Essay on Robotics Home Adoption: Connecting the Dots to Increase User Engagement

Introduction

The disconnect between home robotics and smart home offerings has been a crucial factor that has limited the adoption of home robotics. Availability, consumer awareness, and price have also been factors for consideration. However, vendors such as Amazon have seen the value in backing up the integration of their devices (Chung, Park, & Lee, 2017). Robots aimed at providing social or personal care and interaction have continued to struggle to win consumer adoption and lagging as a segment. Amazon Echo was launched in 2004, and it has extended control to home care robots that ensure functionality, awareness, and appeal to home care robots.

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Key Environmental Factors

The business factors that affected the home robotics market include advanced tasks and mass customization. Alongside automating simple tasks performed by humans in the past, the advanced tasks that experts performed are also automated. Individual product customization has been challenging to achieve because of cost-related issues (Chung, Park, & Lee, 2017). Another business issue affecting the industry is the prices, where consumers unwilling to spend much on premium products.

Failures of Amazon in Anticipating the Robotics Market

Amazon Echo did not read well into the market research and identify the best prices for its products, which explains why it was a huge risk. The initial intention was to sell the Echo for $17, but it retailed at $180 (Haack, Severance, Wallace, & Wohlwend, 2017). The main challenge for Amazon Inc was the packing of all the processing power into the package. Amazon does not release information on the sales of its products. Another issue was in the naming of the product. The Echo was initially called the Flash, and it was later referred to as "Amazon." A common perception among the team members was that the project was destined for failure.

Key Execution Failures

Regardless of the heavy inflow of funds, robotic organizations such as amazon Inc. have failed to mature and sustain in the market. Unlike other industries such as data science, amazon's Echo has taken longer to mature. To ensure technology works, the company undertook to commercialize and bring it to the market without much pay (Jackson & Orebaugh, 2018). The growing failure of the Amazon Echo was linked to the hard nature of robotics. Training machines to execute a simple task is extremely difficult. This is among the reasons that led to the failures of Amazon Inc.

Key Elements of the Business Model Canvas

For amazon echo, the descriptions of its business are the building blocks of the activities it undertakes. Some of the key elements of the canvas are its infrastructure that includes key resources, activities and the partner network. To ensure the maximum operation and minimize risks, amazon Inc. has cultivated buyer-supplier relationships to focus on its main activities (Jackson & Orebaugh, 2018). The business model also focuses on the offering, which is understood from the value propositions. Collections of services and products a business provides to meet the needs of the clients are very necessary for amazon (Jackson, & Orebaugh, 2018). The final element for amazon in the canvas are the customers. To make more sales of Amazon Echo, amazon identified the customers it targeted. These elements in the canvas have ensured better practices to overcome the various challenges affecting amazon echo and the home care robotics market.

Product Strategy

Amazon has realized success in the smart home market by opening its services to anyone. Amazon has tried to adapt feedback by ensuring that consumers engaged with the company. Amazon learnt of Apple Company's mistake where HomeKit was difficult to use and challenging to work with (Zhang et al., 2018). As a service company, Amazon listens and responds to users. Amazon takes the things it creates for internal use to make better products and then tries making these tools available to other people as a service.

Product Positioning

For the older millennial and younger baby boomer populations looking for in-home convenience, amazon echo is the unique intelligent personal assistant device that offers interactive technology. To the 24-50-year-old tech-savvy consumers seeking to satisfy the need for effectiveness at home, amazon echo offers hands-free technology within the household (Zhang et al. 2018). Amazon Echo is a cloud-based software that integrates mobile devices and other external companies to help consumers with any task. Amazon Echo is unique, modern, and innovative, and the value-based payoff is satisfaction and convenience.

Market Strategy

Amazon's market strategy for its echo products includes its prime membership. Amazon has undertaken full advantage of its strong brand power to continue the integration with external organizations and positioning themselves towards the younger baby boomers and older millennial populations. The reliability and trustworthiness of amazon as a brand in the eyes of the consumers has already created the basis for success (Clinton, Cook, & Banik, 2016). Amazon has also used its power to partner with a popular organization to increase sales of the Echo and appeal to a wider customer base. The end goal is growing its market share in the intelligent personal assistant industry. Concerning product distribution and pricing, Amazon's strategies are optimal. As a leader in online retailing, amazon offers the most effective platforms for distributing Echo products.

Conclusion and Implications

As shown from this discussion, the unique selling points of amazon echo are its pricing and value it provides to customers. Amazon has experienced difficulties in introducing and selling the echo product since it was launched in 2004. However, the company has also undertaken various initiatives that have improved the sale of the product, such as better pricing and product differentiation. The key to improved profitability is ensuring the best experience for clients, and this has driven the sales for amazon echo.

References

Chung, H., Park, J., & Lee, S. (2017). Digital forensic approaches for the Amazon Alexa ecosystem. Digital Investigation, 22, S15-S25. https://www.sciencedirect.com/science/article/pii/S1742287617301974

Clinton, I., Cook, L., & Banik, S. (2016). A survey of various methods for analyzing the amazon echo. The Citadel, The Military College of South Carolina. https://pdfs.semanticscholar.org/4764/7a865622106c024d42e680acbb726aeea69d.pdf

Haack, W., Severance, M., Wallace, M., & Wohlwend, J. (2017). Security analysis of the amazon echo. Allen Institute for Artificial Intelligence, 11. https://pdfs.semanticscholar.org/35c8/47d63db1dd2c8cf36a3a8c3444cdeee605e4.pdf

Jackson, C., & Orebaugh, A. (2018). A study of security and privacy issues associated with the Amazon Echo. International Journal of Internet of Things and Cyber-Assurance, 1(1), 91-100. https://pdfs.semanticscholar.org/e80b/6646a8d6c5a6e4b8904db11d8115e83c6b09.pdf

Zhang, N., Mi, X., Feng, X., Wang, X., Tian, Y., & Qian, F. (2018). Understanding and mitigating the security risks of voice-controlled third-party skills on amazon alexa and google home. arXiv preprint arXiv:1805.01525. https://arxiv.org/pdf/1805.01525.pdf