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ProPilot qualifies comparable sales through a tier ladder: a cascade of matching rules that starts strict and loosens step by step until enough comps are found. The result is a comps value plus a quality grade that tells you how strict the underlying matches really are.
Key things to know
  • Tier 1 is the strictest match; the search only falls to looser tiers when it cannot find enough comps.
  • Two cleanup rules run on top of the ladder: price-per-sqft outlier removal and a list-price band that drops sales priced more than 50% away from the subject’s list price.
  • The grade (Excellent to Poor) comes from the average tier of the selected comps, not from the comp count.
  • If too few comps qualify, you get a clear message: “Insufficient comps: found X, need at least Y.”

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How comps qualify

Each candidate sale is tested against the tiers in order. A tier defines: The search collects qualifying sales tier by tier and stops as soon as it has enough comps to meet your org’s minimum. It does not keep descending into weaker tiers once the minimum is met, which keeps the result anchored to the best available matches. Admins can edit every tier’s radius, size window, bed/bath allowance, similarity floor, and grade in Advanced Settings > Comps.

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Cleanup after qualification

  • Outlier removal: sales whose price per square foot sits far from the local median are dropped so a single unusual sale cannot skew the value.
  • List-price band: comps with sale prices more than 50% above or below the subject’s list price are excluded. This filters out data errors and sales that are clearly a different class of property.
Both rules can occasionally remove a sale you consider valid. You can always re-include it manually with Use comp in the comps selector.

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Quality grade

The grade pill summarizes match quality: The grade is computed from the average tier of the comps actually used. If you hand-pick a selection, the grade updates to reflect the tiers of the comps you kept. Each comp also shows its own tier grade in the table and map popup so you can see which sales are dragging the overall grade down.

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Insufficient comps

If fewer comps qualify than your org’s minimum, no value is produced and the property shows “Insufficient comps: found X, need at least Y.” Your options, roughly in order:
  1. Recalculate to pull the latest sales data.
  2. Add Comp manually for sales you know about.
  3. Ask an admin to widen the tier ladder or raise Max Days Old in Advanced Settings > Comps.
  4. Lower Min Comps (last resort - fewer comps means a less reliable value).

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Discount badge

For Active listings, a badge compares the comps value to the list price:
  • 12% under - the property is listed about 12% below its comps value (potential discount).
  • 5% over - the property is listed above its comps value.
The same percentage appears as Discount in the comps selector header and updates live as you change the selection.

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Common questions

Four possibilities: it was removed as a price-per-sqft outlier, it fell outside the list-price band, it stopped passing tier rules (for example a settings change or the sale aged past Max Days Old), or Use comp was toggled off and saved.
The grade measures match strictness, not quantity. Ten comps from a loose tier still grade lower than five comps from the strictest tier. Check each comp’s tier in the table to see where the matches came from.
Yes. The grade depends on what sold nearby recently. A property in an active market can grade Excellent while an identical one in a thin market grades Fair because its comps came from looser tiers.
Most likely the list-price band: if the subject is listed well below market, legitimately higher-priced comps can land outside the plus or minus 50% band. Re-include them manually with Use comp if you trust them.
It can. The grade is recomputed from the average tier of the comps that remain selected, so removing a strict-tier comp and keeping looser ones lowers the grade, and vice versa.
Comps are deal-specific for one address, built from individual sales you can inspect. Neighborhood Benchmarks are area-level statistics for a census tract.

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Limitations

  • Neighborhood similarity depends on census tract data, which is missing in some areas; where unavailable, matching relies on distance and property filters alone.
  • MLS coverage varies by market. Off-market sales are not always captured, and distressed sales can skew values in heavily affected areas.
  • A grade describes match quality, not market certainty. Even Excellent-grade values deserve scrutiny in fast-moving or volatile markets.