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Author Archives: Sonja Schurig

Optimize Inventory Levels with Scraper APIs

Ecommerce businesses frequently encounter inventory challenges. In fact, 56% of retailers report difficulties with accurate inventory tracking. Keeping track of competitor inventory levels is a game-changer for online retailers. Whether you’re looking to maximize sales, anticipate demand, or make smarter pricing decisions, scraping competitor inventory data provides valuable insights. This guide will walk you through the benefits, legal considerations, challenges, and best tools for scraping competitor inventory levels effectively.

Benefits of Scraping Competitor Inventory Data

Monitoring competitor stock levels allows online retailers to make data-driven decisions and stay ahead in a competitive market. Here are some key benefits:

  • Identify When Competitors Run Out of Stock: If a competitor runs out of a high-demand product, you can capitalize on the opportunity by adjusting your pricing, boosting promotions, or ensuring your stock is well-maintained.
  • Efficient Inventory Management: Poor inventory management causes businesses to lose up to 11% of their annual revenue, mainly due to stockouts and overstocking.
  • Improved Omnichannel Management: For companies selling across multiple platforms, scraping ensures accurate inventory representation across all channels.
  • Better Supplier Monitoring: Scraping can extend to supplier websites, helping businesses plan inventory more effectively.
  • Monitor the velocity of competitor sales: When scraping inventory levels over time, you can begin to track sales volumes. 

How to Scrape Competitor Inventory Data Legally and Effectively

Scraping competitor inventory data can be incredibly useful, but it’s essential to follow legal and ethical best practices to avoid violating website terms of service or data privacy laws.

Best Practices for Legal Scraping

  1. Use APIs When Available: Leveraging an API ensures compliant data collection while reducing maintenance costs. 
  2. Scrape Only Publicly Available Data: Avoid accessing password-protected, user-restricted, or proprietary information.
  3. Implement Rate Limiting: Prevent excessive requests that could overwhelm the target website and lead to IP bans.
  4. Focus on Factual Data: Stick to publicly available product codes, prices, and stock levels, which are typically not protected by copyright.
  5. Comply with Data Privacy Regulations: Ensure compliance with laws like GDPR and CCPA by avoiding the collection of personal data.

Steps to Scrape Competitor Inventory Data

  1. Identify Competitors: Determine which retailers you want to track and which specific inventory data is most relevant to your business.
  2. Select a Scraping Tool or API: You can either develop a custom scraper using Python or use a dedicated web scraper API.
  3. Set Up Your Scraper: Configure it to collect essential data such as product names, SKUs, pricing, and stock levels.
  4. Parse and Structure the Data: Organize the collected data in a structured format like CSV or JSON. A dedicated web scraper API can automate the process of structuring and parsing the data for quicker analysis.
  5. Schedule Regular Monitoring: Inventory levels fluctuate frequently, so set up automated scraping at regular intervals to maintain accuracy.

Main Challenges of Scraping Inventory Data

Extracting value from inventory data presents unique challenges compared to other web scraping applications, such as price monitoring.

  • Location-Specific Data: Many retailers require a zip code input to display inventory, meaning you must ensure your scraper accounts for regional availability.
  • In-Stock Validation vs. Inventory Levels: Some sites provide data on whether an item is in stock, while others provide a count of in-stock items.
  • Frequent Website Changes: Retailers often update their website structures, requiring scrapers to be regularly maintained.
  • IP Blocking & Anti-Scraping Measures: Some retailers implement security measures to prevent automated scraping, making API-based solutions a more reliable option.

Where to Find Inventory Data

If you’re looking to scrape inventory data, here are some common sources:

  • Google Shopping – Aggregates product availability across multiple retailers.
  • Amazon – Provides stock levels for millions of products.
  • Walmart – Offers in-store and online inventory tracking.
  • Target – Displays local store stock levels.
  • Home Depot – Shows inventory for both online and in-store products.

Benefits of Traject Data’s Inventory API

Traject Data’s Inventory API simplifies competitor inventory tracking by providing reliable, real-time data from multiple sources with flexible pricing options. Here’s what makes it stand out:

  • Real-Time Updates: Get up-to-the-minute stock levels directly from retailer websites.
  • Multiple Retailers: Access inventory data from a wide range of marketplaces to get a comprehensive view of product availability.
  • Structured Data Format: The API delivers clean, structured data, reducing the need for manual parsing.
  • Coverage: Traject Data provides APIs for Google Shopping, Amazon, Walmart, Home Depot, and Target.

Get Started with Traject Data’s Inventory APIs

If you’re ready to gain a competitive edge with real-time inventory insights, explore Traject Data’s APIs today and start optimizing your inventory strategy.

Ready to See What Traject Data Can Help You Do?

We’re your premier partner in web scraping for SERP data. Get started with one of our APIs for free and see the data possibilities that you can start to collect.

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How to Estimate Sales on Amazon

Sales forecasting on Amazon is a critical component of any successful Amazon business. Improving forecasting accuracy, even by a small percentage, can significantly impact a company’s production and financial planning, marketing strategies, inventory control, and supply chain management.

Without reliable sales forecasts, ecommerce businesses risk overstocking (leading to increased storage costs and potential waste) or understocking (resulting in lost sales and dissatisfied customers). By investing in sales forecasting, Amazon ecommerce businesses can optimize operations, reduce costs, and maximize profits.

But how do you forecast your Amazon sales for a new product you haven’t sold before? Let’s dive in.

What Is Amazon Sales Forecasting?

Amazon sales forecasting is the practice of predicting future customer sales and demand for products sold on Amazon. It involves analyzing historical sales data, market trends, and other relevant factors to estimate future sales volume. This allows sellers to optimize inventory management and make informed decisions about stock levels and pricing to meet customer needs effectively.

How to Forecast Ecommerce Sales using Amazon Data

Amazon sales forecasting relies on analyzing historical data and market trends to predict future demand. But where do you get this data? Fortunately, Amazon is a massive ecommerce platform with a wealth of publicly available data. As of 2025, Amazon holds a 37.8% shareshare of the US ecommerce market—and it’s still growing. Including third-party sellers, the total number of products available on Amazon exceeds 350 million, making it a rich source of historical sales data. So, no matter what product you’re interested in selling, you’ll likely be able to find relevant data for analysis.

Businesses typically use a combination of statistical models, machine learning algorithms, and domain expertise to refine their forecasts. The process often includes:

  • Collecting Data – Gather historical sales data from key sources like Amazon, Walmart, and Google. Consider seasonal trends, competitor insights, and external market factors for a comprehensive analysis.
  • Choosing a Forecasting Model – Utilize time-series analysis, regression models, or AI-driven machine learning techniques.
  • Analyzing Customer Behavior – Incorporate customer demographics, purchase history, and engagement trends.
  • Adjusting for Market Conditions – Factor in economic trends, supply chain disruptions, and promotional campaigns.
  • Validating the Forecast – Compare past forecasts to actual sales to refine and improve accuracy over time.

A well-executed sales forecasting strategy helps ecommerce businesses anticipate demand fluctuations and make proactive business decisions. Not all market conditions can be predicted, so you’ll need to monitor and maintain your algorithm as new market variables are introduced.

What Is the Best Formula for Amazon Sales Forecasting?

For ecommerce demand forecasting, especially when selling a product on Amazon, several commonly used formulas can help predict the number of units sold. Here are some of the most relevant methods:

Exponential SmoothingA forecasting technique that uses a weighted average of past data points to predict future values.
Time Series AnalysisThis method analyzes historical data to identify patterns and trends in demand. It uses statistical techniques to forecast future demand based on past patterns.
Sales Rank-Based EstimationAmazon sellers often use sales rank to estimate potential sales. For example, if a product at rank 25,000 sells 250 units per month, a product at rank 5,000 might sell approximately five times more, or 1,250 units.

Machine learning methods are becoming increasingly prevalent in demand forecasting. However, historical data is crucial—you’ll need a statistically significant dataset to make accurate predictions.

Accurate forecasting requires continuous monitoring and adjustment based on actual performance and market conditions. As the market changes, you’ll need to refine your calculations.

What Is an Amazon Sales Estimation API?

If you’re not a machine learning expert or mathematician, you’ll likely want to leverage an Amazon sales estimation tool. An Amazon Sales Estimation API is a software application that allows businesses to predict future sales revenue for their online store by analyzing historical sales data, market trends, and other relevant factors.

How It Works:

  • Retrieves and processes historical sales data from Amazon for a product.
  • Uses machine learning and statistical models to generate accurate sales forecasts.
  • Provides real-time sales projections to assist with inventory management, marketing, promotion, and pricing strategies as the market evolves.

Benefits of Using an Amazon Sales Estimation API

  1. Improved Inventory Management – Accurate forecasts help businesses maintain optimal stock levels, reducing overstocking and stockouts.
  2. Reduced Costs – Minimizes expenses associated with overstocking and storage.
  3. Enhanced Marketing Strategies – Understanding future demand enables businesses to fine-tune marketing efforts for peak seasons and targeted campaigns.
  4. Optimized Pricing Strategies – Forecasting demand allows businesses to optimize pricing for maximum profitability.
  5. Data-Driven Decision Making – Advanced analytics provide valuable insights that drive smarter, more strategic business choices.
  6. Increased Customer Satisfaction – Ensures products are readily available when customers need them.

Traject Data’s Amazon Sales Estimation API

For businesses looking for a powerful and reliable sales forecasting solution, Traject Data’s Amazon Sales Estimation API is designed to provide accurate and actionable insights.

Key Features:

  • Sales Estimates – Provides sales projections for individual products and categories.
  • Real-Time Data Access – Uses up-to-date market trends and customer behavior insights so you can continually monitor while the market evolves.
  • Customizable Forecasting Parameters – Adjust forecasts based on your products, industry, and geographic location.

By leveraging Traject Data’s Amazon Sales Estimation API, ecommerce businesses can make informed decisions on inventory, pricing, and marketing strategies—ultimately driving higher profitability.See how Traject Data’s Advanced Amazon Sales Estimation API can transform your sales forecasting and explore our detailed API documentation.

Ready to See What Traject Data Can Help You Do?

We’re your premier partner in web scraping for SERP data. Get started with one of our APIs for free and see the data possibilities that you can start to collect.

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SERP Fundamentals for B2B Marketers: What Are You Missing?

In the dynamic realm of B2B marketing, a deep understanding of the Search Engine Results Page (SERP) is paramount for gaining a competitive edge. To truly maximize your online visibility and drive relevant traffic, leveraging a SERP API for B2B is essential. This powerful tool allows you to go beyond basic SEO, providing critical insights into search results that you might otherwise be missing.

What is B2B SERP? 

B2B SERP (Business-to-Business Search Engine Results Page) refers to the set of webpages that appear on a search engine, like Google or Bing, when business professionals search for industry-related information. Unlike B2C searches, B2B SERP is focused on connecting businesses looking for products or services from other businesses.

Why SERP Matters for B2B Marketers

B2B SERP and SEO is a strategy designed to increase organic search traffic and keyword rankings for business websites. A successful B2B SEO strategy puts a company’s website in front of decision-makers actively searching for solutions. Research shows that 72% of B2B buyers begin their research on a search engine, highlighting the importance of SERP visibility.

B2B vs B2C SERP: What’s the Same

SERP Basics remain the same whether you’re targeting business or consumers. While B2B and B2C SEO strategies have distinct differences, several key elements are important for both approaches:

  • Keyword research and optimization: Both B2B and B2C SEO require thorough keyword research to target relevant terms that align with user search intent.
  • Quality content creation: Producing valuable, engaging content is crucial for both B2B and B2C SEO to attract and retain visitors.
  • On-page optimization: Proper optimization of meta tags, headers, and internal linking structures is essential for both types of SEO.
  • Technical SEO: Both B2B and B2C require strong technical SEO, including mobile optimization and fast page load speeds. However, B2B SEO may involve more complex site structures due to the need for detailed product or service information.
  • Link building: Acquiring high-quality backlinks remains a crucial aspect of SEO for both B2B and B2C strategies.
  • Schema markup: Implementing structured data can enhance search visibility for both B2B and B2C websites.
  • Performance metrics tracking: Both approaches require monitoring and analysis of relevant SEO metrics to measure success and make data-driven decisions.

B2B vs. B2C SERP: Key Differences 

While the fundamentals of SEO apply to both B2B and B2C, the execution differs significantly due to audience, sales cycle, and intent. Here’s what sets them apart:

Target Audience and Decision-Making

  • B2B SERP: Targets businesses and involves multiple stakeholders (e.g., CEOs, procurement managers). The goal is to build credibility through in-depth content like whitepapers and case studies.
  • B2C SERP: Targets individual consumers with content designed for quick conversions. Engagement is typically more emotional and impulse-driven.

Buyer’s Journey and Sales Cycle

  • B2B SERP: Features a longer sales cycle (3-12 months) with multiple touchpoints and in-depth research.
  • B2C SERP: Often involves immediate or short-term purchases with a faster decision-making process.

Keyword Strategy

  • B2B SERP: Prioritizes niche, industry-specific keywords with lower search volume but high intent. Long-tail keywords play a crucial role in reaching the right audience. While niche keywords may drive less traffic, their high relevance ensures you attract engaged users who are more likely to convert.
  • B2C SERP: Prioritizes high-volume, broad keywords with a stronger emphasis on transactional terms.

Content Strategy

  • B2B SERP: Includes thought leadership articles, in-depth guides, and whitepapers to establish authority.
  • B2C SERP: Focuses on visually appealing, short-form content like product descriptions and blogs.

Conversion Goals and Metrics

  • B2B SERP: Aims to generate qualified leads and nurture them over time. Key metrics include lead quality and engagement metrics.
  • B2C SERP: Prioritizes immediate sales with metrics like conversion rate and revenue per visit.

Steps to Enhance Your B2B SERP Strategy

  1. Create Buyer Personas: Tailor content and keywords to the search behavior of key decision-makers.
  2. Conduct Niche Keyword Research: Focus on specific industry terms and long-tail keywords that signal purchase intent.
  3. Develop a Topic Cluster Strategy: Use pillar pages linking to related content to improve site structure and SEO authority.
  4. Optimize Product & Service Pages: Enhance metadata, title tags, internal linking, and structured data.
  5. Create High-Value Content: Publish expert guides, case studies, and whitepapers to establish authority.
  6. Implement Technical SEO Best Practices: Ensure fast page speeds, mobile optimization, and proper schema markup.
  7. Build a Strong Backlink Profile: Gain high-quality backlinks through guest posting and industry collaborations.
  8. Monitor & Adjust Strategy Regularly: SEO evolves constantly; track SERP trends and competitor movements.
  9. Utilize a SERP API: Automate competitive analysis and market insights with real-time SERP data.

By implementing these steps, B2B companies can improve their SEO performance, increase organic traffic, and drive more qualified leads to their website. Don’t expect immediate results. SERP rankings and SEO is a long-term game, so it’s important to take your time, run experiments, and implement best practices.  

Why Use a SERP API for B2B SEO?

SERP APIs provide real-time search data, helping marketers analyze keyword rankings, competitor performance, and search trends at scale. Leveraging a SERP API saves time and reduces errors while offering a comprehensive view of the market landscape. You’re able to customize your data analysis by selecting the most relevant fields for your business while obtaining a complete picture of the results. Search engines are constantly updating their algorithms and site structure which makes manual tracking costly. Using a SERP API to scrape publicly available data from search engine results pages (SERPs) is legal as long as you adhere to the search engine’s terms of service and do not violate them. Leveraging a reputable SERP API provider reduces your risk of non-compliance.

How to use a B2B SERP API:

  1. Choose a Provider: Select an API that meets your data needs and budget.
  2. Get an API Key: Sign up and obtain authentication for access.
  3. Build Search Queries: Target relevant industry keywords.
  4. Send API Requests: Retrieve live SERP data for analysis.
  5. Analyze & Optimize: Use the data to refine your SEO strategy and outperform competitors.

Try Traject Data’s SERP API Today

Traject Data offers industry-leading SERP and eCommerce APIs, providing granular localization, deep data sources, and high-speed performance. Our APIs help businesses optimize pricing, track competitors, and gain actionable market insights.
Try Traject Data’s SERP API for free and take your B2B SEO strategy to the next level.

Ready to See What Traject Data Can Help You Do?

We’re your premier partner in web scraping for SERP data. Get started with one of our APIs for free and see the data possibilities that you can start to collect.

View All Serp APIs

How to Keep Your Omnichannel Ecommerce Data Consistent Across Every Platform With a Web Scraping API

The future of ecommerce is omnichannel, and a web scraper API for omnichannel ecommerce is essential for staying competitive. While multichannel selling expands your reach across multiple platforms, omnichannel ecommerce goes a step further by creating a seamless shopping experience across all touchpoints. This approach enhances brand consistency, improves customer engagement, and reduces risk. In this article, we’ll explore the biggest challenges of omnichannel ecommerce and how a web scraper API can help you monitor and optimize your strategy effectively.

Multichannel vs. Omnichannel Ecommerce: What’s the Difference? 

Multichannel – The goal of multichannel e-commerce is to maximize reach by being present on as many sales channels as possible—Amazon, Walmart, social media, websites, physical stores, and more. However, these channels often operate independently, leading to inconsistencies in pricing, inventory, and messaging.

Omnichannel – Retailers that use an omnichannel strategy don’t just sell on multiple platforms—they ensure a consistent, unified experience across them all. Messaging, branding, and pricing are harmonized, so customers receive the same experience whether they shop online, in-store, or on a marketplace like Amazon. The goal is to provide seamless transitions between channels, fostering trust and customer loyalty.

Still not sure if omnichannel is worth the investment? Consider these compelling statistics:

  • Omnichannel retailers retain 90% more customers.
  • Companies with omnichannel customer engagement see a 179% increase in sales revenue on average. 
  • Omnichannel shoppers generate 30% higher lifetime value, making them more profitable long-term.
  • Retailers using three or more channels see a 250% boost in consumer engagement. 
  • 90% of consumers expect a seamless brand experience across all channels—consistency matters more than ever.

The Biggest Challenges of Omnichannel Ecommerce

While omnichannel ecommerce offers a superior customer experience, it comes with significant challenges. Businesses must maintain consistency across platforms to avoid damaging their brand and losing customer trust.

1. Pricing and Messaging Consistency

Customers expect uniform pricing and messaging regardless of where they shop. However, price fluctuations, promotional inconsistencies, and mismatched product descriptions can create confusion and harm credibility.

2. Brand Image & Customer Experience

A strong, recognizable brand is key to customer loyalty. When branding varies across platforms, it creates a disjointed shopping experience that can weaken customer trust and engagement.

3. Data Visibility & Channel Conflict

Many businesses struggle to access real-time insights on sales, inventory, and customer behavior across multiple channels. When different departments prioritize their own sales strategies over an integrated approach, it can lead to conflicts that hurt the overall business.

4. Inventory and Order Management

Keeping stock levels synchronized across all platforms is crucial to avoid overselling or stockouts. Without accurate real-time inventory updates, businesses risk losing sales and disappointing customers.

How a Web Scraper API Can Solve Your Omnichannel Challenges

A web scraper API is an essential tool for maintaining consistency in omnichannel e-commerce, and improving customer experience. Here’s how it helps:

✅ Real-time Data Monitoring – Ensures businesses always have up-to-date information on pricing, inventory, and competitor trends.
✅ Automated Data Collection – Reduces manual effort and increases efficiency in tracking multiple sales channels.
✅ Competitor Benchmarking – Helps businesses stay competitive by tracking competitor pricing and product availability.
✅ Brand Compliance Monitoring – Ensures accurate product descriptions, pricing, and messaging across all platforms.
✅ Review Monitoring – Track customer feedback across multiple channels to ensure customer satisfaction and address issues proactively.

Future-Proof Your Omnichannel Strategy with Traject Data

To succeed in omnichannel ecommerce, businesses need the right tools to collect and analyze data seamlessly. That’s where Traject Data comes in.

  • Wide Coverage Across Channels – Monitor pricing from Amazon, Walmart, Google, Target, Home Depot and Ebay.
  • Reliable Infrastructure – Get real-time data with minimal latency and downtime.
  • Seamless Integrations – Schedule automated data pushes to your preferred destination.
  • Scalability – Handle tens of millions of requests daily as your business grows.
  • Comprehensive Documentation & Support – Get expert guidance and fast issue resolution.
  • Flexible Pricing – Scale costs based on your needs with a free trial before committing.
  • Clean, Structured Data – We handle data parsing, so you get accurate results without extra processing.

Ready to take your omnichannel data monitoring to the next level? Try Traject Data for free and ensure consistency across every platform.

Ready to See What Traject Data Can Help You Do?

We’re your premier partner in web scraping for SERP data. Get started with one of our APIs for free and see the data possibilities that you can start to collect.

View All Serp APIs

Harness the Power of APIs to Optimize Your Pricing Strategy

Digital technology has transformed consumer purchasing power. We can buy anything, anywhere, anytime, and the market is flooded with competition. As of 2025, there are approximately 30.7 million e-commerce stores worldwide. In the crazy world of ecommerce, your pricing strategy can make or break your business.

Companies that implement a structured pricing strategy can see a 40% increase in revenue year-over-year. But how do you implement an effective pricing strategy? A successful pricing strategy must be data-driven. Web scraping APIs for price tracking and competitive pricing provide real-time insights to help businesses make data-driven decisions and stay ahead of the competition.

The Role of Web Scraping APIs in Pricing Strategy

The beauty of online retail means that adjusting your prices based on market conditions is easy. The days of brick-and-mortar fixed pricing are gone. One in five ecommerce businesses now use dynamic pricing, automatically adjusting prices based on demand and inventory. Amazon, in particular, is known for its sophisticated dynamic pricing algorithms which update prices every few minutes based on demand, stock levels, and competitor pricing. Walmart is close behind, changing prices daily. 

The ability to track and analyze competitor pricing trends across multiple channels gives businesses an advantage. However, dynamic pricing makes it nearly impossible to manually stay on top of industry pricing trends. This is where price monitoring scraper APIs come in—they automate pricing intelligence, allowing businesses to track prices in real-time.

Major E-Commerce Platforms for Price Scraping

E-commerce giants like Amazon and Walmart dominate the online marketplace and set industry-wide pricing standards. Extracting pricing data from these platforms provides valuable insights into competitive pricing trends. Monitoring these marketplaces helps businesses react quickly to pricing shifts and implement strategic adjustments to stay ahead. 

Challenges in Price Scraping

While price scraping offers undeniable benefits, it also comes with challenges. Amazon and Walmart use sophisticated anti-scraping measures, including:

  • Bot detection
  • Rate limiting
  • IP blocking
  • CAPTCHAs

This results in frequent outages for homegrown and popular web scraping tools. The best price monitoring API for e-commerce must include advanced technology to handle frequent data updates, maintain accuracy, and avoid detection. 

Why Your Business Needs a Pricing API

A pricing API improves reliability and reduces downtime, ensuring uninterrupted access to real-time pricing data. Unlike traditional scraping methods, it’s faster, more efficient, and requires minimal maintenance.

A robust price monitoring API includes:

  • Built-in proxy management and anti-scraping defenses to bypass bot detection.
  • Automated updates that adapt to website changes without breaking.
  • Faster insights than manual scraping, keeping you ahead of competitors.

Use Cases for a Pricing Monitoring API

  • Competitive Pricing Analysis – Compare competitor pricing and adjust your strategy accordingly.
  • Identify Market Trends – Understand shifts in consumer demand and pricing fluctuations.
  • Price Matching Made Easy – Match or beat competitor prices to attract more customers.
  • Optimized Promotions – Plan strategic discounts using real-time pricing data.
  • Validate Supplier & Distributor Contracts – Ensure pricing agreements are being upheld across all sales channels.

Introducing Traject Data’s New Pricing Solution

At Traject Data, we know how important real-time pricing data is to your strategy. That’s why we’re excited to introduce our latest feature:

🚀 Amazon List Price Data 🚀

This powerful tool is designed to supercharge your pricing strategy by providing seamless access to real-time list prices.

Key Benefits of Traject Data’s APIs

  • Wide Coverage –Monitor pricing from Amazon, Walmart, Google, Target, Home Depot and Ebay.
  • Reliable Infrastructure – Get real-time data with minimal latency and downtime.
  • Seamless Integrations – Schedule automated data pushes to your preferred destination.
  • Scalability – Handle tens of millions of requests daily as your business grows.
  • Comprehensive Documentation & Support – Get expert guidance and fast issue resolution.
  • Flexible Pricing – Scale costs based on your needs with a free trial before committing.
  • Clean, Structured Data – We handle data parsing, so you get accurate results without extra processing.

Ready to Optimize Your Pricing Strategy?

The best way to automate price monitoring with an API is to leverage a trusted pricing intelligence solution like Traject Data. Contact us today to learn how our pricing monitoring APIs can help you gain a competitive edge!

Ready to See What Traject Data Can Help You Do?

We’re your premier partner in web scraping for SERP data. Get started with one of our APIs for free and see the data possibilities that you can start to collect.

View All Serp APIs

Top 5 Amazon Scraper APIs

Amazon dominates the online retail space, holding 37.6% of the U.S. e-commerce market as of 2025—far surpassing competitors like Walmart. With over 310 million users worldwide and 353 million products available, its reach is unmatched. A staggering 89% of consumers prefer Amazon over other online retailers, and beyond e-commerce, Amazon commands 10.4% of the overall U.S. retail market, solidifying its influence across the industry. For businesses looking to stay competitive, an Amazon scraper API is an essential tool for gathering real-time product data, monitoring pricing, and analyzing market trends. In this article, we’ll explore the best Amazon scraper APIs to help you make data-driven decisions.

Benefits of Using Amazon Scraper APIs

Amazon’s pricing strategies and vast data repository profoundly shape the retail market, influencing consumer expectations and pushing competitors to adapt—a phenomenon often referred to as the “Amazon Effect.” This dominance makes publicly available data from Amazon’s site incredibly valuable for businesses seeking to optimize their strategies. However, writing and maintaining your own scraping scripts to collect this data is a labor-intensive task. When scraping data from Amazon, you face a list of challenges:

  • Dynamic page structure: Frequent website updates can break scrapers relying on specific HTML elements. Additionally, Amazon uses A/B testing to evaluate layouts and features.
  • CAPTCHA and anti-scraping mechanisms: Automated scraping attempts are often blocked by CAPTCHAs or other anti-bot techniques.
  • Rate limiting: Amazon may throttle requests, slowing down data extraction if not managed properly.
  • Legal considerations: While scraping public product data is generally allowed, understanding Amazon’s terms of service is essential to avoid compliance issues.
  • Data cleaning and validation: Scraped data may require extensive processing to remove irrelevant information and ensure accuracy.
  • Scalability issues: Extracting large data volumes can become computationally expensive without efficient techniques or cloud-based solutions.
  • And the list is constantly evolving as Amazon develops new ways to combat scraping scripts.

Using a web scraping API tailored for Amazon’s complex structure simplifies these challenges, offering cost-effective, scalable solutions.

Key Criteria for Choosing an Amazon Scraper API

Not all scrapers are created equal. When selecting an Amazon data provider, consider these factors:

  • Reliability: Ensure the API delivers real-time data with minimal latency and downtime.
  • Integrations: Look for seamless compatibility with existing tools or analytics platforms, including batch automation and delivery options.
  • Documentation and Support: Comprehensive documentation reduces the learning curve, while responsive customer support ensures prompt issue resolution.
  • Scalability and Speed: Choose a provider capable of handling large data requests without performance drops.
  • Compliance: Partner with vendors who adhere to Amazon’s terms of service. 
  • Pricing. Flexible, scalable pricing is also key, allowing you to adjust costs based on your current needs as your business grows. Before committing to a contract, leverage a free trial to explore its capabilities and assess whether it’s suitable for your needs.
  • Data cleaning and parsing. Some APIs return data in raw, unstructured formats that require additional parsing to remove extraneous information, which can slow down analysis. Advanced APIs streamline this by automating the parsing process, providing ready-to-analyze data from the start.

Top 5 Amazon Scraper APIs for 2025

1. Traject Data Rainforest API

  • Key Features: Pre-configured for e-commerce, real-time data retrieval.
  • Best For: Retailers needing actionable, real-time e-commerce data. Seamlessly integrates with analytics and reporting tools.
  • Trial Availability: Free trial with a detailed demo available.

2. Oxylabs 

  • Key Features: High-performance data extraction, structured JSON output, geo-targeting.
  • Best For: Proxy management.
  • Trial Availability: 7-day free trial with 5,000 requests.

3. Bright Data 

  • Key Features: Rapid extraction of product details, prices, reviews, and seller information.
  • Best For: Fast, large-scale data retrieval.
  • Trial Availability: No free trial.

4. ScraperAPI

  • Key Features: Scalable, anti-bot measures, proxy management.
  • Best For: Market research, trend monitoring, and competitor analysis.
  • Trial Availability: Limited free plan available.

5. DataForSEO

  • Key Features: Reliable e-commerce data retrieval, customizable API options.
  • Best For: Businesses seeking SEO insights alongside Amazon data.
  • Trial Availability: Free trial available with limited requests.

Amazon Data Collection APIs Compared

Traject Data Rainforest API Oxylabs Bright Data ScraperAPI DataForSEO
Key Features Real-time, pre-configured for e-commerce High-performance, geo-targeting Rapid extraction, structured output Scalable, anti-bot measures Reliable, customizable e-commerce data retrieval
Supported Locations Global Over 200 195 Global Global
Output Formats JSON, CSV JSON JSON, CSV, Excel JSON JSON, CSV, Excel
Free Trial Free trial available 7-day free trial No free trial Limited free plan available Free trial available
Best For Retailers needing real-time, actionable data Proxy Management Market research Trend monitoring SEO insights and Amazon data
Ease of Use User-friendly, Easy to integrate Requires technical expertise Requires technical expertise User-friendly User-friendly
Integrations Seamless with analytics tools Compatible with Python, Java Wide language support RESTful API support SEO and e-commerce platforms
Documentation & Support Detailed docs, dedicated support Comprehensive, 24/7 support Detailed guides, live support Well-documented, chat support Well-documented, dedicated support
Data Parsing Fully structured, real-time updates Structured JSON output Extracts structured data Parses raw HTML/JSON data Structured output with SEO insights

Get Real-Time Amazon Data with Traject Data

Modern Amazon Data Collection APIs eliminate the complexities of manual scraping, offering streamlined, organized data collection tailored to your business needs. Among them, Traject Data’s Rainforest API stands out with its pre-configured e-commerce focus, real-time updates, and ease of integration, making it a top choice for retailers and analysts alike. Click here to get started.

Ready to See What Traject Data Can Help You Do?

We’re your premier partner in web scraping for SERP data. Get started with one of our APIs for free and see the data possibilities that you can start to collect.

View All Serp APIs

How to Scrape Walmart.com

Walmart is the second-largest online retailer in the U.S., after Amazon. By 2025, Walmart’s online sales are projected to hit $3.4 billion. Together, Walmart and Amazon dominate the market so significantly that they effectively set the pricing trends for entire industries.

Walmart’s pricing strategies often send ripple effects across the retail landscape. Other retailers are frequently forced to match Walmart’s prices—often at the expense of their profit margins—or find creative ways to stand out. For anyone looking to stay ahead in the e-commerce game, keeping an eye on Walmart.com is essential.

Why Scrape Walmart? 

Walmart lists over 43 million products online, and this number is increasing each year. This publicly available data is a goldmine for businesses looking to refine their e-commerce strategies. Some of the top use cases for scraping Walmart include:

  • Competitive Pricing Analysis: By extracting pricing information, companies can compare their prices with Walmart’s, helping them stay competitive in the market.
  • Market Research: Scraping product trends, customer reviews, and sales data provides valuable insights into market demand and consumer preferences.
  • Inventory Management: Tracking stock levels and product availability allows businesses to optimize their inventory and reduce stockouts or overstocking.
  • Discount and Promotion Tracking: Automated scraping of coupon data and promotional offers help you stay on top of the latest deals. 
  • SEO and Content Creation: Analyzing Walmart’s product descriptions and keywords can inform SEO strategies and content creation for other e-commerce sites.

Why You Need an API to Scrape Walmart 

To effectively track products, pricing, and reviews at scale, you need an automated solution like a Scraper API. While some developers attempt to build and maintain their own scraping tools, this requires ongoing maintenance and monitoring. Affordable solutions like Traject Data offer a cost-effective and hassle-free alternative. With Traject Data, you’ll get scalability, reliability, reduced maintenance, legal compliance, structured data, and support.

Getting Started with Traject Data’s Walmart Scraper API

Traject Data’s BlueCart API is an API to retrieve public-domain data from Walmart in real-time. You can use BlueCart API to retrieve products, reviews, search results, autocomplete results and category listings from Walmart.

BlueCart API returns clean, structured JSON or CSV results. You can achieve fine-grained control over your request using the request parameters.

Retrieving Search Results for Products on Walmart

Getting search result Walmart data with BlueCart API is as simple as making an HTTP GET request to the request endpoint. The only required parameters are api_key (sign up for free to get an API key) and type (which defines the type of Walmart data you’d like to retrieve). For example, to retrieve search results ( type=search ) for the search term highlighter pens , ordered by best selling products ( sort_by=best_seller ) the BlueCart API request would be:

https://api.bluecartapi.com/request?api_key=demo&type=search&search_term=highlighter+pens&sort_by=best_seller

The search results are shown within the search_results array. For full documentation on the search results response see the Search Results docs.

Getting Data for an Individual Product

Lets say we want to change our query to request a different type of data – information on a specific product, in this case the product with Item ID 27672251 on walmart.com . Here’s the BlueCart API request to achieve that:

https://api.bluecartapi.com/request?api_key=demo&type=product&item_id=27672251

Localizing Results to a Zipcode or Postal Code BlueCart API allows you to retrieve results as they would be seen by a user in a given zipcode or postal code by specifying the zipcode or postal code in the customer_zipcode request parameter.

For example, to request results as they would be seen by a user in US zipcode 77001 you should append the customer_zipcode=77001 request parameter.

For more documentation Traject Data’s Bluecart API visit our Help Center.

Explore Traject Data’s solutions today and see how they can help your business thrive in the digital age.

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Data-Driven Brand Protection: Strategies to Safeguard Your Business

81% of consumers need to trust a brand to consider buying from it, but brand protection is becoming increasingly difficult in the digital age. A single negative article found online can cause a business to lose up to 22% of its customers. Approximately $2 trillion worth of counterfeit products are sold to consumers annually. With the massive size of the internet, brand protection and monitoring isn’t something that can be done manually. Businesses that want to protect their brand image online need data and tools. The most common tool is a brand monitoring scraper API, also known as a brand monitoring data collection API.

What is Brand Monitoring?

Brand monitoring is all about keeping your business’s reputation and identity safe from harm. It means stopping things like counterfeit products, fake websites, and misuse of your logos or trademarks. It’s also about protecting your customers from scams or misinformation that could damage their trust in your brand. In today’s fast-paced digital world, threats can pop up anywhere—on social media, review sites, or forums—so staying on top of them is key. By actively monitoring and addressing these risks, you can make sure your brand stays strong and customers know they can rely on you.

The Role of Scraper APIs in Brand Monitoring

Brand Monitoring Data Collection APIs, or web scraping APIs, are like your brand’s eyes and ears on the internet. They help you keep track of what’s being said about your business by gathering data from customer reviews, social media, pricing information, and search engine results pages (SERPs).

  • Keeping Tabs on Customer Sentiment. APIs can pull reviews from platforms like Amazon, Google, Bing, and Walmart, making it easier to spot trends in customer satisfaction and pinpoint areas where improvements are needed.
  • Spotting Counterfeits. They’re also great at scanning e-commerce sites for unauthorized sellers or counterfeit versions of your products, so you can tackle intellectual property violations head-on.
  • Tracking Brand Mentions. By monitoring mentions of your brand across websites, forums, and social media, these APIs let you stay on top of conversations. This way, you can address misinformation or negative press before it spirals out of control.
  • Catching Fraudulent Activities. Whether it’s fake reviews or bot-generated comments, Data Collection APIs help you detect and deal with anything that might harm your brand’s reputation. They ensure your interactions with customers stay authentic and trustworthy.
  • Omni-channel Consistency. Customers expect a seamless experience across all platforms—whether they’re shopping on Amazon, Walmart, browsing your website, or checking prices in-store. Without consistency in pricing, product descriptions, and availability, your brand can lose credibility.

In short, these APIs are a powerful tool for protecting your brand in today’s digital landscape.

Benefits of Using Scraper APIs for Brand Monitoring and Protection

Manually keeping track of brand mentions is nearly impossible, and creating your own scripts can be expensive and time-consuming to maintain. Thankfully, cost-effective solutions are available that automate brand monitoring for you. Here are some benefits of using a third-party data collection API:

  • Real-time insights for quick decision-making. With data flowing in continuously, you can respond to challenges or opportunities as they arise.
  • Scalability to monitor multiple platforms simultaneously. Whether you’re tracking hundreds of e-commerce listings or monitoring global social media trends, these APIs can handle it.
  • Cost-effectiveness compared to manual monitoring or traditional research. Automation significantly reduces overhead and saves time.
  • Improved accuracy through automation and data analysis. Eliminate human error and ensure precise, actionable insights.

Best Practices for Using Brand Monitoring Data Collection APIs

To get the most out of a Brand Monitoring API, follow these best practices:

  • Adhere to ethical web scraping guidelines. Always respect a site’s terms of service and avoid disruptive practices.
  • Ensure compliance with data privacy laws. Regulations like GDPR and CCPA require careful handling of personal data.
  • Partner with reliable scraper API providers. Working with a trusted provider like Traject Data ensures you’re getting accurate and secure data. 

Traject Data’s Brand Monitoring API Solution

Traject Data’s SerpWOW API is designed to help businesses safeguard their reputation and protect their market share. Its features include:

  • Seamless integration with your existing systems.
  • Scalability to handle large-scale monitoring across multiple channels.
  • Robust support to ensure you’re maximizing the value of your data collection efforts.

In today’s digital-first world, brand protection is more critical than ever. Tools like data collection APIs make it possible to monitor and respond to threats in real-time, ensuring your business stays ahead of the competition and earns the trust of your customers. Ready to protect your brand? Explore Traject Data’s solutions today and see how they can help your business thrive in the digital age.

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Navigating the AI Search Engine Wars: How SERP APIs Keep You Ahead of the Curve

This article explores the current state of the AI search engine wars, the major players involved, and how SERP APIs like Traject Data’s SERPWow can help you stay on top of the game.

The AI Search Engine Wars: What’s Happening?

The “AI search engine wars” refer to the growing competition among tech giants like Google, Microsoft, and Meta—alongside AI pioneers like OpenAI—to develop the most advanced AI-powered search engines. When ChatGPT was released in 2022, many began questioning whether AI could eventually replace traditional search engines. Google’s quick restructuring and aggressive development of AI initiatives show it’s not taking ChatGPT lightly. Other players, both old and new, are also entering the fray, aiming to redefine the search landscape.

 A Timeline of the AI Search Engine Wars

The AI search engine landscape has rapidly evolved, with major tech companies introducing AI-driven features to enhance user experience. Here’s a timeline:

  • November 2022: OpenAI releases ChatGPT, a conversational AI model that brings generative AI to the mainstream. Within five days, it had more than a million users. Users begin turning to ChatGPT for information previously found on Google search. 
  • January 2023: Microsoft invested another $10 billion in OpenAI, bringing its total investment to $13 billion, laying the groundwork for future AI integrations.
  • February 2023: Microsoft integrates OpenAI’s GPT-4 model into Bing, enhancing search functionalities with AI capabilities.
  • March 2023: Google unveiled Bard, its AI chatbot, an open-access tool to rival OpenAI’s ChatGPT, later rebranding the technology as Gemini.
  • December 2023: Google releases Gemini, its latest AI model, claiming to surpass previous state-of-the-art models on most benchmarks.
  • May 2024: Google introduced its Search Generative Experience (SGE) now referred to as AI Overviews at the top of search results, aiming to provide AI-generated summaries to user queries.
  • July 2024: OpenAI launched SearchGPT in phases, starting with a limited release to 10,000 test users on July 25, 2024.
  • October 2024: Meta is pursuing its own AI search engine to put inside its Meta AI tool to replace operations inside Meta that are currently using Google search or Bing.
  • December 2024: OpenAI announces that ChatGPT’s AI search engine is rolling out to all users, both free and paid, expanding access to AI-driven search capabilities.

How AI is Changing Search Engine Optimization (SEO)

These developments underscore the rapid advancements in AI integration within search engines, as companies strive to enhance user experience and redefine search paradigms.

AI is not just changing how search engines function—it’s rewriting the rules of SEO. If AI-powered overviews and chat-style results feel ubiquitous, that’s because they’re reshaping user behavior and, by extension, SEO strategies. AI is transforming search by prioritizing intent and context over traditional keyword-based indexing. Features like conversational queries, personalized results, and AI-generated summaries are becoming the new standard.

Key trends in AI-driven SEO include:

  • Shift to Context and Intent: AI-powered search engines prioritize the user’s intent and context, moving away from a purely keyword-centric approach.
  • Importance of Structured Data: Schema markup and structured data have become essential to helping AI systems understand and surface content effectively.
  • Frequent Algorithm Updates: With AI driving rapid updates, staying current with algorithm changes has become more challenging than ever.

For marketers, this means adapting strategies to align with the evolving landscape, making tools like SERP APIs indispensable.

The Role of SERP APIs in the AI Search Landscape

A SERP API (Search Engine Results Page API) is a tool that provides programmatic access to real-time search engine data. It’s like having a backstage pass to search engine performance, offering invaluable insights for marketers.

Key Benefits of SERP APIs:

  1. Real-Time Data: Access up-to-the-minute ranking data across multiple search engines, including Google, Bing, and Amazon.
  2. Competitive Analysis: Monitor competitors’ rankings and identify trends.
  3. Dynamic Adjustments: Quickly adapt SEO strategies based on algorithm updates and emerging AI-driven features.
  4. Brand management: Track online mentions of your brand and monitor online reviews.  

By leveraging SERP APIs, marketers can stay proactive, ensuring their strategies align with the latest search engine advancements.

Practical Tips for Leveraging SERP APIs

To get the most out of SERP APIs in the AI search era, consider these actionable tips:

  • Monitor Rankings Regularly: Set up automated monitoring to track ranking changes on both traditional and AI-powered search engines.
  • Analyze AI Features: Pay attention to AI-specific elements like rich snippets and conversational search results to identify optimization opportunities.
  • Optimize for Context: Use insights from SERP APIs to fine-tune your content for both intent-based and traditional ranking factors.

How Traject Data’s SERPWow API Can Help

The AI search engine wars are transforming how we think about search and SEO. Staying agile in this rapidly evolving landscape requires the right tools, and SERP APIs like Traject Data’s SERPWow are essential for maintaining a competitive edge.

Ready to future-proof your SEO strategies? Start leveraging Traject Data’s SERPWow API to stay ahead in the AI search engine wars.

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Bing Search Market Share is Growing: Why It Matters and How to Rank Higher with APIs

You’ve worked hard at your Google SEO, and you finally made it to the top. Mission accomplished. A job well done. But then someone on your team mentions they couldn’t find your company in a search. That can’t be right—you see your company right at the top of the page. Then you think to ask, what search engine are you using? It turns out, they’re using Bing.

This article will cover Bing SEO tips and the SERP APIs you’ll need to capture this lucrative market.

What is Bing and Who Are Its Users?

The Google search engine dominates the market to the point that “I’m going to google that” is synonymous with online search. But it’s not the only search engine on the market. Bing is Microsoft’s search engine and Google’s biggest competitor. For many Microsoft users, they may not even realize they are using Bing because it’s so tightly integrated with other Microsoft products. Bing is the default search engine of the Microsoft Edge browser and is embedded within Microsoft 365 products. If you’re in a Microsoft environment, it’s hard not to use Bing.

Bing’s reach extends beyond Microsoft. Microsoft’s Cortana, Xbox and Amazon’s Alexa leverage Bing’s search engine. Ever asked Alexa a question? Turns out you’re a Bing user.

When comparing Bing users to typical Google search users, Bing users tend to be slightly older (average age 45), better educated, more affluent, and more likely to be married with children at home—making them a highly desirable market.

The current AI Search Wars put additional emphasis on the need to pay attention to Bing. The rise of AI-powered search engines is drastically changing how search engines work. Microsoft has partnered with OpenAI to leverage ChatGPT in its Bing browser, while Google is using a home-grown AI solution. The search engine that wins could be the one with the best AI.

Searching for how to optimize Bing SEO

Why Bing’s Growing Market Share Matters

On average, Bing ads outperform Google in several key metrics: 

  • Bing shopping campaigns have a 45% higher ad click-through rate (CTR) than Google.
  • Bing’s average cost per click (CPC) on shopping ads is 30% lower than Google’s.
  • The average cost to acquire a customer (CPA) is about 40% lower through Bing shopping than on Google shopping.

How Does Bing’s Search Engine Differ from Google?

Like me, maybe you thought ranking high on Google would automatically put you at the top of other search engines, but unfortunately, that’s not the case. In many instances, Bing’s ranking criteria are clearer than Google’s, making it easier to achieve high rankings if you follow their guidelines. Let’s break down the similarities and differences:

SEO ranking criteria shared by both Bing and Google:

  • Publish great content that’s relevant and useful to your audience.
  • Include videos and images—they help keep users engaged.
  • Use schema markup to give search engines more context about your pages.
  • Write compelling meta tags and descriptions
  • Focus on earning high-quality backlinks from reputable sites.

Areas where Bing SEO differs from Google:

  • Domain Age and Authority: Bing gives older domains more credit compared to Google.
  • Desktop vs. Mobile: While Google prioritizes mobile-friendly sites, Bing leans more toward desktop users—but still values mobile-friendly ones.
  • Social Signals: Bing pays attention to social media activity. So, an active social presence can help your ranking.
  • Exact Match Keywords: Bing prefers when your keywords match exactly—so keep it specific.
  • Keyword Stuffing Tolerance: Bing might cut you a little more slack with keyword stuffing, but don’t overdo it. Both search engines frown on this practice.

Tools to Improve Your Bing SEO

To master Bing SEO, you’ll need the right tools. Here are the essentials for your toolkit:

  1. Bing Webmaster Tools: Microsoft’s free platform provides reporting, diagnostics, and notifications to improve your site’s performance in Bing search. It also includes a keyword research tool.
  2. Sitemap Submission Tools: Submitting a sitemap through Bing Webmaster Tools ensures Bing can efficiently crawl and index your website pages.
  3. SERP APIs: Search engine algorithms are constantly changing. A SERP API allows you to monitor your rankings and those of your competitors, giving you the data you need to adapt your strategy.

Leverage Traject Data’s SerpWow to Rank Higher on Bing

SEO for Bing is similar to Google, and both require consistent data and monitoring. To maximize your reach, you need a SERP API that can track and monitor both search engines. Don’t miss out on 16% of the US desktop search market when you can leverage a SERP API to help you climb the ranks on both platforms.

Traject Data’s SerpWow API does just that. It monitors Google, Bing, Yahoo, Baidu, Yandex, Naver, Amazon, and eBay, giving you comprehensive insights to optimize your SEO strategy across multiple search engines.

Start climbing the ranks with Traject Data’s SerpWow today.

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We’re your premier partner in web scraping for SERP data. Get started with one of our APIs for free and see the data possibilities that you can start to collect.

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