<description>Looking through each listings to find any missing data points for phone, regular hours, website links, and description.
<prompt>Identify each listing record that is missing a value for “primaryPhone”, “regularHours”, “websiteUrl”, or “profileDescription”. Output shoud be presented in two parts. First a summary in the form of:
Follow summary with a table with 3 columns: Title, Address and the list of which of the 4 fields are missing. Skip over listings with a complete data set. In the table use labels as for Phone, Regular Hours, URL, Description.
<title>Location naming consistency
<category>Listings
<description>Ensuring the business names presented for each location comply your legal entities and Google guidelines.
<prompt>Explore all of the record values for “LocationName”. Present a table with 2 columns: each unique name structure for “LocationName”, the count of the unique values.
<title>Primary category check
<category>Listings
<description>Ensuring that each location has the correct primary categories.
<prompt>Explore all of the record values for “primaryCategory.categoryId”. Present a table with 2 columns: each unique name structure for “primaryCategory.displayName”, the count of the unique values.
<title>Evaluating descriptions
<category>Listings
<description>Looking at the descriptions for each location to identify common and unique content.
<prompt>Evaluate the field: profileDescription, look for consistencies for each field. Output: 3-column table that presents an 20-word abbreviation of the profileDescription field and then the number of locations with that exact value, removing any duplicates.
<title>Special hours confirmation
<category>Listings
<description>Making certain that each location has the correct special hours presented to the public.
<prompt>Identify all the listings with a missing value for locationSpecialHours. Output: Present a summary statement of the findings that include a count of locations both with and without special hours and then a table listing our each location missing values for locationSpecialHours. Output table should be 3 columns: LocationName, Address, locationSpecialHours.
<title>Health Score evaluation
<description>Identifying a listing with a poor health score and list out the opportunities
<prompt>Look at the field “healthScoring” in the data file. Present a table of each listing with a value below “60”. Output the results with a summary statement such as “We have found 4 locations with Health Scores below 60 and then a table with 3 columns: StoreCode, locationName, healthscore.
Simple
<title>Negative review themes
<type>Reviews
<description>Identify the reasons shared by customers for negative reviews.
<prompt>[whatever prompt needed for 1-star and 2-star reviews from the last week, present the themes contained in the contents].
<title>Postitive review themes
<type>Reviews
<description>Identify the main themes shared by clients in positive reviews..
<prompt>[whatever prompt needed for 5-star reviews from the last week, present the themes contained in the contents].
<title>Comprehensive Review Summary
<description>Full insights into location reputation performance for the prior week, evaluating reviews and sentiment analysis.
<prompt>[whatever is needed to figure out how to produce something like the following]
## Weekly Customer Review Summary
### Overview
This week, we analyzed xxx customer reviews from Google, Facebook, and Yelp [source column], showing an overall positive trend compared to last week. Our sentiment analysis revealed key insights into customer satisfaction and areas for improvement.
### Review Analysis
**Overall Review Score: 4.21** (Up from 4.15 last week)
1. **Customer Service Excellence**
Our customer service team continues to impress, with a significant increase in positive sentiment. Customers frequently praised our staff's responsiveness and problem-solving skills.
2. **Improved Delivery Performance**
The largest improvement was seen in delivery speed, with many customers nothing faster-than-expected shipping times.
3. **Product Quality Consistency**
Product quality maintains a high score, with customers particularly impressed by the durability and design of our latest product line.
### Areas for Improvement
1. **Pricing Concerns**
While still positive overall, we saw a slight dip in price satisfaction. Some customers expressed concerns about recent price adjustments on select items.
2. **Website Enhancement Opportunities**
Despite an improvement in website usability scores, some customers suggested further enhancements to the search functionality and mobile experience.
### Sample Customer Feedback
"Exceptional service! The support team went above and beyond to resolve my issue quickly. The product quality is outstanding, and it arrived earlier than expected. Highly recommend!"
### Action Items
1. Investigate pricing strategy for products with decreased satisfaction.
2. Continue to optimize website search functionality and mobile experience.
3. Share positive feedback with the customer service and logistics teams to reinforce excellent performance.
### Summary
This week's analysis shows significant improvements across most areas, with customer service and delivery speed leading the positive trends. Continued focus on pricing strategy and website enhancements will help address the minor concerns raised by customers.
Review Rating
{Provide a list of all locations with an average review score of less than 4.0}
<prompt>Look at the field “healthScoring” in the data file. Present each listing with a value below “30”. Output the results with a summary statement such as “We have found 4 locations with Health Scores below 30 and then paragraph format with the design
)**Location Name**, **healthScore** \n
Address, City, State, Postal, Country \n\n
Look at the field “healthScoring” in the data file. Present each listing with a value below “30”. Output the results with a summary statement such as “We have found 4 locations with Health Scores below 30 and then in a 3-column table format with the design of:
**Location Name**, **healthScore** \n
Address, City, State, Postal, Country \n\n
Look at the field “healthScoring” in the data file. Present each listing with a value below “30”. Output the results with a summary statement such as “We have found 4 locations with Health Scores below 30 and then paragraph format with the design
