Lulu And Georgia Customer Experience Dashboard

Our Data & Methodology

This report explains the insights on the main dashboard which is shown below. To build our analysis, we first had to create a reliable dataset. While Trustpilot publicly shows a total of 5,457 reviews, our data scrape was able to retrieve 5,080. From that group, we then identified and removed 144 duplicate entries. This leaves us with a clean, final dataset of 4,936 unique customer reviews spanning from 2019 to 2025. All the charts and KPIs on the dashboard are based on this accurate number.

Data Source: Trustpilot

Link to the Dataset: Download

Understanding Our Dataset

To build the analysis, we began by scraping 16 fields from Trustpilot and then enriched this data by creating four new columns using Natural Language Processing (NLP).

Original Scraped Data Fields:

Title: The headline of the customer's review.

Title_URL: The direct web link to the review.

Customer_Icon: The icon or image for the customer's profile.

Customer_Name: The name of the customer who left the review.

Location: The customer's country.

Review_Date: The date the review was originally posted.

Rating_Image_URL: A link to the star rating image.

Customer_Rating: The star rating the customer gave (1-5).

Customer_Review: The full written text of the customer's feedback.

Other_Reviews_Customer: Number of reviews he had given to other companies.

Updated_Date: The date the review was last updated by the customer, if any.

Updated_Comment: The text of the customer's update, if any.

Review_Through_Link: Notes on how the review was sourced ("Organic feedback" or "Through Link").

Reply: Whether support responded or not.

Support_Reply_Date: The date the company responded.

Support_Response: The full text of the company's public reply.

New Enriched Data Fields (Created via NLP):

Customer_Review_Reason: Tells us the main topic of the complaint (e.g., "delivery issue").

Category: Shows the main product category being discussed (e.g., "Furniture," "Rugs").

Sub_Category: Identifies the specific sub-category (e.g.,"Area Rugs," "Home Lighting").

Gender: Obtained from the customer's name for demographic context.

Key Metrics & Visualizations

Key Performance Indicators (KPIs)

Total Reviews

Avg Rating

Response Rate

Charts and Visualizations

Rating Distribution (Donut Chart)

Review Volume by Product Category (Vertical Bar Chart)

Customer Complaint Reasons (Horizontal Bar Chart)

Customer Reviews Over Time (Line/Area Chart)

Review Breakdown by Gender (Pie Chart)

Recent Customer Reviews (Table)

Summary

Based on our analysis of nearly five thousand customer reviews, the overall 3.42 out of 5 average rating is not the main story. The most important finding is that our customer experience is highly polarized. We have a large group of very happy customers, with 2,814 leaving a perfect 5 star review, but we also have a very large group of extremely unhappy customers, with 960 leaving a 1 star review. This shows that the customer journey is inconsistent, resulting in either a great experience or a terrible one.

Our analysis has pinpointed the exact cause of this negative feedback. The number one complaint, by a wide margin, is "Delivery Issue". This single problem was mentioned 799 times. To put that in perspective, this is more than double the next closest issue, "general feedback", which had 373 mentions. We also see that this problem is directly tied to our key product categories, "Furniture" and "Rugs" , which are our most reviewed items. This strongly indicates that the logistics and fulfilment process for these large, bulky items is the primary source of customer frustration.

The key takeaway is that the path to improving our overall rating is clear. We must focus on preventing the 1 star experiences by addressing this core operational problem. Improving the delivery process for furniture and rugs will have the single biggest impact on customer satisfaction. The data also highlights a clear opportunity to improve our engagement, as our team currently replies to about 36 percent of all reviews. By responding to more of this feedback, we can solve problems and gather more detailed insights.

Live Dashboard

https://lookerstudio.google.com/u/0/reporting/0b6aa4af-2f5f-407a-95a0-ae49f4ee7f25/page/p_dvn0zo6bxd