NPS Benchmarks in Salt Lake City, USA

Last update: January 1, 2026

Next update: February 1, 2026

Salt Lake City


Salt Lake City NPS (Overall)

Last Month29.70.00 pts
6 Months Ago30+0.30 pts
12 Months Ago30.2+0.50 pts

Salt Lake City NPS Evolution (Overall)

Industries Overview — Salt Lake City

# Industry NPS Δ vs 1M Δ vs 6M Δ vs 12M
1 Airlines 24 0.00 pts +1.00 pts +3.00 pts
2 Apparel 26 0.00 pts 0.00 pts -1.00 pts
3 Automotive Dealers and Service 27 +1.00 pts +3.00 pts +2.00 pts
4 B2B SaaS: Core Apps 45 +1.00 pts -2.00 pts +2.00 pts
5 Car Manufacturers 35 -1.00 pts -2.00 pts -1.00 pts
6 Consumer Electronics 27 0.00 pts -1.00 pts 0.00 pts
7 Consumer Services 36 -1.00 pts 0.00 pts -2.00 pts
8 Cosmetics and Beauty 33 -1.00 pts -2.00 pts -1.00 pts
9 Energy and Utilities 16 0.00 pts 0.00 pts 0.00 pts
10 Entertainment and Streaming 26 0.00 pts +1.00 pts +3.00 pts
11 Fintech and Digital Banking 43 -1.00 pts -2.00 pts -4.00 pts
12 General Retail, Multicategory 24 0.00 pts +4.00 pts +4.00 pts
13 Hotels and Resorts 40 +1.00 pts +5.00 pts +3.00 pts
14 Internet Service Providers 17 0.00 pts 0.00 pts 0.00 pts
15 Luxury Goods 39 +1.00 pts 0.00 pts 0.00 pts
16 Packaged Food and Beverage 25 -1.00 pts -1.00 pts 0.00 pts
17 Quick Service Restaurants 26 +1.00 pts -1.00 pts -3.00 pts
18 Restaurants, Full Service 27 0.00 pts +2.00 pts +2.00 pts
19 Sports Teams and Leagues 28 0.00 pts +2.00 pts +4.00 pts
20 Supermarkets and Grocery 30 0.00 pts -2.00 pts -1.00 pts

What it delivers?

The NPS Index Report gives you a clear view of customer loyalty across the markets that matter. Each month we compile Net Promoter Score benchmarks for key industries and break them down by country, region, and city. You see your space at a glance. Then you see your context. That combination turns NPS from a single number into a decision tool. Trends become visible. Seasonality is obvious. Outliers no longer trick you.

This report is built for operators and analysts who need to act. You get clean monthly snapshots, directional movement, and variance indicators that highlight where to dig. Want to know if your 3-point dip is noise or a real shift? You will know. Need to brief the team with one chart per market plus a short narrative? Done. Use the benchmarks to set realistic targets, size the gap to leaders, and test if new initiatives are moving the needle.

Data History

  • From January 2024: Data is available for Canada and the United States.
  • From September 2025: Data collection expands to include France, Spain, Italy and Germany.

Methodology

We aggregate public review data from platforms such as Google, TripAdvisor, and Yelp via a multi-source API, ingesting continuously and snapping everything to monthly windows. Listings are matched to real businesses using name, address, and category signals; duplicates and closed venues are removed to protect panel integrity.

Every review passes spam and anomaly checks that include burst detection, reviewer history scoring, language verification, and platform cross-validation. We run NLP to identify intent and experience dimensions, map native 0–10 recommendation answers directly when present, and otherwise infer promoter, passive, and detractor classes from text and rating context with calibrated thresholds. For each industry and geography, NPS is computed as promoters minus detractors, with Bayesian smoothing to stabilize low-volume samples and confidence ranges published alongside the point estimate.

We normalize categories to a unified industry taxonomy, align time zones, standardize language, and apply weighting so large markets do not overpower smaller ones within a region. Monthly values are reported as exact snapshots, and a rolling three-month view clarifies trend direction while preserving month-to-month comparability. We publish a monthly NPS only when minimum sample size and coverage criteria are met, with methods, thresholds, and known limitations disclosed in the report's technical notes.

Finally, models and pipelines are audited continuously with backtests and drift checks, and any detected bias or source change triggers a documented review and re-calibration.