Blog #8

•

Madison

Analyzing Online Reviews & Suggestions – The HomeSlice Group

  • Positive review analysis

– For the positive review analysis, I will go to Google Maps and other social media pages 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: 

These words were highlighted as what customers were satisfied with Welcoming Environment, Helpful and Supportive Staff, Commitment to Client Success, Professionalism, Passion and dedication, and Reputation and Trustworthiness. 

  • 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: Welcoming, Helpful, Supportive, Best, Grow, Work hard, Love, Wonderful, Professionalism, Media Group, Rapid City, Company, Trust

 The image below shows how they separated the frequency in descending order. 

AI also added this as the conclusion, “The reviews reflect a strong emphasis on customer service, professionalism, and a passion for helping clients grow. The most frequently used words, “best” and “helpful,” signal a high level of customer satisfaction, while terms like “work hard”, “love”, and “wonderful” emphasize the company’s dedication and enthusiasm. The connection to Rapid City highlights the company’s strong local reputation, and keywords like “trust” and “media group” associate it with reliability and expertise in advertising.

The overall association between excellence, customer support, and local success makes it clear that The HomeSlice Group is well-regarded for both its professional service and its positive, client-focused approach.” 

 

  • Recommendation
    • For this step I used the prompt, “What would be suggestions from the findings?”
    • Result: 
  1. Emphasize Client-Centered Service in Marketing
  2. Promote the Passion and Dedication of Your Team
  3. Highlight Your Professionalism and Expertise
  4. Reinforce Local Reputation and Community Engagement
  5. Foster Long-Term Relationships and Client Loyalty
  6. Leverage “Best” Reputation for Growth
  7. Create a Referral Program
  8. Communicate Trust and Reliability Clearly
  9. Keep Nurturing Team Development

 

  • Negative review analysis
    • Review collection
      • This step is going to be brief because there are very few low ratings, and they all have no commentary included with them. The intent is to find out what could be done better based on the lowest-ranking reviews. I will be including as many findings as I can across multiple platforms to try and come up with ways to improve these ratings. 

 

  • Analyzing negative reviews
    • First analysis
      • I applied the prompt, “What are the customers least satisfied with based on the reviews?”, then I included that there was a 3-Star and a 1-Star review. 
      • Result:

Here is what Chatgpt was able to say:

“To analyze what customers might be least satisfied with based on the 3 out of 5 stars and 1 out of 5 stars reviews, we would need to examine those specific reviews for any negative feedback or areas of concern. However, since the detailed content of the reviews isn’t provided in your question, I can offer some general approaches based on the typical factors that lead to less-than-perfect reviews.”

The potential dissatisfaction areas include service issues, expectations unmet, quality of work, pricing concerns, and technical errors. 

 

  • Second analysis (further analysis – word association)
    • This step was to detect any negative words used and how often they were used. Considering there are no words used in the negative reviews I am going to conclude a generalized idea of what could be happening. 
    • Result:

We can conclude that because the lowest ranking review was 3 and 1 stars there was some form of a negative experience. However, without any context, there is no way to know what specifically was unmet and what to work on directly. 

  • Recommendation
    • This step is supposed to ask AI what it would suggest The HomeSlice Group can do differently based on the negative reviews. 
    • Result: 
  1. Strengthen Client Communication and Expectations Management
  2. Enhance Customer Support and Service Experience
  3. Focus on Delivering Tangible Results and High-Quality Work
  4. Improve Transparency in Pricing and Value Proposition
  5. Foster Continuous Feedback and Improve Based on Customer Insights
  6. Address Specific Client Concerns from Negative Reviews
  7. Strengthen Brand Messaging and Positioning
  8. Encourage Reviews and Testimonials to Counter Negative Feedback

Thank you for reading!

•