Benefits of Web Data Scraping on Etsy
For people living under the rock, Etsy is the community-driven and global marketplace in which people can buy and sell unique items.
The Etsy website provides three important information:
Associated Searches
Product Pricing
Product Reviews
We can utilize this data to do decisive market research for niche or make an ultimate product: the product pricing will stay a bit under an average pricing, all negative reviews associated to products’ quality are considered and the products could be sold in packages based on associated searches from competitors.
Price-Matching Competition Products
You may set up a job, which runs everyday at 7 AM that produces a report having average pricing of that day and target the products that you’re fascinated about.
You may adjust the pricing in the shop before the customers get up and make the products extra competitive.
Competitor Monitoring
Let’s assume that your shop is getting 10 orders per day. You have positive reviews and customers are very happy with your product. Still, the orders start decreasing! You are knocking your head and you don’t understand what to do.
Now, if you start using a web scraping tool for monitoring your competitors, then you would discover that they have reduced the pricing for their product by $5.
So, you’re presently selling very expensive products in comparison to your competitor. You should understand that it is a huge jump in the right way, as you’d recognize the reason after the drop of your sales as well as now you will be ready to cope with this situation.
Analyze Reviews and Understand Customers’ Needs
Product reviews provide important data about customer’s perceptions about the products. If your competitor is selling a goof looking product however, its material quality is low, you can easily make a similar product having add-on quality materials.
The customers will most probable to choose your products over a lower-quality option.
Role of Web Scraping
As one of our clients didn’t want to devote a whole week creating a scraping solution, they have decided to utilize X-Byte’s web scraping services with 100M+ rotating proxies as well as 1,000 requests per month.
His biggest concern was that Etsy might block the IP address while extracting the website. But X-Byte has covered all the things well.
Step 1 — Finding the Required Information
We want to get the average pricing for Fallout t-shirts and for that, we have scraped the initial 3 pages of Etsy website, scraped the pricing as well as calculated an average price.
We have scraped the URLs given below:
https://www.etsy.com/search?q=t-shirt+fallout
https://www.etsy.com/search?q=t-shirt+fallout&page=2&ref=pagination
https://www.etsy.com/search?q=t-shirt+fallout&page=3&ref=pagination
From those pages, we got a products list (ul.tab-reorder-container.wt-grid.wt-grid — block > li), as well as for every product, we have scraped the present price ( .v2-listing-card_info .n-listing-card_price .currecncy-value).
Step 2 — Installing the Dependencies
Before writing any code, we require to install these dependencies:
Axios : the Promise-based HTTP customer for Node.JS
Cheerio : the HTML markup parser used for Node.JS having syntax of jQuery
Step 3 — Website Scraping
Produce a index.js file as well as paste the given code:
const cheerio = require(‘cheerio’);
const axios = require(‘axios’);
const api_key = ‘********************************’;
const urls = [
‘https://www.etsy.com/search?q=t-shirt+fallout',
‘https://www.etsy.com/search?q=t-shirt+fallout&page=2&ref=pagination',
‘https://www.etsy.com/search?q=t-shirt+fallout&page=3&ref=pagination'
];
const api_url = https://api.webscrapingapi.com/v1?api_key=${api_key}&session=20210505&url=;
(async () => {
let total_price = 0;
let products_count = 0;
for(let i = 0; i < urls.length; i++) {
let response;
try {
response = await axios.get(api_url + encodeURIComponent(urls[i]));
} catch (error) {
console.log(error);
process.exit();
}
const $ = cheerio.load(response.data);
const $products = $(‘ul.tab-reorder-container.wt-grid.wt-grid — block > li’);
// Parse the products list
}
console.log(Average price: ${parseFloat(total_price/products_count).toFixed(2)});
process.exit();
})();
This code would use the X-Byte Web Scraping API for scraping Etsy pages as well as create products list.
Step 4 — Scrape and Estimate the Average Pricing
Replace // Parse the products list using the given code:
$products.each((index, product) => {
const $product = $(product);
const $currencyValue = $product.find(‘.v2-listing-card_info .n-listing-card_price .currency-value’);
const price = parseFloat($currencyValue.eq(0).text());
if(price) {
total_price += price;
products_count++;
}
})
The code repeats over the product list, scrapes the product pricing and converts that into the float, as well as stores the pricing and product counts for all the future usage.
Step 5 — Testing
Run this script using the given command:
node index.js
In case, the planets get aligned as well as there are no bugs in the code, then you would get an average pricing for Fallout t-shirts. This time, the average pricing is $20.21, you can say not great but not terrible either!
So, the client has set the product price to $19.99 in his shop.
Making a Sell on Etsy is Easier Using a Data Scraper
It was an example about how powerful the scraping APIs can be with global e-commerce platforms. With the given code, you could find an average pricing for any products within seconds!
In case, you are having some spare time, you can utilize the similar code for scraping the product pages for reviews as well as perform a sentiment analysis about the reviews. It will provide you important data about how products from a competition are obtained by customers.
A web scraper can assist you in staying ahead of the competitors, setting the right product price, as well as make new products with learning from competitors’ poor reviews.
In case you want to find out more about how a web scraper can assist a seller using price intelligence , contact X-Byte Enterprise Crawling or ask for a free quote!
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