A Benchmark for Banks’ Strategy in Online Presence – An Innovative Approach Based on Elements of Search Engine Optimization (SEO) and Machine Learning Techniques

Camelia Elena Ciolac ()
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Camelia Elena Ciolac: The Bucharest Academy of Economic Studies, Romania

Economia. Seria Management, 2011, vol. 14, issue 1, 91-105

Abstract: This paper aims to offer a new decision tool to assist banks in evaluating their efficiency of Internet presence and in planning the IT investments towards gaining better Internet popularity. The methodology used in this paper goes beyond the simple website interface analysis and uses web crawling as a source for collecting website performance data and employed web technologies and servers. The paper complements this technical perspective with a proposed scorecard used to assess the efforts of banks in Internet presence that reflects the banks’ commitment to Internet as a distribution channel. An innovative approach based on Machine Learning Techniques, the K-Nearest Neighbor Algorithm, is proposed by the author to estimate the Internet Popularity that a bank is likely to achieve based on its size and efforts in Internet presence.

Keywords: SEO; Internet Website Popularity; banking industry; Machine Learning; K-Nearest Neighbors. (search for similar items in EconPapers)
JEL-codes: C81 O33 (search for similar items in EconPapers)
Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:rom:econmn:v:14:y:2011:i:1:p:91-105

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