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A Study on Impact of Video Content in Vlogs to Increase Traffic Generation

Issue Abstract

Abstract
This study explores the impact of integrating video content into blogs as a strategy to enhance traffic generation. As the digital landscape evolves, online platforms are constantly seeking innovative methods to engage and attract audiences. Video content has emerged a s a dynamic and captivating medium, offering a multisensory experience that appeals to a wide audience. This research investigates how incorporating videos within blog posts can contribute to increased traffic and user engagement. The study employs a mixed methods approach, combining quantitative analysis of website traffic metrics and qualitative examination of user feedback. A sample of blogs is selected to implement video integration, while a control group maintains traditional text based content. Variou s key performance indicators, including page views, bounce rates, and user interactions, are monitored over a specified period. Preliminary findings indicate a positive correlation between the inclusion of video content and heightened user engagement. Vid eo enhanced blogs demonstrate a noticeable increase in average session duration, suggesting that visitors are more likely to spend extended periods exploring multimedia rich content. Moreover, initial analysis of social media sharing and backlinking patter ns suggests that video infused blogs are more likely to be shared across online platforms, potentially contributing to organic traffic growth. The qualitative component of the study involves gathering user feedback through surveys and comments sections. Th is data aims to shed light on user preferences, satisfaction levels, and perceived value of video content within the blogging context. Insights from these qualitative responses are intended to complement the quantitative results and provide a more comprehe nsive unders tanding of the user experience. The implications of this research extend beyond the immediate context of traffic generation, encompassing aspects of content strategy, audience engagement, and the evolving nature of online consumption. The findi ngs are expected to offer actionable insights for content creators, digital marketers, and platform developers seeking to optimize their online presence through the strategic incorporation of video content within blog formats.
KEYWORDS: Video content, Vlog s, Traffic generation,social media, Content strategy.


Author Information
Sneha.L
Issue No
5
Volume No
4
Issue Publish Date
05 May 2024
Issue Pages
107-119

Issue References

Reference

1.Kashi Venkatesh Vishwanath.et.al,‖ Realistic and responsive network traffic generation‖. https://doi.org/10.1145/1159913.1159928
2.  T Lehtimaki, J Salo, H Hiltula and M Lankinen ( 2009).“Harnessing web 2.0 for business to business marketing: literature r eview and an empirical perspective from Finland. https://urn.fi/URN:ISBN:9789514291203
3. M Cha, H Kwak, P Rodriguez, YY Ahn… ACM Transactions on…, 2009 Analyzing the Video Popularity Characteristics of Large Scale User Generated Content Systems” 10.1109/TNET.2008.2011358
4. Abhari, A., Soraya, M. (2010) 2010)“Workload generation for Multimed Tools Appl 46 , 91 118. https://doi.org/10.1007/s11042 009 0309 5
5. Wen Gao.et.al, (2010). “Vlogging: A survey of videoblogging technology on the web”. https://doi.org/10.1145/1749603.17 49606 Chamara Kattadige.et.al, (2021) “A Generative Adversarial Framework for Synthetic Video Traffic Generation”. https://doi.org/10.1109/WoWMoM51794.2021.00034
6. Tuti Widiastuti.et.al,(202 1) “The Commodification of Virtual Community Content in Increasing Media Traffic”. https://doi.org/10.17645/mac.v9i2.3737
7. Xiaobin Liu.et.al (2021), 2021),” Vlog Based Multimodal Composing: Enhancing EFL Lea rners’ Writing Performance”, Appl. Sci. 2021, 11(20), 9655; https://doi.org/10.3390/app11209655
8. AA Fathinasari, Purnomo. Indonesia Journal (2023), “ Analysis of the Study of Digital Marketing Potential on Product Purchase Decisions in Generation Z” https://doi.org/10.37275/oaijss.v6i5.174
9. Guillaume Jourjon.et.al, (2022). “VideoTrain: GAN based adaptive framework for synthetic video traffic generation  https://doi.org/10.1016/j.comnet.2022.108785.