— the reporting window (last week, last month, last quarter, custom date range)
Data source
:
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."
Comparison period
(optional) — prior period or year-over-year for trend context
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:
Metric
This Period
Prior Period
Change
Target
Status
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 Effort
High Effort
High Impact
Do first
Plan for next sprint
Low Impact
Do if time allows
Deprioritize
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
Metric
Definition
Benchmark Range
What It Tells You
Delivery rate
Emails delivered / emails sent
95-99%
List health and sender reputation
Open rate
Unique opens / emails delivered
15-30%
Subject line and sender effectiveness
Click-through rate (CTR)
Unique clicks / emails delivered
2-5%
Content relevance and CTA effectiveness
Click-to-open rate (CTOR)
Unique clicks / unique opens
10-20%
Email content quality (for those who opened)
Unsubscribe rate
Unsubscribes / emails delivered
<0.5%
Content-audience fit and frequency tolerance
Bounce rate
Bounces / emails sent
<2%
List quality and data hygiene
Conversion rate
Conversions / emails delivered
1-5%
End-to-end email effectiveness
Revenue per email
Total revenue / emails sent
Varies
Direct revenue attribution
List growth rate
(New subscribers - unsubscribes) / total list
2-5% monthly
Audience building health
Social Media
Metric
Definition
What It Tells You
Impressions
Number of times content was displayed
Content distribution and reach
Reach
Number of unique users who saw content
Audience breadth
Engagement rate
(Likes + comments + shares) / reach
Content resonance
Click-through rate
Link clicks / impressions
Traffic driving effectiveness
Follower growth rate
Net new followers / total followers per period
Audience building
Share/Repost rate
Shares / reach
Content virality and advocacy
Video view rate
Views / impressions
Video content hook effectiveness
Video completion rate
Completed views / total views
Video content quality and length fit
Social share of voice
Your mentions / total category mentions
Brand visibility vs. competitors
Paid Advertising (Search and Social)
Metric
Definition
What It Tells You
Impressions
Times ad was shown
Budget utilization and targeting breadth
Click-through rate (CTR)
Clicks / impressions
Ad creative and targeting relevance
Cost per click (CPC)
Total spend / clicks
Cost efficiency of traffic generation
Cost per mille (CPM)
Cost per 1,000 impressions
Awareness cost efficiency
Conversion rate
Conversions / clicks
Landing page and offer effectiveness
Cost per acquisition (CPA)
Total spend / conversions
Full-funnel cost efficiency
Return on ad spend (ROAS)
Revenue / ad spend
Revenue generation efficiency
Quality Score (search)
Google's relevance rating (1-10)
Ad-keyword-landing page alignment
Frequency
Average times a user sees the ad
Ad fatigue risk
View-through conversions
Conversions from users who saw but did not click
Display/awareness campaign influence
SEO / Organic Search
Metric
Definition
What It Tells You
Organic sessions
Visits from organic search
SEO effectiveness and content reach
Keyword rankings
Position for target keywords
Search visibility
Organic CTR
Clicks / impressions in search results
Title and meta description effectiveness
Pages indexed
Number of pages in search index
Crawlability and site health
Domain authority
Third-party authority score
Overall site strength
Backlinks
Number of external sites linking to you
Content authority and off-page SEO
Page load speed
Time to interactive
User experience and ranking factor
Organic conversion rate
Organic conversions / organic sessions
Content quality and intent alignment
Top entry pages
Most-visited pages from organic search
Content driving the most organic traffic
Content Marketing
Metric
Definition
What It Tells You
Pageviews
Total views of content pages
Content reach and distribution
Unique visitors
Distinct users viewing content
Audience size
Average time on page
Time spent on content pages
Content engagement and depth
Bounce rate
Single-page sessions / total sessions
Content-audience fit and UX
Scroll depth
How far users scroll on a page
Content engagement through the piece
Social shares
Times content was shared on social
Content resonance and virality
Backlinks earned
External links to content
Content authority and SEO value
Lead generation
Leads attributed to content
Content conversion effectiveness
Content ROI
Revenue attributed / content production cost
Overall content investment return
Overall Marketing / Pipeline
Metric
Definition
What It Tells You
Marketing qualified leads (MQLs)
Leads meeting marketing qualification criteria
Top-of-funnel effectiveness
Sales qualified leads (SQLs)
MQLs accepted by sales
Lead quality
MQL to SQL conversion rate
SQLs / MQLs
Marketing-sales alignment and lead quality
Pipeline generated
Dollar value of opportunities created
Marketing impact on revenue
Pipeline velocity
How fast deals move through pipeline
Campaign urgency and quality
Customer acquisition cost (CAC)
Total marketing + sales cost / new customers
Efficiency of customer acquisition
CAC payback period
Months to recover CAC from revenue
Unit economics health
Marketing-sourced revenue
Revenue from marketing-originated deals
Direct marketing contribution
Marketing-influenced revenue
Revenue from deals where marketing touched
Broader 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:
Executive summary (3-5 sentences)
Key metrics dashboard (table with 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
Budget spend vs. plan
Quarterly Business Review (QBR)
Strategic review for leadership:
Quarter performance vs. goals
Year-to-date trajectory
Channel ROI analysis
Campaign performance summary
Competitive and market observations
Strategic recommendations for next quarter
Budget request and allocation plan
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:
Directional trends
is the metric consistently going up, down, or flat over 4+ periods?
Inflection points
where did performance change direction and what happened then?
Seasonality
are there predictable patterns by day of week, month, or quarter?
Anomalies
one-time spikes or drops — what caused them and are they repeatable?
Leading indicators
which metrics change first and predict future outcomes?
Trend Analysis Process
Chart the metric over time (at least 8-12 data points for meaningful trends)
Identify the overall direction (upward, downward, flat, cyclical)
Calculate the rate of change (is it accelerating or decelerating?)
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
Model
How It Works
Best For
Limitation
Last touch
100% credit to last interaction before conversion
Understanding final conversion triggers
Ignores awareness and nurture
First touch
100% credit to first interaction
Understanding top-of-funnel effectiveness
Ignores nurture and conversion drivers
Linear
Equal credit to all touchpoints
Fair representation of all channels
Does not reflect relative impact
Time decay
More credit to touchpoints closer to conversion
Balanced view favoring recent interactions
May undervalue awareness
Position-based (U-shaped)
40% first, 40% last, 20% split among middle
Valuing both discovery and conversion
Somewhat arbitrary weighting
Data-driven
Algorithmic credit based on conversion patterns
Most accurate representation
Requires 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
Identify
which metrics are underperforming vs. target or benchmark?
Diagnose
where in the funnel is the problem? (impressions, clicks, conversions, retention)
Hypothesize
what is causing the underperformance? (audience, message, creative, offer, timing, technical)
Prioritize
which fixes will have the biggest impact with the least effort?
Test
design an experiment to validate the hypothesis
Measure
did the change improve the metric?
Scale or iterate
roll out wins broadly; iterate on inconclusive or failed tests
Optimization Levers by Funnel Stage
Funnel Stage
Problem Signal
Optimization Levers
Awareness
Low impressions, low reach
Budget, targeting, channel mix, creative format
Interest
Low CTR, low engagement
Ad creative, headlines, content hooks, audience targeting
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?"