over 1 year ago
One way to build richer Alexa skills is to make sure you provide relevant and dynamic information to customers every time they use your skill. For example, if you create a simple fact skill, a user may find the experience interesting the first and second time they use the skill but after that, they will keep running into the same information and might no longer see value in using your skill. Using open data can help you pull information that is relevant and different every time your customer comes back to use your skill. Here is a quick example to illustrate how this could work (Btw, this hasn't been built yet for those of you still looking for ideas...)
Imagine a customer who faces allergies when exposed to poor air quality. This is not uncommon for city dwellers around the world. This customer could benefit from using an Alexa Skill that helps identify the air quality at a location on a particular day. By using data from OpenAQ as an example, the skill could help customers learn about the most recent air quality measurement in their area. A customer could ask: “Alexa, ask [NAME OF SKILL] what the air quality is in [CITY NAME]?”. You can check out this recent machine learning blog on predicting the impact of weather on urban air quality using Amazon Sagemaker.
This is a great example to illustrate that customer would come back to use the skill more often because not only does it make information more accessible, it also provides relevant information to them on a day-to-day basis.
As a reminder, your Devpost submission is due by September 17th at 5PM, ET (Find out what time that is in your city) but you have until October 1 to get your skill through certification. Good luck everyone!
If you have any questions about the hackathon, please post on the discussion forum.