Finding the Best Products to Resell on eBay: A Data-Driven Approach

Stop following the crowd and start following the data

In a world where everyone’s looking for the next big flip, finding profitable items to resell on eBay feels like searching for a needle in a haystack. Sure, there are countless articles telling you to “just sell sneakers” or “flip vintage electronics,” but if everyone’s reading the same generic advice, you’re walking into a bloodbath of competition.

Here’s the truth: The best things to resell on eBay are the ones nobody’s telling you about.

And the most reliable way to find them? Getting your hands dirty with data.

Why Most Resellers Fail Before They Start

Let’s face it – most reselling “gurus” are selling recycled lists that were already outdated when they wrote them. By the time you read that article about “Top 50 Hot Items to Flip This Season,” thousands of others have seen it too. The market gets saturated, margins get crushed, and suddenly that “can’t-miss opportunity” leaves you with inventory nobody wants.

This is why intuition matters, but hard-fact data matters even more.

Many resellers start by following standard advice – buying pallets of returned items from big box stores, scouring thrift shops for vintage clothes, or dropshipping trending products seen on social media. While these approaches can generate some income, they often require excessive work for mediocre returns.

The game-changer for successful resellers comes from shifting away from following generic advice and instead making decisions based on solid data.

The Web Scraping Revolution for Resellers

Web scraping sounds technical, but it’s simply the process of automating data collection from websites. For eBay resellers, it’s like having X-ray vision into what’s actually selling, not what people claim is selling.

Here’s how this works:

Beyond “What’s Hot” Lists

When most people research products to sell, they Google something like “best items to flip on eBay” and get a listicle from 2019. But what if you could see, in real-time:

• • Which items have the highest sell-through rates
• • The actual profit margins (not just listing prices)
• • Which categories have the lowest competition
• • Seasonal trends before they become obvious to everyone else

This isn’t theoretical – this is exactly what web scraping delivers.

Understanding Proxies: Your Digital Disguise

Before diving into scraping, let’s talk about proxies. Think of them as your digital disguise when collecting data.

What is a proxy?: The moment you start running any automated software on eBay, you’ll almost be 100% of the time be blocked because you’re detected as a bot. Now, here’s where proxy comes in, you’ll be given a new identity through a different IP (replacing the one of your home internet). You can’t just use any proxy, you need one that gives you the same real behavior of that of a real home. This is known as a residential proxy.

Why you need proxies:

• • Without them, websites can block you for making too many requests
• • They allow you to appear as different users from different locations
• • They prevent your IP from getting banned
• • They let you scale your data collection efforts

Building Your First Web Scraper (Easier Than You Think)

You don’t need a computer science degree to build a basic scraper. Here are three approaches, from easiest to most powerful:

Level 1: No-Code Scraping (What you see is what you get, even the fields included)

• • Tools like Octoparse or ParseHub let you point-and-click to extract data
• • Browser extensions like DataMiner can scrape eBay search results with zero coding
• • Import the data directly to Excel or Google Sheets for analysis

Level 2: Semi-Technical Approach (Best approach, but it does cost more)

• • Services like ScrapingBee handle the technical headaches and let them manage the bulk of the scraping code
• • You just provide URLs and tell it what data you want
• • They manage proxies, CAPTCHAs, and browser emulation for you

Level 3: Full Control – you make your own version (hardest but most rewarding)

• • Python with libraries like Beautiful Soup, Scrapy, and Botasaurus (a free, open-source library that simplifies web scraping)
• • Node.js with Puppeteer for JavaScript lovers
• • Custom scrapers that can extract exactly what you need

Looking quite intimidating right? Well good thing we live in the age of AI. You do have to put in the work to make it work, but using tools like ChatGPT, DeepSeek, Claude, Gemini, your life just became way easier. It’s all about the willingness to learn and try again and again.

The Reality of eBay Scraping: What You Need to Know

When it comes to scraping eBay, there are some important realities that most generic tutorials won’t tell you:

eBay Is Actually Easier to Scrape Than You Think

Unlike platforms like Amazon or Walmart that aggressively hunt down and block scrapers, eBay tends to be more lenient. Many resellers have successfully scraped thousands of products in just a few hours without getting blocked. For small to medium research projects, you might not even need proxies at all.

This is great news for beginners – you can often start with simpler setups and still get valuable data. Using multithreading (running multiple scraping processes simultaneously) can dramatically increase your collection speed without immediately triggering blocks.

Proxies: Start Cheaper Than You Think

While residential proxies are often pushed as the only safe option, here’s a money-saving truth: properly configured data center proxies can work perfectly fine for eBay scraping. They’re significantly faster and much less expensive. This is especially true with ByteZero’s unlimited Datacenter plans, where you’ll be paying per day for unlimited data so that you can relax and have predictable costs.

The secret is in the details – configure proper request headers and user agents to mimic real browser behavior. Combined with smart navigation techniques (like stopping page loads once you have the data you need), this approach can save you serious cash on your research operations.

When calculating the ROI of your reselling business, don’t forget to factor in these proxy costs alongside storage and other operational expenses. Start with the most cost-effective approach and upgrade only when necessary.

Technical Hurdles to Watch For

One common challenge with eBay is accessing product descriptions. eBay loads these in an iframe from another subdomain, which often rejects direct requests. This is why simple HTTP request libraries sometimes miss crucial content.

For complete data collection, consider tools like Selenium that automate actual browsers, or browser extensions like “Web Scraper” which handle these complex page structures more effectively. These tools can navigate the same way a real user would, accessing content that direct requests might miss.

Why You Can’t Just Use eBay’s API

You might wonder why scraping is necessary when eBay has an official API. The answer is simple: eBay’s APIs only return active listings, not sold listings. Since sold listings contain the most valuable data for market research (actual prices items sold for rather than what sellers hope to get), the API falls short for serious resellers.

eBay used to provide this data through their API but later restricted it to select partners, leaving scraping as the most reliable method for comprehensive research.

What Data Actually Matters (And Where to Find It)

So what should you actually be scraping? Here’s where to focus your efforts:

Completed Listings Analysis

The gold mine of eBay research is the “Sold Items” filter. This shows you what actually sold, not just what people hope will sell. For each category you’re interested in, scrape:

• • Final selling prices (not just asking prices)
• • Sell-through rates (what percentage of listings actually sold)
• • Average time to sale
• • Shipping costs (to calculate true margins)

By comparing sold versus unsold items in the same category, you can identify patterns in what makes certain listings successful while others languish.

Competitor Intelligence

Want to know who’s crushing it in your niche? Scrape data on:

• • Top sellers in your category
• • Their listing strategies
• • Item descriptions and title patterns
• • Photography styles and quality
• • Pricing strategies and special offers

This isn’t about copying others – it’s about understanding what works and why, then doing it better.

Listing Optimization Patterns

After scraping thousands of listings, clear patterns emerge:

• • Which keywords appear most frequently in successful listings
• • Optimal title lengths and structures
• • Description formats that lead to higher conversions
• • Best days and times to list specific categories
• • Price points that maximize profit while maintaining volume

These insights let you optimize your listings based on what’s actually working right now, not what worked last year.

Seasonal Trend Prediction

By scraping historical data, you can identify seasonal trends before they happen:

• • When demand for certain items starts rising
• • How long price peaks typically last
• • Which categories show the strongest seasonal patterns
• • The ideal time to buy inventory before seasonal spikes

This lets you stock up on items right before demand explodes, not after prices have already peaked.

Practical Example: Finding a Profitable Niche

Here’s how data-driven research can uncover a profitable niche that wouldn’t appear on typical “hot items” lists:

Consider a case where a reseller built a simple scraper to analyze women’s clothing sales across different subcategories. After collecting data on over 50,000 completed listings, they discovered something interesting: vintage 1980s sweaters with specific patterns had:

• • 87% sell-through rate (compared to 34% for the broader category)
• • Average profit margins 3.2x higher than category average
• • Lower return rates than similar items
• • Significantly fewer sellers than buyers

More importantly, these items weren’t appearing on any “what to sell” lists because they weren’t obvious unless someone was specifically looking at the data patterns.

A savvy reseller could source these specific sweaters from local thrift stores where they were priced based on being “old sweaters” rather than “vintage fashion.” This kind of data-driven niche identification can lead to a single category generating more profit than several broader categories combined.

The Ethical Considerations

Before you jump in, let’s address the ethical aspects of web scraping:

• • Respect robots.txt files – These tell scrapers which parts of a site are off-limits
• • Implement rate limiting – Don’t hammer servers with requests
• • Only collect public data – Never try to access private information
• • Use the data for personal research – Not for redistribution
• • Consider official APIs first – Many platforms offer them

eBay does have an API, but it has limitations for this kind of research. With ethical scraping practices and good proxy usage, you can stay within acceptable boundaries.

From Data Collection to Decision Making

Having data is one thing – knowing what to do with it is another. Here’s a recommended framework for turning raw scraping results into actionable business decisions:

• • Identify Patterns – Look for consistent correlations between listing characteristics and outcomes
• • Test Hypotheses – Use small inventory purchases to verify your findings
• • Scale Gradually – Once verified, increase inventory in proven niches
• • Continuously Monitor – Markets change; keep scraping to stay ahead
• • Adapt Quickly – Be willing to pivot when the data shows shifts

This approach minimizes risk while maximizing your ability to capitalize on opportunities others miss.

Beyond Product Selection: Advanced Applications

Once you’ve mastered basic scraping for product research, you can level up to more sophisticated applications:

Dynamic Pricing Algorithms

Create systems that automatically adjust your prices based on:

• • Competitor pricing changes
• • Overall market supply
• • Time of day/week effects on conversion rates
• • Seasonal demand fluctuations

This lets you maximize profit without constant manual adjustments.

Inventory Forecasting

Use historical data to predict:

• • When to restock specific items
• • How much inventory to maintain
• • When to liquidate before demand drops
• • Which new items to test based on emerging patterns

This prevents both stockouts and excess inventory.

Cross-Platform Arbitrage

Expand your scraping to other platforms to find:

• • Items underpriced on one platform that sell well on eBay
• • Supply sources where you can acquire inventory below market value
• • Emerging trends on social platforms that haven’t hit eBay yet

This creates opportunities for arbitrage across different marketplaces.

When to Sell the Shovel Instead of Digging for Gold

As you develop expertise in data-driven reselling, you might discover an even more valuable opportunity: selling your knowledge and tools to other resellers.

Consider creating:

• • Custom scraping tools for specific niches
• • Data reports on emerging opportunities
• • Training programs on data-driven reselling
• • Software that automates the research process

Many successful resellers eventually transition from selling products to selling information and tools to other sellers – often at much higher profit margins and with less inventory hassle.

Getting Started Today

If you’re ready to leave behind generic advice and build a data-driven reselling business, here’s your action plan:

• • Start Small – Pick one category you’re interested in
• • Use Basic Tools – Begin with browser extensions or no-code scrapers
• • Focus on Sold Items – Analyze what’s actually selling, not just what’s listed
• • Look for Patterns – Identify characteristics of successful listings
• • Test and Validate – Make small inventory investments to test your findings
• • Scale What Works – Double down on validated opportunities
• • Continuously Learn – The market evolves; your research should too

Remember, the goal isn’t to find the “perfect product” that everyone sells. It’s to discover underserved niches where you can build expertise and reputation while maintaining healthy margins.

Conclusion: Data as Your Competitive Edge

In a marketplace where most sellers follow the same generic advice, your ability to extract and act on data becomes your unfair advantage. Web scraping isn’t just a technical skill – it’s the difference between following trends and spotting them before anyone else.

The best things to resell on eBay aren’t found in listicles or YouTube videos. They’re hidden in the data, waiting for someone curious and persistent enough to find them.

That someone could be you.

Note: Always review eBay’s terms of service and consult legal advice before implementing web scraping at scale. This article is for educational purposes and doesn’t constitute legal advice.