The Camera Marketplace as a Certified Outcome Product: Integrating the 10Ps Framework, DUAL Architecture and Growth Hacking Strategy for e Marketplace

DOI

https://www.doi.org/10.59256/indjcst.20260501082

Published In

Volume 5, Issue 1 (2026)

Published Online

January-April 2026

Pages

684-695

Article Type

Original Article

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India's AI surveillance market stands at a critical inflection point: a regulatory shift restricting Chinese surveillance equipment under MeitY/STQC certification, the rise of edge AI hardware, and the proliferation of B2B digital marketplaces converge to create an unprecedented strategic opportunity. This paper presents an integrated research framework synthesising two foundational contributions — the 10Ps of New Age Marketing (Gujar, 2024, 2025) and the IndoAI Camera eMarketplace Strategy Framework (2026) — into a unified, academically grounded model for designing and scaling India's first Certified Outcome Product marketplace for AI cameras. The paper establishes that the conventional 7Ps marketing mix is structurally inadequate for AI-embedded, compliance-driven, multi-buyer hardware products. The proposed architecture extends the marketing mix to 10Ps — incorporating Personalization, Platforms, and Performance Analytics — and then operationalises these through the DUAL Framework (Decode, Unlock, Authenticate, Layer) specifically designed for dual-buyer contexts where a layman decision-maker (school principal, factory owner) and a technical evaluator (IT manager, procurement officer) must both be served simultaneously on the same product listing. Using the Growth Hacking AARRR loop as the operational engine, the paper maps buyer personas, purchase psychology, compliance architecture, and UX principles to the 10Ps pillars. It introduces the AIRI (AI Readiness Index) score as a platform trust mechanism and the Appization/NeurHub™ model as an analogy for platform network effects in edge AI. The paper further introduces the concept of 'Data Threshold Awareness' as an 11th meta-principle — warning against premature growth hacking in pre-data phases — and provides IndoAI's implementation roadmap as a live case study. The findings offer marketers, platform designers, and AI hardware manufacturers a replicable strategic blueprint applicable across Indian enterprise markets.