Does NPS Really Predict Revenue in Healthcare Clinics? I Spent 12 Weeks Finding Out.

Source: Dev.to

Why I Questioned NPS in Healthcare (The Origin Story)

For 6+ years grinding in Brazilian aesthetic healthcare clinics, I saw NPS treated like gospel: everyone worshipped NPS.

Every month: Net Promoter Score. No clinician, manager, or exec could point to data linking patient “loyalty” to the bottom line. That gap haunted me – and sparked my Master’s deep dive at Torrens University Australia, under Prof. Dr. Bushra Naeem (ICT R&D expert in digital transformation).

REM502’s structure turned this frustration into rigorous research:

• Assessment 1 – Critical Literature Review
  Dissected 12+ studies and pinpointed gaps. I zeroed in on NPS’s unproven link to financials – literature screamed “patient experience matters” (e.g., Godovykh & Pizam, 2023), but nothing validated a revenue correlation in healthcare. This identified the “knowledge gap” (emotion detection, sentiment‑to‑outcomes, NPS weaknesses) and set my direction: test it empirically.

• Assessment 2 – Research Tools & Methodologies
  Built on the gap, formalising my hunch into science. Crafted research questions (e.g., “Does NPS correlate with revenue growth?”), hypotheses (H1: Positive link), and a quantitative toolkit (Python pipeline for correlation/regression).

• Assessment 3 – Full Research Proposal
  Synthesised everything into a publication‑ready plan: pragmatic‑positivist design, ethics framework, and ICT software flow. It’s not just academic – it’s a blueprint for production BI systems.

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What the Research Says (And What’s Missing)

I reviewed 12+ peer‑reviewed studies across patient experience, NPS methodology, loyalty theory, and AI‑based feedback systems.

What we KNOW

• Patient experience improves loyalty (Godovykh & Pizam, 2023)
• NPS is widely used but criticised (Dawes, 2024)
• AI sentiment analysis is technically strong (Alkhnbashi et al., 2024)
• Patient feedback predicts operational quality (Shankar & Yip, 2024)
• Emotions affect engagement (Angelis et al., 2024)

What NO ONE HAS DONE

❌ Validate whether NPS statistically predicts revenue in healthcare.

That gap became my research question.

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The Dataset (27,000 Survey Responses, 36 Months)

Thanks to Pro‑Corpo Estética, a healthcare group in Brazil, I obtained:

Why this dataset is gold
It lets us test the common assumption: “When NPS goes up, revenue should go up too.”

Time to find out.

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The Data Pipeline (Python + Pandas + Statsmodels)

Workflow

Raw CSV
→ Cleaning & Missing Values
→ Outlier Detection
→ Aggregation (clinic‑month)
→ Derived Metrics (revenue growth %, lagged NPS)
→ Correlation Tests
→ Regression Modelling
→ Visualisations / Dashboard

Code Example: Correlation Analysis

import pandas as pd
from scipy.stats import pearsonr, spearmanr

df = pd.read_csv("clinic_nps_revenue_clean.csv")

# Calculate revenue growth
df['revenue_growth'] = df.groupby('clinic')['revenue'].pct_change() * 100

# Pearson Correlation
pearson_r, pearson_p = pearsonr(
    df['nps_score'].dropna(),
    df['revenue_growth'].dropna()
)

print(f"Pearson r = {pearson_r:.3f}, p = {pearson_p:.4f}")

Planned Models

• Pearson & Spearman correlation
• Linear regression (with lagged variables)
• K‑means clustering (clinic behaviour patterns)
• Visual dashboards (Streamlit)

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Does NPS Predict Revenue? (3 Possible Scenarios)

I built a decision‑impact framework:

Further resources

• GitHub:
• Portfolio: