Two revolutionary technologies stand out as perfect answers for this small designer clothes and accessories company looking to start an e-commerce platform and combine it with an online presence: social media, social computing, and intelligent systems. Social networking, crowdsourcing, social media, and other collaborative tools are ways of involving consumers directly. This influences the brand and increases consumer awareness. Using artificial intelligence, machine learning, predictive analytics and other futuristic technologies entails automating business-critical processes and allows for informed decision-making based on data. The key concern this enterprise needs to figure out is how it can rock its brand beyond the borders of a physical store. This problem can be eliminated by adopting a solution that utilizes the two ICT methods’ inherent qualities.
The Principal Business Issue
For this shop, where designer clothes and accessories will be sold, we plan to add a website and solely rely on its internet presence rather than the shop itself. The inefficiency with which the company can engage and service clients in the online environment and its competitors, like Nordstrom Rack, Macy’s, Zappos, and others, is currently needed because of a lack of deep e-commerce capabilities (Hamide, 2020). The main issue concerns that, until now, there has yet to be a specific technological platform that can run the website, process orders, control inventory, handle relationships with customers, and analyze data, among other important features.
Using Social Computing to Engage Customers
Social media applications serve as platforms to build and maintain customer relationships. Implementing social computing technologies results in efficient means for interchanges between consumers and simultaneously supports two-way interaction. E-commerce giants that are front runners in the sport of clothing are already using social networks very emphatically. One instance is through “The Thread”, which incorporates Nordstrom Rack’s online social components, including sharing looks, giving advice, and talking to others in the community. Macy’s employs influencers, branded hashtags, and contests to connect with on-trend customers on Facebook, Instagram, and Twitter (Steinhoff et al., 2018). Social media administration tools, an online customer forum, product reviews and Q&A, and social media marketing and advertisement are game-changing elements for this company. They make it more convenient to dialogue with the clients to collect their views on styles and new items.
Sensible Systems for Automated Processes
AI, machine learning and advanced data analytics solutions with an intelligent system that can be used for effective process automation and data-driven decision-making can also be introduced simultaneously. The future of this business is under scrutiny from Nordstrom’s data hub, with customer analytics enabling unified insights across channels and Zappos that utilizes machine learning for optimal user suggestions. Competition has already experienced such frenzied operational efficiencies (Osamuyimen et al., 2023). A plausible application of intelligent systems is in inventory management, in which AI powers that interpret with machine learning algorithms, demand forecasting, and price and promotion optimization can be computerized. In addition, audience segmentation with integrated market marketing purposes can be driven by customer data analytics and personalized product suggestions can be fueled by the same.
Suggested All-Inclusive Resolution
I advise using an integrated, best-of-breed solution that unifies potent social computing and intelligent systems capabilities under a single platform in order to address the issues raised and satisfy all-important technological requirements fully: I advise using an integrated, best-of-breed solution that unifies potent social computing and intelligent systems capabilities under a single platform in order to address the issues raised and satisfy all-important technological requirements fully:
Parts of Social Computing
Monitoring listening and social media management tools are important.
Convened a forum or a consumer group online.
Product evaluations and Q&A
Advertising and marketing on social media Intelligent Systems Components
AI-powered forecasting and inventory control
Pricing optimization and forecasting demand using predictive models.
Automated segmentation and analytics of customer data will be the key enablers of customer centricity.
Personalized suggestions are being enhanced with the help of machine learning.
A system that integrates all online shopping requirements -like automated inventory management, data-driven marketing, and decision intelligence- is within the specified technological requirements, effortlessly fulfilling them. According to (Nock & and Baker, 2019), these technologies’ Correct and harmonious integration aims to optimize internal processes and business analytics and provide customers with a personalized e-commerce experience.
Overall Advantages and Security Issues
Going forward, this company may see a lot of e-commerce success as it integrates social computing for customer involvement with business intelligence and data-driven decision-making technologies. A strategy of user-produced material, which especially involves two-way communication, will lead to building customer relationships and loyalty. In the backroom of the business, the data can be precisely analyzed for optimization in the same period (Ahmad et al., 2020). However, data protection, security, and privacy must be considered first by any organization that handles human data with such high trust. Privacy features like encryption, two-word authentication, strong access controls, and log auditing must be integrated into the designed system. A security expert must review the security certification and practices of all possible third-party technology providers.
Social computing and intelligent systems with resilient security systems can be the best providers for this company in terms of an effective technological choice. Operating tools will be developed using the talents of modern e-commerce, process automation and data-driven decision-making (Arash, 2010). Moreover, customers’ enhanced usefulness and engagement will forge new relationships and strengthen loyalty for ages to follow.
References
Ahmad, S., Suraya Miskon, Alabdan, R., & Iskander Tlili. (2020). Towards Sustainable Textile and Apparel Industry: Exploring the Role of Business Intelligence Systems in the Era of Industry 4.0. Sustainability, 12(7), 2632–2632. https://doi.org/10.3390/su12072632
Arash Bahrammirzaee. (2010). A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert and hybrid intelligent systems. Neural Computing and Applications, 19(8), 1165–1195. https://doi.org/10.1007/s00521-010-0362-z
Hameide, K. K. (2020). Managing Fashion. In Routledge eBooks. Informa. https://doi.org/10.4324/9781351106856
Nock, D., & Baker, E. (2019). Holistic multi-criteria decision analysis evaluation of sustainable electric generation portfolios: New England case study. Applied Energy, pp. 242, 655–673. https://doi.org/10.1016/j.apenergy.2019.03.019
Osamuyimen, E., None Oluwatoyin Ajoke Farayola, None Funmilola Olatundun Olatoye, None Obiageli Chinwe Nnabugwu, & None Chibuike Daraojimba. (2023). BUSINESS INTELLIGENCE TRANSFORMATION THROUGH AI AND DATA ANALYTICS. Engineering Science & Technology Journal, 4(5), 285–307. https://doi.org/10.51594/estj.v4i5.616
Steinhoff, L., Denni Arli, Weaven, S., & Kozlenkova, I. V. (2018). Online relationship marketing. Journal of the Academy of Marketing Science, 47(3), 369–393. https://doi.org/10.1007/s11747-018-0621-6
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