“The conversations of the future are between a person and a machine” (Hood, 2017). You might have seen the movie ‘Her’ where an advanced female AI voice-assistant and a man build a relationship together. We are not there yet, but conversations with machines are definitely on the rise. Today, 40% of the adults use voice search once per day and the prediction for 2020 is that 50% of the searches will be done through voice (Jeffs, 2018). Smart-speakers in houses and offices are used to channel voice-searches. Amazon Echo, had the first mover advantage in 2014, and currently dominates the market with a share of roughly 70% (Quartz, 2018). In 2017, Google Home was launched, followed by the Apple HomePod. Microsoft and Facebook are also aiming to release their first smart-speaker later in the year.
To better understand smart-speakers and virtual assistants this blog analyses the business model of the Amazon Echo with Alexa as virtual assistant. Specifically the following questions are discussed:
1.How does Amazon create value for customers?
2.How does Amazon profit?
3.How does Amazon maximise efficiency in its developer’s network?
4.How does Amazon deal with privacy?
1. Customer value
voice-requests, music, calling and banking
The Echo allows customers to request actions at a virtual assistant using voice. Voice is faster and more convenient than typing and more easy to do while moving (Agrawal, 2017). You can ask Alexa to play specific music, search wikipedia for answers, do maths, set timers, set events or play voice games. More advanced uses cases are the ability to call, message someone, check your bank account or transfer money. More uses cases are available on the Amazon Echo and instead of the App terminology on mobile platforms, these voice programs called “Skills”.
The Echo can be connected with other devices such as your lights, fridge, thermostat, locks on doors. Routines can be set, for example with “Alexa goodnight” to shut down lights and lock-doors at once (Newman, 2017).
You can order products from the Amazon store using your Echo. With the re-order command you can re-order a certain product and Alexa will review your purchase history to see what brand you want (Gartenberg, 2017)
As Grönroos and Voimo (2013) discuss, Amazon can be seen as the value facilitator, offering the Echo, assistant and skills for the customer to create value in-use. Moreover, as experience increases more value for the customer emerges. Especially with AI learning from the customer, a system views can be taken towards value creation. Emergent properties arise, when the customer continuously interacts with AI, allowing the customer and AI to create more and more personalized value which could not be predicted ex-ante.
At this moment the monetisation of the Echo or Alexa is not the focus of Amazon. Amazon aims to capture the complete market and improve the product (Simonite, 2016). Several revenue paths exists and will be more important as the customer base and frequency of use increases:
- Increased sales via improved recommendations. Recommendations stems from understanding the customer and delivery of recommendations (Adomavicius and Tuzhilin’s, 2005). Voice-conversations with Alexa provide valuable information on who the customer is, what he/she wants and in the customer funnel he/she is. This data can be merged with data with the other data Amazon has to form a completer picture. This customer understanding improves the recommendations Amazon can provide and increases the sales revenue for Amazon or marketing advice revenue. For the latter, Amazon can use the understanding to better advice other companies on how to target a specific customer.
- Increased sales via easier customer journey. Voice is more natural than typing and hence it has become easier to order a product. It is expected that replenishment orders, for example for toilet paper or batteries, will be increase. See figure 1 for a forecast of US voice payments and number of voice-users.
- Ads revenue. Amazon is looking into promoted search results for voice-searches on Alexa. Partner companies would bid to end up high in the search results, which is even more important for voice than with a desktop/mobile search (Newman, 2018).
- Skills commission fee. Similar to Apple taking a share from app purchases in the Appstore, Amazon could take a share from skill subscriptions or in-skill purchases to earn money from its open platform. This brings us to the next subsection: efficiency.
Amazon has the platform challenge that it wants to increase participation on the customer as well as the developer side. Amazon is experimenting with its internal institutional arrangements (IA) with developers. Carson et al. (1999) would argue that a contractual arrangement is an efficient IA if it can, among other criteria, increase the profit of the system and of individual contributors. Since 2018, Amazon offers the option for in-skill purchases with Amazon Pay, such that users can pay developers. Subscriptions is a second channel through which developers can earn money. Profits for developers and Amazon can still be improved if discoverability of Skills, which is harder in a voice-based environment, increases. The contribution of developers also depends on the easy of use of the developer’s toolkit (Hollander, 2017).
How does Amazon use your data. “Alexa uses your voice recording to answer your questions, fulfill your requests, and improve your experience and our services,” Amazon says. “This includes training Alexa to interpret speech and language to help improve her ability to understand and respond to your requests.” (Newman, 2018b).
Amazon only records data when Alexa is triggered, meaning, when the ‘wake word’ Alexa is mentioned, and allows users to review and delete voice-recordings. If you want to delete bulk recordings you need to go to the Amazon website. There is no method to have your recordings automatically deleted. (Barett, 2017)
Amazon aims to better and better understand the customer which includes deducting your emotions from speech (Dickson, 2018). The external institutions about privacy will highly influence what Amazon is able to do and not do with your data in the future and how specifically transparency information should be provided.
Voice-search and virtual assistants are on the rise with smart speakers as their physical embodiment. Customer value is derived from using voice to ask questions, shop and control home furniture. As AI advances, more personalised and emergent value arises for the customer. Monetisation is not a focus yet for Amazon, but which massive adoption in the future, there will be plenty of ways to profit from the Echo and Alexa. Improved recommendation systems, sales, ad placement and commissions on Skill subscriptions are examples of profit avenues. Institutional challenges arise for Amazon in the best alignment of developer incentives and when future privacy regulations change.
Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE transactions on knowledge and data engineering, 17(6), 734-749.
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Amazon Echo’s dominance in the smart-speaker market is a lesson on the virtue of being first