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Title: BIZPROBE: A GEOLOCATION-DRIVEN AND SCALABLE FRAMEWORK FOR LOCAL BUSINESS INTELLIGENCE AND OUTREACH AUTOMATION
Authors: Waqas Ahmad, Salman Qadri, Muhammad Kashif Majeed, Suleman Saleem, Israr Hussain, Nasir Umer
Journal: Kashf Journal of Multidisciplinary Research (KJMR)
| Category | From | To |
|---|---|---|
| Y | 2024-10-01 | 2025-12-31 |
Publisher: Kashf Institute of Development & Studies
Country: Pakistan
Year: 2025
Volume: 2
Issue: 6
Language: en
DOI: 10.71146/kjmr483
Keywords: Data-driven Decision MakingBusiness IntelligenceGeolocation ServicesOutreach AutomationLocal Market AnalysisScalable Framework
In today’s digital commerce landscape, small and medium-sized enterprises (SMEs) frequently encounter challenges in efficiently managing market data, moni- toring competitors, and executing effective outreach strategies. Despite the increas- ing demand for localized business intelligence, existing solutions often lack niche- specific data enrichment and competitor analysis features tailored for freelancers and entrepreneurs. This paper introduces BizProbe, an integrated business man- agement and competitor analysis platform designed to automate the collection, structuring, and analysis of local business data. Leveraging external APIs, geoloca- tion services, and a relational database, BizProbe enables users to search for busi- nesses within user-defined locations and niches, retrieve enriched details, identify competitors, and execute personalized outreach campaigns. The system addresses operational inefficiencies in traditional market research by providing structured, up- to-date data for informed decision-making. Additionally, this project demonstrates the practical application of web technologies, location-based services, and data an- alytics in developing a scalable and user-centric platform for business profiling and competitive analysis.
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