This case study highlights how our advanced web scraping solutions empowered a leading FMCG client to identify and respond to Amazon Fresh vs BigBasket price difference across essential grocery categories. The client faced inconsistencies in retail pricing on both platforms, which were affecting their pricing strategy and consumer trust. We deployed targeted data extraction tools to capture SKU-level pricing, availability, and promotions daily. Our system delivered structured reports and dashboards to track fluctuations in price comparison Amazon Fresh data, enabling the client to gain real-time market intelligence. The insights revealed undercutting strategies, promotional gaps, and pricing inconsistencies that were previously unnoticed. This allowed the client to optimize their listing strategies, adjust distributor-level MOPs, and negotiate better retail terms. Our scraping solution not only streamlined decision-making but also supported a more competitive pricing model across digital retail platforms.
A Well-known Market Player in the Online Grocery Business
iWeb Data Scraping Offerings: Utilize our Amazon Fresh Grocery and Supermarket Data Extraction Services to provide grocery price data.
The client, a leading consumer goods brand, faced growing complexity in managing pricing strategies across online grocery platforms. With multiple SKUs listed on both BigBasket and Amazon Fresh, maintaining consistency and competitiveness became increasingly complex. There was no visibility into how their products were being priced, discounted, or promoted by resellers and third-party distributors. They lacked a competitive pricing scraping solution for Big Basket and Amazon to capture real-time fluctuations. Manual tracking methods were time-consuming and prone to error. Moreover, without actionable B2B price intelligence grocery platforms, their marketing and supply chain teams were making blind decisions. The biggest hurdle was understanding the price variance Amazon Fresh and BigBasket dataset analysis, especially during flash sales and promotional cycles. They needed a reliable, automated solution that could track price shifts at the SKU and region levels to maintain profitability and retail alignment.
To address the client's challenge, we deployed our Big Basket Grocery Delivery Data Scraping Services combined with a tailored solution for Amazon Fresh. Our system extracted real-time price data, promotional offers, and stock statuses across both platforms. By using this data, the client could calculate grocery price gap Amazon vs BigBasket scraper data with high accuracy across different regions. We conducted an item-level price disparity grocery apps global study covering daily essentials and FMCG products to reveal margin fluctuations and pricing inconsistencies. Additionally, our Grocery Stores Location data scraping allowed them to correlate price differences based on location, helping to localize pricing strategy and supply chain efficiency. Our solution not only streamlined data collection but also visualized trends over time, empowering the client's analytics team with valuable insights to adjust pricing tactics in sync with the competitive market environment.
The outcome of the project delivered a measurable impact. With our Online Grocery & Supermarket Data Extraction Services , the client was able to access high-quality, structured pricing data across Amazon Fresh and BigBasket in real-time. Our Grocery Pricing Data Intelligence Services empowered their analytics team to identify price gaps, monitor competitor strategy, and make dynamic pricing adjustments across regions. The use of Grocery and Supermarket Store Datasets allowed them to visualize product-level disparities and location-specific patterns, improving decision-making. Ultimately, the project enabled the client to enhance competitiveness and drive better margins in the online grocery space.
"Their expertise in grocery data scraping gave us a decisive edge in a highly competitive retail environment. With detailed and structured data from both Amazon Fresh and BigBasket, we could identify pricing gaps and adjust our product listings accordingly. Their team ensured timely delivery, clean datasets, and continuous support throughout the project. The insights helped us uncover regional variations and run dynamic pricing campaigns with measurable results. We now rely on their services as a consistent source of pricing intelligence."
—Director of Product Strategy
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