Pricing

Roofing Price Library Software for Accurate Claims

Build a private price standard for roofing trades and reduce underpricing in active claims.

Built on your own claim and scope history, not public assumptions.

Pricing consistency

stronger estimator discipline

Recovery potential

missed-line visibility

Decision speed

fewer manual checks

Standardization

fewer outlier values

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Why this page

Protect margin by replacing guesswork with structured pricing references.

  • Private rate histories by trade and material.
  • Missing line suggestions from historical patterns.
  • Consistent pricing support for estimates and supplements.

Document excerpts

Production-ready document templates for internal review and client-facing rollout:

Price library anomaly alert (sample)

Pricing Intelligence

Roof replacement line audit

Observed premium value may be outside normal claim range for 30+ year asphalt shingle replacements.

Historical min / avg / max: $15,400 / $16,700 / $19,500
Current draft: $23,200
Recommendation: add scope note and confirm line justification before send.

Private pricing intelligence

Create a living library from completed claims.

  • - Trade-level line history
  • - Min/max/avg references
  • - Region-aware pricing context

Estimate strength checks

Detect when key lines are outside expected ranges.

  • - Auto-flags in active jobs
  • - Recovery-aware recommendations
  • - Estimate review support

Supplement support

Find likely add-backs before claim closure.

  • - Comparative line references
  • - Gap notifications
  • - Historical trend support

Frequently asked questions

Can this replace our existing spreadsheet?

It can replace fragmented sheets and keep pricing inside one workspace.

How does it improve estimates?

It highlights expected ranges and potential underpriced lines.

Can pricing be restricted by team

Access is controlled by workspace roles and permissions.

How often does it refresh?

The library grows as claims and scopes are added.

Can we compare by trade and geography?

Yes, data can be grouped by job type and location context.