Product Price Comparison Integrations

@crtvecode

To achieve robust price-comparison coverage for the Product Master platform, I understand you need to integrate live data from major online stores like Amazon, Flipkart, and others while ensuring that SKU recognition is seamless despite differing naming conventions. This is crucial for delivering a comprehensive view to your users. I will implement source integrations for each retailer, ensuring automatic retry and rate-limit handling to maintain data flow. The matching algorithm will intelligently group identical products and flag discrepancies for review, while the REST or GraphQL API will be optimized to return consolidated price snapshots in under 500 ms. Additionally, I will create setup scripts or Docker files for easy deployment, along with minimal monitoring hooks to catch any failures early. I’m ready to get started on this right away and can provide a proof-of-concept pull from two stores as the initial milestone. My experience with e-commerce integrations and data normalization will ensure a smooth and efficient process. Rajavel Node.js Developer | TypeScript | E-commerce Integrations

@rizwange4

Hi, I can build the **Product Master price-comparison backend** in Node.js + TypeScript, integrating your available affiliate APIs/feeds and normalizing price, MRP, discounts, stock, currency, units, and product attributes. I’ll start with the requested **2-store proof of concept**, then expand to Amazon, Flipkart, Croma, Reliance Digital, Myntra, Meesho and other authorized sources. I’ll also implement smart SKU/product matching, mismatch flagging, retries, rate-limit handling, caching, and documented REST/GraphQL APIs targeting sub-500ms common queries. Docker/setup scripts, health checks, logging, optimization, and complete API documentation will be included. **Availability:** Full-time over the next month **Timeline:** 3–5 weeks **Rate:** Flexible / milestone-based Best regards, **Muhammad Rizwan** **LA**

@onkarkulkarni8

Hello, I checked your "Product Price Comparison Integrations" project description, it looks like the focus is on delivering a clean, responsive website that works well across all devices. I prefer understanding the expected layout and user experience first, then building pages that closely match the design while keeping the code organized and easy to maintain. Feel free to share the design or current website, and I'll suggest the best implementation along with a realistic timeline. Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@shayankhan333

Matching the same SKU across Amazon and Flipkart is the hard part here, titles diverge and only a fuzzy match on brand plus model plus pack size holds up. I'll wire the affiliate feeds and gap-fill scrapers behind a Node/TypeScript gateway, add the matcher with a review queue for low-confidence pairs, and expose REST with Redis-cached snapshots. Meesho has no clean affiliate API, worth flagging. Past scraping and affiliate work sits here: https://www.freelancer.com/u/shayankhan333 1) Which retailers already have partner feeds versus needing scraping? 2) REST or GraphQL for the first milestone? Cheers Shayan

@tyronet2

Product Master needs more than seven retailer connectors—the difficult part is normalising inconsistent catalogues and reliably recognising the same product across stores without slowing price queries. At Poundit I worked on Node.js e-commerce systems with product data, API integrations and transactional workflows, which maps closely to this aggregation layer. I’d build the service in Node.js/TypeScript with isolated retailer adapters, retries, rate-limit handling and a common normalized product schema. Matching would combine strong identifiers such as GTIN/model/SKU where available with normalized brand, model and specification signals, assigning confidence scores and routing uncertain matches for review. Consolidated snapshots can be cached/indexed to target sub-500 ms reads rather than querying retailers synchronously. Docker, health checks, logging and documented REST/GraphQL contracts would be included. Which two retailers and partner feeds do you want used for the initial proof of concept?

@monicasynthesis

Hello, I’d be happy to build the Product Master price-comparison backend. I have 5+ years of experience in Node.js, TypeScript, APIs, e-commerce integrations, and data normalization. I will provide: • Retailer integrations for Amazon, Flipkart, Croma, Reliance Digital, Myntra, Meesho, and available partner sources • Automatic retries, rate-limit handling, and error monitoring • Smart product matching across different retailer naming conventions • Normalized price, MRP, discount, stock, currency, units, and specifications • Fast REST/GraphQL API targeting <500 ms for common queries • Docker/setup files for local and cloud deployment • Health checks, logging, and clear technical documentation I suggest starting with the two-store proof of concept, validating the matching and data model, then scaling to the remaining sources and optimizing performance. Warm Regards, Monica Bhatia

@rajeshrolen

Hello, I understand the importance of providing users with accurate and real-time product price comparisons across multiple online stores. My expertise lies in developing robust backend solutions for e-commerce platforms, making me the perfect fit for your project. I will utilize Node.js with TypeScript to create clean and well-documented REST/GraphQL endpoints for seamless data retrieval. Implementing a smart matching layer, I will ensure consistent SKU recognition across various stores, guaranteeing accurate and normalized data for downstream analytics. Key deliverables will include source integrations for each listed retailer, a reliable matching algorithm, and a speedy API response time of under 500 ms. Additionally, I will provide setup scripts for easy deployment and minimal monitoring hooks for early issue detection. You can view my past e-commerce and affiliate projects on my portfolio at https://www.freelancer.com/u/rajeshrolen I am available to dedicate my full attention to this project over the next month and am eager to discuss further details in a chat. Looking forward to the opportunity to collaborate on this exciting project. Sincerely, Rajesh Rolen

@novatech2210

⚠️ IF YOU'RE NOT HAPPY YOU DON'T PAY ⚠️ I think we're a strong fit for your project. I specialize in JavaScript, Node.js, RESTful API, Data Integration. For this brief (The Product Master platform needs robust price-comparison coverage across India’s major online store) I would isolate the bottleneck, confirm acceptance criteria, and ship a clean, measurable fix you can verify in staging before it hits production. I'd keep the architecture simple, secure, responsive, and easy for you to manage after handover. Multiple 4.0-rated reviews on Freelancer (16 total), payment verified. I can start against a 7-day delivery window. I'd love to chat about your project! The worst that can happen is you walk away with a free consultation. Regards, N0VATECH

@Cruz1217

When retailer feeds use different SKU formats, matching the same product becomes fragile. I’ll build a normalization layer that strips brand prefixes, normalizes units, and hashes key attributes before feeding a fuzzy matcher. The API will expose the merged view via a TypeScript Node.js service that can answer price queries in under 500 ms. A common mistake is to rely on a single exact string match, which leaves out many cross-store listings. You’ll get a clean REST or GraphQL endpoint that returns consistent price snapshots and flags mismatches for review.

@Anika1802

Hi, I carefully studied the description of your project and can confirm that I understand your needs and am interested in your project. I have the necessary experience and expertise to start as soon as possible. I have strong experience in Node.js, TypeScript, REST/GraphQL APIs, e-commerce integrations, affiliate feeds, data normalization, product matching, rate-limit handling, retries, Docker, and monitoring. I can build the retailer integrations, normalize price/stock/product data, and develop a smart matching layer to identify the same products across different sources. I can follow your milestone approach, starting with a proof of concept for two stores and then expanding to the remaining sources, optimization, and documentation. Please contact me via Freelancer Chat to discuss the existing affiliate feeds, API access, matching requirements, and next steps in detail. Best Regards, Vandini

@maheshverma6831

Hello! I can build the Node.js/TypeScript price aggregation layer with retailer integrations, rate-limit handling, product matching, normalized data and fast REST/GraphQL APIs. Let’s discuss milestones here.

@thinkbotictech

Hi I can build the Node.js/TypeScript price-comparison backend with retailer integrations, rate-limit/retry handling, product matching, normalized data, and fast REST/GraphQL APIs. I’ll start with the two-store POC, then scale to the full retailer set with Docker setup, monitoring, optimization, and documentation. 1. Do your existing affiliate feeds/API credentials cover Amazon, Flipkart, Croma, Reliance Digital, Myntra, and Meesho? 2. Do you already have a preferred product-matching key such as SKU/GTIN/ASIN, or should I design the matching algorithm? if looking for expert then lets connect (expereince 7 yrs in development) lets chat I will complete this task soon

@CliveMSoftware

I've built several multi-retailer data pipelines and affiliate feed integrations for comparison platforms. I'll start with Amazon and Flipkart as your proof-of-concept, handling auth, rate limiting, retry logic, and normalizing their feeds into a unified schema. The matching algorithm will use product name similarity (fuzzy matching), category alignment, and SKU cross-referencing to group identical items across stores, with a flagging system for manual review on edge cases. I'll expose both REST and GraphQL endpoints returning normalized price snapshots, stock status, and core attributes in under 500ms using Redis caching where needed. Full setup includes Docker, health checks, structured logging, and comprehensive API docs. I'm available full-time for the next month and can work in milestones: POC (₹3500), full retailer expansion (₹6000), optimization and monitoring (₹2500). Portfolio available on request with references from similar projects.

@infovergetech

I can build the product price-comparison integration layer with reliable multi-store APIs, normalized product data, and scalable price aggregation. * Integrate partner APIs to fetch and normalize product details, prices, availability, offers, shipping, and affiliate links, with a clean API layer for your frontend. * Implement caching, rate-limit handling, retries, duplicate/SKU matching, schema validation, monitoring, and fallback handling so one failing retailer never breaks the comparison engine. I’ll prioritize official APIs wherever available and keep each retailer integration modular for easy future expansion. Which stores/APIs are confirmed for the initial integration?

@designerbros

I'm Boobesh Kumar, co-founder of Designer Bros. We build high-throughput scraping pipelines, real-time e-commerce aggregators, and low-latency Node.js/TypeScript APIs with resilient rate-limit handling and intelligent fuzzy-matching layers. How We Will Engineer the Product Master Price-Comparison Engine: Resilient Retailer Connectors: Standardizing affiliate feeds and headless scraper pipelines (Puppeteer/Playwright with rotating proxies and exponential backoff) across Amazon, Flipkart, Croma, Reliance Digital, Myntra, and Meesho. Fuzzy SKU Matching Algorithm: Implementing a hybrid matching layer (Levenshtein distance, token-sort ratios, and normalized model numbers/brand names) with Redis caching to consolidate cross-store product listings and flag low-confidence matches. High-Performance API: Exposing clean, normalized TypeScript REST/GraphQL endpoints with Redis caching, delivering multi-store price/stock payloads in <500 ms. Containerization & Observability: Packaging the architecture with Docker, structured logging (Winston/Pino), and /health monitoring hooks for production readiness. Milestone Schedule & Rate: Delivering across your 3 milestones at $25/hr or milestone fixed pricing ($1,200–$1,600 total), available 35+ hours/week immediately.

@Riteshn48

After reviewing your requirements and the Product Master platform, you want a backend service that can collect live price, MRP, discount, stock and product attributes from Amazon, Flipkart, Croma, Reliance Digital, Myntra, Meesho and additional approved sources. I understand that the data from every retailer will have different naming, units, specifications and formats, so it needs to be normalised before being exposed through your API. The matching layer is especially important because the same SKU can appear with different titles, descriptions or attribute formats across stores. I will first create a common product schema, map retailer-specific fields into that structure, then use identifiers, brand/model information, specifications and title similarity to match products. Ambiguous matches will be flagged instead of automatically combining potentially different products. Please open the chat window so that I can share my portfolio and we can proceed further on this project. In addition to your project needs, I'll provide you with clean source code, free bug patches, and maintenance. I am awaiting your positive response. Regards Ritesh N

@rahulsimraiya131

Rahul here, Your biggest challenge is not simply scraping prices it’s reliably matching the same products across multiple Indian retailers and delivering clean, fast comparison data. I can build the integration layer to handle that reliably while keeping the architecture scalable. I've built similar e-commerce data and affiliate integrations using Node.js, TypeScript, REST APIs, product matching, and automated data pipelines. Key deliverables: ◆ Integrate retailer feeds/APIs with retries and rate-limit handling ◆ Smart product matching and mismatch detection across stores ◆ Fast REST/GraphQL API with normalized price and stock data ◆ Docker setup, health checks, logging, and complete documentation One question: Do your existing Amazon/Flipkart partner feeds provide stable product IDs such as ASIN or SKU for matching? I can start immediately and would be happy to discuss the details.

@irhaa63

Hello, I can develop the Product Master price-comparison backend using **Node.js + TypeScript**, with a scalable architecture for retailer integrations, product matching, and fast consolidated queries. I’ll integrate available APIs/affiliate feeds for Amazon, Flipkart, Croma, Reliance Digital, Myntra, Meesho and other approved sources, while respecting their API terms and rate limits. Data will be normalized for price, MRP, discount, stock, currency, units and specifications. I’ll also implement: • Automatic retry, timeout and rate-limit handling • Smart SKU/product matching using identifiers and normalized attributes • Mismatch detection for manual review • REST/GraphQL API with documentation • Caching and indexing targeting <500ms common queries • Docker/setup scripts • Health checks and structured logging **Milestones:** 2-store POC → full integrations → optimization/documentation. Estimated timeline: **1-2 days**, depending on API/feed access. Availability: **Full availability over the next month.** Rate: fixed milestone pricing after reviewing the existing codebase. Best Regards, **Faiza**

@JustinBee85

I recently helped a business achieve a stronger digital presence with a modern, professional application that improved how they managed their operations and connected with their customers. I can help you create a clean, reliable, and user-friendly price comparison integration for Product Master that supports your goals and delivers a seamless experience. I understand the importance of robust integrations and a smart matching layer to ensure data consistency across various retailers. My strong experience in Node.js, TypeScript, and API development, along with my proven track record in e-commerce projects, positions me well for this task. I have successfully completed similar projects, earning 75+ 5-star reviews and ranking in the top 1% among 75 million users. I am ready to bring your idea to life with a polished and reliable solution. I am available to start immediately and can provide a milestone structure that aligns with your review process. Regards, JustinBee85.