British Airways Customer Review Dashboard

Project Overview

This project develops an interactive Tableau dashboard for exploring 1,324 British Airways customer reviews across time, geography, aircraft, traveler type, seat class, and multiple service dimensions.

The objective was not simply to visualize review data, but to build a compact decision-support interface that allows a user to move between high-level performance signals and more detailed customer-experience patterns.

Interactive Tableau Dashboard

Use the dashboard below to select a service metric and filter the review population by time, traveler type, seat class, geography, or aircraft.

Business Question

Customer-review data can contain useful information about service quality, but individual reviews are difficult to interpret at scale.

This dashboard was designed to answer questions such as:

• How do overall customer ratings change over time?
• How does customer experience differ by traveler type and seat class?
• Are there meaningful geographic differences in review patterns?
• How do ratings compare across aircraft types?
• Which service dimensions appear stronger or weaker?
• How can a reviewer move quickly between broad trends and more specific segments?

The result is an exploratory dashboard that supports both summary-level review and targeted filtering.

Data

The analytical dataset contains 1,324 British Airways customer reviews spanning March 2016 through October 2023.

Review data includes:

• overall rating;
• recommendation status;
• traveler type;
• seat class;
• aircraft;
• route;
• review date and flight date;
• seat comfort;
• cabin staff service;
• food and beverages;
• ground service;
• value for money; and
• entertainment.

A separate country reference table provides country, country code, continent, and region fields used to support geographic analysis.

Dashboard Design

The Tableau workbook is organized around four analytical views:

Summary

Provides the selected metric at a high level so users can quickly understand the current filtered population.

Monthly Trend

Shows how the selected metric changes over time, making it possible to identify changes in customer experience across the review period.

Geographic View

Maps review performance geographically using country-level review information joined to continent and region attributes.

Aircraft Comparison

Compares the selected metric across aircraft groups to support equipment-level exploration.

These views are combined into a single dashboard so the same filters and selected metric can be applied across multiple analytical perspectives.

Interactive Controls

A parameter-driven metric selector allows users to switch among:

• Overall Rating
• Cabin Staff Service
• Entertainment
• Food
• Ground Service
• Comfort
• Value

Additional filters allow the dashboard to be segmented by:

• review date;
• traveler type;
• seat class;
• continent; and
• aircraft.

This design reduces the need for separate dashboards for every service measure while allowing users to explore the same business question from several dimensions.

Key Findings

Several patterns are visible in the review data:

• The full dataset averages approximately 4.19 out of 10 for overall rating.
• 572 of 1,324 reviews recommend British Airways, representing roughly 43% of the sample.
• Average overall ratings were materially lower in 2023 than in several earlier years in the dataset.
• Solo Leisure reviewers show a higher recommendation rate than Business travelers in the source data.
• The review population is geographically concentrated in Europe, which should be considered when interpreting geographic comparisons.

These findings are descriptive rather than causal. The dashboard is intended to support exploration and pattern identification rather than establish why a particular customer group or time period received a given rating.

Data Quality and Limitations

The dashboard should be interpreted as an exploratory customer-review analysis rather than a representative measure of the entire British Airways customer population.

Important limitations include:

• the dataset reflects submitted reviews rather than a random customer sample;
• review volume varies materially by year;
• geography is concentrated in a relatively small number of markets;
• aircraft labels are not fully standardized across every record;
• service-specific fields contain unrated responses represented by sentinel values in the source data and must be excluded from average-rating calculations; and
• customer-review data can reflect selection bias because customers with unusually positive or negative experiences may be more likely to submit reviews.

These limitations are important when translating dashboard patterns into operational conclusions.

Decision-Support Value

The dashboard demonstrates how customer-feedback data can be transformed into a usable exploratory decision-support tool.

A business user could use the interface to:

• identify periods of declining or improving customer ratings;
• compare customer experience across traveler segments;
• examine differences among seat classes;
• identify service dimensions requiring deeper investigation;
• compare aircraft-level review patterns; and
• isolate geographic segments for additional analysis.

The dashboard is designed to support investigation and prioritization rather than replace deeper operational or causal analysis.

Skills Demonstrated

This project demonstrates practical capability in:

• Tableau dashboard development;
• calculated fields and parameters;
• interactive filtering;
• dashboard layout and visual hierarchy;
• temporal analysis;
• geographic analysis;
• categorical comparison;
• data integration;
• customer-experience analytics;
• exploratory data analysis; and
• analytical communication and decision support.

Technical Evidence

Tableau Public

Project Files

The portfolio project is supported by:

• the Tableau workbook;
• the British Airways review dataset; and
• the country / geography reference dataset.

Project Status

Interactive dashboard complete and published to Tableau Public.

The portfolio case study adds business framing, methodology, analytical interpretation, limitations, and direct access to the live interactive dashboard. '''