Webinar Q&A Recap: Dark Matter Data and AI-Driven Innovation: the Future is Here

December 14, 2022

Kate McBee

Category: Customer Experience, Customer Retention, Customer Success as a Service, Customer Success Maturity, Customer Success Operations, Customer Success Strategy

Speaker: Lisa Palmer, Chief AI Strategist at AI Leaders

During this session, host Peter Armaly was joined by Lisa Palmer, Chief AI Strategist at AI Leaders, to discuss how artificial intelligence will impact the way jobs are performed, how products are developed, and how service is delivered over the next few years. Lisa’s insightful answers to the audience’s questions are outlined below.


Q: Where do you see AI playing an important role in Customer Success Platforms?

A: I absolutely see an important role there. I think that being able to elevate the level of information that you have as CS professionals at the moment that you’re interacting with people, there’s just no way that doesn’t create value. And artificial intelligence has the ability to help us to scale, to look at data at scale in ways that we’re not able to do from a human perspective. There is so much data that impacts what happens with Customer Success that it’s absolutely an area that is right for AI to make a significant impact.


Q: What are your thoughts on ChatGPT / (GPT-3, 3.5, and 4) and how CS can utilize this technology? Are you aware of teams already implementing this technology in CS playbooks/motions?

A: Should people start experimenting with it? Absolutely. This is a fun tool. It helps people to understand what the power, capability, and possibilities are of this kind of AI. That’s, you know, obviously alive and well, that’s why you should try it out. I encourage people to try out any of these large language model-informed tools so that they really start to understand and can visualize and experience firsthand what is possible. I think that you should go and play with this, or play with something like Dolly Tool, you know, to create generative AI art. If you’re somebody that likes code, go out and play with a code generator. There are all kinds of artificial intelligence tools for free online to help you craft emails, to help you to craft quick paragraphs. There are all kinds of these tools that are available to you, that you could already be using whether or not your employer is heavily embracing them or not, to better serve your customers.

So, should you try it? Absolutely. I encourage you to do so, and these are the kinds of things that we have the opportunity to use to help evolve your organization. Help to evolve the way you’re thinking about solving problems and addressing processes that you have through some of these tools that are in the wild. So, with regard specifically to this particular language model response, it’s fun to play with. You’ll probably be shocked at some of what it will tell you when you try it out. It’s obviously got all the markers of the challenges that come with AI that learns based on data that it gathers from the wild. So, there are challenges with it around, you know, discrimination and different kinds of bias and things that happen because humans are biased. And the main thing, the main data source that’s feeding it are, you know, interactions with humans and information that’s coming from humans. So, take that with a grain of salt. I certainly wouldn’t use it without heavy edits, but it’s also just a really powerful way to learn and experience firsthand what’s possible.


Q: Recommendation engines are BRILLIANT! Have you seen successful ways or tools that can do this effectively outside of the product itself? Obviously not ideal – but what’s possible?

A: So, I have seen these, and I have to be honest, I haven’t done a search of the markets, particularly in the CS space, and you know certainly we could talk about that later here but, as far as is it possible? It absolutely is possible. So imagine the same types of recommendation engines that are used to identify what you will likely buy on Amazon, for example, that same kind of technology from a recommendation engine perspective can be leveraged with a CS framework in mind, so a lot of these technologies that have started in retail are proliferating into other parts of businesses, and are becoming part of Operations, and not just High-End lofty goals, but really becoming embedded in daily enterprise, B2B operations.


Q: What recommendations do you have for companies (SMBs) that don’t have access to data scientists? How can they leverage the data they have with an AI approach?

A: Oh, I love this. I love this question, love the perspective. So not everyone’s going to have data scientists, that is just the reality. There are a lot of different situations available today. So there is a concept, Data Science as a Service, you can actually buy. You can gain access to data engineering, data science work, and data analytics work, you can gain access to those things in a subscription manner, which is fairly new but is really gaining ground. And we are seeing a lot of organizations in the SMB space look for this kind of Data Science as a Service approach. So, there are opportunities out there. There are also a lot of these freebie tools, depending on what it is that you are trying to accomplish. If it is making emails at scale, videos at scale, writing or pulling together information. There are just tremendous tools at zero cost today that you could use.


Watch the recording of this webinar to catch up on the full conversation!