  • When you need to translate complex data into an executive-ready report.
  • When identifying underperforming areas that require optimization.

Advantages

  • Standardizes reporting formats across different marketing channels.
  • Provides clear, actionable insights rather than just raw data.
  • Helps align marketing activities with business objectives.
  • Facilitates data-driven decision-making through prioritized recommendations.
  • Supports various reporting cadences from weekly standups to quarterly reviews.

Usage examples

“Generate a monthly performance report for our paid social campaigns.”
The agent will pull or request paid social data, compare it against the previous month, highlight top-performing posts, and suggest optimizations for the next month.
“Create a QBR summary for our email marketing channel.”
The agent will produce a strategic review including open rates, CTR, list growth, and recommendations for upcoming email experiments.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/anthropics/performance-report/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip performance-report.zip -d .agents/skills

Documentation by Anthropic

Performance Report

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Generate a marketing performance report with key metrics, trend analysis, insights, and optimization recommendations.

Trigger

User runs /performance-report or asks for a marketing report, performance analysis, campaign results, or metrics summary.

Inputs

  1. Report type — determine which type of report the user needs:

    • Campaign report — performance of a specific campaign

    • Channel report — performance across a specific channel (email, social, paid, SEO, etc.)

    • Content performance — how content pieces are performing

    • Overall marketing report — cross-channel summary (weekly, monthly, quarterly)

    • Custom — user-defined scope

  2. Time period — the reporting window (last week, last month, last quarter, custom date range)

  3. Data source:

    • If ~~marketing analytics is connected, discover what accounts and platforms are available, then pull performance data automatically

    • If ~~product analytics is connected: pull performance data automatically

    • If not connected: ask the user to provide metrics. Prompt with: "Please paste or share your performance data. I can work with spreadsheets, CSV data, dashboard screenshots described in text, or just the key numbers."

  4. Comparison period (optional) — prior period or year-over-year for trend context

  5. Stakeholder audience (optional) — who will read this report (executive summary style vs. detailed analyst view)

Report Structure

1. Executive Summary
  • 2-3 sentence overview of performance in the period

  • Headline metric with trend direction (up/down/flat vs. prior period)

  • One key win and one area of concern

2. Key Metrics Dashboard

Present core metrics in a summary table:

MetricThis PeriodPrior PeriodChangeTargetStatus

Status indicators:

  • On track (meeting or exceeding target)

  • At risk (below target but within acceptable range)

  • Off track (significantly below target)

Metrics by Report Type

Campaign Report:

  • Impressions and reach

  • Click-through rate (CTR)

  • Conversion rate

  • Cost per acquisition (CPA)

  • Return on ad spend (ROAS) or ROI

  • Total conversions/signups/leads

Channel Report (Email):

  • Emails sent, delivered, bounced

  • Open rate

  • Click-through rate

  • Unsubscribe rate

  • Conversion rate

Channel Report (Social):

  • Impressions and reach

  • Engagement rate (likes, comments, shares)

  • Follower growth

  • Click-through rate

  • Top-performing posts

Channel Report (Paid):

  • Spend

  • Impressions and clicks

  • CTR

  • CPC and CPM

  • Conversions and CPA

  • ROAS

Channel Report (SEO/Organic):

  • Organic sessions

  • Keyword rankings (movement)

  • Pages indexed

  • Backlinks acquired

  • Top-performing pages

Content Performance:

  • Pageviews and unique visitors

  • Time on page

  • Bounce rate

  • Social shares

  • Conversions attributed to content

  • Top and bottom performers

Overall Marketing Report:

  • Total leads generated

  • Marketing qualified leads (MQLs)

  • Pipeline contribution

  • Customer acquisition cost (CAC)

  • Channel-by-channel summary

3. Trend Analysis
  • Performance trend over the period (week-over-week or month-over-month)

  • Notable inflection points and what caused them

  • Seasonal or cyclical patterns observed

  • Comparison to benchmarks or targets

4. What Worked
  • Top 3-5 wins with specific data

  • Why these performed well (hypothesis)

  • How to replicate or scale

5. What Needs Improvement
  • Bottom 3-5 performers with specific data

  • Hypotheses for underperformance

  • Recommended fixes

6. Insights and Observations
  • Patterns in the data that are not obvious from the metrics alone

  • Audience behavior insights

  • Content or creative themes that resonated

  • External factors that may have influenced performance (seasonality, news, competitive moves)

7. Recommendations

For each recommendation:

  • What to do

  • Why (linked to a specific insight from the data)

  • Expected impact (high, medium, low)

  • Effort to implement (high, medium, low)

  • Priority (immediate, next sprint, next quarter)

Prioritize recommendations in a 2x2 matrix format:

Low EffortHigh Effort
High ImpactDo firstPlan for next sprint
Low ImpactDo if time allowsDeprioritize
8. Next Period Focus
  • Top 3 priorities for the upcoming period

  • Tests or experiments to run

  • Targets for key metrics

Metric Definitions and Benchmarks

Email Marketing
MetricDefinitionBenchmark RangeWhat It Tells You
Delivery rateEmails delivered / emails sent95-99%List health and sender reputation
Open rateUnique opens / emails delivered15-30%Subject line and sender effectiveness
Click-through rate (CTR)Unique clicks / emails delivered2-5%Content relevance and CTA effectiveness
Click-to-open rate (CTOR)Unique clicks / unique opens10-20%Email content quality (for those who opened)
Unsubscribe rateUnsubscribes / emails delivered<0.5%Content-audience fit and frequency tolerance
Bounce rateBounces / emails sent<2%List quality and data hygiene
Conversion rateConversions / emails delivered1-5%End-to-end email effectiveness
Revenue per emailTotal revenue / emails sentVariesDirect revenue attribution
List growth rate(New subscribers - unsubscribes) / total list2-5% monthlyAudience building health
Social Media
MetricDefinitionWhat It Tells You
ImpressionsNumber of times content was displayedContent distribution and reach
ReachNumber of unique users who saw contentAudience breadth
Engagement rate(Likes + comments + shares) / reachContent resonance
Click-through rateLink clicks / impressionsTraffic driving effectiveness
Follower growth rateNet new followers / total followers per periodAudience building
Share/Repost rateShares / reachContent virality and advocacy
Video view rateViews / impressionsVideo content hook effectiveness
Video completion rateCompleted views / total viewsVideo content quality and length fit
Social share of voiceYour mentions / total category mentionsBrand visibility vs. competitors
Paid Advertising (Search and Social)
MetricDefinitionWhat It Tells You
ImpressionsTimes ad was shownBudget utilization and targeting breadth
Click-through rate (CTR)Clicks / impressionsAd creative and targeting relevance
Cost per click (CPC)Total spend / clicksCost efficiency of traffic generation
Cost per mille (CPM)Cost per 1,000 impressionsAwareness cost efficiency
Conversion rateConversions / clicksLanding page and offer effectiveness
Cost per acquisition (CPA)Total spend / conversionsFull-funnel cost efficiency
Return on ad spend (ROAS)Revenue / ad spendRevenue generation efficiency
Quality Score (search)Google's relevance rating (1-10)Ad-keyword-landing page alignment
FrequencyAverage times a user sees the adAd fatigue risk
View-through conversionsConversions from users who saw but did not clickDisplay/awareness campaign influence
MetricDefinitionWhat It Tells You
Organic sessionsVisits from organic searchSEO effectiveness and content reach
Keyword rankingsPosition for target keywordsSearch visibility
Organic CTRClicks / impressions in search resultsTitle and meta description effectiveness
Pages indexedNumber of pages in search indexCrawlability and site health
Domain authorityThird-party authority scoreOverall site strength
BacklinksNumber of external sites linking to youContent authority and off-page SEO
Page load speedTime to interactiveUser experience and ranking factor
Organic conversion rateOrganic conversions / organic sessionsContent quality and intent alignment
Top entry pagesMost-visited pages from organic searchContent driving the most organic traffic
Content Marketing
MetricDefinitionWhat It Tells You
PageviewsTotal views of content pagesContent reach and distribution
Unique visitorsDistinct users viewing contentAudience size
Average time on pageTime spent on content pagesContent engagement and depth
Bounce rateSingle-page sessions / total sessionsContent-audience fit and UX
Scroll depthHow far users scroll on a pageContent engagement through the piece
Social sharesTimes content was shared on socialContent resonance and virality
Backlinks earnedExternal links to contentContent authority and SEO value
Lead generationLeads attributed to contentContent conversion effectiveness
Content ROIRevenue attributed / content production costOverall content investment return
Overall Marketing / Pipeline
MetricDefinitionWhat It Tells You
Marketing qualified leads (MQLs)Leads meeting marketing qualification criteriaTop-of-funnel effectiveness
Sales qualified leads (SQLs)MQLs accepted by salesLead quality
MQL to SQL conversion rateSQLs / MQLsMarketing-sales alignment and lead quality
Pipeline generatedDollar value of opportunities createdMarketing impact on revenue
Pipeline velocityHow fast deals move through pipelineCampaign urgency and quality
Customer acquisition cost (CAC)Total marketing + sales cost / new customersEfficiency of customer acquisition
CAC payback periodMonths to recover CAC from revenueUnit economics health
Marketing-sourced revenueRevenue from marketing-originated dealsDirect marketing contribution
Marketing-influenced revenueRevenue from deals where marketing touchedBroader marketing impact

Reporting Templates by Cadence

Weekly Marketing Report

Quick-scan format for team standups:

  • 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

Standard stakeholder report:

  1. Executive summary (3-5 sentences)

  2. Key metrics dashboard (table with 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

  7. Budget spend vs. plan

Quarterly Business Review (QBR)

Strategic review for leadership:

  1. Quarter performance vs. goals

  2. Year-to-date trajectory

  3. Channel ROI analysis

  4. Campaign performance summary

  5. Competitive and market observations

  6. Strategic recommendations for next quarter

  7. Budget request and allocation plan

  8. Key experiments and learnings

Dashboard Design Principles
  • Lead with the metrics that map to business objectives (not vanity metrics)

  • Show trends over time, not just point-in-time snapshots

  • Include comparison context: prior period, target, benchmark

  • Use consistent color coding: green (on track), yellow (at risk), red (off track)

  • Group metrics by funnel stage or business question

  • Keep dashboards to one page/screen — detail goes in appendix

  • Update cadence should match decision cadence (real-time for paid, weekly for content)

Trend Analysis and Forecasting

Trend Identification

When analyzing performance data, look for:

  1. Directional trends: is the metric consistently going up, down, or flat over 4+ periods?

  2. Inflection points: where did performance change direction and what happened then?

  3. Seasonality: are there predictable patterns by day of week, month, or quarter?

  4. Anomalies: one-time spikes or drops — what caused them and are they repeatable?

  5. Leading indicators: which metrics change first and predict future outcomes?

Trend Analysis Process
  1. Chart the metric over time (at least 8-12 data points for meaningful trends)

  2. Identify the overall direction (upward, downward, flat, cyclical)

  3. Calculate the rate of change (is it accelerating or decelerating?)

  4. Overlay key events (campaigns launched, product changes, market events)

  5. Compare to benchmarks or targets

  6. Identify correlations with other metrics

  7. Form hypotheses about causation (and plan tests to validate)

Simple Forecasting Approaches
  • Linear projection: extend the current trend line forward (useful for stable metrics)

  • Moving average: smooth out noise by averaging the last 3-6 periods

  • Year-over-year comparison: use last year's pattern as a baseline, adjusted for growth rate

  • Funnel math: forecast outputs from inputs (e.g., if we generate X leads at Y conversion rate, we will get Z customers)

  • Scenario modeling: create best case, expected case, and worst case projections

Forecasting Caveats
  • Short-term forecasts (1-3 months) are more reliable than long-term

  • Forecasts based on fewer than 12 data points should be flagged as low confidence

  • External factors (market shifts, competitive moves, economic changes) can invalidate trend-based forecasts

  • Always present forecasts as ranges, not exact numbers

Attribution Modeling Basics

What Is Attribution?

Attribution determines which marketing touchpoints get credit for a conversion. This matters because buyers typically interact with multiple channels before converting.

Common Attribution Models
ModelHow It WorksBest ForLimitation
Last touch100% credit to last interaction before conversionUnderstanding final conversion triggersIgnores awareness and nurture
First touch100% credit to first interactionUnderstanding top-of-funnel effectivenessIgnores nurture and conversion drivers
LinearEqual credit to all touchpointsFair representation of all channelsDoes not reflect relative impact
Time decayMore credit to touchpoints closer to conversionBalanced view favoring recent interactionsMay undervalue awareness
Position-based (U-shaped)40% first, 40% last, 20% split among middleValuing both discovery and conversionSomewhat arbitrary weighting
Data-drivenAlgorithmic credit based on conversion patternsMost accurate representationRequires significant data volume
Attribution Practical Guidance
  • Start with last-touch attribution if you have no model in place — it is the simplest and most actionable

  • Compare first-touch and last-touch to understand which channels drive awareness vs. conversion

  • Use position-based (U-shaped) as a reasonable middle ground for most B2B companies

  • Data-driven attribution requires high conversion volume to be statistically meaningful

  • No model is perfect — use attribution directionally, not as absolute truth

  • Multi-touch attribution is better than single-touch, but any model is better than none

Attribution Pitfalls
  • Do not optimize one channel in isolation based on single-touch attribution

  • Awareness channels (display, social, PR) will always look bad in last-touch models

  • Conversion channels (search, retargeting) will always look bad in first-touch models

  • Self-reported attribution ("how did you hear about us?") provides useful qualitative color but is unreliable as quantitative data

  • Cross-device and cross-channel tracking gaps mean attribution data is always incomplete

Optimization Recommendations Framework

Optimization Process
  1. Identify: which metrics are underperforming vs. target or benchmark?

  2. Diagnose: where in the funnel is the problem? (impressions, clicks, conversions, retention)

  3. Hypothesize: what is causing the underperformance? (audience, message, creative, offer, timing, technical)

  4. Prioritize: which fixes will have the biggest impact with the 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 broadly; iterate on inconclusive or failed tests

Optimization Levers by Funnel Stage
Funnel StageProblem SignalOptimization Levers
AwarenessLow impressions, low reachBudget, targeting, channel mix, creative format
InterestLow CTR, low engagementAd creative, headlines, content hooks, audience targeting
ConsiderationHigh bounce rate, low time on pageLanding page content, page speed, content relevance, UX
ConversionLow conversion rateOffer, CTA, form length, trust signals, page layout
RetentionHigh churn, low repeat engagementOnboarding, email nurture, product experience, support
Testing Best Practices
  • Test one variable at a time for clean results

  • Define the success metric before launching the test

  • Calculate required sample size before starting (do not end tests early)

  • Run tests for a minimum of one full business cycle (typically one week for B2B)

  • Document all tests and results, regardless of outcome

  • Share learnings across the team — failed tests are valuable information

  • A test that confirms the status quo is not a failure — it builds confidence in your current approach

Continuous Optimization Cadence
  • Daily: monitor paid campaigns for budget pacing, anomalies, and disapproved ads

  • Weekly: review channel performance, pause underperformers, scale winners

  • Bi-weekly: refresh ad creative and test new variants

  • Monthly: full performance review, identify new optimization opportunities, update forecasts

  • Quarterly: strategic review of channel mix, budget allocation, and targeting strategy

Output Formatting

  • Use tables for data presentation

  • Bold key numbers and trends

  • Keep the executive summary concise (suitable for forwarding to leadership)

  • Include a "detailed appendix" section for granular data if the user provided a lot of metrics

After the Report

Ask: "Would you like me to:

  • Create a slide-ready summary of these results?

  • Draft a stakeholder email with the key takeaways?

  • Dive deeper into any specific metric or channel?

  • Set up a reporting template you can reuse next period?"

Files

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Requirements and compatibility

Written for: Claude Code, Claude apps

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter

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anthropics/knowledge-work-plugins · marketing/skills/performance-report · commit e050c2e
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