NPS Benchmarks in Italy

Last update: January 1, 2026

Next update: February 1, 2026

Italy


Italy NPS (Overall)

Last Month33.2+0.10 pts
6 Months AgoN/An/a
12 Months AgoN/An/a

Italy NPS Evolution (Overall)

Italy's Cities Overview — All Industries combined

# City NPS Δ vs 1M Δ vs 6M Δ vs 12M
1 Bari 32.1 -0.20 pts n/a n/a
2 Bologna 34.9 +0.20 pts n/a n/a
3 Catania 32.4 -0.50 pts n/a n/a
4 Florence 33.6 0.00 pts n/a n/a
5 Genoa 31 +0.20 pts n/a n/a
6 Milan 33.9 +0.30 pts n/a n/a
7 Naples 31.9 0.00 pts n/a n/a
8 Palermo 31.7 +0.10 pts n/a n/a
9 Rome 33.8 +0.30 pts n/a n/a
10 Turin 32.4 +0.10 pts n/a n/a
11 Venice 34.8 +0.10 pts n/a n/a
12 Verona 34.8 +0.50 pts n/a n/a

Industries Overview — Italy (All Cities Combined)

# Industry NPS Δ vs 1M Δ vs 6M Δ vs 12M
1 Airlines 31.6 +0.10 pts n/a n/a
2 Apparel 28.2 -0.40 pts n/a n/a
3 Automotive Dealers and Service 33.6 +0.20 pts n/a n/a
4 B2B SaaS: Core Apps 43.6 -0.20 pts n/a n/a
5 Car Manufacturers 36.6 +0.40 pts n/a n/a
6 Consumer Electronics 29.8 +0.20 pts n/a n/a
7 Consumer Services 32.1 -0.30 pts n/a n/a
8 Cosmetics and Beauty 36.6 -0.10 pts n/a n/a
9 Energy and Utilities 17 0.00 pts n/a n/a
10 Entertainment and Streaming 28.3 0.00 pts n/a n/a
11 Fintech and Digital Banking 43 0.00 pts n/a n/a
12 General Retail, Multicategory 30.2 +0.30 pts n/a n/a
13 Hotels and Resorts 49.4 0.00 pts n/a n/a
14 Internet Service Providers 22.3 -0.30 pts n/a n/a
15 Luxury Goods 47.7 +0.40 pts n/a n/a
16 Packaged Food and Beverage 24.7 -0.50 pts n/a n/a
17 Quick Service Restaurants 29.2 +0.80 pts n/a n/a
18 Restaurants, Full Service 37.3 +0.50 pts n/a n/a
19 Sports Teams and Leagues 32.6 -0.10 pts n/a n/a
20 Supermarkets and Grocery 28.2 +0.30 pts n/a n/a

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.