Amazon Brands And Exclusives
Dataset from "Amazon Puts Its Own 'Brands' First Above Better-Rated Products"
@kaggle.thedevastator_amazon_s_dominance_in_e_commerce_why_you_should
Dataset from "Amazon Puts Its Own 'Brands' First Above Better-Rated Products"
@kaggle.thedevastator_amazon_s_dominance_in_e_commerce_why_you_should
This dataset contains information on the quality and sales of products on Amazon, as well as on the percentage of time that Amazon's own products are featured in the Buy Box. It also includes data on the top searches and generic searches on Amazon, as well as on the percentage of panelists who ranked each trait as very important or somewhat important when choosing a product on Amazon
- Determine which features are most important to customers when they are shopping on Amazon.
- Understand how Amazon's own products compare to other products in terms of quality and sales.
- Study how Amazon's marketing and ranking algorithms work, in order to optimize product listings on the site
Acknowledgements
The datasets used in this article were provided by The Markup
License
> License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
> No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.
File: combined_queries_with_source.csv
| Column name | Description |
|---|---|
| search_term | The search term used on Amazon. (String) |
| source | The source of the search term. (String) |
File: quality_and_sales_comparisons.csv
| Column name | Description |
|---|---|
| search_term | The search term used on Amazon. (String) |
| position_first_amazon | The position of the first Amazon product in the search results. (Integer) |
| position_first_non_amazon | The position of the first non-Amazon product in the search results. (Integer) |
| position_first_wholly_non_amazon | The position of the first wholly non-Amazon product in the search results. (Integer) |
| amazon_stars | The average star rating for Amazon products in the search results. (Float) |
| amazon_reviews | The average number of reviews for Amazon products in the search results. (Integer) |
| non_amazon_stars | The average star rating for non-Amazon products in the search results. (Float) |
| non_amazon_reviews | The average number of reviews for non-Amazon products in the search results. (Integer) |
| wnon_amazon_stars | The average star rating for wholly non-Amazon products in the search results. (Float) |
| wnon_amazon_reviews | The average number of reviews for wholly non-Amazon products in the search results. (Integer) |
File: amazon_trademarked_brands.csv
| Column name | Description |
|---|---|
| Word Mark | The word mark of the product. (String) |
| Goods and Services | The goods and services associated with the product. (String) |
| Filing Date | The date on which the product was filed. (Date) |
File: fig2-scatter.csv
| Column name | Description |
|---|---|
| **** | |
| Category | The category of the product. (String) |
| Perc Products | The percentage of products in the category that are sponsored. (Float) |
| Perc #1 spot | The percentage of products in the category that are in the #1 spot in the search results. (Float) |
| Perc first row | The percentage of products in the category that are in the first row of the search results. (Float) |
File: fig3a-heatmap_amzn.csv
| Column name | Description |
|---|---|
| **** |
File: fig3b-heatmap-unaffilated.csv
| Column name | Description |
|---|---|
| **** |
File: fig3c-heatmap-sponsored.csv
| Column name | Description |
|---|---|
| **** |
File: fig4-panel-brands.csv
| Column name | Description |
|---|---|
| **** | |
| Brand | The brand of the product. (String) |
| Is an Amazon product | Whether the product is an Amazon product or not. (Boolean) |
| Is not an Amazon product | Whether the product is not an Amazon product or not. (Boolean) |
| Not sure | Whether it is not sure if the product is an Amazon product or not. (Boolean) |
File: fig5-panel_ranking.csv
File: fig6-RF-feature_importance.csv
| Column name | Description |
|---|---|
| **** | |
| 0 |
File: fig7-1vN.csv
File: appendix-RF_ablation_feature_permutations.csv
File: appendix-RF_singlefeature.csv
File: table1-not_always_labelled.csv
| Column name | Description |
|---|---|
| **** | |
| percentage | The percentage of products that are sponsored. (Numeric) |
File: table2-RF_ablationstudy.csv
File: table2-panel_ranking.csv
File: table3-appendix-generic.csv
| Column name | Description |
|---|---|
| **** |
The
CREATE TABLE amazon_trademarked_brands (
"word_mark" VARCHAR,
"goods_and_services" VARCHAR,
"filing_date" VARCHAR,
"owner" VARCHAR
);CREATE TABLE appendix_rf_ablation_feature_permutations (
"cols" VARCHAR,
"accuracy" DOUBLE
);CREATE TABLE appendix_rf_singlefeature (
"feature" VARCHAR,
"accuracy" DOUBLE
);CREATE TABLE combined_queries_with_source (
"search_term" VARCHAR,
"source" VARCHAR
);CREATE TABLE fig2_scatter (
"unnamed_0" BIGINT -- Unnamed: 0,
"category" VARCHAR,
"perc_products" DOUBLE,
"perc_1_spot" DOUBLE -- Perc #1 Spot,
"perc_first_row" DOUBLE
);CREATE TABLE fig3a_heatmap_amzn (
"unnamed_0" BIGINT -- Unnamed: 0,
"product_order" DOUBLE
);CREATE TABLE fig3b_heatmap_unaffilated (
"unnamed_0" BIGINT -- Unnamed: 0,
"product_order" DOUBLE
);CREATE TABLE fig3c_heatmap_sponsored (
"unnamed_0" BIGINT -- Unnamed: 0,
"product_order" DOUBLE
);CREATE TABLE fig4_panel_brands (
"unnamed_0" BIGINT -- Unnamed: 0,
"brand" VARCHAR,
"is_an_amazon_product" BIGINT,
"is_not_an_amazon_product" BIGINT,
"not_sure" BIGINT
);CREATE TABLE fig5_panel_ranking (
"trait" VARCHAR,
"n__of_panelists" BIGINT -- % Of Panelists
);CREATE TABLE fig6_rf_feature_importance (
"unnamed_0" VARCHAR -- Unnamed: 0,
"n_0" DOUBLE -- 0
);CREATE TABLE fig7_1vn (
"all_features" DOUBLE,
"without_stars_delta" DOUBLE,
"without_reviews_delta" DOUBLE,
"without_is_amazon" DOUBLE,
"without_is_shipped_by_amazon" DOUBLE,
"without_is_sold_by_amazon" DOUBLE,
"without_is_top_clicked" DOUBLE,
"without_random_noise" DOUBLE,
"up_to_product" BIGINT
);CREATE TABLE quality_and_sales_comparisons (
"search_term" VARCHAR,
"position_first_amazon" DOUBLE,
"position_first_non_amazon" BIGINT,
"position_first_wholly_non_amazon" DOUBLE,
"amazon_stars" DOUBLE,
"amazon_reviews" DOUBLE,
"non_amazon_stars" DOUBLE,
"non_amazon_reviews" DOUBLE,
"wnon_amazon_stars" DOUBLE,
"wnon_amazon_reviews" DOUBLE
);CREATE TABLE table1_not_always_labelled (
"unnamed_0" VARCHAR -- Unnamed: 0,
"percentage" DOUBLE
);CREATE TABLE table2_panel_ranking (
"trait" VARCHAR,
"n__of_panelists" BIGINT -- % Of Panelists
);CREATE TABLE table2_rf_ablationstudy (
"feature" VARCHAR,
"accuracy" DOUBLE,
"change_of_accuracy" DOUBLE
);CREATE TABLE table3_appendix_generic (
"unnamed_0" VARCHAR -- Unnamed: 0,
"top_searches" VARCHAR,
"unnamed_2" VARCHAR -- Unnamed: 2,
"generic_searches" VARCHAR,
"unnamed_4" VARCHAR -- Unnamed: 4
);Anyone who has the link will be able to view this.