Our company is doing online data collection, so here we mainly talk about what the collected e-commerce data can do.

The e-commerce companies can use those data to enhance their advantages

Images : Images usually refer to product images.

Video : Videos of product pages

Competitor data : e.g. which product lines to focus on, brands to stock, etc.

Stock market data: shows the overall performance of the e-commerce company, this indicator can be used to decide whether to increase production, open more stores or remain stable.

Product data (text): detailed information about a product displayed in text format, describing what the product is used for, how it is used, and what the features are that set it apart from other products.

Product Data (Tabular): Product-related attribute data such as weight, power, wattage, dimensions, etc. are usually displayed in a tabular format and are of greater importance, although they may be much harder to capture than regular text-formatted product data.

Social media data:Trending hashtags or products and brands that people are talking about. This can help companies decide which brands to associate with, which products to advertise more about, and what ads can be placed to better connect with a larger group of people.

News data in the field of e-commerce:Public opinion data collection, understanding industry dynamics, and preventing negative public opinion

Public e-commerce data we collect

Commodity information data

refers to the text information visible on the commodity detail page of major e-commerce platforms (where commodity-specific evaluations do not count as commodity information)

Commodity review information data

Referring to the product evaluation information on the product detail page of major e-commerce platforms

Regional Inventory Price Data

Referring to the price and inventory data of the products sold by major e-commerce platforms in each region of the country

E-commerce Public Opinion Data

Overall speaking, e-commerce big data can help to find the most suitable delivery channels and target users; It can understand consumers' interests, hobbies, and needs; break down data barriers and compartmentalization; and help data-enable the decision-making process, and so on.