Forecast material trends to bid smarter and avoid cost overruns.
Small construction business owners lose money due to inaccurate job estimating that causes constant underbidding amid fluctuating material costs.
TrendBid analyzes historical and predictive material price data to recommend bid buffers for your jobs. Upload estimates, see trend charts and future projections powered by ML. Track win rates and profitability from data-driven bids.
Small construction business owners bidding on jobs
ML-powered trend forecasting specific to regional markets, beyond current prices.
friendly
Interactive graphs of material prices over time.
ML predicts next 30/60/90 day prices.
Suggests % markup based on volatility.
Input bid, get trend-adjusted version.
Log bids vs wins to improve forecasts.
Location-specific trends.
Share trend reports with clients.
Train on user data.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| location | text | Yes |
| created_at | timestamp | No |
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| name | text | No |
| forecasted_total | int | Yes |
| outcome | text | Yes |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| estimate_id | uuid | No |
| material | text | No |
| historical_avg | int | No |
| forecast_30d | int | Yes |
| volatility_pct | int | Yes |
Relationships:
/api/estimatesCreate and analyze estimate
/api/trends/:materialGet trend data
/api/forecast/:idRun ML forecast
/api/user-estimatesList user's estimates
/api/winrateCalculate win stats
No buffers
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 120 | 2% | $36 | $432 |
| Month 6 | 600 | 7% | $630 | $7,560 |
Trend analysis stops underbidding before it starts.
Run Google ads on 'construction material price trends'. Share free trend reports in contractor newsletters. Cold email from Angie’s List contractors.
Scheduling
No forecasting
Trend-specific, solo-focused
User-submitted outcomes improve ML accuracy (data moat).
AI maturity + ongoing inflation volatility.
ML forecast inaccuracy
Ensemble models + disclaimers
High AI compute costs
Cache predictions
Success: 50+ responses, 70% interest
Success: 200 signups
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