E-Commerce Data

Client Background: A mid-market sporting goods retailer headquartered in Chicago, Illinois, with an annual online revenue of $85M and a catalog of 45,000+ active SKUs across categories including fitness equipment, outdoor gear, and athletic apparel.

Challenge: The client’s pricing team was manually benchmarking competitor prices on Amazon and Dick’s Sporting Goods using weekly exports — a process that took 3 full-time analysts and still produced data that was 5–7 days stale by the time it reached the repricing tool. The lag was causing consistent margin erosion: competitors undercut their prices on high-velocity SKUs within hours of catalog updates, and the team had no visibility into promotional bundling strategies.

Solution: Hir Infotech deployed a custom real-time price monitoring pipeline covering 12 competitor domains, including Amazon, Dick’s Sporting Goods, REI, and Walmart US. Our AI-driven scrapers ran hourly sweeps of the client’s priority SKU list (28,000 products), with 15-minute intervals on their top 2,500 revenue-driving items. Data was delivered via structured API directly into their repricing software, normalized against their internal product catalog using UPC matching. A MAP violation alerting module was added to flag any reseller pricing below the client’s MAP thresholds.

Results: Within 90 days of deployment, the client’s price-response time improved by 48%. MAP violation detection eliminated an estimated $340,000 in annual unauthorized discounting. The pricing team was reduced from 3 full-time analysts to 1 part-time oversight role, with the extracted savings reinvested into paid search. Overall online revenue grew 17% in the first two post-deployment quarters, attributed directly to competitive pricing precision.

Client Testimonial: “The difference in our pricing agility is night and day. Hir Infotech’s data feeds are clean, reliable, and genuinely real-time. Our category managers finally feel like they’re ahead of the market instead of chasing it.” — VP of E-Commerce, Sporting Goods Retailer, Chicago, IL

Client Background: A fashion marketplace platform based in Hamburg, Germany, aggregating 800+ independent fashion brands and operating across Germany, Austria, and Switzerland (DACH region). The platform manages 1.2 million active SKUs across womenswear, menswear, and accessories.

Challenge: The client’s merchandising team had no structured view of how competitor platforms (Zalando, About You, ASOS DE) were positioning products, managing seasonal pricing cycles, or structuring their category hierarchies. Without this intelligence, their own category managers were making assortment and pricing decisions based on instinct rather than data. They also needed to ensure all data collection was fully GDPR-compliant, as previous vendor relationships had created legal uncertainty.​

Solution: Hir Infotech designed a GDPR-compliant competitor intelligence program covering three platforms, extracting non-personal product data including SKU-level pricing, category placement, trend tagging, discount depth, and new arrival cadence. A full Legitimate Interest Assessment (LIA) was conducted and documented before any data collection began. Data was delivered weekly in structured CSV and JSON formats, mapped to the client’s internal taxonomy using AI-powered category alignment.​

Results: After six months, the client’s category hit rate on trending products improved by 34%, as their buying team could now identify emerging trend categories on competitor platforms 3–4 weeks earlier than before. Seasonal markdown timing was optimized, reducing end-of-season overstock by 22%. The legal team confirmed zero compliance incidents across the engagement.

Client Testimonial: “We needed a partner who understood both the data challenge and the European regulatory environment. Hir Infotech delivered both — impeccably. The intelligence they provide has become a central input into our quarterly buying strategy.” — Chief Merchandising Officer, Fashion Marketplace, Hamburg, Germany

Client Background: A consumer electronics brand based in London, UK, selling wireless audio products on Amazon UK, Amazon DE, and Amazon FR. Annual Amazon revenue of £28M, with a core product range of 14 SKUs and a challenger position in the premium headphone segment.

Challenge: The brand’s product team was receiving thousands of customer reviews per month across three Amazon marketplaces in three languages. They had no scalable way to systematically analyse review content for product defect signals, feature requests, or competitive sentiment patterns. Critical product improvement insights were buried in spreadsheets, and new product development cycles were based on intuition rather than structured customer voice data.

Solution: Hir Infotech built a multilingual review extraction and NLP-powered sentiment analysis pipeline covering Amazon UK, DE, and FR. We extracted 100% of historical and new reviews across the client’s SKUs and 12 competitor products, classifying content by sentiment polarity, topic category (battery life, sound quality, comfort, connectivity), and market (UK/DE/FR). Insights were delivered monthly via a structured dashboard-ready dataset and quarterly via a human-analysed trend report prepared by our data intelligence team.

Results: The product team identified a recurring Bluetooth latency complaint pattern in DE reviews — an issue invisible in UK data alone — that led to a firmware update deployed within 8 weeks. Post-update, 1-star reviews on Amazon DE dropped by 41% and the product’s overall DE rating improved from 3.9 to 4.4 stars within 3 months. New product development now uses competitor review mining as a formal input into feature prioritization.

Client Testimonial: “Hir Infotech gave us a product intelligence capability we simply didn’t have before. The multilingual review analysis opened our eyes to market-specific issues that we were completely blind to. That firmware update alone paid for the entire engagement many times over.” — Head of Product, Consumer Electronics Brand, London, UK

Client Background: A premium cosmetics distributor based in Paris, France, managing distribution rights for 14 international beauty brands across France, Spain, Belgium, and Italy. The company’s brands are sold through 400+ authorized online retailers across the four markets.

Challenge: The client’s brand compliance team was receiving frequent complaints from brand principals about unauthorized discounting and grey-market resellers undercutting MAP pricing across multiple European platforms. Manual monitoring of 400+ reseller sites across four countries in three languages was operationally impossible with their internal team.​

Solution: Hir Infotech deployed a multi-market MAP compliance monitoring system, covering 400+ authorized retailer domains plus a grey-market watchlist of 60+ unauthorized sites across France, Spain, Belgium, and Italy. Our scrapers ran daily sweeps of all brand-relevant SKUs, flagging any pricing below MAP thresholds with reseller identity, URL, screenshot evidence, and violation timestamp. All data was delivered via a structured compliance dashboard with email alerts for critical violations.

Results: Within 60 days, 87 active MAP violations were identified and escalated to brand principals. 64 violations were resolved through retailer communication within the first month. Grey-market listings on unauthorized sites were reduced by 71% following coordinated enforcement action enabled by Hir Infotech’s violation evidence packages. Brand principals renewed distribution agreements with increased confidence in the client’s compliance posture.

Client Testimonial: “This service transformed our brand compliance capability from reactive firefighting to proactive enforcement. The data quality is exceptional, and the multi-country coverage is something we couldn’t achieve in-house. Our brand partners are genuinely impressed.” — Head of Brand Compliance, Cosmetics Distributor, Paris, France

Client Background: A B2B wholesale e-commerce platform based in Melbourne, Australia, connecting 2,200+ product suppliers with 18,000+ business buyers across the ANZ region. The platform’s catalog contains 3.4 million active product listings with historically inconsistent attribute completeness.

Challenge: The platform’s catalog quality score averaged 61% attribute completeness, resulting in poor internal search performance, high buyer abandonment rates, and a significant volume of customer service queries related to missing product information. Suppliers were unable to consistently provide complete product data at scale, and the internal enrichment team could not keep pace with new listing volumes.

Solution: Hir Infotech’s AI-powered product data enrichment pipeline was deployed to process the entire 3.4 million SKU catalog. Our system extracted missing attributes from manufacturer websites, distributor portals, and global product databases, then applied AI-driven normalization to align all records to the platform’s internal taxonomy. Enriched records were delivered in batches via direct API integration with the platform’s PIM system, with ongoing enrichment for new listings running at an SLA of 48-hour turnaround.

Results: Catalog attribute completeness rose from 61% to 94% within six months. Internal search click-through rates improved by 38%, and buyer abandonment on product pages fell by 29%. Customer service queries related to missing product data dropped by 55%. The platform’s supplier onboarding team used the improved enrichment capability as a key selling point in new supplier acquisition.

Client Testimonial: “The catalog transformation Hir Infotech delivered was genuinely remarkable. Going from 61% to 94% completeness across 3.4 million SKUs — in six months — was beyond what we thought was achievable. Our buyer experience has improved measurably, and suppliers love the quality.” — CTO, B2B Wholesale Platform, Melbourne, Australia

Client Background: A mid-market private equity firm based in New York City with an active portfolio of 11 consumer retail and e-commerce brands, collectively generating $600M+ in annual online revenue. The firm’s value creation team required systematic market intelligence to inform portfolio company pricing, M&A target screening, and competitive landscape assessments.

Challenge: The investment team had no scalable process for aggregating structured e-commerce market data across the portfolio’s competitive landscapes. Consultants were engaged for one-off research projects, producing reports that were expensive, slow to deliver, and impossible to update continuously. The team needed always-on market intelligence across pricing, product assortment, and review performance for both portfolio companies and acquisition targets.

Solution: Hir Infotech designed a continuous market intelligence program delivering weekly structured datasets across 45 competitor brands spanning 6 retail categories and 4 major e-commerce platforms (Amazon, Walmart, Target, Shopify DTC storefronts). Custom analytics layers were built to surface SKU-level pricing trends, review trajectory scores, new product launch velocity, and promotional cadence patterns — all formatted for direct consumption by the firm’s internal data analysts.

Results: The firm’s value creation team reduced their external research spend by $420,000 annually while operating with significantly more current and granular intelligence. During one M&A evaluation, Hir Infotech’s competitor review analysis revealed a systematic product quality decline at the acquisition target — intelligence that influenced deal terms and ultimately saved the firm an estimated $3.2M in post-acquisition remediation costs. Three portfolio companies revised their pricing strategies based on the intelligence feeds, with an average gross margin improvement of 2.8 percentage points.

Client Testimonial: “Hir Infotech has become an embedded intelligence capability for our portfolio. The combination of coverage, accuracy, and speed is unlike anything we’ve accessed through traditional research channels. It’s genuinely changed how we approach deal diligence.” — Managing Director, Value Creation, Private Equity Firm, New York City, NY

Client Background: A B2B growth marketing agency based in Amsterdam, Netherlands, managing digital commerce strategies for 35 direct-to-consumer (DTC) brands across Europe. The agency’s clients compete primarily in lifestyle, homeware, and personal care categories on Shopify-based storefronts.

Challenge: The agency’s strategists needed systematic, ongoing visibility into competitor DTC storefronts — covering promotional strategy, product launch timing, pricing architecture, and homepage content changes — to inform campaign planning and new product recommendations for their clients. Manual competitor monitoring was unsustainable across 35 client accounts with an average of 10 competitors each.​

Solution: Hir Infotech deployed a Shopify-specific storefront monitoring service covering 350 competitor DTC sites across the agency’s full client portfolio. Our GDPR-compliant pipelines captured weekly snapshots of homepage promotions, product pricing, new arrivals, discontinued SKUs, bundle offers, and loyalty program messaging. Data was delivered via structured Google Sheets API integration, enabling the agency’s strategists to access clean, normalized intelligence directly within their existing workflow.

Results: The agency reduced competitor research time per client account from an average of 6 hours per week to under 45 minutes — a 87% time saving across the team. Campaign planning cycles shortened by 2 weeks on average, as strategists could identify and react to competitor promotional patterns proactively. Four clients reported market share gains attributed in part to faster campaign responses enabled by the monitoring intelligence.

Client Testimonial: “This has changed how our entire strategy team works. We now have eyes on 350 competitor storefronts, every week, without a single hour of manual work. The data quality is excellent, and the GDPR compliance gave us complete peace of mind for our European clients.” — Head of Strategy, Digital Commerce Agency, Amsterdam, Netherlands