Positive Review Analysis:
Review Collection:
This week, I am looking at positive reviews for Apple using google reviews. Using Chat GPT, I will analyze the reviews to find what customers are most satisfied about, key words in the reviews, and what is suggested in the reviews.
Analyzing Positive Reviews:
First Analysis:
To find information on how customers are feeling towards Apple, I gave Chat GPT a prompt along with 4 and 5 star reviews.
Prompt: What are the customers most satisfied with based on the reviews?
Chat GPT gave this response:
“Based on these reviews, customers are most satisfied with the service experience, especially the staff. A few clear themes show up repeatedly”
The main themes include:
-Exceptional customer service
-Knowledgeable and skilled employees
-Efficiency and problem solving
-Personalized and positive experience
-Store environment and experience
Second Analysis:
To find common words and associations in the reviews, I used the following the prompt.
Prompt: Extract positive keywords from those reviews, and analyze the frequency and associations of these keywords.
Chat GPT gave this response:
“Here’s a structured breakdown of positive keywords, along with their frequency and how they tend to cluster together (associations) based on the reviews you provided.”
Common words included:
-Friendly
-Helpful
-Professional
-Informative
-Efficient
Recommendation:
I asked Chat GPT to create marketing recommendations for Apple.
Prompt: What would be suggestions from the findings?
Chat GPT gave this response:
“Based on the keyword frequency and associations, the reviews point very clearly to what the store is doing well—and where it can double down or improve. Here are practical, insight-driven suggestions:”
Results included:
-Invest heavily in staff training
-Hire and reward personality, not just skill
-Maintain speed without sacrificing service
-Focus on complete problem resolution
-Expand educational and hands on experiences
Analyzing Negative Reviews:
First Analysis:
To find information on how customers are feeling towards Apple, I gave Chat GPT a prompt along with 1 and 2 star reviews.
Prompt: What are the customers least satisfied with based on the reviews?
Chat GPT gave this response:
“From these negative reviews, clear patterns of dissatisfaction emerge. Unlike the positive reviews (which were very consistent), the complaints cluster into a few major problem areas.”
The main themes include:
-Poor customer service
-Long wait times
-Lack of help
-Inconsistent treatment
-Poor problem resolution
Second Analysis:
To find common words and associations in the reviews, I used the following the prompt.
Prompt: Extract negative keywords from those reviews, and analyze the frequency and associations of these keywords.
Chat GPT gave this response:
“Here’s a structured negative keyword analysis from the reviews, including extracted keywords, frequency patterns, and how they cluster together (associations).“
Common words included:
-Disrespectful
-Unprofessional
-Long wait
-Left without service
-Rude
Recommendation:
I asked Chat GPT to create marketing recommendations for Apple.
Prompt: What would be suggestions from the findings?
Chat GPT gave this response:
“The negative keyword patterns point to a few clear operational and service breakdowns. Here are targeted, actionable suggestions directly tied to those findings:”
Results included:
-Fix customer service behavior
-Improve wait time management
-Create clear ownership of each customer
-Prioritize problem resolution over sales
-Improve communication channels
Personal Overview:
I thought it was interesting to see how Chat GPT can pull out this information from only giving it Google reviews. Chat GPT did a great job and picking out the key words to make the reviews short and snappy. It allowed me to be able to see what is going right and wrong with the company. This can be helpful in my future because I want to get into marketing research, so being able to understand where companies are going right and wrong can help the company I work for to make it better than competitors.
