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Amazon: Cloud Cam and Amazon Key service remove friction from home delivery

by Werner Goertz  |  October 25, 2017  |  Submit a Comment

Today’s announcements from Amazon underscore Amazon devices’ strategy to immerse the consumer in the Amazon ecosystem, drive consumption and remove friction.

Amazon’s indoor connected cameras (Cloud Cam) are parts of a cloud-enabled delivery process that is aware of the consumer’s purchase, tracking last-mile delivery status and working towards an improved buying experience.

It addresses a concern of many single-household and apartment complex dwellers: how to ensure safe delivery when the recipient is not present? The Cloud Cam hardware is part of the Connected Home service that not only monitors the whereabouts of your 150-pound Great Dane, but can also be used to anticipate a certain delivery event, authenticate the delivery person and temporarily allow access to the unattended home. Every step of that delivery process is monitored and recorded.

This service is available to Amazon Prime customers today (since the entire buying experience, including last-mile delivery process is captured). Interesting to see how others (Google – Walmart) will respond. Amazon has been thinking hard about last mile delivery (Amazon Fresh delivery, drones, …) and this one example of removing friction from the entire experience.


  • What happens when your Great Dane takes a bite out of the delivery person – who’s liable?
  • How to deal with the all-too-frequent network/connectivity outages? (Happens more often than you think – Connected Home hubs still have no self-healing capabilities).
  • Device setup is still a headache: the new Echo Plus hub has auto-detect capabilities which don’t seem to be supported by this release of Cloud Cam.



Werner Goertz
Research Director
1 years at Gartner
21 years IT Industry

Werner Goertz is a Research Director within Gartner's Personal Technnologies team, where he covers personal devices (smartphones, PCs/Ultrabooks, tablets/ultramobiles and wearables) and IoT. A special emphasis of his research lies in the Human Machine Interface (HMI) and multimodal I/O technologies: voice/speech processing and recognition, facial recognition and eye tracking, biometrics and motion/gesture control. Read Full Bio

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