Introduction: Why Pricing Intelligence Matters in the Tyre Industry

The tyre industry is one of the most competitive segments within the automotive sector. Manufacturers, wholesalers, and distributors handle hundreds of SKUs—across multiple brands, models, and sizes—where pricing shifts weekly based on stock levels, regional demand, and promotional campaigns.

For global tyre brands, visibility into how distributors price products across different regions has become critical. With new entrants offering aggressive discounts online, even a small price deviation can affect dealer loyalty, margins, and market share.

A leading global tyre manufacturer approached Actowiz Solutions to build an AI-powered web-scraping solution capable of collecting and analyzing competitor pricing data from multiple distributor websites across the United States and Europe. The goal was to automate price benchmarking, track stock fluctuations, and deliver actionable insights for pricing strategy and sales planning.

Client Overview

The client is a global player in tyre design, manufacturing, and distribution for passenger and commercial vehicles. Their sales network spans the US, EU, and Asia, supported by a wide network of distributors and retail partners.

While the company had strong in-house analytics capabilities, the team lacked access to real-time competitor pricing data. Distributor websites often update prices daily, making manual monitoring impossible. The company wanted a solution that could:

• Collect competitor product prices automatically from four major distributor sites

• Detect price differences between regions and brands

• Identify promotional events, discounts, and stockouts

• Deliver clean, structured datasets for internal analytics tools

The Business Challenge

Data Fragmentation Across Distributors

Each distributor website had a unique design, search structure, and product taxonomy. While some offered clear SKU-level details, others displayed unstructured data such as “Best Seller” or “Limited Offer” without standardized tags. The client’s team needed to scrape and normalize this data for a consistent pricing benchmark.

Dynamic Content and Anti-Bot Systems

Distributor websites used modern JavaScript frameworks with dynamic content loading. Many pages required client-side rendering or AJAX calls. Additionally, anti-bot firewalls (like Akamai and Cloudflare) made standard scraping tools ineffective.

Regional Price Variation

Prices for the same tyre model varied significantly between the US and EU due to logistics, import duties, and market positioning. Manual monitoring could not track these changes in real time.

Need for Automated Benchmarking

The brand needed not only raw data but also actionable intelligence—for example:

• Which distributors offered consistent price undercuts

• Which SKUs had the highest margin erosion

• Which models frequently went out of stock

The solution had to extract, process, and visualize these trends efficiently.

The Actowiz Solutions Approach

Actowiz Solutions designed a multi-layered, AI-driven scraping framework customized for automotive and tyre data collection.

Discovery and Scoping

Our data engineering team conducted a discovery audit of the four distributor websites. Each was mapped for:

• Page structures and HTML layouts

• Product listing patterns

• Dynamic rendering methods (React, Vue, or server-side)

• Pricing and promotion fields

• Stock and availability markers

This phase allowed us to design site-specific crawlers to capture every relevant data point.

AI-Driven Crawlers and Scheduling

We deployed AI-assisted crawlers capable of handling:

• JavaScript rendering through headless browsers

• Intelligent throttling to mimic human browsing

• Adaptive scheduling based on traffic intensity and update frequency

Crawlers ran at specific time intervals (daily or twice per week, depending on region) to capture price changes in near real time.

Data Fields Extracted

Each data record captured included:

• Brand: Tyre manufacturer name

• Model Name: Product line (e.g., SportDrive, EcoGrip)

• Size: Tyre dimensions (e.g., 225/45 R17)

• Price (Local Currency): Current listed price

• Discount (%): Applicable promotional discount

• Availability: Product status – In stock, Limited stock, or Out of stock

• Distributor Name: Source or retailer site name

• Region: Market region such as US or EU

• Timestamp: Date and time when data was extracted

Sample Data Extract (Illustrative)

Bridgestone – Turanza T005

• Size: 225/45 R17

• Price: $138.90

• Discount: 10%

• Availability: In Stock

• Distributor: TireRack

• Region: USA
  
  

Michelin – Pilot Sport 4

• Size: 225/45 R17

• Price: €142.00

• Discount: 5%

• Availability: In Stock

• Distributor: Oponeo

• Region: EU
  
  

Continental – EcoContact 6

• Size: 205/55 R16

• Price: $125.50

• Discount: 0%

• Availability: Low Stock

• Distributor: Discount Tire

• Region: USA
  
  

Pirelli – Cinturato P7

• Size: 225/50 R18

• Price: €161.30

• Discount: 8%

• Availability: In Stock

• Distributor: MyTyres

• Region: EU

From these records, Actowiz generated cross-region comparison dashboards, allowing analysts to visualize price differences at brand and SKU levels.

Data Cleaning and Normalization

Data normalization was crucial to ensure consistent analysis. Actowiz’s AI pipelines automatically handled:

• Currency Conversion: All EU prices converted to USD using daily exchange rates.

• Unit Standardization: Metric and imperial measurements aligned for uniform comparison.

• Duplicate Detection: Removal of similar SKUs listed across multiple distributors.

• Error Correction: Automated tagging of anomalies such as missing values or outdated listings.

This produced a clean, analytics-ready dataset delivered in CSV, Excel, or via API integration.

Analytics and Visualization

To make insights actionable, the final step involved creating a Tyre Pricing Benchmark Dashboard using Power BI and Tableau integration.

Key Metrics Displayed:

• Average Price per Brand & Size Segment: Helps identify market positioning and premium vs. budget gaps.

• Price Difference (US vs EU): Highlights regional variations for each model.

• Discount Frequency Tracker: Shows which distributors offer regular promotions.

• Stock Availability Heatmap: Displays supply bottlenecks or overstock risks.

• Historical Price Trends: Weekly changes for top 20 SKUs, allowing forecasting of promotional cycles.

These insights helped marketing and sales teams identify pricing inefficiencies, hidden opportunities, and competitive risks before they affected profitability.

Technology Stack

• Scraping Framework: Custom Python scrapers using Requests and Playwright

• AI Components: NLP-based field extraction and anomaly detection

• Storage Layer: AWS S3 and PostgreSQL for scalable data storage

• Data Cleaning: Performed using Pandas and NumPy

• Analytics & Visualization: Insights visualized through Power BI and Tableau

• Automation: Managed via Apache Airflow scheduler and AWS Lambda

• Delivery: Data shared through REST API and a secure client dashboard

Actowiz’s modular design allowed the system to scale up to more distributors or new regions without rewriting core logic.

Overcoming Technical Challenges

Handling Anti-Bot Mechanisms

Distributor websites often employed rate-limiting and CAPTCHA checks. Actowiz’s crawlers used:

• Dynamic user-agent rotation

• Proxy IP pools by region

• Request-interval randomization

• AI-based human behavior simulation

This ensured uninterrupted data flow while remaining fully compliant with website policies.

JavaScript-Heavy Pages

By integrating Playwright headless browsers, our system accurately rendered dynamic product pages and extracted data from client-side scripts.

Pricing Format Variations

Different sites displayed prices in formats like “$138.90”, “138.9 USD”, or “EUR 142,0”. Our AI parser recognized and standardized these across locales automatically.

Continuous Monitoring

Schedulers ensured crawlers ran consistently, while system alerts notified the team of any structural website changes, ensuring 99.6% uptime for data collection.

Results and Impact

The AI-based tyre data scraping solution delivered measurable results within the first month.

Manual effort for price tracking

• Before: 18 hours/week

• After Actowiz: 1 hour/week
  
  

Data freshness

• Before: 7–10 days old

• After Actowiz: <24 hours
  
  

Price accuracy

• Before: ~70%

• After Actowiz: 98.5% verified
  
  

Competitive response time

• Before: 3–5 days delay

• After Actowiz: Same-day reaction
  
  

Market visibility

• Before: Limited (2 sites)

• After Actowiz: Full (4 distributors, 2 regions)

Key Outcomes:

• 25% faster pricing decisions: Teams adjusted prices proactively based on competitor data.

• 15% reduction in distributor disputes: Transparent price parity data built stronger dealer trust.

• Improved margin forecasting: Accurate visibility into market averages helped prevent underpricing.

• Automated dashboards: Eliminated manual report preparation.

Strategic Insights Derived

Beyond automation, the data provided strategic intelligence that changed the client’s market approach.

• Regional Price Gaps: US distributors offered an average 8–10% lower retail price than EU counterparts, influencing the global pricing roadmap.

• Promotion Timing: The data revealed a consistent pattern—EU distributors launched sales mid-month, while US distributors ran weekend flash discounts.

• Stock Shortage Alerts: Low stock signals on high-demand SKUs allowed the procurement team to pre-allocate production accordingly.

• Emerging Competitors: Crawlers identified new distributor sites listing budget tyre brands at aggressive pricing—an early competitive threat flag.

Broader Business Value

The initiative extended beyond just pricing comparison. It laid the groundwork for a long-term data-driven strategy:

• Demand Forecasting: Analyzing search volume and stock status trends allowed better production planning.

• Dynamic Pricing Engine: The scraped data fed into predictive algorithms, allowing future price automation.

• Cross-Team Collaboration: Marketing, sales, and operations teams now used unified data sources.

• Scalability: The same framework was later expanded to cover aftermarket parts and accessories.

Compliance and Ethical Scraping Practices

Actowiz Solutions adheres strictly to ethical data collection standards.

• Only publicly available data was scraped.

• Robots.txt and rate-limit policies were respected.

• Data was processed securely and shared only for authorized internal analytics.

This ensured full compliance with both US and EU data privacy norms (GDPR and CCPA).

Future Expansion

After the success of this deployment, the tyre manufacturer planned additional phases:

• Adding 10+ distributor websites from Asia and the Middle East

• Integrating social listening data (user reviews, ratings, and feedback)

• Incorporating AI models to predict optimal discount rates by region

• API-based data feeds for real-time integration with ERP systems

This ongoing collaboration aims to turn pricing intelligence into a competitive differentiator.

Why Actowiz Solutions

Actowiz Solutions has become a preferred partner for the automotive and tyre industry due to its ability to combine scalable crawling, AI-based cleaning, and actionable insights.

Key differentiators include:

• Proven track record across 30+ automotive and manufacturing clients

• Dedicated regional data servers ensuring faster access and compliance

• Pre-built dashboards for competitive analysis

• End-to-end customization for API, Excel, or visualization-based delivery

Our tyre pricing intelligence projects have shown that data accuracy, frequency, and visualization are the three pillars of success for any competitive pricing program.

Transform your pricing strategy with real-time tyre market data.

Actowiz Solutions helps global automotive brands capture, clean, and analyze pricing and availability data from any website or region.

Conclusion

The tyre industry is undergoing rapid transformation as B2B and B2C channels overlap. Competitive pricing intelligence has become the foundation for staying profitable and agile.

Through this project, Actowiz Solutions demonstrated how AI-driven web scraping can deliver immediate and strategic benefits:

• Real-time visibility into distributor pricing

• Accurate benchmarking across regions

• Actionable insights for sales and production planning

For any automotive or tyre company seeking to understand their competitive landscape, such intelligence is no longer optional—it’s a necessity.

Learn More >> https://www.actowizsolutions.com/ai-powered-web-scraping-tyre-market-intelligence.php 

Originally published at https://www.actowizsolutions.com