Our Cost Methodology

How we source our cost information

Pricing in home services varies enormously. The same job can differ by hundreds or thousands of dollars depending on your region, the age and condition of your home, the materials you choose, the season, and which contractor you hire. A range that holds in Cleveland can be well off in San Diego.

Treat our numbers as the shape of the cost, not the cost itself. We are explicit about this because most cost guides are not. If a figure is presented to you as precise, ask where it came from.

The evidentiary hierarchy we use

Not all published prices are evidence of the same quality. We rank sources by how close they sit to an actual transaction, and a figure’s verification status depends on which tiers support it.

A figure is not marked verified on Tier 3 evidence alone. This matters more than it sounds, because Tier 3 is where most cost content on the internet lives, and a large share of it is published by lead-generation marketplaces whose pricing pages exist to move a reader into a quote form. That business model does not make their numbers wrong. It does mean the numbers were not produced to be accurate — they were produced to be plausible enough to keep someone reading until the form appears, and nobody is contractually bound by them afterward.

We read those sources. We use them to triangulate and to check whether we are an outlier. We do not count them as proof, and we do not cite them as authority.

We also weight convergence over volume. Three sites repeating the same figure is not three sources if the figure has one origin, and in this category it very often does. Two independent Tier 1 prices that agree are stronger evidence than a dozen Tier 3 pages that agree with each other.

Normalizing before comparing

The most common way a cost guide misleads is not by publishing a false number. It is by publishing a true number for a different thing. Before comparing any figure to a source, we normalize on three axes:

• Scope. Materials-only, installed, or turnkey. A materials price presented as an installed price understates by roughly the labor share of the job — frequently half of it.
• Unit. Per square foot, per linear foot, per room, per fixture, per visit, or a project total. Per-unit figures are only comparable after multiplying through by a stated typical quantity.
• Component versus system. The price of a deck surface is not the price of a deck; framing, railings, and stairs are part of the object a homeowner is buying.

Where a figure survives normalization and still disagrees with Tier 1 sources, it is an error. Where the disagreement disappears once the unit is corrected, it was a labeling failure — which we treat as an error too, because a reader cannot be expected to detect it.

Our first audit, and what it found

In August 2026 we ran the first formal audit of our own cost data, and we are publishing the result rather than describing the process and leaving you to assume it went well.

Design. We sampled 25 headline cost figures — the summary range that opens a cost article. Selection was stratified by service: one figure per service, drawn at even intervals across the alphabetized list of the 84 services that had a parseable headline range, so that the sample spanned the taxonomy rather than clustering in one trade. Each figure was then checked against sources retrieved at the time of the audit, under the hierarchy above, and classified with a fixed rubric.

Stated plainly: roughly a quarter of the figures we checked were materially wrong, and another quarter were too broad to be useful. About half did the job we publish them to do.

Precision of these estimates. Twenty-five is a small sample and we will not pretend otherwise. The 95% confidence interval on the materially-wrong rate runs from 12% to 43%; on the sound rate, from 34% to 70%. The true figures are somewhere in those bands, and a larger audit will move them. We are reporting a first measurement, not a settled fact.

Error analysis

The errors were not random. Five of the six wrong figures were wrong in the same direction — too low — and they failed through the same mechanism: the bottom of the range was a materials-only, component-level, or best-case price presented as an installed, typical one. Examples we corrected included a composite decking figure that priced the deck surface rather than the deck, a fence figure below any installed price we could find for even the cheapest material, and an appliance service-call figure that turned out to be an hourly labor rate wearing a flat-fee label.

A secondary pattern appeared in articles that passed: stated averages tended to sit at or below the floor of Tier 1 installed pricing. An average beneath the manufacturer’s own entry-level installed price is not an average.

What the statistics do and do not support. Five of six errors falling in one direction is suggestive, but at this sample size it is not statistically significant — a sign test returns p = 0.22, which is comfortably within what chance produces. What raises our confidence is not the count but the mechanism: unit substitution can only ever bias a figure downward, because the excluded component always has a non-negative cost. We are treating the low bias as a real and directional effect on mechanistic grounds while being clear that the sample alone does not establish it.

This distinction matters to us because it determines the remedy. Random error is fixed by checking figures one at a time. Systematic error is fixed by changing the rule that produced it — in this case, requiring that any range labeled “installed” have an installed price at its floor.

A method that did not work

We first attempted to find these errors by script, on the theory that a mechanical pattern could be detected mechanically across the whole library. That attempt failed, and the failure is instructive enough to report.

The scanner flagged 344 articles. Hand-checking a sample of the flags found that nearly all were defects in the scanner rather than in the articles: two materials priced differently within one article were read as a self-contradiction, unrecognized units such as per board foot and per cubic yard were parsed as dollar totals, and articles opening with a table had a table row mistaken for their headline figure. The flag list was discarded in full.

A corrected pass produced a cleaner and more useful negative result. Across 242 headline figures, zero contained an internal contradiction — every figure agreed with every other figure in the same article. That internal coherence is why automated detection cannot work here: our figures are consistently wrong in the same direction rather than randomly inconsistent, and consistency is invisible to a consistency checker. Verification requires comparison against the outside world, one figure at a time.

Known limitations

• The sample was stratified, not randomized. It spans the taxonomy but is not a probability sample, so the confidence intervals above should be read as indicative rather than exact.
• Only headline figures were audited. Our library contains roughly 9,995 distinct dollar ranges; the 242 headline figures are about 2.4% of them, and they are the subset most likely to be read and least likely to be checked by a reader.
• All figures are national. We do not currently publish regional adjustments, and regional variation is frequently larger than the error rates reported here.
• Published prices drift. A verification is a statement about a date, which is why we show the date.

What we changed

• The identified errors were corrected against the sources that contradicted them.
• Any range labeled “installed” must now carry an installed price at its floor.
• Articles whose figures have been checked carry a dated verification line beside the numbers. Articles without that line have not been checked.
• Verification is proceeding outward from the figures homeowners search for most.

Corrections

If a number here looks wrong, tell us. We would rather fix a figure than defend it. Include the article and the number you are questioning, and if you have a quote in hand that contradicts us, that is the most useful thing you can send.

Corrections are not a formality. The most valuable evidence we receive comes from homeowners who have just been quoted a real price on a real house, because that is the one figure no published source can give us.

Common questions

Cost information is reviewed at least twice a year. Audit of record: August 2026. This page last reviewed: August 2026.