Explore the infinite possibilities of data sets and proxy IPs, Brightdata helps you open a data-driven future!

foreword

In today's era of information explosion, data sets have become one of the most important core development assets of enterprises or individuals, such as the current booming data of e-commerce with explosive products and so on. However, how to effectively collect and utilize these data is a very challenging problem.

For example: the characteristics of the current webpage data are fast update and huge, and many websites have "anti-collection" technology, especially commercial websites such as e-commerce, and those platforms related to travel information (including food, accommodation and travel) will be based on data from IP users in different regions provide different information, not to mention that many websites have content restrictions due to regions.

As an important part of data management and related technologies such as network agents, data sets are being paid attention to and used by more and more enterprises and professionals.

Liangdata started as a proxy network, and today it has become the leader of the global web data collection platform . The main reasons are as follows.

1. Covering more than 72 million proxy IPs around the world.
2. With the support of patented technology, the team has developed an automatic data collector for collection in the industry: only need to know the website, no need to know any technology, and no infrastructure platform (such as self-built computer room, engineer team, etc.). )
3. Web page data collection can cover global websites, and any public web page data can be collected for you.
4. By cleaning, integrating, adding and then structuring the data - it can provide you with a ready-to-use data set.

1. The concept and application scenarios of data sets and network proxy IP

1.1 What is a dataset?

In the era of big data, datasets have become an important way for enterprises and individuals to obtain and utilize data. Brightdata, as a company focusing on dataset services, is committed to providing efficient, safe and convenient data management solutions for users.

Public big data sets are one of the main data sets provided by Liangdata. These data sets cover data resources in various fields, including social media data, job platform data, e-commerce platform data, etc., such as LinkedIn, Amazon e-commerce Data Amazon, Overseas Douyin Tiktok. Through the effective integration, processing and analysis of these data, Liangdata can help users better understand market trends, user needs, hot product recommendations and other information, thereby improving business efficiency and competitiveness.

E-commerce data is one of the key areas that Liangdata focuses on. With the rapid development of e-commerce, data such as transaction records, user behavior, and product information on e-commerce platforms are widely used in market data analysis, user portrait construction, and product recommendation. Bright Data's dataset service can help e-commerce companies better understand user needs, optimize product design, and improve marketing effects.

Data insight technologies based on artificial intelligence, such as machine learning and deep learning, can help companies better understand user needs, optimize product design, and improve marketing effects through the analysis and mining of e-commerce data. The dataset service provided by Liangdata can provide users with accurate market trend analysis, user behavior prediction, product recommendation and other services to help users better complete their business. It can also provide e-commerce insights and market data analysis for brands and retailer services.

1.2 What is the network proxy IP?

In the Internet era, network proxy IP has become one of the important means of network security and data privacy protection. At the same time, Liangdata, as a company focusing on network proxy IP services, is committed to providing efficient, safe and convenient network proxy services for the majority of users.

Dynamic residential proxy is one of the main network proxy methods provided by Brightdata. Through dynamic residential proxy technology, users can route their network requests to different proxy servers, so as to achieve the purpose of anonymously accessing the Internet. This proxy method can not only protect the privacy of users, but also help users bypass the anti-crawler mechanism of some websites and improve the efficiency of data collection.

Computer room proxy is also another major network proxy method that Liangdata focuses on. Through the computer room proxy technology, users can send their network requests to the designated server in the computer room for processing, thereby realizing remote access and management of data. This proxy method can help users better manage their own data, improve work efficiency and security.

In addition to dynamic residential proxy and computer room proxy, Liangdata also provides various types of network proxy services, including static IP proxy, HTTP proxy, mobile proxy, etc., to meet the needs of different users. At the same time, Liangdata's network proxy service also supports multi-platform use, including Windows, Mac OS, Linux and other operating systems, as well as common browsers and applications.

2. What can bright data do?

2.1 What are the advantages of Liangdata's network proxy IP?

1. Dynamic Residential Proxy: This service allows users to route their network requests to different proxy residential servers, thereby achieving the purpose of anonymously accessing the Internet. This proxy method is most suitable for websites with hard blocking, simulated real user access, large-scale operations requiring a large number of IPs, and operations requiring a large number of high-resolution geolocations.
2. ISP static residential proxy: This service can help users send their network requests to the designated real static residential IP for processing, thereby realizing remote access and management of data. It is suitable for use cases that require a static IP, and the success rate will be much higher than that of the proxy IP in the computer room.
3. Computer room proxy: This service can help users send their network requests to the designated server in the computer room for processing, thereby realizing remote access and management of data. It is more suitable for simple websites with high-speed operations and a large number of operations.
4. Mobile Agent: This service can help users send their network requests to designated mobile devices for processing, thereby realizing remote access and management of data. As the name suggests, it is best suited for website situations that require mobile device access.
5. Search engine crawler SERP: This service can help users optimize their websites for search engines, thereby improving their ranking and exposure. By using Liangdata's search engine crawler SERP service, users can obtain more accurate and comprehensive keyword search results, so as to better understand market demand and user behavior. It is most suitable for the relevant scenario requirements of extracting customized and structured data from search engine result pages.

2.2 What are the characteristics of bright data datasets?

1. Covering global scenarios using structured and accurate public big data sets: Brightdata has structured and accurate public big data sets covering global scenarios, including data sets in multiple fields such as e-commerce, work, and social networking. These data sets have been carefully screened and processed to ensure their accuracy and reliability, which can help users better understand market demand and user behavior.
2. Customized datasets on demand: In addition to providing public large dataset services, BrightData also supports users to customize their own datasets on demand. Users can select parameters such as data set type, data volume, and data quality according to their own needs, so as to obtain more accurate data analysis results.
3. Brightdata e-commerce insight based on artificial intelligence: Brightdata's e-commerce insight service is based on artificial intelligence technology, which can help users deeply understand market trends, product competition, user needs and other information. Through technical means such as machine learning and natural language processing, Liangdata can provide users with more accurate and comprehensive e-commerce insights and analysis results. Ecommerce insights and market share data intelligence for brands and retailers.
   

2.3 How does Liangdata's network proxy IP service ensure network security?

Liangdata's network proxy IP service adopts a variety of security measures, from data encryption to anonymous access to multi-level security protection and real-time monitoring, etc., which can provide users with comprehensive security protection.

1. Data encryption: Liangdata's network proxy IP service adopts advanced encryption technology to encrypt user data, thus ensuring data security.
2. Anonymous access: Liangdata's network proxy IP service allows users to access the Internet anonymously, avoiding the risk of users' personal information being leaked.
3. Multi-level security protection: Liangdata's network proxy IP service adopts multi-level security protection measures, including firewall, DDoS attack protection, intrusion detection, etc., thus ensuring the user's network security.
4. Real-time monitoring: Liangdata's network proxy IP service also provides a real-time monitoring function, which can detect and deal with any abnormal situation in time to ensure the user's network security.
   

3. Use Liangdata in actual combat to solve the pain points of cross-border e-commerce

The biggest pain point of China's cross-border e-commerce is "cross", cross-country, cross-language, cross-cultural, cross-logistics and so on. In the relatively unknown "battlefield", each of the different links and roles in the cross-border e-commerce chain has pain points that need to be faced.

Next, for some common business scenarios, let’s take a practical look at how to use Bright Data to solve related pain points in cross-border e-commerce operations.

3.1 Pain point 1: brand-related positioning of brands

The pain point for brand owners is mainly cross-platform positioning: such as brand price, image and other related promotions.

With the development of the market, e-commerce platforms have become more diversified. Different regions have different e-commerce platforms for different consumers. For brand owners, how to quickly capture the market and increase brand awareness is an important issue.

Take some random electronic products as examples. For example, we found a very well-known and excellent bluetooth headset Yamaha on Amazon. Let’s go to your company’s official website to find the relevant price

. I searched for this excellent and well-known earphone at the moment, but unexpectedly found that only 452 is needed.

The price marked by its dealers is much lower than that on the official website. However, this price does not include shipping costs and possible customs duties. After taking into account various costs, it is actually not much different from the price on the brand’s official website.

Therefore, when conducting e-commerce sales, when pricing products, it is necessary to formulate different price strategies according to different platforms, audiences, and rules, and at the same time ensure that distribution/agents, etc., are synchronized with brand prices, visuals, and other strategies.

To this end, we can use Bright Data's dynamic residential network, computer room agent and mobile network, as well as Bright Network unlocker to collect public network data including prices, use of pictures, use of trademarks, etc., to ensure the brand's price on the e-commerce platform, etc. Consistency of relevant data information.

3.2 Pain point 2: The cost of cross-market drainage is high but the return is not high

In today's digital age, cross-platform distribution has become an important means for companies to promote products. However, this strategy also poses some challenges. One of them is the increase in drainage costs. Since different marketing platforms have different attributes and audiences, enterprises need to invest more resources to attract users when promoting on multiple platforms. This leads to an increase in the cost of attracting traffic, and may also reduce the rate of return.

For example, social platforms such as TikTok, Twitter, and Instagram are all very popular marketing platforms right now. The audience groups of these platforms are different, so enterprises need to formulate corresponding strategies according to the characteristics of different platforms when promoting products. This means that enterprises need to invest more human, material and financial resources on multiple platforms to achieve better promotion effects.

In addition, with the intensification of market competition, companies need to constantly look for new marketing platforms and channels to expand their brand influence and market share. This also means that enterprises need to continuously invest more resources in market research and analysis in order to find the most suitable promotion platform and strategy for them.

So how do we solve this kind of problem with bright data?
1. First of all, we need to clarify the audience characteristics of each social platform, so that advertisements must also match their preferences.
2. According to the public report data of Statista, a well-known data organization, 26% of the respondents are Amazon, 19% are AliExpress, and 11% are eBay as the preferred cross-border e-commerce platform for global consumers.
3. With the current crazy development of social media, young people are more inclined to buy on Facebook, women generally like to "submit orders" on TikTok and Pinterest, while men hope to find their favorite products on Twitter and Twitch.

And how to know these platforms or e-commerce data sets? We can directly purchase these data through Liangdata to obtain some platform information we want and so on.

For example the product sample data for an Amazon product is as follows.

Through filters, we can further filter data subsets to facilitate our further acquisition, processing and analysis of data.

3.3 Pain point 3: Difficult to choose hot cross-border e-commerce models

Due to the need to cross the differences in different cultures and cognitions, the selection of products for specific overseas countries needs to rely more on the public data provided by the webpage. In the context of globalization, companies need to consider factors such as culture, customs, and values ​​in different countries and regions in order to better meet the needs of local consumers. Therefore, understanding the public data of the target market is very important for enterprises to select overseas products.

Open data can help companies understand competitors in the target market and industry dynamics. By studying competitors' products and pricing strategies, companies can find their own competitive advantages and formulate corresponding marketing strategies. At the same time, paying attention to industry trends can help companies seize market opportunities and adjust product strategies in a timely manner to adapt to market changes.

In addition, open data can help companies understand consumer behavior and preferences in target markets. By analyzing data such as consumers' purchase records and browsing records, companies can better understand consumers' needs and preferences, thereby optimizing product design and marketing strategies, and improving product market competitiveness.

If you look at the best-selling product list manually page by page and organize it into data for analysis, then the task is too heavy and it takes a lot of time. Moreover, many merchants do not have the programming ability to capture web page data, nor do they have a suitable proxy IP to quickly, efficiently and truly capture data. Then we can use Liangdata's Web Scraper IDE to scrape.

We select Amazon's crawler template, put the found destination address url into the code, and then it can run.
After running the code for the target product url, you can download the relevant data information in the target product webpage.

4. Use bright data to obtain Wal-Mart products in various price ranges and process them easily

First, we use Bright Data to obtain information about Wal-Mart related products.

Choose to download the data as csv format.

You can see the data display as follows.

Next, we will process the relevant data through Python ~
first read the data in the csv file through the code, the code is as follows:

import pandas as pd
data = pd.read_csv('Walmart products dataset.csv')
data.head()

Next we process the value of the 'final_price' column named "data". First, we define a function named "display_price", which converts the input value x to a floating point number, and intercepts from the second character (that is, removes the first character). If the conversion fails, the price is set to 0. Then, use the apply method to apply this function to each element of the 'final_price' column and store the result back into the original 'final_price' column. Finally, the processed 'final_price' column is returned.

Then we make relevant drawing icons to obtain an intuitive data display:

import matplotlib.pylab as plt
plt.figure(figsize=(16,8))
data.groupby('timestamp')['final_price'].mean().plot()
plt.show()

It can be seen that in each time period, the price range of some hot-selling products:

5. Summary of Bright Data

After using Bright Data products, are you very interested in Bright Data?

Liangdata is a company that started with a commercial proxy IP network. Its proxy IP network covers 195 countries around the world and has more than 72 million IP resources. These IP resources include dynamic residential IP, static residential IP, computer room proxy IP and mobile proxy IP, etc., and are among the best in the industry in terms of IP quality, proxy network speed and success rate.

As a leading company in the agency network industry, Netlight Data has not only made continuous breakthroughs in technology, but also developed a series of useful tools to provide users with more convenient services. In addition, they also have large data sets covering major external networks, such as Amazon Amazon, Douyin overseas version TIKTOK, and LinkedIn and other well-known website data resources. These data can help users better understand the needs and trends of overseas markets, and provide strong support for the development of enterprises.

And it is worth mentioning that, by combining artificial intelligence, Bright Data has also launched an e-commerce intelligence tool called "Bright Data Insight". This tool can help users deeply understand the consumer behavior and preferences of the target market, so as to formulate more accurate marketing strategies. For users who are interested in the e-commerce market, this is undoubtedly a very valuable tool.

Liangdata started as an agency network, and today it is the leader of the global web data collection platform! Welcome everyone to experience Liangdata!