Sasquatch Sightings Intelligence Platform
Where data science meets cryptid folklore
Product Hypothesis
"Bigfoot reports cluster where bear populations are sparse—either we've found behavioral evidence of an unknown species, or we're about to revolutionize bear misidentification studies."
The Data Matrix
| Data Source | Features | My Adjustments |
|---|---|---|
| BFRO Reports | 50K+ sightings since 1958 | Cleaned hoax flags, geocoded missing coordinates |
| USGS Bear Data | Population density by county | Created "misidentification probability" scores |
| Census Data | Human population density | Weighted sightings by reporter likelihood |
Deliverables
- Tableau dashboards showing heatmap correlations between:
- Sighting clusters vs. bear territories
- Report frequency vs. human population density
- Misidentification scoring system (because let's be real—some "squatches" are just drunk bears)
- Public-facing filters so researchers can control for:
- Time of year (breeding season = more false IDs?)
- Report credibility (Class A vs. Class C sightings)
Product Roadmap
| V1 (May) | Visualization tool for researchers | → Basic correlation analysis |
| V2 (Future) | Crowdsourced verification | → "Confirm/deny" voting for sightings |
| V3 (Later) | Academic API | → Auto-alerts for new cluster patterns |
Stakeholder Pitch
"Right now, cryptid research runs on coffee and folklore. My platform replaces guesswork with data-driven hot zones—so you can:
- Prioritize field surveys using misidentification probability scores
- Allocate resources based on credible sighting clusters
- Publish papers with statistically significant patterns
Because if Bigfoot exists, we'll find it. And if not? We'll at least understand why thousands of people keep seeing giant hairy things in the woods."