For the past 15 years, every content management system and enterprise knowledge base has been built around some version of Search Engine Optimization (SEO) to make it easier for readers to find the valuable data hidden in your documentation. But that's a passive approach to making your data discoverable and relies on the hope that the answers your employees and customers need have already been documented and published.
First impressions matter, which is why Customer Success Teams are crucially important to the success of your company. They are often the first non-salespersons your customers meet, and they make sure that customers are satisfied and, well, successful with your solution.
There are lots of chatbots on the market today, and many of them are (supposedly) designed to help with customer support. While each type of support bot has its pros and cons, none of them are truly ready to fully replace human support representatives. Understanding that reality is key to implementing your support bot the right way.
The best customer support representatives don't just know the best answers to common questions, they know how to find any answer to any question -- and they depend on an internal knowledge base to do it. Unfortunately, too many modern knowledge base solutions let down the support reps that rely on them.
Chatbots are being sold as the artificial intelligence cure-all for every business problem under the sun -- except sales. No one seriously believes that A.I. can replace actual humans when it comes to closing the most complex (and profitable) sales deals.
Artificial intelligence is making headlines by helping companies like Google, Facebook, and Tesla sell better products, but A.I. can also help any company -- including yours -- sell products better. And it starts by empowering your sales enablement team.
Join Rob May, the CEO and Co-founder of Talla, and Brooke Torres, founding team member and Director of Marketing at Talla, for a weekly look into AI trends and the future of AI in the enterprise. We will be joined by exciting guests in the space including: CEO's of AI companies, VC's, data scientists, and more.
We've argued before that generalized artificial intelligence is generally unprofitable (and maybe impossible), but there are some real-world examples of just how hard it can be for A.I. to get competent at even very narrow tasks. For example, you'd have no trouble asking your friend for a restaurant recommendation, but it's really difficult to teach A.I. to perform the same task well.
Everyone from Elon Musk to the late Stephen Hawking to an entire research institute are warning about the dangers of an A.I. apocalypse, where some real-life version of SkyNet or HAL 9000 will rise up to wipe out pesky human life. This is probably alarmist, not just because general artificial intelligence like we see in the movies may be impossible, but because -- for the foreseeable future -- there's no money in it.