Analyzing Online Reviews & Suggestions – Midwest Marketing
- Positive review analysis
For the positive review analysis, I will go to Google Maps to retrieve reviews posted. Then taking all 5-star ratings and placing them into Chatgpt, I ask AI what customers are most satisfied with. Then I ask for what keywords are most frequent and what the keywords are most likely associated with. Then I asked AI what it would suggest based on the previous findings.
- Analyzing positive review
- First analysis
- I first used the prompt “What are the customers most satisfied with based on the following reviews:” then I pasted all 5-star ratings behind it.
- Result:
- First analysis
These words were highlighted as what customers were satisfied with Customer Service & Personalization, Responsiveness & Collaboration, Marketing Expertise & Creativity, Flexibility & Adaptability, Quality of Work, and Professionalism.
- Second analysis (further analysis – word association)
- Next, I used the prompt “Extract positive keywords from those reviews, and analyze the frequency and associations of these keywords”
- Result:
These words are what AI picked up the most: Friendly, Helpful, Professional, Responsive, Creative, Efficient, Collaborative, Knowledgeable, Supportive, Flexible, Quality, Great, Amazing, Thorough, Organized, Innovative, Budget-conscious, Pleasure, Recommended, Fantastic
The image below shows how they separated the frequency in descending order.
AI also added this as the conclusion, “The reviews emphasize the customer service (friendly, helpful, supportive), professionalism (knowledgeable, responsive, organized), and creativity/quality (creative, innovative, thorough, quality) provided by Midwest Marketing. The company also gets strong praise for being collaborative and flexible, making it easy for clients to work with them and get the results they need within their budget. These positive keywords reinforce the company’s reputation for being highly customer-focused, capable, and effective in their marketing efforts”
- Recommendation
- For this step I used the prompt, “What would be suggestions from the findings?”
- Result:
- Leverage Exceptional Customer Service
- Expand on Expertise and Knowledge
- Focus on Creativity and Innovation
- Strengthen the Client-Centric Approach
- Highlight the Efficiency and Organization
- Capitalize on Word-of-mouth and Referrals
- Promote Budget-Conscious Solutions
- Address Potential Gaps in the Market
- Negative review analysis
- Review collection
- This step is going to be brief because the lowest review was 4 stars and overall positive in the description. The intent is to find out what could be done better based on the lowest-ranking reviews.
- Review collection
- Analyzing negative reviews
- First analysis
- I applied the prompt, “What are the customers least satisfied with based on the reviews?”, then I applied the only review that is less than 5 stars.
- Result:
- First analysis
Here is what Chatgpt was able to say:
- Second analysis (further analysis – word association)
- This step was to detect any negative words used and how often they were used. Considering Chatgpt said that the review was positive I did not complete this step.
- Result:
We can conclude that because the lowest ranking review was 4 stars and positive they don’t have any negative data to look at for this step.
- Recommendation
- This step is supposed to ask AI what it would suggest Midwest Marketing do differently based on the negative reviews.
- Result:
Because there were none I will include what Chatgpt says are possible areas of interest to increase efforts in. The only thing they said to possibly attempt to try was, “clarity around specific services, scalability, and pricing transparency”.