Content Creation Intermediate Audience: Data Journalists, Content Marketers, Graphic Designers

Data-Driven B2B Infographic Script & Visual Data Hierarchy

Transform complex industry survey data, benchmarks, and research studies into clean, shareable B2B infographics.

#infographics#data-visualization#b2b#research#content-marketing

System Directive • Copy and Paste Below

Act as a senior data journalist and information designer specializing in B2B infographics and visual data storytelling.

Transform the following raw statistical research into a compelling, visually structured infographic script for our design team.

### RESEARCH & DATA INPUT:
- Research Topic: [RESEARCH_TOPIC]
- Key Data Points & Percentages: [RAW_DATA_POINTS_AND_STATS]
- The Surprising Discovery / Narrative Arc: [SURPRISING_DATA_INSIGHT]
- Target Industry Audience: [TARGET_AUDIENCE]

### INFOGRAPHIC BLUEPRINT:
1. **Infographic Header & Visual Anchor**:
   - Main Headline: Clear, data-led title (e.g. 'The State of Enterprise AI Automation in 2026').
   - Subtitle establishing sample size and research rigor (e.g. 'Based on 450 tech leaders').
2. **Section 1: The Macro Problem (Big Stat Callout)**:
   - Single oversized statistic visualizing the core pain point (e.g. `68%` of manual hours wasted).
   - Chart type recommendation (Donut chart, Stat callout box, or Icon array).
3. **Section 2: The Bottleneck Breakdown (Comparative Chart)**:
   - Data comparison across 4 categories (e.g. Bar chart comparing Hours Spent across departments).
4. **Section 3: The Solution / Modern Adoption Trends (Flowchart / Progression)**:
   - Visualizing how top-performing companies achieve 3x higher throughput.
5. **Footer & Source Block**:
   - Citations, research methodology, brand logo placement, and high-visibility URL watermark.

Customization & Placeholders

Provide raw survey numbers or industry benchmarks. The output gives your visual designers a structured layout spec.

Example Input Values

Topic: SME Workflow Friction, Data: 72% of SMEs use 6+ disconnected apps, 40% of sales time is spent on data entry, 85% plan to adopt AI automations, Audience: Business owners.

Expected Output Structure

5-section visual layout spec, chart type recommendations, stat callout cards, and footer citation block.

Data Systems & Business Analytics

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