As a business owner or marketer in 2024, data is your most valuable resource. And when it comes to local business data, there‘s no richer source than Yelp. With over 224 million reviews and 5.2 million businesses listed, Yelp is a treasure trove of insights waiting to be mined.
But extracting all that valuable data manually would take countless hours of painstaking work. That‘s where Yelp scrapers come in. These tools allow you to automatically collect Yelp data at scale and export it to structured formats like Excel.
In this comprehensive guide, I‘ll show you why you should be scraping Yelp, what data is available, and exactly how to extract it using pre-built Yelp scrapers. I‘ll also share some tips and best practices to help you get the most out of your scraped data while staying compliant with Yelp‘s terms of service. Let‘s dive in!
5 Reasons to Scrape Yelp Data for Your Business
So what can you do with Yelp data once you‘ve scraped it? Here are five key use cases:
Competitor research and analysis – Collect data on your competitors‘ Yelp listings, including their ratings, review counts, price ranges, and most popular dishes/products. Analyze their strengths and weaknesses to identify opportunities.
Lead generation – Scrape business contact details like names, phone numbers, and website URLs to build targeted lead lists for your sales team. Filter by location, category, rating, and more to find the most promising prospects.
Industry and market research – Gather data on businesses in your industry and local market to spot trends, benchmark performance, and inform your strategies. Track things like pricing, popular offerings, and customer sentiment over time.
Reputation monitoring – Keep tabs on your own Yelp listing and online reputation by scraping your reviews and ratings. Quickly identify and respond to any negative feedback before it escalates.
Listing optimization – Make sure your Yelp business profile is complete, accurate and optimized to rank well and drive customer actions. Use scraped data to fine tune your listing title, categories, hours, delivery options, COVID-19 updates and other fields based on top performers.
Of course, there are many other applications of Yelp data depending on your specific goals and circumstances. But hopefully these spark some ideas!
What Data Can You Scrape from Yelp?
Now that you know why you might want to scrape Yelp, let‘s look at what exact data points are available. Yelp offers a wealth of structured data on every business listing, including:
- Business name
- Address
- Phone number
- Website URL
- Hours of operation
- Price range ($-$$$$)
- Categories/tags
- Rating (1-5 stars)
- Review count
- User-submitted photos
- Health inspection scores (for restaurants)
- COVID-19 updates (delivery options, safety measures, etc.)
You can also scrape unstructured text data from user reviews, including:
- Reviewer name
- Rating (1-5 stars)
- Review text
- Review date
- Review language
Note that full review text is only available for the first page of reviews on each listing. Beyond that, Yelp only provides truncated snippets. But 1 page is often enough to get a sense of customer sentiment.
In addition to the listing data itself, you can also collect Yelp search and category page results. This allows you to get aggregate stats like how many Japanese restaurants there are in Chicago or the top 10 bars in NYC by review count.
Challenges of Scraping Yelp
Scraping Yelp isn‘t always easy. Like many websites, Yelp has anti-scraping measures in place to prevent bots and scripts from harvesting their data. Some common obstacles include:
CAPTCHAs – Those annoying "I‘m not a robot" tests that require you to identify objects in blurry images. These are triggered if Yelp detects suspicious traffic from an IP address.
IP blocking – If Yelp catches you scraping, they may block your IP address temporarily or permanently. This prevents you from accessing their site at all.
Rate limiting – Even if your IP isn‘t blocked, making too many requests too quickly can cause Yelp to throttle your access and slow you down.
Dynamic loading – Many elements on Yelp pages are loaded dynamically via JavaScript after the initial page load. This can trip up basic scrapers that only grab the initial HTML.
Website changes – Yelp periodically redesigns elements of their site, which can break scrapers that rely on specific page structures, CSS classes or tags.
Fortunately, modern Yelp scraping tools are designed to handle these challenges for you. They use advanced techniques like IP rotation, dynamic rendering, machine learning and frequently updated templates to successfully extract Yelp data at scale. We‘ll look at exactly how they work in the next section.
How to Scrape Yelp Data Using a Pre-Built Tool
The easiest way to scrape Yelp data into Excel is by using a pre-built Yelp scraping tool. These tools provide a user-friendly interface for non-technical folks to extract Yelp data without writing any code.
My favorite is ScrapeHero‘s Yelp Scraper. It‘s a powerful yet intuitive tool that covers all the data points mentioned above. Here‘s how to use it:
Sign up for a free ScrapeHero account and navigate to the Yelp Scraper.
Pick one of the pre-made scraping tasks:
- Get reviews from a list of Yelp business URLs
- Get details of businesses from a search results URL
- Get results for a search term across multiple cities
Enter your parameters. If using the search tasks, provide your desired search terms, locations and max pages to scrape. If using the reviews task, simply paste in a list of Yelp listing URLs.
Click ‘Start‘ to run the scraper. It will automatically control the crawling speed to avoid detection. Depending on the amount of data, it may take anywhere from a few minutes to a few hours.
Once the scrape is complete, download your data as a CSV or Excel file. You can even schedule the scraper to run weekly or monthly and have the file emailed to you automatically.
That‘s it! With just a few clicks, you can extract thousands of data points from Yelp into structured spreadsheets ready for analysis. No coding or technical skills needed.
This is just one example – there are other good Yelp scraping tools out there like Parsehub, Octoparse and DataHen. Most work in a similar fashion. Just be aware that some have limited free plans that cap the amount you can scrape before paying.
Tips for Yelp Scraping Success and Compliance
Before you start gleefully grabbing data from Yelp, there are a few things to keep in mind. Following these tips will help you get better data while staying in Yelp‘s good graces:
Read Yelp‘s robots.txt file and terms of service. They outline what is and isn‘t allowed when it comes to scraping. In general, they prohibit using their data for commercial purposes without a license.
Don‘t scrape user‘s personal information like names and profile pics. Yelp considers this sensitive info. Stick to public business data and aggregate review stats/text.
Limit how fast and often you scrape. Use delays between requests to avoid slamming Yelp‘s servers. A good rule of thumb is no more than 1 request per second per IP.
Respect Yelp‘s copyright on their data. Don‘t reproduce large chunks of reviews verbatim or user-submitted photos without permission. Extracting facts/quotes and linking back is usually fine.
Use the data ethically and don‘t try to reverse engineer Yelp‘s algorithms or ranking systems. They will not be happy if you attempt this.
Keep your scraper up to date with Yelp‘s latest site changes. If you‘re building your own tool, monitor it for breakages and be prepared to update your code when needed.
As long as you play by the rules and use your scraped data responsibly, you likely won‘t ruffle any feathers at Yelp HQ. But when in doubt, consult a lawyer well-versed in data scraping and terms of service.
Putting Your Yelp Data to Work
Scraping Yelp data is just the first step – now you need to actually analyze and use it to improve your business. Here are a few ideas:
Plug review text into a sentiment analysis tool to gauge customer emotions at scale. Look for trends in what people love or hate about your business and competitors.
Analyze competitors‘ performance over time in Excel. Create graphs showing how their rating, review count, and other KPIs change week-over-week or month-over-month.
Use a text analysis tool to extract common phrases, keywords and topics from reviews. This can help identify your top selling points and areas for improvement.
Geocode the addresses of scraped businesses and create a map visualization. Spot clusters, voids and opportunities in different neighborhoods and zip codes.
Build a basic review dashboard in Excel showing your latest reviews, overall rating, common praises and complaints. Share it with your team to keep customer feedback top of mind.
There‘s no shortage of ways to slice and dice your Yelp data once it‘s in a structured format like Excel. The key is to experiment, look for insights and take action on what you find.
Wrapping Up
Yelp is an incredibly rich source of local business data just waiting to be tapped by savvy business owners and marketers. With a Yelp scraper tool, you can quickly and easily extract masses of valuable info on your customers, competitors and market.
By analyzing this data in Excel and other tools, you can surface insights to help you attract more customers, improve operations and outsmart the competition. Just remember to always put your customer‘s needs first and use your scraped data ethically.
Hopefully this guide has given you a solid foundation to start scraping Yelp for your business. The only thing left to do is pick a scraper tool and start extracting data – your future self will thank you.
Happy scraping!