SXSW 2016: Messaging Bots

My most recent post on LinkedIn cross-posted here.

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This past weekend, I had the pleasure of moderating the “Testing Your (Aritificial) Intelligence” panel at SXSW. On the panel, we had Dror Oren from Kasisto (vertical messaging assistant for banking), Alex Lebrun from Facebook M (horizontal messaging assistant) and Dimitra Vergryi from SRI (runs the speech research lab). Much of our early discussion was regarding the future of assistants in-part drawing on some of my experiences from SRI and Tempo AI but we quickly moved to the hot topic of messaging bots and the role of AI.

If you’re not familiar with messaging bots, I encourage you to read “The Bot Paradigm” from The Information as well as Jonathan Libov’s super-aggregation of messaging UX design. In short, messaging (communication) represents our primary workflow (day-to-day) and as exemplified by applications like WeChat, messaging can be used to facilitate other experiences (eg shopping, sending money, customer support).

This new modality has the disruptive potential of replacing all app experiences and if so, would represent an opportunity as significant as the iPhone App Store was to publishers.

Some panel takeaways:

  1. Horizontal (general purpose) assistants are hard! Users do not know what to ask nor remember what primary use case to use the assistant for. In addition, the technical complexity of the system is exponentially greater in that you have to deal with out of context and extreme queries. For example, Alex mentioned they no longer intend to support “pet delivery” in FB M since that’s a use case out of their machine automation wheelhouse.
  2. Standalone messaging apps don’t stand a chance. I found this feedback interesting in that they are advocating that messaging bot experiences need to be built upon the existing large players (eg WhatsApp, Slack, Facebook Messenger, Google Hangouts etc). This intuitively makes sense since the App Store is no longer a great growth channel.
  3. App bot discovery and the ultimate app store for messaging bots is still unclear. Having played with the app store within FB Messenger, I found the workflow to be sub-par. Alex and Dror suggested displaying related app bots as you type within Messenger (in-context). This certainly would be an improvement at  smaller scale but will remain a challenge if we have 100s of K of messaging bots. The ultimate design of the APIs that the messaging apps provide will be critical.
  4. Personas are necessary for messaging bots to. I found this interesting in that personas can certainly lighten the mood and set expectations but can also be tiring when you want expedience. See slides I presented on mobile AI/UX design at SXSW a previous year (wish I had a video of the presentation with the voice-over).
  5. Machine-powered conversational NLP is a very long-way out. Dror felt you must go vertical and thus their focus on the banking sector. Alex said that the FB research team described conversational NLP as level 10 technical difficulty and AlphaGo as level 1 (my FB post on the AlphaGo AI milestone). All of the panelists also acknowledged that building a data corpus (collection of queries/conversation) for training is the real challenge in any AI application.
  6. Key initial industries to be disrupted by messaging bots were financial services, customer service, commerce and travel. Not surprisingly, some of these categories are identical to what we saw with early vertical Siri-clones.

In summary, messaging bots represent the next growth channel and will spawn new billion dollar opportunities; excited to see it happen!

Author: mobileraj

Mobile!

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