Despite all the hype and promotion from bot enthusiasts, many bots (or automated response agents) have struggled to find an engaged and returning audience. After measuring millions of conversations across several hundred bots on Facebook, SMS, Kik and Slack on Botmetrics, we’ve gained key insights on what separates the best bots from the also rans.
As artificial intelligence algorithms infiltrate the enterprise, organizational learning matters as much as machine learning. How should smart management teams maximize the economic value of smarter systems?
Business process redesign and better training are important, but better use cases – those real-world tasks and interactions that determine everyday business outcomes – offer the biggest payoffs. Privileging smarter algorithms over thoughtful use cases is the most pernicious mistake I see in current enterprise AI initiatives. Something’s wrong when optimizing process technologies take precedence over how work actually gets done.
Developing deeper relationships with our readers is a big priority for HuffPost. So when Facebook Messenger announced its bot platform in April 2016, we were excited.
The platform offered us the opportunity to connect with our audience on a one-to-one level in a way that was actually scalable. No one has completely mastered the space yet. But in our trials, we’ve learned a lot about how brands can use bots to interact with their audiences. If you’re creating a bot, here are a few things you should keep in mind.
The introduction of payments in messaging apps could affect chatbots in the same way that the introduction of in-app payments affected the App Store. Without integrated payments, the chatbot ecosystem is akin to iOS apps before Apple introduced in-app payments, Livingston notes; while there were some useful and engaging experiences, it was difficult for brands to drive revenue.