How to Scrape Pinterest Data

Pinterest Scraping
April 1, 2025 • 7 minutes of reading

Pinterest has huge volumes of useful data, but how can businesses collect it efficiently?

Manually gathering images, descriptions, and insights from the platform can be time-consuming and prone to errors. Web scraping can provide a means of automating your data extraction, making the process quicker and more efficient.

This guide will walk you through everything regarding how Pinterest scraping works and how to perform it ethically and legally.

What is Pinterest scraping?

Pinterest is a visual discovery platform and social networking site that allows users to discover, save, and share images and videos on virtual pinboards. From wedding planning to home décor, fitness tips to recipe ideas, Pinterest inspires over 450 million active users globally. It’s a place for businesses to understand consumer preferences, recognize trends, and plan strategies.

Pinterest data is invaluable for businesses and individuals looking to enhance their strategies. For businesses, it can help analyze consumer behavior, track trends, and create data-driven marketing campaigns. Content creators can use the data to understand engagement patterns to tailor their content to what resonates most with audiences. Researchers can study societal trends, preferences, and visual culture.

The insights from Pinterest’s vast repository of data allow businesses to predict market trends, identify audience interests, and refine product strategies effectively. If you are new to web scraping check out our dedicated article on the basics of web scraping here.

Many types of data can be extracted from Pinterest, including:

  • Images: High-quality visuals curated by users, often tied to specific themes or ideas.
  • Videos: Short clips, tutorials, and product demos gaining popularity on the platform.
  • Profile data: Public information such as user bio, boards, and follower counts.
  • User preferences: Insights into what users save, like, or pin most frequently.
  • Trends: Seasonal or topics that gain traction across categories.
  • Engagement metrics: Data on the number of pins, repins, likes, and comments, helping measure content popularity and influence.

Datamam, the global specialist data extraction company, works closely with customers to get exactly the data they need through developing and implementing bespoke web scraping solutions.

Datamam’s CEO and Founder, Sandro Shubladze, says: ”Whether it’s tracking emerging trends or analyzing user behavior, the data extracted from Pinterest offers a unique window into what resonates with audiences.”

Why scrape Pinterest?

Pinterest scraping assists businesses and individuals in making better decisions, enhancing their marketing approaches, and innovating.

Pinterest data can help marketers get an idea of their audience and create content according to consumer interests. Scraping popular keywords, pin descriptions, and hashtags can help to refine SEO strategies and increase reach. A retailer, for example, might use scraped data to identify trending seasonal styles and incorporate them into their advertising campaigns.

Pinterest profiles often contain valuable public information, such as links to personal websites or business contact details. Scraping this data enables businesses to build targeted lead lists efficiently.

Pinterest trends reflect real-time shifts in consumer interests, making it a valuable source for trend forecasting. Scraping engagement data and content categories helps businesses stay ahead of market changes. A beauty brand might monitor the rise of specific makeup techniques or product categories, for example, by scraping popular pins and boards, enabling them to launch timely products.

Pinterest’s focus on visual content makes it a perfect platform for advertising. Businesses can scrape data to understand what content gets the most visibility and tailor their ads to fit Pinterest’s ecosystem.

In a recent Datamam project, for example, an online retailer was able to extract Pinterest information about pins that related to their product line. By analyzing the engagement of users, this company was able to not only identify top categories but also increase sales by 20% through targeted promotions.

If you’re exploring social media platforms beyond Pinterest, our article on scraping LinkedIn data can help you extract valuable insights from professional profiles and company pages.

Sandro says: ”Brands can leverage trend data to stay ahead. Ethical and strategic use of Pinterest data ensures that businesses not only meet their goals but also deliver more meaningful experiences to their customers.”

Scraping data from Pinterest is generally legal, but this does depend on the collection method and usage of the data. Generally, it is legal to scrape publicly available data, but one must pay attention to Pinterest’s Terms of Service (ToS) and ethical practices to avoid any potential legal or reputational risks. Learn more about the laws and ethical implications of web scraping in our guide.

Pinterest offers the REST API, a legitimate and structured way to access data. This API allows developers to retrieve information, such as pins, boards, and user profiles, within the platform’s guidelines. It enables businesses to access data in compliance with Pinterest’s ToS, and to obtain structured information whilst managing rate limits effectively.

Although the API is ideal for extracting certain data types, it can be limited when looking at bulk historical data, which is where custom scraping might come into play.

Pinterest does not inform account owners when images are downloaded from their accounts. However, whenever such information is used, crediting the source should always be considered, especially for commercial purposes, to avoid any intellectual property violation and for ethical reasons.

How can businesses scrape ethically and legally?

There are a number of key precautions businesses can take to avoid legal and ethical risks, including:

  1. Focus on public data only: Scrape only data that is freely available without requiring logins or bypassing restrictions. Avoid scraping private boards or user-sensitive information.
  2. Attribute properly: Ensure that any downloaded images or content are credited to their original creators, as per copyright requirements.
  3. Avoid overloading servers: Use rate limits and proxies to prevent excessive requests that could disrupt Pinterest’s services.
  4. Use data responsibly: Do not repurpose scraped data for spam, fraud, or other unethical activities. Misuse of data can lead to legal consequences and damage your reputation.

Following these rules allows businesses and individuals to gain useful insights while extracting data from Pinterest legally and ethically. For advanced data extraction, working with a  trusted services provider can ensure efficiency whilst following best practices and compliance with the law.

Sandro says: “Through the REST API provided by Pinterest, it’s possible to obtain useful data whilst complying with the website’s guidelines. However, one must remember not to lose focus on public data, not overload any server, and respect intellectual property by attributing content correctly.”

How to scrape Pinterest

1.      Set up and planning

Define the data you want to extract, such as images, descriptions, or engagement metrics. Identify the target URLs (e.g., specific boards or profiles) and ensure they comply with Pinterest’s publicly accessible data policies.

Review Pinterest’s Terms of Service and take precautions to scrape responsibly, such as using proxies.

2.    Install relevant tools

Some of the key tools for Pinterest scraping are as follows:

  • Python: A versatile programming language used for web scraping.
  • Requests: For sending HTTP requests to access web pages.
  • Beautiful Soup: For parsing and extracting HTML data.
  • Selenium: For handling dynamic content or JavaScript-rendered pages.
  • Pandas: A powerful library for data manipulation and analysis.

Install these tools using a package manager like pip:

pip install requests 
pip install beautifulsoup4 
pip install selenium 
pip install pandas

3.    Extract and parse data

Write a script to access Pinterest pages and extract relevant data. Below is an example using Python: It is important to consider that some Pinterest pages rely on JavaScript, requiring advanced tools like Selenium or Puppeteer to scrape effectively.

import requests
from bs4 import BeautifulSoup

# Access a Pinterest page
url = 'https://www.pinterest.com/example-board/'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

# Extract image URLs
image_urls = []
images = soup.find_all('div', {'role': 'listitem'})

for item in images:
    image_urls.append(item.find('img')['src'])

4.    Storage and use

Save the scraped data in structured formats like CSV or JSON for easy analysis.Use a database (e.g., MongoDB or MySQL) for large-scale data storage and retrieval. Apply the data for analytics, marketing, or trend identification, always ensuring compliance with ethical guidelines.

# Saving image urls in CSV file using pandas library
import pandas as pd

df = pd.DataFrame(image_urls, columns=['image_url'])
df.to_csv('pinterest_images.csv', index=False, encoding='utf-8')

# Saving image urls in JSON file
import json

with open('pinterest_images.json', 'w', encoding='utf-8') as f:
    f.write(json.dumps(image_urls, indent=2))

How Datamam can help

Scraping Pinterest the right way requires technical expertise and compliance with legal and ethical standards. Datamam specializes in creating tailored scraping solutions that address these challenges.

By using Datamam’s services, you can:

  • Access Pinterest data efficiently and ethically.
  • Overcome technical limitations such as dynamic content and rate restrictions.
  • Receive structured and actionable data ready for analysis, without the hassle of building and maintaining your scraping infrastructure.

Sandro says: “While Python, Beautiful Soup, and Selenium are extremely powerful in scraping data, they usually tend to be limited either by the rate at which requests are made or by the presence of dynamic content.”

“Partnering with a professional service provider like Datamam allows you to go beyond overcoming obstacles to access this data effectively and responsibly, fully adhering to the policies of each platform, so you can focus on transforming the information into concrete strategies.”

For more information on how we can assist with your web scraping needs, contact us.

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