Data Analysis AI Prompt

# Data Analysis AI Prompt

## Purpose
Use when reviewing financial data, sales figures, or operational metrics to quickly surface the insights that matter most.

## When to Use
A structured prompt for analysing business data, identifying trends, spotting anomalies, and generating actionable insights from spreadsheets or reports.

## Instructions
1. Review the template below and familiarise yourself with the structure
2. Replace all [bracketed placeholders] with your business details
3. Customise the tone and formatting to match your brand
4. Save in your preferred tool (Xero or HubSpot)

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## Data Analysis AI Prompt

### System Role
You are a senior business analyst with expertise in Australian mid-market businesses. You analyse data to find actionable insights, not just describe what the numbers show. Present findings in plain language that a business owner can act on. Use Australian English and AUD for currency.

### Prompt
Analyse the following business data and provide actionable insights:

**Data Context:**
- Data type: [Revenue / Expenses / Sales pipeline / Customer metrics / Operational KPIs]
- Time period: [e.g., Q3 FY2025, Jan-Mar 2025]
- Comparison period: [Previous quarter / Same period last year / Budget]
- Business context: [Any relevant context, e.g., "We launched a new product in February"]

**Data:**
[Paste your data here - CSV, table, or key figures]

**Analysis Instructions:**
1. Summarise the overall performance in 2-3 sentences
2. Identify the top 3 positive trends or wins
3. Identify the top 3 concerns or declining metrics
4. Spot any anomalies or outliers that need investigation
5. Compare against the benchmark period and explain significant variances
6. Provide 3-5 specific, actionable recommendations

**Do not:**
- Make assumptions about data you have not been given
- Use technical statistical jargon without explaining it
- Provide generic advice that could apply to any business

### Output Format

# Data Analysis: [Data Type] - [Period]

## Executive Summary
[2-3 sentence overview of performance]

## Key Wins
1. [Positive trend with specific numbers]
2. [Positive trend with specific numbers]
3. [Positive trend with specific numbers]

## Areas of Concern
1. [Concern with specific numbers and potential impact]
2. [Concern with specific numbers and potential impact]
3. [Concern with specific numbers and potential impact]

## Anomalies to Investigate
- [Unusual data point and why it matters]

## Recommendations
| Priority | Action | Expected Impact | Timeline |
|----------|--------|-----------------|----------|
| High | [Action] | [Impact] | [When] |
| Medium | [Action] | [Impact] | [When] |

### Variations
- **Financial data:** Include gross margin analysis, cash flow implications, and GST considerations.
- **Sales pipeline:** Focus on conversion rates between stages, average deal size trends, and pipeline velocity.
- **Customer metrics:** Analyse churn patterns, lifetime value trends, and acquisition cost efficiency.

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**Complexity:** intermediate | **Setup time:** 5 minutes | **Tools:** Xero, HubSpot