While I promised not to spam you with too many blog posts, it seems I’ve taken restraint to a bit of an extreme in the past year. Thanks for your patience!
One reason I’ve been quiet is that I’ve been working on another project which finally shipped. I’m pleased to let you know that we now have a LinkedIn Learning (formerly Lynda.com) class: Customer Service Using AI and Machine Learning.
Service / Support and technology are both passions of mine, and it was fantastic to be able to combine them in this course. I took my first AI class back in 1985 and my first class on Neural Networks and what we would now call Deep Learning in 1986. It’s taken a long time for these technologies to make a real impact, but now that they’re here, they’re changing everything—starting with service and support.
Some Key Takeaways
I learned some fascinating things while working on this course. Here are some key “a-has” for me:
- You can buy, not just build. Not too many years ago, people who wanted to deploy emerging digital technologies generally had to build their own—off-the-shelf wasn’t an option. That has changed. In the course, I have brief sections on ML-powered search engines, chatbots, and QA tools. These tools are really working in production and at scale. And new vendors are coming out with more AI-powered functionality, such as escalation prediction, all the time.
The days of needing a tame data scientist and dedicated development team to do anything in this space are over.
- But there’s no free lunch. Even the best tools require investment to work. Most forms of machine-learning want training data—lots and lots of training data. It needs to be high-quality data, too. These technologies are different from traditional software in many fascinating ways, but the old adage applies as much as it ever did: “garbage in, garbage out.”
This also applies to the content technologies like search engines and chatbots serve up, too. Without a strong foundation of knowledge management, like Knowledge-Centered Service (KCS®), you can have incredible technology cleverly delivering unusable or out-of-date content. Get your knowledge house in order before deploying these tools.
- Innovators have plenty of room to innovate. Despite the fact that there are now tools for applying AI to the business, leaders in this space are still creating their own solutions designed for their specific strategies, business models, and pain points. As an industry, we’ve come up with many fabulous solutions, but I think there are still many more to be discovered. And, as toolkits and practices continue to improve, I think the potential business benefits from AI and ML are limited only by our imaginations.
Because custom-developed solutions will be a way to gain competitive advantage, I spend time in this course on a frequently-overlooked topic: how do you work with data scientists and developers to bring your concepts to production? Too often, we’ve seen data scientists assigned to support organizations leave because they didn’t get good requirements from the business. I bet the requirements were there, but their effective communication wasn’t. We provide specific techniques for bridging that gap.
What Marketing People Call the “Call to Action”
I admit, I had a real blast putting this course together. The LinkedIn Learning team was fantastic to work with, and they did everything they could to help the course sound and look good. (Who knew I’d ever have a hair and makeup person looking after me?)
Many of you work for companies that have a Lynda / LinkedIn learning account. If so, the course is free to you, and it’ll only take a shade more than an hour to get through, broken into bite-sized segments. If your company doesn’t have an account, buying courses à la carte is straightforward and cost-effective…and maybe even something you can expense. So, I’d love it if you took the course or shared it with someone who might be interested. And even more than that, I’d love it if you joined in the discussion on LinkedIn or here. Share your own experiences, ask questions, correct mistakes, and add your voice to the conversation…please!
https://www.linkedin.com/learning/customer-service-using-ai-and-machine-learning/
and on Lynda.com:
https://www.lynda.com/Business-tutorials/Customer-Service-Using-AI-Machine-Learning/2254038-2.html
That’s a wrap!
