Integrating Updated Google Street View and Aerial Imagery to Enhance Buyer Trust and Sustainable Marketing in Malaysian Real Estate
Keywords:
Malaysia, google street view, aerial view, real estate marketing, buyer trust, sustainabilityAbstract
Digital marketing tools have been widely adopted across various industries worldwide, as well as in Malaysia. These tools have enabled Malaysian property developers to obtain real-time insights into purchasers and create a valuable channel for communicating with customers more effectively. Platforms such as iProperty and PropertyGuru, as well as Google Search and Maps, and micro websites that embed virtual tours are the first interactions buyers build with developers. Yet there is often a mismatch between the online information available through the satellite or street view and what real estate agents or developers show. Available Street View and satellite images seen by the public often show outdated representations of projects, which do not necessarily correspond with reality but have had a significant impact on many developments. This inconsistency often undercuts buyer confidence and dilutes the faith in the credibility of developments’ digital marketing efforts. The study aims to examine how customized updates of Google Street View and Aerial View photos raise accuracy, transparency, and reliability in Malaysian real estate marketing. Hence, this paper furthermore contains a case study involving the M Legasi Show Village launched recently by Mah Sing Group. According to findings, custom-developed GSV clarifies the project condition as the latest imagery captured and may enhance marketing sustainability by reducing unnecessary printed materials and travel to the site. To summarize the findings, it shows that the updated GSV and AV content offer an elevated level of transparency in marketing and enhance buyer perception within the Malaysian real estate sector.
References
Anguelov, D., Dulong, C., Filip, D., Frueh, C., Lafon, S., Lyon, R., Ogale, A., Vincent, L., & Weaver, J. (2010). Google Street View: Capturing the world at street level. Computer, 43, 32–38. https://doi.org/10.1109/MC.2010.170
Azmi, A., Ibrahim, R., Abdul Ghafar, M., & Rashidi, A. (2021). Smarter real estate marketing using virtual reality to influence potential homebuyers’ emotions and purchase intention. Smart and Sustainable Built Environment. Advance online publication.
Badland, H. M., Opit, S., Witten, K., Kearns, R. A., & Mavoa, S. (2010). Can virtual streetscape audits reliably replace physical streetscape audits? Journal of Urban Health, 87, 1007–1016. https://doi.org/10.1007/s11524-010-9505-x
Biljecki, F., & Ito, K. (2021). Street view imagery in urban analytics and GIS: A review. Landscape and Urban Planning, 215, 104217. https://doi.org/10.1016/j.landurbplan.2021.104217
Group of Companies. (2025). Google Maps contributions dashboard: Company data (33,204 photos, 1,345 property updates, 278,888,535 total views).
Goel, R., Garcia, L. M. T., Goodman, A., Johnson, R., Aldred, R., Murugesan, M., … Woodcock, J. (2018). Estimating city-level travel patterns using street imagery: A case study of using Google Street View in Britain. PLOS ONE, 13, Article e0196521. https://doi.org/10.1371/journal.pone.0196521
Google Maps. (2024). M Legasi Show Village – Public Street View (outdated version). Retrieved October 2025 from https://maps.app.goo.gl/QptGRKBpDFoUHR3u8
Google Maps. (2025). M Legasi Show Village – Commissioned Aerial and Street View (updated version). Retrieved October 2025 from https://maps.app.goo.gl/15VfyqXWG3SVQm7NA
Low, S., Ullah, F., Shirowzhan, S., Sepasgozar, S. M. E., & Lee, C. L. (2020). Smart digital marketing capabilities for sustainable property development: A case of Malaysia. Sustainability, 12(13), 5402. https://doi.org/10.3390/su12135402
Liu, L., Silva, E. A., Wu, C., & Wang, H. (2017). A machine learning-based method for the large-scale evaluation of the qualities of the urban environment. Computers, Environment and Urban Systems, 65, 113–125. https://doi.org/10.1016/j.compenvurbsys.2017.06.003
Ministry of Economy Malaysia. (2023). National Energy Transition Roadmap (NETR). Retrieved from https://ekonomi.gov.my
Mitrovic, K., Novakovic, N., Spajic, J., & Cosic, I. (2021). Augmented reality in marketing – State of the art. Proceedings of the 32nd International DAAAM Symposium 2021, 566–575. https://doi.org/10.2507/32nd.daaam.proceedings.081
Naik, N., Philipoom, J., Raskar, R., & Hidalgo, C. (2014). Streetscore: Predicting the perceived safety of one million streetscapes. In Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW’14) (pp. 793–799). IEEE. https://doi.org/10.1109/CVPRW.2014.121
Parman, S., Fahrudin, R., Lesmana, M. A., & Putra, P. S. (2023). Penggunaan teknologi augmented reality untuk meningkatkan pengalaman pelanggan dalam pemasaran produk real estate. Jurnal Digit, 13(2), 189. https://doi.org/10.51920/jd.v13i2.354
Rehman, F., Nawaz, T., Ahmed, I., & Hyder, S. (2014). Some insights in the historical perspective of hierarchy of effects model: A short review. Information Management and Business Review, 6(6), 301–308.
Sukma Wijaya, B. (2012). The development of hierarchy of effects model in advertising. International Research Journal of Business Studies, 5(1), 73–85.
Law, S., Shen, Y., & Seresinhe, C. (2017). An application of convolutional neural networks in street image classification: The case study of London. In GeoAI’17: Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery (pp. 5–9). ACM. https://doi.org/10.1145/3149808.3149810
Berland, A., & Lange, D. A. (2017). Google Street View shows promise for virtual street tree surveys. Urban Forestry & Urban Greening, 21, 11–15. https://doi.org/10.1016/j. ufug.2016.11.006.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Eliga Rezaie, Shafi Bin Mohamad
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles in the Journal of Sustainable Innovation and Impact (JSII) are published open access under the Creative Commons Attribution 4.0 International License (CC BY 4.0). Authors retain copyright and grant the journal a non-exclusive license to publish. Readers may share, adapt, and build upon the work for any purpose, including commercial, provided proper attribution is given to the original work and source.
