how to get the best prices for your products with scraping and price intelligence<br />

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

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

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

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

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.


def parse_hotels(driver):
    """ To parse the web page using the BeautifulSoup

    Args:
        driver (Chromedriver): The driver instance where the hotel details are loaded
    """
    # Getting the HTML page source
    html_source = driver.page_source

    # Creating the BeautifulSoup object with the html source
    soup = BeautifulSoup(html_source,"html.parser")
    
    # Finding all the Hotel Div's in the BeautifulSoup object 
    hotel_tags = soup.find_all("div",{"data-prwidget-name":"meta_hsx_responsive_listing"})
    
    # Parsing the hotel details 
    for hotel in hotel_tags:
        # condition to check if the hotel is sponsored, ignore this hotel if it is sponsored
        sponsored = False if hotel.find("span",class_="ui_merchandising_pill") is None else True
        if not sponsored:
            parse_hotel_details(hotel)
    print("The Hotels details in the current page are parsed")

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!