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Customer issue
Context
This company (confidential, ongoing), an innovative company, specialized in AI, wanted to create a an automated revenue analysis system leveraging no-code tools and AI.The goal was to design an automated workflow where users could enter financial data via a form and receive an in-depth analysis of revenue risks, underlying causes, and AI-generated strategic recommendations. The results would be stored in Airtable and presented in an interactive dashboard..
ActivDev developed aey automation steps. comprehensive blueprint for AI DANGER, utilizing Make (Integromat), GPT-4, Perplexity AI, Typeform, and Airtable.This case study outlines our approach and key automation steps.
The Challenges
Confidential SaaS faced the following challenges:
- Manual data collection – No structured process for gathering financial indicators.
- Lack of advanced AI analysis – Needed an intelligent system to identify trends and risks.
- No interactive dashboard – Required a visual tool for decision-making.
- Incomplete automation – Needed seamless integration between multiple no-code tools.
Work carried out by ActivDev
ActivDev developed aey automation steps. a complete blueprint for an automated revenue analysis system based on:
Data Collection via Typeform
An interactive Typeform was set up to collect structured data:
- Company name, industry, revenue model
- Sales and marketing data (CAC, ARPU, conversion rate, churn rate, etc.)
- Business challenges (low traffic, pricing issues, customer acquisition, etc.)
- Contact details and report preferences
Automation with Make.com and AI Analysis
Once the form is submitted, Make triggers an automation sequence:
- Data processing and storage – Structuring and storing data in Airtable (Raw Data Table).
- AI analysis with GPT-4 – Sending data to OpenAI's API to:
- Identify major financial risks
- Analyze root causes (internal & external factors)
- Generate three strategic action steps
- Real-time market insights with Perplexity AI
- Research industry trends and competitor benchmarks
- Analyze common challenges for similar businesses
- Merging AI results – GPT-4 integrates Perplexity AI insights for a hybrid analysis.
- Risk scoring system – Automatically categorizing businesses as High, Medium, or Low Risk.
Visualization with Airtable Interface Designer
To facilitate result interpretation, an Airtable dashboard was proposed:
- Revenue trends – Graphs comparing historical and projected revenue.
- Risk indicators – Color-coded danger levels (High, Medium, Low).
- Cause analysis – AI explanation of negative trends.
- Strategic recommendations – Corrective actions suggested by GPT-4.
- Automated PDF report generation (optional).
Slack Alerts for High-Risk Cases
For optimal responsiveness, a Slack Webhook was added to:
- Send real-time alerts for high-risk cases.
- Share a link to the dashboard and PDF report.
Automated PDF Report Generation
A detailed analysis report was designed using DocuPilot:
- Structured report with AI recommendations.
- Download link sent via Slack and email.
- Automatic archiving in Google Drive.
Results and Impact
- 70% reduction in revenue analysis time.
- Actionable AI insights – GPT-4 provided tailored risk assessments.
- Real-time market data – Perplexity AI ensured up-to-date and relevant insights.
- Automated reporting – No manual processing required.
- Dynamic dashboard – Instant visualization of AI-generated results.
Why This Approach Revolutionizes No-Code Automation
This case study highlights the power of no-code and AI for optimized decision-making:
- GPT-4 for strategic intelligence
- Perplexity AI for real-time market tracking
- Make.com for workflow automation
- Airtable for interactive and customized reporting
- Slack and PDF Automation for efficient collaboration
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Results
70% reduction in revenue analysis time.