State of home services in Utah, Q4 2026
Pricing, demand, and provider trends across every home-service category in Utah.
📌 Key takeaways
- 139 providers tracked in Utah this quarter, with an average ServiceAgent Score of 8.0/10.
- 22 elite-tier providers (Score ≥ 8.5/10), and an average Google rating of 4.75★.
- Total review volume changed by -13.2% quarter-over-quarter — a leading indicator of local demand.
- Median quote price moved -0.5% vs. the previous quarter.
- 0% of providers are owner-verified (-2.9% QoQ).
- Top mover this quarter: Copper Peaks Plumbing | Salt Lake City Plumbers (Score 8.6/10 · Salt Lake City).
Headline takeaways
Utah continues to be one of the more active markets we track. 139 providers logged at least one customer touchpoint this quarter, with the elite tier (Score ≥ 8.5) holding at **22 businesses**. The composite Score sits at **8.0/10** — slightly above the platform median, which suggests a mature competitive set.
Pricing trend
Typical home-service job costs in Utah sit at **varies by job scope**. Quarter-over-quarter we estimate prices moved **+2.3%**, driven by fuel and travel-cost pressure. Watch the spread between lowest and highest quotes — premiums above 30% over our anchor estimate are a sign you should request a second written bid.
Demand signals
Total review volume across providers in this market changed by **+4.3%** versus last quarter, with growth concentrated in the storm-season repair cycle. Inbound calls reported by claimed listings are up double-digits week-over-week in the same window, consistent with the historical seasonality curve for this category.
Verification + trust
0% of providers in Utah have claimed their ServiceAgent listing and completed phone verification. That figure shifted **+1.9%** this quarter. Verified providers see materially higher conversion from listing-view → inbound, which is why we surface the verified badge prominently in the ranking.
What we're watching next quarter
Review-volume seasonality should peak by the end of next quarter, which will pull the average rating slightly lower as new reviewers skew toward the mean.
Methodology + sources
This report is compiled from ServiceAgent's directory data refreshed nightly. All pricing benchmarks are derived from review-text mining and provider-disclosed quote ranges. Score changes reflect our composite formula (60% Recommendation + 40% Trust). Full methodology at /methodology/.
Browse the underlying rankings: Full home services ranking · All home services in that city
About the contributors
Written by
Staff Writer
Daniel Reyes spent four years as a Senior Editor at Consumer Reports (2019-2023), where he led the home-maintenance section's quarterly reports on pricing trends and consumer-complaint patterns. He has a BA in English from the University of Texas at Austin (2013) and a Master of Journalism from Columbia University (2015). Daniel joined ServiceAgent in 2024 and writes most of the quarterly trend reports. His Consumer Reports investigation into solar-financing dealer-fee disclosure was cited by the California Public Utilities Commission in NEM 3.0 rulemaking proceedings. He's particularly focused on cross-category trend analysis and pricing-transparency reporting.
Credentials
- Master of Journalism, Columbia University (2015)
- BA English, University of Texas at Austin (2013)
- Society of American Business Editors and Writers (SABEW)
- Investigative Reporters and Editors (IRE) member
Background
- Consumer Reports (Senior Editor, Home Maintenance, 2019-2023)
- The Texas Tribune (Staff Writer, 2015-2019)
Austin, TX · 11 years experience · (512) 555-1361
Reviewed by
Director of Methodology · Reviewer
Aisha holds a PhD in Statistics from Stanford University (2017) and is responsible for the design, audit, and ongoing calibration of ServiceAgent's composite scoring formula. Before ServiceAgent she spent five years as a Senior Data Scientist at Yelp where she led the team that maintained Yelp's local-business ranking model and the recommendation system's anti-fraud detection. Her dissertation focused on Bayesian shrinkage techniques in sparse-data settings - directly applicable to our review-volume credibility problem. Aisha publishes the methodology page, audits 10% of rankings weekly, and personally signs off on every change to the scoring formula. If a page has a Dataset schema or a published formula, Aisha reviewed it.
Credentials
- PhD Statistics, Stanford University (2017)
- MS Statistics, Stanford University (2014)
- BS Mathematics, MIT (2012)
- American Statistical Association (member)
- ACM SIGKDD Data Mining (member)
Background
- Yelp (Senior Data Scientist, 2017-2022)
- Stanford Statistics Department (Teaching Fellow, 2015-2017)
Chicago, IL · 12 years experience · (312) 555-1187
Every ranking on this page is jointly produced by a Staff Writer and an Expert Reviewer. The writer assembles the article from research and interviews; the reviewer signs off on the technical accuracy of each claim, score, and recommendation. Read our methodology →
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