README.md

metadata

pretty_name: EU-Retail-UX-Feedback-Live
license: cc-by-4.0
language:
  - en
  - fr
  - de
multilinguality:
  - multilingual
size_categories:
  - n<10K
task_categories:
  - text-classification
tags:
  - ecommerce
  - retail
  - user-experience
  - customer-feedback
  - sentiment-analysis
  - text-classification
  - multilingual
  - ux
  - customer-service
  - product-reviews
  - tabular
  - text
  - timeseries
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/ux_feedback_live.parquet

EU-Retail-UX-Feedback-Live

Real-time, GDPR-anonymised user-experience (UX) feedback collected from the e-commerce website, mobile app and customer-service platform of a large European retail company (1000+ employees) operating in the United Kingdom, France and Germany. The dataset is refreshed every 30 minutes, and every published version is immutable, checksummed and taggable so it is fully auditable and rollback-able.

Quick summary

Attribute	Value
Dataset name	EU-Retail-UX-Feedback-Live
Refresh cadence	every 30 minutes
Encoding	UTF-8
Markets	United Kingdom, France, Germany
Languages	en-GB, fr-FR, de-DE
Latest version	v1.2.0
Total records (latest)	6,498
License	CC BY 4.0

Why this dataset exists

To continuously optimise the customer experience, the company collects feedback across the full shopping journey — page loading speed, search relevance, product recommendations, checkout flow, delivery experience and after-sales support. This dataset powers:

• sentiment analysis / rating prediction models,
• multilingual text-classification of experience dimensions,
• root-cause analysis of UX pain points per market,
• dashboards tracking CX health over time.

Data fields / schema

Each record contains the following fields:

Column	Type	Description
feedback_id	string	Unique record identifier (pseudonymous).
user_pseudo_id	string	Pseudonymous user identifier (HMAC-SHA256, not reversible without salt).
session_id	string	Pseudonymous browsing/session identifier.
market_region	string	United Kingdom, France or Germany.
country_code	string	ISO 3166-1 alpha-2 code: GB, FR, DE.
language	string	BCP-47 language tag: en-GB, fr-FR, de-DE.
timestamp	string	ISO 8601 UTC timestamp of the feedback event.
experience_dimension	string	One of 6 dimensions (see below).
rating	int	Score from 1 (very poor) to 5 (excellent).
feedback_text	string	Free-text feedback, UTF-8 encoded, in the market language.
device_type	string	desktop, mobile or tablet.
source_channel	string	website, mobile_app or customer_service.

Experience dimensions

page_load_speed, search_relevance, product_recommendations, checkout_flow, delivery_experience, after_sales_support

Coverage

• Markets: United Kingdom (GB), France (FR), Germany (DE) — balanced, 1/3 each.
• Languages: en-GB, fr-FR, de-DE (feedback text matches the market language).
• Channels: website, mobile app, customer service.
• Devices: desktop, mobile, tablet.
• Time range: rolling 24h window, refreshed every 30 minutes.

GDPR compliance (pseudonymisation & minimisation)

This dataset was built in line with the EU General Data Protection Regulation (GDPR) (Regulation (EU) 2016/679). The pipeline performs:

1. Deletion of direct identifiers — fields user_email, user_name, phone_number and address are dropped and never published. No direct personal data is present in this dataset.
2. Pseudonymisation — the real user identifier is replaced by a pseudonymous ID derived with HMAC-SHA256 plus a secret salt (user_pseudo_id), and session identifiers are pseudonymised as well (session_id). The salt is stored separately and access-controlled, so the mapping cannot be reconstructed from the published data.
3. Free-text scrubbing — residual PII patterns (e-mail addresses, phone numbers, UK/FR/DE postcodes, card-like numbers) are redacted from the feedback_text field before upload.
4. Data minimisation — only the attributes required for UX analytics are published; no financial, biometric or sensitive data is collected.
5. Purpose limitation & retention — pseudonymised records are retained only for as long as needed for CX analysis; raw (identifiable) data is held in a restricted internal store with a short retention policy and is never uploaded to the Hub.

Full documentation of the anonymisation measures is provided in gdpr/anonymisation_report.md and the reproducible pipeline is in scripts/generate_ux_feedback.py.

⚠️ This dataset contains synthetic feedback used for demonstration and model-development purposes. No real customer data is included.

Versioning & auditability

The dataset is updated every 30 minutes. Version management follows semantic versioning and is designed to be auditable and rollback-able:

• Immutable snapshots are stored under snapshots/<version>/.
• Every version has a SHA-256 checksum (parquet and CSV) recorded in versions/manifest.json.
• A human-readable history is maintained in versions/CHANGELOG.md.
• Each published version corresponds to a git commit/tag on the Hub (v1.0.0, v1.1.0, v1.2.0, …), so any previous version can be restored with a single checkout (rollback).
• The canonical, latest snapshot always lives at data/ux_feedback_live.parquet.

Version	Window (UTC)	Added	Total	SHA-256 (parquet)
v1.0.0	2026-08-12T13:47 → 2026-08-13T13:47	4,998	4,998	3882044c…e54
v1.1.0	2026-08-13T13:47 → 14:17	750	5,748	e0488237…ccb
v1.2.0	2026-08-13T14:17 → 14:47	750	6,498	1365bc41…875

Usage

from datasets import load_dataset

ds = load_dataset("toolathon123/EU-Retail-UX-Feedback-Live", split="train")
print(ds)

import pandas as pd
df = pd.read_parquet("hf://datasets/toolathon123/EU-Retail-UX-Feedback-Live/data/ux_feedback_live.parquet")

Limitations

• Synthetic data: the free-text feedback is generated, not collected from real customers, and may not fully reflect real-world language variation.
• The dataset is refreshed continuously; results should always be pinned to a specific version (e.g. v1.2.0) for reproducible experiments.
• Ratings are not expert-verified; treat them as user-reported signals.