RJP: Voice interfaces are very powerful and will play a role in our future. RA: Can you tell me more about the Google home version of eBay ShopBot?
All boats will rise with the tide as we continue to develop more human-friendly AI capabilities. Once the AI is capable of reasoning and empathy, it can be expressed through a variety of end points or interfaces, such as IoT devices in your living room or in your car, as well as a chatbot. Put simply, a chatbot is one of many endpoints for AI. Chatbots powered by keyword search engines will obviously not benefit in the same way. RJP: If chatbots are powered by the same AI that is investing in creating algorithmic human consciousness, they would benefit from these advancements. RA: A big theme we’re hearing discussed around AI is the idea of empathy and emotional intelligence – how do you think that can come into chatbots? This two-pronged approach will help accelerate our path toward automation and self-service delivered through bots. This is not a challenge exclusive to AI, but rather a combination of automated customer service technology and a more comprehensive knowledge base that covers the majority of issues that customers face today. RJP: In order for this to occur, we need to arm our commerce systems with more self-service information, to enable our customers to find answers on their own. RA: If Gartner predicts that by the year 2020, 85% of customer interactions will be managed without a human, what do you think needs to improve to make that viable?
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We are learning very quickly how to recognize the world’s products visually. At eBay, we have billions of descriptions, billions of images, and billions of items. We’re seeing growth here, but it’s still the early innings.Īlso, computer vision algorithms continue to improve the more things they can 'see' and learn from. We need to develop a relationship with each customer, a personalized experience that will strengthen the more a user interacts with the bot this requires deep learning, in addition to natural language understanding.
This method does not build trust or confidence between a bot and a user. The vast majority of bots today simply pass keywords from a user's message as input into a search engine, which then returns search results in a messaging window. NLU is vital to capturing shopping intent, from which a rich shopping experience can occur. RJP: True artificial intelligence is the key. RA: How are you seeing the technology becoming more intelligent? This will help tremendously with the exposure and more casual adoption of bots in messaging.īots are still a nascent platform for commerce, but the more bots learn from user behavior, the faster they can evolve and adapt to create a seamless and natural experience.
Organizing a directory, catalog, or bot 'store' not unlike an App Store is on the horizon. Also, we want to make it easier to discover and learn that great shopping bots exist on these large platforms.Īs the bot industry matures, so too must the platforms that support them. The messaging canvas where chats occur can be laid out in new and different ways to support product browsing when shopping versus using a single column flow for sequential chat messages. This is an area where improvements can be made. The user experience and interface of messaging platforms were not initially built for search, discovery or purchase. RJP: There is definitely still work to be done by both the messaging platforms and brands to ensure bots are advancing, to make the conversations with shoppers meaningful. RA: There’s been a fair amount of criticism that such bots aren’t the best user experience, what are your thoughts on what needs to improve?
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