Data connector details

  • Category: Product Reviews
  • Connector type: Standard

Description

Use the Amazon Review connector to retrieve and analyze customer feedback on items sold on Amazon.

Data Limitations

  • This data connector supports all global Amazon web sites.
  • Amazon restricts data to 15,000 reviews per product URL. 
  • You can have a number of product URLs in each Amazon Review connector; the total maximum number of reviews for each data crawl is 50,000.

If your reviews exceed these limitations, you can Schedule data crawls to retrieve the data incrementally.

Input fields

When setting up the connector, provide the URL of the product or products for which you want to analyze customer reviews. 

  • Product URL (*required): On the Amazon web site, navigate to the product and from the address bar, copy the URL, then paste it into this field.
  • Add new search: To analyze multiple versions of the product or multiple products, click this as many times as needed to add more URLs.
  • Upload: Click to upload a file containing a list of product URLs. Takes a TXT file with one URL per line.
    (CSV is also acceptable, but it must have one URL per line.)
  • Comment Limit: To avoid going over Amazon's data restrictions, it is a good practice to set a limit on the number of comments returned.

You can change your date range on the second page of the wizard, or optionally Schedule data crawls to update your data stream periodically.

Data dictionary

This connector returns the following fields that you can use in analysis.

comment_buy_model

  • Description: Model specification for the reviewed product.
  • Category: meta
  • Example: Roomba 960

comment_color

  • Description: Color specification for the reviewed product.
  • Category: meta

comment_create_time

  • Description: Date and time of the review.
  • Category: date index
  • Example: 43855

comment_detail_link

comment_rating

  • Description: Reviewer's rating for the product.
  • Category: KPI
  • Example: 3

comment_size

  • Description: Size specification for the reviewed product.
  • Category: meta

comment_title

  • Description: Title of the review.
  • Category: text index
  • Example: Beware of dark edged area rugs

comment_up_votes

  • Description: Number of people who found the review helpful.
  • Category: meta
  • Example: 0

context

  • Description: Free-form text of the review.
  • Category: text index
  • Example: I have the attached area rug that the 960 will not clean because it thinks it is going over a cliff. According to IROBOT there is no way to disable the cliff sensor even though there are no stairs on my first floor. There solution was to spend $900 for their newest vacuum. My solution is to by a cheaper Shark. I would return but have been fighting this problem for two months. Guess I will have to live with it. I wouldn't spend the extra money for an IROBOT.

country

  • Description: Reviewer's country.
  • Category: geo index
  • Example: United States

crawler_time_stamp

  • Description: Date and time on which the review was crawled.
  • Category: meta
  • Example: 1580160738652

data_source

  • Description: Data source of the review.
  • Category: meta
  • Example: amazon

product_brand

  • Description: Brand name of the product reviewed.
  • Category: meta
  • Example: iRobot

product_id

  • Description: Amazon ID of the product reviewed.
  • Category: meta
  • Example: B01ID8H6NO

product_name

  • Description: Amazon product name of the product reviewed.
  • Category: meta
  • Example: iRobot Roomba 960 Robot Vacuum- Wi-Fi Connected Mapping, Works with Alexa, Ideal for Pet Hair, Carpets, Hard Floors

product_price

  • Description: Amazon price of the product reviewed.
  • Category: meta

product_review_count

  • Description: Total number of reviews for the product.
  • Category: meta
  • Example: 3108

product_url

time_stamp

  • Description: Date and time of the review.
  • Category: date index
  • Example: 1579910400000

user_addr

user_is_buyer

  • Description: Value indicating whether the reviewer purchased the product reviewed.
  • Category: meta
  • Example: TRUE

user_name

  • Description: Name of the reviewer.
  • Category: user index
  • Example: Jeffrey H. Edwards

Data

  • Description: Adds all output fields to a list visualization.

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