# Analytics dashboard Human Guide

## What This Is For
Upload your LinkedIn Analytics export file (xlsx). It gives the agent a clearer input/output frame for marketing analytics: what context to ask for, what decisions to make, and what usable artifact to return.

Use this as a human-readable version of the Analytics dashboard agent skill. It is meant for marketers, operators, founders, and other non-coders who want the workflow without reading agent-specific implementation instructions.

## When To Use This
- Use this when you need a repeatable process for analytics dashboard.
- Use this when the task needs judgment, examples, constraints, or a clear output format rather than a one-off prompt.
- Use this when you want to hand an AI assistant enough context to produce a usable marketing artifact.

## When Not To Use This
- Do not use this when you only need a quick factual answer.
- Do not use this when the work depends on private data you cannot share with the assistant.
- Do not use this as a replacement for legal, compliance, financial, or medical review.

## What You Need Before Starting
- The goal or business outcome you want.
- The audience, customer segment, or market context.
- Any source material the assistant should respect, such as notes, briefs, examples, URLs, or brand guidance.
- Constraints such as tone, length, channel, deadline, region, or approval requirements.
- A clear definition of what a good final answer should look like.

## Step-By-Step Workflow
1. State the job clearly: "Use the Analytics dashboard guide to help me with..."
2. Add context: audience, goal, offer, channel, source material, and constraints.
3. Ask the assistant to identify missing inputs before producing the final output.
4. Have the assistant follow the skill-specific guidance below.
5. Review the result against the final checklist and ask for revisions where needed.

## Skill-Specific Guidance
- **DISCOVERY**: overall impressions and reach
- **ENGAGEMENT**: daily impressions and engagements over time
- **TOP POSTS**: top 50 posts, ranked by engagements and by impressions (two tables to merge)
- **FOLLOWERS**: daily new followers plus total count
- **DEMOGRAPHICS**: job titles, locations, industries, seniority, company size, top companies
- Average engagement rate (engagements / impressions)
- Daily impressions (left y-axis) and engagements (right y-axis) over the full date range
- Highlight the top 3 spike days with markers
- 7-day moving average trendline overlaid
- X axis: impressions. Y axis: engagements
- Colour-code posts into four quadrants:
- **Stars**: high reach + high engagement

## Decision Points And Nuance
The original skill emphasizes: CRITICAL: Auto-start on load, Step 1. Get the export file, Step 2. Parse the data, Step 3. Build the interactive dashboard, Headline metrics (top row cards), Engagement trend (line chart), Follower growth (area chart), Post performance scatter, Day-of-week heatmap, Audience breakdown (bar charts).

Use these questions to steer the work:
- What is the intended audience or buyer?
- What source material must be preserved?
- What should the assistant optimize for: clarity, persuasion, accuracy, speed, creativity, or conversion?
- What examples represent the desired quality bar?
- What should the assistant avoid?

## Common Mistakes
- Never invent metrics not present in the export.

## Copy-And-Paste Prompt
```text
Use the Analytics dashboard human guide.

My goal:
[Describe the business outcome]

Audience:
[Describe who this is for]

Context and source material:
[Paste notes, examples, links, or existing copy]

Constraints:
[Tone, length, channel, timeline, must-include items, must-avoid items]

Before producing the final output, ask me for any missing information that would materially improve the result.
```

## Final Checklist
- [ ] The output matches the original goal.
- [ ] The audience and context are reflected in the answer.
- [ ] Important constraints and source material were preserved.
- [ ] The assistant made the relevant decisions explicit.
- [ ] The final artifact is ready to use, review, or hand to the next person.

## Source
This guide was generated from the charlie947/social-media-skills skill entry for `analytics-dashboard`.

## Source Skill Notes
These notes preserve the nuance from the original skill. Use them as supporting reference when the workflow above feels too generic.

# Analytics Dashboard

## CRITICAL: Auto-start on load

When this skill triggers, go straight to Step 1.

## Step 1. Get the export file

Ask:

> Upload your LinkedIn Analytics export file (xlsx).
>
> Not sure how to get it? Go to LinkedIn Analytics, set your date range (30, 60, or 90 days works well), and click Export in the top right.

Wait for the file upload.

## Step 2. Parse the data

Read every sheet in the file. Expect these sheets:

- **DISCOVERY**: overall impressions and reach
- **ENGAGEMENT**: daily impressions and engagements over time
- **TOP POSTS**: top 50 posts, ranked by engagements and by impressions (two tables to merge)
- **FOLLOWERS**: daily new followers plus total count
- **DEMOGRAPHICS**: job titles, locations, industries, seniority, company size, top companies

Clean any messy headers. Merge the two TOP POSTS tables (by engagements and by impressions) into one unified dataset per post. De-duplicate.

## Step 3. Build the interactive dashboard

Create a single React artifact. Dark theme (background `#0f1117`), accent colours for charts. Use Recharts for all visualisations.

Include these panels in this order:

### Headline metrics (top row cards)
- Total impressions
- Total reach
- Total new followers
- Average daily impressions
- Average daily engagements
- Average engagement rate (engagements / impressions)
- Total posts tracked

### Engagement trend (line chart)
- Daily impressions (left y-axis) and engagements (right y-axis) over the full date range
- Highlight the top 3 spike days with markers

### Follower growth (area chart)
- Daily new followers
- 7-day moving average trendline overlaid
- Cumulative follower gain

### Post performance scatter
- X axis: impressions. Y axis: engagements
- Colour-code posts into four quadrants:
  - **Stars**: high reach + high engagement
  - **Viral but shallow**: high reach + low engagement
  - **Niche gold**: low reach + high engagement
  - **Underperformers**: low reach + low engagement
- Hoverable dots showing post URL and date

### Day-of-week heatmap
- Average impressions and engagements by day of week
- Highlight the strongest days

### Audience breakdown (bar charts)
- Job titles
- Industries
- Seniority
- Company size
- Top locations

### Formatting rules
- Format numbers: `67K` not `67000`, `1.2M` not `1200000`
- Total follower count prominent at the top
- Responsive layout (works on laptop and large display)
- Dark background, high contrast chart colours

## Step 4. Written strategic analysis