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Optimizing SEO with ISP Proxies

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Optimizing SEO consists of optimizing both on-page SEO and off-page SEO Content On-page SEO is what you can do on the website itself. Examples include design, content, load time, accessibility, blogging, etc. Off-site SEO is the activities you can perform off-site. For example, building backlinks to your site; citations, social media, visitor posts on your blog, etc.

However, there is a need to create pre-surveys for content, at which point you can use Long-Term ISP Proxies to collect data. Long-Term ISP Proxies have a long rotation time compared to residential proxies and can remain alive except for server reboots. Buy now and get Black Friday proxies discounts.

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If you are looking for code to collect SEO data related to ISP proxies, the following Python sample code can help you grab the data using an API to be used in conjunction with ISP proxies:

Installing Dependencies

First, make sure you have the following Python libraries installed:

pip install requests beautifulsoup4 pandas

Sample Code

The following code will simulate crawling SEO data using ISP proxies and storing the results in a Pandas DataFrame for further analysis:

import requests
from bs4 import BeautifulSoup
import pandas as pd
 
# Configure ISP proxies (assuming you already have a list of ISP proxies)
PROXY = {
    “http": ‘http://your_proxy_here’, 
    “https": ”https://your_proxy_here”
}
 
# Set the target URL to be crawled (e.g. Google search results page)
TARGET_URL = “https://www.google.com/search?q=ISP代理+SEO”
 
# Define a function to fetch the page content
def fetch_page(url).
    try.
        response = requests.get(url, proxies=PROXY, timeout=10)
        response.raise_for_status() # check if the request was successful or not
        return response.text
    except requests.exceptions.RequestException as e:: print(f “f”, “f”, “f”, “f”, “f”)
        RequestException as e: print(f “Request failed: {e}”)
        return None
 
# Parse HTML and extract SEO related information (e.g. title, description, URL, etc.)
def parse_seo_data(html_content):: soup = BeautifulSoup(html_content)
    soup = BeautifulSoup(html_content, 'html.parser')
    
    # Extract titles
    titles = [title.text for title in soup.find_all('h3')]
    
    # extract description (note: Google search results do not directly display the description, usually the description will be in the meta tags or in the search summary)
    descriptions = [desc.text for desc in soup.find_all('span', {'class': 'aCOpRe'})]]
    
    # Extract links (URLs)
    links = [links['href'] for link in soup.find_all('a', href=True)]
    
    return titles, descriptions, links
 
# Fetch SEO data
html_content = fetch_page(TARGET_URL)
if html_content.
    titles, descriptions, links = parse_seo_data(html_content)
 
    # Store the data in a Pandas DataFrame
    data = {
        “Title": titles, ‘Description’: descriptions, ‘Title’: titles, ‘Description’: descriptions
        “Description": descriptions, ‘URL’: links
        “URL": links
    }
    
    df = pd.DataFrame(data)
    print(df.head()) # display the first 5 rows of data
else.
    print(“No data crawled”)

Description:

Proxy Settings: You can configure ISP proxies via the PROXY dictionary. In practice, you can dynamically switch proxies to prevent blocking.

Target URL: Set the URL you want to crawl in TARGET_URL, the example is Google search result page, but you can replace it with other pages.

SEO Data: The extracted SEO data includes the page title (h3 tag), description (span tag with aCOpRe text), and links (href in a tag).

Data Storage: The extracted data is stored in Pandas DataFrame for subsequent analysis and processing.

Caveats:

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Legality: When using proxies to crawl data, please make sure to follow the crawler policy and legal regulations of the target website.

Proxy Pooling: If you need to use multiple ISP proxies to disperse requests, consider implementing proxy pooling.

Anti-crawler mechanisms: For websites with strong anti-crawler mechanisms, additional processing may be required, such as adding request headers, simulating browser behavior, resolving CAPTCHA, etc.

This code helps you collect SEO data through ISP proxies and is easy to extend and optimize.

 

On-page and off-page content, backlinks, curation, blogs, advertisements, etc. together make up the SEO strategy. Examples include screen reader accessibility as well as design and load time. Let's say your site scores 100/100 on Google's Page Speed Score.SEO is not a short-term one-click switch to get you on the first page. A good SEO strategy takes 6-12 months to pay off. It's a long-term investment. For short-term gains, you can place Google ads to show up at the top of relevant searches and be seen when customers are looking for your services.

So SEO + advertising + social media management make up a complete marketing strategy to maximize your online presence and get seen by as many customers as possible online.

If you don't have an SEO person, you can search for your client's keywords in large metropolitan areas in different states and open all the top-ranking websites. Research your competitors' keywords to see what keywords they are ranking for and then find the best keywords to steal and outrank them, i.e. the opening code section.

You can use keyword research tools such as finding keywords with low competitiveness or high search volume and write content around them to find the keyword gap between you and your competitors.

Instagram Reel, ubersuggest and Semrush can all be used. Once you've found your keywords, enter them into chatGPT and have it write new content based on what's on those pages, then edit it to make it sound more human. Then add the content to the site. Then look for what sections, what order, what content and where the keywords need to be placed on a site. I also do this for internal service pages (called content silos).

Even if you're not an SEO expert, you can reach your goals by focusing on the fundamentals and what Google wants to see. Of course, traditional SEO will help too, such as backlinking, blogging, guest posting, content creation and promotion. But if you don't have the budget for that, then you can get by focusing on content on the page that you can control.

These content silos are also very helpful for placing ads. They have a very high conversion rate. For example, place an ad for interior painting services and direct them to the interior painting services page. Users click on the ad and are directed to a page that describes the service and then they find out what they came here for. Most small business owners send ads to their homepage. But when someone goes to the homepage, they have to go find the service they wanted when they clicked on the ad. If they don't find it there, they bounce off the homepage. Then the business owner wonders why none of their ads are converting.

If I had the budget, I would have an SEO professional proofread my AI content to make it more natural and make sure we use the best keywords that are much cheaper than writing content.