Turn your chats into insights. Track conversations, trends, and performance — all in one dashboard.
onlyfans-conversational-analytics helps creators make sense of their conversations by turning raw chat data into easy-to-understand insights.
Once your conversations are analyzed, you’ll see all your key metrics visualized in an interactive dashboard where you can track engagement, response times, and audience sentiment over time.
Each topic or theme includes detailed metrics you can filter by date or time range:
| Metric | Description |
|---|---|
| Volume | Total number of conversations about a topic. |
| % of Total | How much of your overall chat activity that topic represents. |
| Trend | Shows whether conversation volume is growing or dropping compared to the previous period. |
| AHT (min) | Average handling time — how long your typical chat lasts from start to finish. |
| % Silence | Average percentage of silence time (no messages exchanged) across conversations. |
| Turns | Average number of times the conversation switches between you and your fan. |
| Sentiment | Average mood or tone of your fans, from 0 (negative) to 1 (positive). |
- 📊 See what topics drive the most engagement
- 🕒 Measure your response efficiency
- 💖 Understand your fans’ overall sentiment
- 🧠 Identify trends and performance patterns
- 🔧 Developer-friendly API for custom dashboards and integrations
Developer setup instructions coming soon.
For now, you can connect your data pipeline and visualize your chat analytics via the provided dashboard once conversations are ingested and processed by Insights.
The system design aligns with Azure Cosmos DB’s Gremlin API (for graph storage and traversal) and vector embeddings (for semantic similarity and NLP-driven inference).
Data pipelines process text via transformer-based NLP models, extracting entities and relationships to populate a Labeled Property Graph (LPG).
This architecture supports both:
- Creator analytics dashboards (via time-series and metric aggregation), and
- Psychotherapy research graphs (via semantic and relational modeling).
Built for creators who care about connection
This project also serves as a foundation for graph-based psychotherapy research, modeling interactions and interventions as interconnected nodes and edges to study relational and dynamic patterns of change.
See Research Releases for more information!