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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM59987

AN EVALUATON OF ANSWER ENGINE OPTIMIZATION (AEO) READNIESS ACROSS MAJOR E-COMMERCE MARKETPLACE WEBSITES IN A COMPETITVE DIGITAL ENVIRONMENT

Stream/Area:

-

Subject:

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Paper ID:

IJSREM59987

Volume:

10 |

4 |

April 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM59987

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

TJ

Tanisha Jaswal

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Abstract

It examines how Answer Engine Optimization (AEO) can strengthen smartphone-related e-commerce visibility in India by comparing four query groups drawn from a secondary dataset: a broad budget query, a processor-focused feature query, a brand query, and a student use-case query. The findings show that brand-focused and user-need-focused queries outperform narrow feature queries across traffic,

KEYWORDS

breadth page quality domain strength and backlink support. The study argues that answer-led visibility improves when content directly matches buyer intent uses natural-language question framing provides concise comparisons and is structured for summarisation by answer engines and AI assistants. Although the data remain exploratory the analysis suggests that AEO should complement SEO by improving answer extraction trust and recommendation readiness. The paper concludes that smartphone pages are more likely to be surfaced in answer-first search systems when they combine intent clarity structured comparison and clear product guidance

Cite This Article

Tanisha Jaswal, "AN EVALUATON OF ANSWER ENGINE OPTIMIZATION (AEO) READNIESS ACROSS MAJOR E-COMMERCE MARKETPLACE WEBSITES IN A COMPETITVE DIGITAL ENVIRONMENT," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, April 2026. https://doi.org/10.55041/IJSREM59987

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Publication Date

4/9/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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