Dark Mode
Retail Watch Market Analysis Data
Retail & Consumer Behavior
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
A collection of information on various watch products is available for research or analysis. This data gathers details on a wide array of watches, covering aspects from branding and pricing to style and target audience. It can be valuable for market analysis, understanding consumer preferences, and identifying trends within the watch industry.
Columns
- Titles: The names or titles of the watch products.
- Brand_names: The brand names of the watches.
- Images_links: Links to the images of the watches.
- Prices: The prices of the watches.
- Offers: Special offers or discounts available on the watches.
- Gender: The intended gender for the watch, such as men, women, or unisex.
- Type: The style of the watch, including categories like analog, sports, or smartwatch.
Distribution
The dataset is provided as a single CSV file named
watches.csv, with a size of 215.67 kB. It contains 975 records and 8 columns. There are no missing or mismatched values reported in the data.Usage
This dataset is suitable for a variety of applications, including:
- Market Research: Analysing pricing strategies, brand popularity, and product assortments in the e-commerce sector.
- Competitive Analysis: Comparing product offerings and discount strategies between different watch brands like Fastrack and Titan.
- Trend Analysis: Identifying popular watch types (e.g., analog) and gender targeting (e.g., unisex) in the market.
- Data Science Projects: Building recommendation engines or predictive models for watch prices and sales.
Coverage
The dataset covers a range of watch products available through e-commerce services. Demographically, it includes watches specified for men and women, with a significant portion labelled as unisex. The data does not have a specified time range and is not expected to be updated.
License
CC0: Public Domain
Who Can Use It
- Market Analysts: To study the accessories and clothing market, focusing on watch brands and consumer trends.
- E-commerce Businesses: To inform pricing, inventory, and marketing strategies for online watch sales.
- Data Scientists: For building and training machine learning models related to product classification and price prediction.
- Academic Researchers: To conduct studies on consumer behaviour and marketing in the retail sector.
Dataset Name Suggestions
- Watch Product & Pricing Data
- E-commerce Watch Listings
- Retail Watch Market Analysis Data
- Watch Brand & Style Catalogue
Attributes
Original Data Source: Retail Watch Market Analysis Data
QUALITY