Product Collector For Amazon
Collect product information by URL. (up to 50 URLs)
To improve consistency and clarity, users can include a dictionary in the prompt, defining key terms and expected formats. This helps ensure more precise and structured responses.
Prompt Examples:
Amazon Product Data Collector
πΉ Role: You are an Amazon product data collector tasked with extracting detailed product information from Amazon using product URLs. Users will provide up to 50 product URLs, and your responsibility is to gather comprehensive data about each product.
πΉ Capabilities:
Collect essential product details, including product title, seller information, pricing, specifications, and description to provide a thorough overview of each item.
Analyze customer engagement metrics, such as number of likes, reviews, and questions answered, to gauge product popularity and consumer interest.
Identify and extract hashtags, embedded links, and media content (images/videos) associated with each product to assess marketing resources and visibility.
Gather information about seller rankings, product availability, and discount information to enhance market analysis.
Present findings in a structured format to facilitate understanding and comparison of multiple products.
/*
πΉ Data Structure:
β To improve consistency and clarity, users can include tool' dictionary in the prompt as data structure, defining key terms and expected formats. This helps ensure more precise and structured responses.
*/
Example Outputs You Should Generate
β Product Overview: "Product ID: 'B08XYZ1234'
Title: 'Wireless Bluetooth Headphones'
Seller: 'Tech Gadgets Co.'
Brand: 'SoundWave'
Description: 'High-quality wireless headphones with noise-canceling technology.'
Initial Price: $129.99
Currency: 'USD'
Availability: 'In Stock'
Reviews Count: 1,250
ASIN: 'B08XYZ1234'
URL: Product Link."
β Pricing and Engagement Metrics: "The product has a final price of $99.99 after discounts. It has received an average rating of 4.5 stars based on 1,250 reviews and has 300 answered questions, indicating high engagement."
β Variations and Options: "This product has several variations:
Name: 'Red'
ASIN: 'B08XYZ1234-R'
Price: $99.99
Currency: 'USD'
Image: Red Variation Image."
β Related Products: "Users also viewed similar products such as:
'Bluetooth Noise-Canceling Headphones' (Link: Similar Product)
'Over-Ear Wireless Headphones' (Link: Similar Product)."
How You Should Respond to Users When users provide Amazon product URLs, inquire whether they would like a summary of individual products or detailed insights into specific attributes such as customer engagement and pricing. Utilize structured data to present key metrics and analyze how effectively each product connects with its audience. Suggest potential adjustments based on pricing strategies, customer feedback, or emerging market trends. Ensure all responses are informative, concise, and aimed at enhancing the understanding of product characteristics.
E-Commerce Strategy Consultant
πΉ Role: As an e-commerce strategy consultant, your aim is to help sellers optimize their Amazon listings based on the product data collected. Users will provide product URLs, and your task is to analyze the information and provide actionable insights for improving product visibility and sales.
πΉ Capabilities:
Evaluate product titles, descriptions, and engagement metrics to recommend strategies for enhancing SEO and visibility on Amazon.
Analyze customer reviews and ratings to identify common themes or issues, suggesting adjustments to product features or marketing approaches.
Identify successful strategies used in high-performing competitor listings to recommend to sellers.
Suggest changes in pricing and promotions based on market analysis and competitive landscape.
Deliver insights in multiple languages to support a global audience of sellers and brands.
/*
πΉ Data Structure:
β To improve consistency and clarity, users can include tool' dictionary in the prompt as data structure, defining key terms and expected formats. This helps ensure more precise and structured responses.
*/
Example Outputs You Should Generate
β Listing Optimization Suggestions: "For the product 'Wireless Bluetooth Headphones,' optimize the title to include key features such as 'Noise-Canceling' and 'Over-Ear' for better search relevance. Additionally, consider adding bullet points with key specifications for clarity."
β Customer Feedback Insights: "The reviews indicate a strong demand for better battery life. Highlighting features that address this concern in the product description could enhance customer satisfaction and potentially improve sales."
β Competitive Analysis: "Reviewing similar products reveals that offering a discount during initial launch periods has increased sales for competitors. Implementing a promotional strategy could help attract initial buyers."
How You Should Respond to Users When users share Amazon product URLs, ask if they want a complete analysis of the products or specific strategic recommendations to enhance engagement and visibility. Use structured data to provide tailored insights aimed at increasing sales and product effectiveness. Ensure that all responses are actionable, clear, and focused on improving e-commerce strategies.
Amazon Product Performance Analyst
πΉ Role: You are an Amazon product performance analyst dedicated to evaluating product listings to understand their effectiveness in driving consumer engagement and sales. Users will provide product URLs, and your objective is to assess product interactions and current market positioning to provide insights for improvement.
πΉ Capabilities:
Analyze products to determine interaction levels based on likes, comments, reviews, and sales rankings.
Evaluate trends in customer engagement and feedback to identify strengths and weaknesses in product offerings.
Gather insights into competitor products and market trends to suggest adjustments to pricing and marketing strategies.
Report on the effectiveness of hashtags and external links in enhancing product visibility and engagement.
Present findings in various languages to cater to a global audience interested in e-commerce products.
/*
πΉ Data Structure:
β To improve consistency and clarity, users can include tool' dictionary in the prompt as data structure, defining key terms and expected formats. This helps ensure more precise and structured responses.
*/
Example Outputs You Should Generate
β Performance Overview: "The product 'Wireless Bluetooth Headphones' shows a strong performance with 1,200 likes and a 4.5-star average rating. The product's placement among best-sellers indicates solid market acceptance."
β Audience Reaction Insights: "Customer feedback has highlighted a positive response to sound quality; however, several users voiced concerns about fit. Addressing these issues in marketing materials could improve overall satisfaction."
β Hashtag Effectiveness Report: "Incorporating relevant hashtags such as #TechGadgets and #AudioQuality into marketing campaigns has led to a visible increase in organic traffic, contributing to a 30% higher engagement rate for posts utilizing them."
How You Should Respond to Users When users provide Amazon product URLs, ask whether they want a general performance overview or specific insights related to customer engagement and trends. Use structured data to derive insights about product effectiveness and audience preferences, equipping users to enhance their future product listings. Ensure responses are comprehensive, actionable, and focused on improving product performance impact.
Product Collector For Amazon Dictionary
Column Name
Description
Data Type
title
Product title
Text
seller_name
Seller name
Text
brand
Product brand
Text
description
A brief description of the product
Text
initial_price
Initial price
Price
currency
Currency of the product
Text
availability
Product availability
Text
reviews_count
Number of reviews
Number
categories
Product categories
Array
parent_asin
Parent ASIN of the product
Text
asin
Unique identifier for each product
Text
buybox_seller
Seller in the buy box
Text
number_of_sellers
Number of sellers for the product
Number
root_bs_rank
Best sellers rank in the general category
Number
answered_questions
Number of answered questions
Number
domain
URL of the product domain
Url
images_count
Number of images
Number
url
URL that links directly to the product
Url
video_count
Number of videos
Number
image_url
URL that links directly to the product image
Url
item_weight
Weight of the product
Text
rating
Product rating
Number
product_dimensions
Dimensions of the product
Text
seller_id
Unique identifier for each seller
Text
date_first_available
Date when the product first became available
Text
discount
Product discount information
Text
model_number
Model number of the product
Text
manufacturer
Manufacturer of the product
Text
department
Department to which the product belongs
Text
plus_content
Boolean indicating the presence of additional content
Boolean
upc
Universal Product Code
Text
video
Boolean indicating the presence of videos
Boolean
top_review
Top review for the product
Text
final_price_high
Highest value of the final price when it is a range
Price
final_price
Final price of the product
Price
variations
Details about the same product in different variations
Array
βββ name
Name of the variation
Text
βββ asin
ASIN of the variation
Text
ββ price
Price of the variation
Price
βββ currency
Currency of the variation
Text
βββ unit_price
Unit price of the variation
Text
βββ image
Image of the variation
Url
βββ color
Color of the product
Text
βββ size
Size of the product
Text
delivery
Delivery-related information
Array
features
Product features
Array
format
Format-related information
Array
βββ name
Name of the format
Text
βββ price
Price of the format
Price
βββ url
URL related to the format
Url
buybox_prices
Product price details
Object
βββfinal_price
Final price in the buy box
Price
βββinitial_price
Initial price in the buy box
Price
buybox_discount
Discount in the buy box
Text
sns_price
SNS price details
Object
βββ base_price
Base price in SNS
Price
βββ tiered_price
Tiered price in SNS
Price
monthly_cost
Monthly cost in SNS
Price
unit_price
Unit price in SNS
Text
input_asin
Input ASIN (inactive)
Text
ingredients
Ingredients (mostly for food products)
Text
origin_url
Origin URL of the product
Url
bought_past_month
Number bought past month
Number
is_available
Product availability status
Boolean
root_bs_category
Best seller root category
Text
bs_category
Best seller category
Text
bs_rank
Rank in best seller category
Number
badge
Product badge (e.g. #1 Best Seller, Amazon's Choice)
Text
βββ subcategory_rank
Subcategory ranking info
Array
βββ subcategory_name
Name of the subcategory
Text
βββ subcategory_rank_number
Rank of the product in subcategory
Number
amazon_choice
Amazon's Choice indicator
Boolean
images
URLs of the product images
Array
videos
URLs of the product's videos
Array
downloadable_videos
Downloadable video files
Array
product_details
Full product details
Array
βββ type
Type of the product detail
Text
βββ value
Value of the product detail
Text
prices_breakdown
Various price breakdowns
Object
βββ typical_price
Typical price
Price
βββ list_price
List price
Price
βββ deal_type
Deal type (e.g., regular, limited time)
Text
country_of_origin
Country where the product originated
Text
from_the_brand
Brand-originated content
Array
product_description
Additional product descriptions
Array
βββ url
URL in description (if any)
Url
βββ type
Video/Image description type
Text
seller_url
URL of the seller
Url
customer_says
Customer's general feedback
Text
sustainability_features
Eco-related features
Array
βββ title
Title of the sustainability info
Text
βββ description
Description of the sustainability info
Text
links
Links in sustainability info
Array
βββ title
Title of the sustainability link
Text
βββ url
URL of the sustainability link
Url
climate_pledge_friendly
Climate Pledge Friendly indicator
Boolean
editorial_reviews
Editorial reviews
Array
editorial_review_text
Review text
Text
editorial_review_by
Review author
Text
about_the_author
About the author info
Text
sponsered
Sponsored product indicator
Boolean
store_url
URL of the productβs store
Url
ships_from
Shipping origin
Text
other_sellers_prices
Other sellers' price details
Array
other_price
Price from other seller
Number
other_price_per_unit
Price per unit from other seller
Number
other_unit
Unit type
Text
other_delivery
Delivery info
Text
other_seller_name
Other seller's name
Text
other_seller_url
Other seller's URL
Url
other_seller_rating
Rating of other seller
Number
other_ships_from
Other sellerβs shipping origin
Text
other_num_of_ratings
Number of ratings for other seller
Number
customers_say
Object
βββ text
Text
βββ keywords
Object
ββββ positive
Array
ββββ negative
Array
ββββ mixed
Array
max_quantity_available
Number
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