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MagicBricks vs 99acres vs Housing: Listing Data Study 2026

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  Introduction Actowiz analyzed 200,000+ listings across MagicBricks, 99acres, and Housing.com in 8 Indian cities. Findings: the same property appeared on multiple portals with asking-price differences in 32% of matched cases (median gap ₹X lakh / Y%); duplicate and stale listings inflated raw inventory counts by 32%; and portal coverage skews sharply by city — no single portal gives a complete market picture anywhere. The Problem With Reading One Portal India's property portals are marketing channels, not registries. Brokers cross-post with different prices, listings outlive actual availability, and each portal's broker network skews coverage by city and segment. Anyone using portal data — buyers, proptechs, lenders, researchers — needs to know how big these distortions are. We measured them. Methodology ParameterCoveragePortalsMagicBricks, 99acres, Housing.comCitiesMumbai, Delhi NCR, Bengaluru, Pune, Hyderabad, Chennai, Ahmedabad, KolkataListings analyzed200,000+ (resale + re...
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Shein vs Temu vs Amazon Fashion: Pricing Data Study 2026

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Introduction TL;DR: Actowiz tracked 30,000+ matched fashion SKUs across Shein, Temu, and Amazon Fashion (US market) over 60 days. Findings: Temu undercut comparable items by 24% on average but with the highest price volatility; Shein refreshed assortment 5.6× faster than Amazon; and flash-discount mechanics — not list price — drive the real price gap. Tariff and de-minimis policy shifts have made week-over-week monitoring essential for anyone competing in fast fashion. Why This Comparison Matters in 2026 Fast fashion's price war has moved from stores to algorithms. Shein and Temu run aggressive dynamic pricing and gamified discounts, while Amazon Fashion competes on Prime logistics and breadth. For brands, the question isn't just "who is cheaper" — it's how each platform constructs its price: list price, flash discount, coupon stack, and shipping threshold all behave differently. Methodology Platforms Covered: Shein, Temu, and Amazon Fashion (US). Product Categor...
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Booking vs Agoda vs Expedia: Hotel Price Parity Data 2026

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  Introduction TL;DR: Actowiz tracked identical room types at 2,500 hotels across 15 cities on Booking.com, Agoda, and Expedia over 60 days. Findings: the same room on the same dates showed different prices across OTAs in 42% of observations; Agoda's headline rates ran lowest in Bangkok, Bali, and Singapore while taxes-and-fees presentation reversed many gaps at checkout; and mobile-only/member rates broke advertised parity in 32% of cases. Why Rate Parity Is the Travel Industry's Data Problem Hotels promise OTAs rate parity; OTAs compete to break it through member pricing, mobile rates, and packaging. For hotels, parity violations leak revenue and damage direct-booking strategy. For OTAs and metasearch, parity gaps are the competitive product. Nobody can manage what they can't see — and seeing it requires scraping identical room-date pairs across platforms continuously. Methodology Platforms Covered: Booking.com, Agoda, and Expedia. Cities Covered: 15 major destinations,...
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NBFC Uses Multi-State RERA Data for Real Estate Lending Intelligence | Actowiz Solutions

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  Introduction 10 markets covered across 6 states 85,000+ projects normalized into one schema Monthly refresh incl. QPR & status changes Client: Listed Indian NBFC, AUM ₹35,000+ Cr (name withheld) Industry: BFSI — Construction Finance Use Case: Market monitoring & underwriting intelligence Coverage: Mumbai, Pune, Nashik, Ahmedabad, Vadodara, Surat, Delhi-NCR, Chennai, Bengaluru, Hyderabad Delivery: Monthly refresh to client data warehouse + analyst dashboard About the Client Our client is a listed non-banking financial company with assets under management exceeding ₹35,000 crore. Construction finance and real estate account for roughly a fifth of its book. For its asset-management and underwriting teams, understanding each market — how active it is, what product mix developers are launching, which promoters are delivering on time — is fundamental to both origination decisions and portfolio monitoring. In the post-RERA era, the single richest public source for this is projec...
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Netflix vs Prime vs Hotstar: Catalog & Pricing Data 2026

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  Introduction TL;DR: Actowiz analyzed catalog metadata — 45,000+ title listings — and plan pricing across Netflix, Prime Video, and JioHotstar in India and the US. Findings: Prime Video listed the largest raw catalog while Netflix led in originals share; JioHotstar's regional-language depth (X% of its Indian catalog) is its structural moat; and per-title-value (catalog ÷ plan price) varies X× between markets for the same platform. Why OTT Catalog Data Matters Streaming competition is fought on three measurable axes: catalog breadth, content mix, and price architecture. Studios deciding licensing strategy, platforms benchmarking content gaps, and analysts modelling churn all need the same thing — structured, current catalog metadata. Platforms don't publish it; their public catalog pages reveal it. Methodology Platforms Covered: Netflix, Prime Video, and JioHotstar. Markets Covered: India and the USA. Title Listings Captured: 45,000+ movies and series (metadata only). Metada...
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