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performance-report

skill · 392 lines · Apache-2.0 · marketing/skills/performance-report/SKILL.md

The facts

Its description

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 the agent reads to decide when to use it.

From its settingsline 3

When it starts

A person asks for a marketing performance report or a summary of how campaigns, channels, or content performed over a period, especially when the results need to be turned into an executive-ready read with next-period priorities. The description also covers wrapping a campaign and preparing weekly, monthly, or quarterly channel summaries for stakeholders.

Things a person might say (the model's guesses)

  • “Put together a performance report for last quarter's email campaigns.”
  • “I need a monthly marketing summary for the leadership team — what worked and what didn't.”
  • “Here are our paid ad numbers; how did we do and what should we change next period?”

A model's summary of when it is used.

A model's reading

What it takes when started

<time period or campaign>

What to type after its name when you start it.

From its settingsline 4

Stops for a person

1 line stops to ask a person

Lines that stop and wait for a person before going on. Found by matching words, so treat them as pointers.

Found by matching wordsline 31

What it leads to

Other skills this one hands off to, calls, requires or offers instead, as a model read them.

A model's reading

Licence

Apache-2.0, from marketing/LICENSE

The terms its author shares it under, which let it be shown here.

From the repositorylicence text

The text

Open on GitHub

Most marks come from matching words in the file, so treat them as pointers.

1---
2name: performance-report
3description: 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.
4argument-hint: "<time period or campaign>"
5---
6
7# Performance Report
8
9> If you see unfamiliar placeholders or need to check which tools are connected, see [CONNECTORS.md](../../CONNECTORS.md).
11Generate a marketing performance report with key metrics, trend analysis, insights, and optimization recommendations.

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.

Raw lines 1 to 12
13## Trigger
15User runs `/performance-report` or asks for a marketing report, performance analysis, campaign results, or metrics summary.

Trigger

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

Raw lines 13 to 16
17## Inputs
191. **Report type** — determine which type of report the user needs:
20 - **Campaign report** — performance of a specific campaign
21 - **Channel report** — performance across a specific channel (email, social, paid, SEO, etc.)
22 - **Content performance** — how content pieces are performing
23 - **Overall marketing report** — cross-channel summary (weekly, monthly, quarterly)
24 - **Custom** — user-defined scope
262. **Time period** — the reporting window (last week, last month, last quarter, custom date range)
283. **Data source**:
29 - If ~~marketing analytics is connected, discover what accounts and platforms are available, then pull performance data automatically
30 - If ~~product analytics is connected: pull performance data automatically
31 - 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."
334. **Comparison period** (optional) — prior period or year-over-year for trend context
355. **Stakeholder audience** (optional) — who will read this report (executive summary style vs. detailed analyst view)

Inputs

  1. Report type — determine which type of report the user needs:
  2. Campaign report — performance of a specific campaign
  3. Channel report — performance across a specific channel (email, social, paid, SEO, etc.)
  4. Content performance — how content pieces are performing
  5. Overall marketing report — cross-channel summary (weekly, monthly, quarterly)
  6. Custom — user-defined scope
  1. Time period — the reporting window (last week, last month, last quarter, custom date range)
  1. Data source:
  2. If ~~marketing analytics is connected, discover what accounts and platforms are available, then pull performance data automatically
  3. If ~~product analytics is connected: pull performance data automatically
  4. 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."
  1. Comparison period (optional) — prior period or year-over-year for trend context
  1. Stakeholder audience (optional) — who will read this report (executive summary style vs. detailed analyst view)
Raw lines 17 to 36
Uses an outside tool ~~marketing :29
Uses an outside tool ~~product :30
Involves a person ask the user :31
37## Report Structure

Report Structure

Raw lines 37 to 38
39### 1. Executive Summary
40- 2-3 sentence overview of performance in the period
41- Headline metric with trend direction (up/down/flat vs. prior period)
42- One key win and one area of concern

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
Raw lines 39 to 43
44### 2. Key Metrics Dashboard
46Present core metrics in a summary table:
48| Metric | This Period | Prior Period | Change | Target | Status |
49|--------|------------|--------------|--------|--------|--------|
51Status indicators:
52- On track (meeting or exceeding target)
53- At risk (below target but within acceptable range)
54- Off track (significantly below target)
56#### Metrics by Report Type
58**Campaign Report:**
59- Impressions and reach
60- Click-through rate (CTR)
61- Conversion rate
62- Cost per acquisition (CPA)
63- Return on ad spend (ROAS) or ROI
64- Total conversions/signups/leads
66**Channel Report (Email):**
67- Emails sent, delivered, bounced
68- Open rate
69- Click-through rate
70- Unsubscribe rate
71- Conversion rate
73**Channel Report (Social):**
74- Impressions and reach
75- Engagement rate (likes, comments, shares)
76- Follower growth
77- Click-through rate
78- Top-performing posts
80**Channel Report (Paid):**
81- Spend
82- Impressions and clicks
83- CTR
84- CPC and CPM
85- Conversions and CPA
86- ROAS
88**Channel Report (SEO/Organic):**
89- Organic sessions
90- Keyword rankings (movement)
91- Pages indexed
92- Backlinks acquired
93- Top-performing pages
95**Content Performance:**
96- Pageviews and unique visitors
97- Time on page
98- Bounce rate
99- Social shares
100- Conversions attributed to content
101- Top and bottom performers
103**Overall Marketing Report:**
104- Total leads generated
105- Marketing qualified leads (MQLs)
106- Pipeline contribution
107- Customer acquisition cost (CAC)
108- Channel-by-channel summary

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
Raw lines 44 to 109
110### 3. Trend Analysis
111- Performance trend over the period (week-over-week or month-over-month)
112- Notable inflection points and what caused them
113- Seasonal or cyclical patterns observed
114- Comparison to benchmarks or targets

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
Raw lines 110 to 115
116### 4. What Worked
117- Top 3-5 wins with specific data
118- Why these performed well (hypothesis)
119- How to replicate or scale

4. What Worked

  • Top 3-5 wins with specific data
  • Why these performed well (hypothesis)
  • How to replicate or scale
Raw lines 116 to 120
121### 5. What Needs Improvement
122- Bottom 3-5 performers with specific data
123- Hypotheses for underperformance
124- Recommended fixes

5. What Needs Improvement

  • Bottom 3-5 performers with specific data
  • Hypotheses for underperformance
  • Recommended fixes
Raw lines 121 to 125
126### 6. Insights and Observations
127- Patterns in the data that are not obvious from the metrics alone
128- Audience behavior insights
129- Content or creative themes that resonated
130- External factors that may have influenced performance (seasonality, news, competitive moves)

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)
Raw lines 126 to 131
132### 7. Recommendations
133For each recommendation:
134- What to do
135- Why (linked to a specific insight from the data)
136- Expected impact (high, medium, low)
137- Effort to implement (high, medium, low)
138- Priority (immediate, next sprint, next quarter)
140Prioritize recommendations in a 2x2 matrix format:
142| | Low Effort | High Effort |
143|---|---|---|
144| **High Impact** | Do first | Plan for next sprint |
145| **Low Impact** | Do if time allows | Deprioritize |

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
Raw lines 132 to 146
147### 8. Next Period Focus
148- Top 3 priorities for the upcoming period
149- Tests or experiments to run
150- Targets for key metrics

8. Next Period Focus

  • Top 3 priorities for the upcoming period
  • Tests or experiments to run
  • Targets for key metrics
Raw lines 147 to 151
152## Metric Definitions and Benchmarks

Metric Definitions and Benchmarks

Raw lines 152 to 153
154### Email Marketing
156| Metric | Definition | Benchmark Range | What It Tells You |
157|--------|-----------|----------------|-------------------|
158| Delivery rate | Emails delivered / emails sent | 95-99% | List health and sender reputation |
159| Open rate | Unique opens / emails delivered | 15-30% | Subject line and sender effectiveness |
160| Click-through rate (CTR) | Unique clicks / emails delivered | 2-5% | Content relevance and CTA effectiveness |
161| Click-to-open rate (CTOR) | Unique clicks / unique opens | 10-20% | Email content quality (for those who opened) |
162| Unsubscribe rate | Unsubscribes / emails delivered | <0.5% | Content-audience fit and frequency tolerance |
163| Bounce rate | Bounces / emails sent | <2% | List quality and data hygiene |
164| Conversion rate | Conversions / emails delivered | 1-5% | End-to-end email effectiveness |
165| Revenue per email | Total revenue / emails sent | Varies | Direct revenue attribution |
166| List growth rate | (New subscribers - unsubscribes) / total list | 2-5% monthly | Audience building health |

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
Raw lines 154 to 167
168### Social Media
170| Metric | Definition | What It Tells You |
171|--------|-----------|-------------------|
172| Impressions | Number of times content was displayed | Content distribution and reach |
173| Reach | Number of unique users who saw content | Audience breadth |
174| Engagement rate | (Likes + comments + shares) / reach | Content resonance |
175| Click-through rate | Link clicks / impressions | Traffic driving effectiveness |
176| Follower growth rate | Net new followers / total followers per period | Audience building |
177| Share/Repost rate | Shares / reach | Content virality and advocacy |
178| Video view rate | Views / impressions | Video content hook effectiveness |
179| Video completion rate | Completed views / total views | Video content quality and length fit |
180| Social share of voice | Your mentions / total category mentions | Brand visibility vs. competitors |

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
Raw lines 168 to 181
182### Paid Advertising (Search and Social)
184| Metric | Definition | What It Tells You |
185|--------|-----------|-------------------|
186| Impressions | Times ad was shown | Budget utilization and targeting breadth |
187| Click-through rate (CTR) | Clicks / impressions | Ad creative and targeting relevance |
188| Cost per click (CPC) | Total spend / clicks | Cost efficiency of traffic generation |
189| Cost per mille (CPM) | Cost per 1,000 impressions | Awareness cost efficiency |
190| Conversion rate | Conversions / clicks | Landing page and offer effectiveness |
191| Cost per acquisition (CPA) | Total spend / conversions | Full-funnel cost efficiency |
192| Return on ad spend (ROAS) | Revenue / ad spend | Revenue generation efficiency |
193| Quality Score (search) | Google's relevance rating (1-10) | Ad-keyword-landing page alignment |
194| Frequency | Average times a user sees the ad | Ad fatigue risk |
195| View-through conversions | Conversions from users who saw but did not click | Display/awareness campaign influence |

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
Raw lines 182 to 196
197### SEO / Organic Search
199| Metric | Definition | What It Tells You |
200|--------|-----------|-------------------|
201| Organic sessions | Visits from organic search | SEO effectiveness and content reach |
202| Keyword rankings | Position for target keywords | Search visibility |
203| Organic CTR | Clicks / impressions in search results | Title and meta description effectiveness |
204| Pages indexed | Number of pages in search index | Crawlability and site health |
205| Domain authority | Third-party authority score | Overall site strength |
206| Backlinks | Number of external sites linking to you | Content authority and off-page SEO |
207| Page load speed | Time to interactive | User experience and ranking factor |
208| Organic conversion rate | Organic conversions / organic sessions | Content quality and intent alignment |
209| Top entry pages | Most-visited pages from organic search | Content driving the most organic traffic |

SEO / Organic Search

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
Raw lines 197 to 210
211### Content Marketing
213| Metric | Definition | What It Tells You |
214|--------|-----------|-------------------|
215| Pageviews | Total views of content pages | Content reach and distribution |
216| Unique visitors | Distinct users viewing content | Audience size |
217| Average time on page | Time spent on content pages | Content engagement and depth |
218| Bounce rate | Single-page sessions / total sessions | Content-audience fit and UX |
219| Scroll depth | How far users scroll on a page | Content engagement through the piece |
220| Social shares | Times content was shared on social | Content resonance and virality |
221| Backlinks earned | External links to content | Content authority and SEO value |
222| Lead generation | Leads attributed to content | Content conversion effectiveness |
223| Content ROI | Revenue attributed / content production cost | Overall content investment return |

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
Raw lines 211 to 224
225### Overall Marketing / Pipeline
227| Metric | Definition | What It Tells You |
228|--------|-----------|-------------------|
229| Marketing qualified leads (MQLs) | Leads meeting marketing qualification criteria | Top-of-funnel effectiveness |
230| Sales qualified leads (SQLs) | MQLs accepted by sales | Lead quality |
231| MQL to SQL conversion rate | SQLs / MQLs | Marketing-sales alignment and lead quality |
232| Pipeline generated | Dollar value of opportunities created | Marketing impact on revenue |
233| Pipeline velocity | How fast deals move through pipeline | Campaign urgency and quality |
234| Customer acquisition cost (CAC) | Total marketing + sales cost / new customers | Efficiency of customer acquisition |
235| CAC payback period | Months to recover CAC from revenue | Unit economics health |
236| Marketing-sourced revenue | Revenue from marketing-originated deals | Direct marketing contribution |
237| Marketing-influenced revenue | Revenue from deals where marketing touched | Broader marketing impact |

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
Raw lines 225 to 238
239## Reporting Templates by Cadence

Reporting Templates by Cadence

Raw lines 239 to 240
241### Weekly Marketing Report
242Quick-scan format for team standups:
243- **Top 3 metrics** with week-over-week change
244- **What worked** this week (1-2 bullet points with data)
245- **What needs attention** (1-2 bullet points with data)
246- **This week's priorities** (3-5 action items)

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)
Raw lines 241 to 247
248### Monthly Marketing Report
249Standard stakeholder report:
2501. Executive summary (3-5 sentences)
2512. Key metrics dashboard (table with MoM and target comparison)
2523. Channel-by-channel performance summary
2534. Campaign highlights and results
2545. What worked and what did not (with hypotheses)
2556. Recommendations and next month priorities
2567. Budget spend vs. plan

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
Raw lines 248 to 257
258### Quarterly Business Review (QBR)
259Strategic review for leadership:
2601. Quarter performance vs. goals
2612. Year-to-date trajectory
2623. Channel ROI analysis
2634. Campaign performance summary
2645. Competitive and market observations
2656. Strategic recommendations for next quarter
2667. Budget request and allocation plan
2678. Key experiments and learnings

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
Raw lines 258 to 268
269### Dashboard Design Principles
270- Lead with the metrics that map to business objectives (not vanity metrics)
271- Show trends over time, not just point-in-time snapshots
272- Include comparison context: prior period, target, benchmark
273- Use consistent color coding: green (on track), yellow (at risk), red (off track)
274- Group metrics by funnel stage or business question
275- Keep dashboards to one page/screen — detail goes in appendix
276- Update cadence should match decision cadence (real-time for paid, weekly for content)

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)
Raw lines 269 to 277
278## Trend Analysis and Forecasting

Trend Analysis and Forecasting

Raw lines 278 to 279
280### Trend Identification
281When analyzing performance data, look for:
2831. **Directional trends**: is the metric consistently going up, down, or flat over 4+ periods?
2842. **Inflection points**: where did performance change direction and what happened then?
2853. **Seasonality**: are there predictable patterns by day of week, month, or quarter?
2864. **Anomalies**: one-time spikes or drops — what caused them and are they repeatable?
2875. **Leading indicators**: which metrics change first and predict future outcomes?

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?
Raw lines 280 to 288
289### Trend Analysis Process
2901. Chart the metric over time (at least 8-12 data points for meaningful trends)
2912. Identify the overall direction (upward, downward, flat, cyclical)
2923. Calculate the rate of change (is it accelerating or decelerating?)
2934. Overlay key events (campaigns launched, product changes, market events)
2945. Compare to benchmarks or targets
2956. Identify correlations with other metrics
2967. Form hypotheses about causation (and plan tests to validate)

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)
Raw lines 289 to 297
298### Simple Forecasting Approaches
299- **Linear projection**: extend the current trend line forward (useful for stable metrics)
300- **Moving average**: smooth out noise by averaging the last 3-6 periods
301- **Year-over-year comparison**: use last year's pattern as a baseline, adjusted for growth rate
302- **Funnel math**: forecast outputs from inputs (e.g., if we generate X leads at Y conversion rate, we will get Z customers)
303- **Scenario modeling**: create best case, expected case, and worst case projections

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
Raw lines 298 to 304
305### Forecasting Caveats
306- Short-term forecasts (1-3 months) are more reliable than long-term
307- Forecasts based on fewer than 12 data points should be flagged as low confidence
308- External factors (market shifts, competitive moves, economic changes) can invalidate trend-based forecasts
309- Always present forecasts as ranges, not exact numbers

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
Raw lines 305 to 310
311## Attribution Modeling Basics

Attribution Modeling Basics

Raw lines 311 to 312
313### What Is Attribution?
314Attribution determines which marketing touchpoints get credit for a conversion. This matters because buyers typically interact with multiple channels before converting.

What Is Attribution?

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

Raw lines 313 to 315
316### Common Attribution Models
318| Model | How It Works | Best For | Limitation |
319|-------|-------------|----------|------------|
320| Last touch | 100% credit to last interaction before conversion | Understanding final conversion triggers | Ignores awareness and nurture |
321| First touch | 100% credit to first interaction | Understanding top-of-funnel effectiveness | Ignores nurture and conversion drivers |
322| Linear | Equal credit to all touchpoints | Fair representation of all channels | Does not reflect relative impact |
323| Time decay | More credit to touchpoints closer to conversion | Balanced view favoring recent interactions | May undervalue awareness |
324| Position-based (U-shaped) | 40% first, 40% last, 20% split among middle | Valuing both discovery and conversion | Somewhat arbitrary weighting |
325| Data-driven | Algorithmic credit based on conversion patterns | Most accurate representation | Requires significant data volume |

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
Raw lines 316 to 326
327### Attribution Practical Guidance
328- Start with last-touch attribution if you have no model in place — it is the simplest and most actionable
329- Compare first-touch and last-touch to understand which channels drive awareness vs. conversion
330- Use position-based (U-shaped) as a reasonable middle ground for most B2B companies
331- Data-driven attribution requires high conversion volume to be statistically meaningful
332- No model is perfect — use attribution directionally, not as absolute truth
333- Multi-touch attribution is better than single-touch, but any model is better than none

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
Raw lines 327 to 334
335### Attribution Pitfalls
336- Do not optimize one channel in isolation based on single-touch attribution
337- Awareness channels (display, social, PR) will always look bad in last-touch models
338- Conversion channels (search, retargeting) will always look bad in first-touch models
339- Self-reported attribution ("how did you hear about us?") provides useful qualitative color but is unreliable as quantitative data
340- Cross-device and cross-channel tracking gaps mean attribution data is always incomplete

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
Raw lines 335 to 341
342## Optimization Recommendations Framework

Optimization Recommendations Framework

Raw lines 342 to 343
344### Optimization Process
3451. **Identify**: which metrics are underperforming vs. target or benchmark?
3462. **Diagnose**: where in the funnel is the problem? (impressions, clicks, conversions, retention)
3473. **Hypothesize**: what is causing the underperformance? (audience, message, creative, offer, timing, technical)
3484. **Prioritize**: which fixes will have the biggest impact with the least effort?
3495. **Test**: design an experiment to validate the hypothesis
3506. **Measure**: did the change improve the metric?
3517. **Scale or iterate**: roll out wins broadly; iterate on inconclusive or failed tests

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
Raw lines 344 to 352
353### Optimization Levers by Funnel Stage
355| Funnel Stage | Problem Signal | Optimization Levers |
356|-------------|---------------|---------------------|
357| Awareness | Low impressions, low reach | Budget, targeting, channel mix, creative format |
358| Interest | Low CTR, low engagement | Ad creative, headlines, content hooks, audience targeting |
359| Consideration | High bounce rate, low time on page | Landing page content, page speed, content relevance, UX |
360| Conversion | Low conversion rate | Offer, CTA, form length, trust signals, page layout |
361| Retention | High churn, low repeat engagement | Onboarding, email nurture, product experience, support |

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
Raw lines 353 to 362
363### Testing Best Practices
364- Test one variable at a time for clean results
365- Define the success metric before launching the test
366- Calculate required sample size before starting (do not end tests early)
367- Run tests for a minimum of one full business cycle (typically one week for B2B)
368- Document all tests and results, regardless of outcome
369- Share learnings across the team — failed tests are valuable information
370- A test that confirms the status quo is not a failure — it builds confidence in your current approach

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
Raw lines 363 to 371
372### Continuous Optimization Cadence
373- **Daily**: monitor paid campaigns for budget pacing, anomalies, and disapproved ads
374- **Weekly**: review channel performance, pause underperformers, scale winners
375- **Bi-weekly**: refresh ad creative and test new variants
376- **Monthly**: full performance review, identify new optimization opportunities, update forecasts
377- **Quarterly**: strategic review of channel mix, budget allocation, and targeting strategy

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
Raw lines 372 to 378
379## Output Formatting
381- Use tables for data presentation
382- Bold key numbers and trends
383- Keep the executive summary concise (suitable for forwarding to leadership)
384- Include a "detailed appendix" section for granular data if the user provided a lot of metrics

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
Raw lines 379 to 385
386## After the Report
388Ask: "Would you like me to:
389- Create a slide-ready summary of these results?
391- Dive deeper into any specific metric or channel?

After the Report

Ask: "Would you like me to:

Raw lines 386 to 392
Names a skill stakeholder-update :390
Names a skill report-builder :392

From anthropics/knowledge-work-plugins at 2574e29, 2026-10-27. Skills read by DeepSeek V4.1 Flash on 2026-11-04. Summary and techniques by Claude Opus 5.5 on 2026-11-06.