Bernard Slowey: Forget Chatbots! Smart Brands Are Moving to AI Agents!

Summary

Podcast Summary: Marketing Trends - Episode: Bernard Slowey: Forget Chatbots! Smart Brands Are Moving to AI Agents!

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Introduction

In this illuminating episode of Marketing Trends, host Stephanie Postols, alongside collaborator Lauren Wood, delves deep into the transformative world of AI agents with Bernard Slowey, Senior Vice President of Digital Customer Success at Salesforce. The conversation centers around Salesforce's groundbreaking tool, AgentForce, and its pivotal role in reshaping customer experience and marketing strategies.

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Bernard Slowey’s Journey in Tech

[00:00] Bernard Slowey: Bernard begins by reflecting on his extensive career in the tech space, starting as a part-time tech support agent at AOL during his college years. He shares anecdotes about the dramatic technological advancements he's witnessed over the past decade, highlighting the shift from physical CDs to cloud-based solutions and the evolution of customer support from face-to-face interactions to sophisticated AI-driven systems.

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The Transformation of Technology and Introduction to AI Agents

[02:25] Bernard Slowey: Discussing pivotal moments of technological transformation, Bernard likens the advent of AI agents to previous breakthroughs like the internet and teleservices. He emphasizes how AI agents, such as Salesforce's AgentForce, offer 24/7 availability, access to vast content repositories, and the ability to handle interactions using natural human language, marking a significant leap from traditional chatbots.

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Defining AI Agents vs. Traditional Chatbots

[06:46] Bernard Slowey: Bernard clarifies the distinction between traditional chatbots and AI agents. While chatbots operate on predefined scripts with limited responsiveness, AI agents like AgentForce leverage large language models trained on extensive, company-specific content. This allows them to provide more accurate, personalized, and context-aware responses, enhancing the overall customer experience.

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Applications and Use Cases of AgentForce

[08:46] Bernard Slowey: Expanding on the capabilities of AgentForce, Bernard explains that beyond answering queries, AI agents can perform actions on behalf of customers. For instance, resetting a password or processing refunds autonomously represents a paradigm shift from merely conversational interfaces to actionable assistant roles, thereby streamlining customer interactions and driving efficiency.

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Salesforce’s Implementation of AgentForce: A Case Study

[15:52] Bernard Slowey: Bernard recounts Salesforce's rapid deployment of AgentForce on their help portal. Within just four and a half weeks, Salesforce transitioned from a traditional support system to an AI-driven interface capable of handling over 450,000 conversations since its launch on October 11th. This swift implementation underscores AgentForce's flexibility and scalability, even within the complex ecosystem of a massive B2B enterprise.

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Lessons Learned: Balancing Hard and Soft Skills

[28:15] Bernard Slowey: A critical insight Bernard shares is the initial oversight in training AgentForce solely on hard skills—focusing on factual, technical responses—while neglecting soft skills such as empathy and appropriate messaging. Recognizing this, Salesforce integrated soft skill training into AgentForce's programming, enabling the AI to handle sensitive situations with the requisite empathy, akin to a human support agent. This dual focus on the "head and the heart" has been instrumental in enhancing AgentForce's effectiveness.

Notable Quote:

[28:24] Bernard Slowey: "We were treating it like an old school chatbot... Instead it was like, no, no, you're smart. We went back into AgentForce and coached it just like you would coach a human employee."

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Metrics and Measuring Success

[30:19] Bernard Slowey: To gauge AgentForce's performance, Salesforce employs various metrics including resolution rates, customer-confirmed resolutions, conversation handoffs to human agents, and abandonment rates. Transparency is a cornerstone of their strategy, with real-time metrics displayed publicly to build trust and demonstrate efficacy.

Notable Quote:

[34:45] Bernard Slowey: "Transparency is key for trust. So what we've done is down the bottom, you can see down here we actually have a live ticker to show how many AgentForce conversations."

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Impact on the Human Workforce

[57:49] Bernard Slowey: Bernard addresses concerns about AI replacing human jobs by emphasizing that AI agents are designed to augment, not replace, human employees. For example, support engineers can focus on more complex issues while AgentForce handles routine queries, thereby enhancing productivity and job satisfaction.

Notable Quote:

[60:20] Bernard Slowey: "One of the things we've been really trying to do is, like, with our support engineers is making sure they're part of our AgentForce launch."

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Future of Customer Experience and Cross-Functional Collaboration

[50:37] Bernard Slowey: The integration of AI agents necessitates greater collaboration across marketing, sales, and customer support teams. Bernard envisions AI agents acting as a cohesive layer that bridges departmental silos, ensuring a unified and personalized customer journey from onboarding to support.

Notable Quote:

[52:44] Bernard Slowey: "Now you have this agentic layer that goes across all of them... it brings the relevant agent into the conversation."

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Unique Perspectives and Contrarian Views

[62:00] Bernard Slowey: Bernard shares a contrarian belief that while data is foundational, it isn't everything. He advocates for the importance of intuition and gut instincts in decision-making, especially when data might not capture the full context or underlying motivations behind customer behaviors.

Notable Quote:

[63:05] Bernard Slowey: "I don't think data is everything... sometimes I think the best decision goes against what data tells you."

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Advice for Customer Experience Leaders

[69:46] Bernard Slowey: As the conversation wraps up, Bernard offers a poignant piece of advice: true customer obsession requires continual engagement and understanding of customer interactions. He emphasizes spending time reviewing customer feedback and interactions to genuinely grasp and enhance the customer experience.

Notable Quote:

[69:46] Bernard Slowey: "You gotta be spending time even in the digital space... look like, I think to be truly customer obsessed, you have to be looking at your calendar and going, how many hours a week am I actually talking to customers or reading something that was interaction with them?"

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Closing Thoughts

The episode concludes with Bernard highlighting the continual evolution of roles and responsibilities in the age of AI, stressing the need for new skill sets like prompt engineering and AI management. He underscores the collaborative potential of AI agents to not only enhance customer support but also to drive innovation across various business functions.

Final Quote:

[65:19] Bernard Slowey: "Everything will change... some things will change completely. Other things will augment, other things will be a little bit different, you know, and. But I think everything will change."

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Conclusion

This episode of Marketing Trends offers a comprehensive exploration of AI agents' role in modern marketing and customer experience. Bernard Slowey's insights into Salesforce's AgentForce provide valuable lessons on implementation, balancing technical and empathetic responses, and fostering cross-functional collaboration. For marketers and CX leaders alike, this discussion serves as a crucial guide to navigating and leveraging AI advancements effectively.

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For those interested in a deeper dive, including metrics and real-time data on AgentForce's performance, Bernard invites listeners to visit Salesforce's help portal and explore detailed blogs and resources available.

Transcript

[Bernard Slowey]

We were treating it like an old school chatbot. Don't do this if that do this right. Instead it was like, no, no, you're smart. We went back into AgentForce and we coached it just like you would coach a human employee. And that solved that problem. What we forgot to do with AgentForce is we trained it on the hard skills, but we didn't focus on the soft skills. And we talk about this as the head and the heart. We now have a digital workforce that will augment our human workforce.

[Stephanie Postols]

You're like the original case study and companies can just copy paste your strategy.

[Bernard Slowey]

I think we have these moments in time with technology, like every years or something. There's just something that transforms it.

[Stephanie Postols]

What kind of company is this for? I'm thinking at least as like a small business owner. Is this something that a small business owner can use?

[Lauren Wood]

I think it solves so many of the problems that we've been seeing in the customer experience space.

[Bernard Slowey]

It's this transformational moment that I think every company is like, wow, how do I enable this? And how can I use this for my customers?

[Stephanie Postols]

What if your marketing campaigns weren't just reactive, but proactively shaped by real time customer behavior? And what if AI could tell you exactly when your customer is ready to buy? Welcome back to Marketing Trends. I'm your host, Stephanie Postols, and in this episode, I did something a little bit different. I crashed one of our other podcasts called Experts of Experience, where they dive deep into all things customer experience. But don't worry, our host, Lauren Wood, was a willing accomplice. We got to sit down with Bernard Slowey, who's the SVP of digital customer success at Salesforce, and we talked about the tool that's taking the world by storm called Agent Force. So if you're wondering how AI agents can actually impact your marketing, not in some hypothetical way, but in how you build campaigns, nurture your customers, and drive real revenue. This episode is for you. All right, let's get into it.

[Lauren Wood]

Brynard, welcome to the show. It's so great to have you.

[Bernard Slowey]

I am very excited to be here. Thank you so much for having me.

[Lauren Wood]

So we want to kick it off by taking a trip down memory lane and talk a little bit about your history and what you've seen over the past wow, decade plus in the tech space. And I know you started your career in customer service as a project manager at aol, is that correct?

[Bernard Slowey]

I actually started as a tech support agent for AOL and worked my way up.

[Lauren Wood]

The project manager agent?

[Bernard Slowey]

Yeah. Yeah, I Was a tech support agent part time when I was in college. That was where I started.

[Lauren Wood]

Amazing. And so you've seen a lot of change. Can you tell us a little bit about what you've seen since then until now?

[Bernard Slowey]

Yeah, you made me feel old, by the way, when you said that, which kind of made me laugh. But it has been a while. It has been a while. Yeah. God, it's incredible change actually when I think back on it, because I started as I was in college and I needed a way to fund my college activities. I worked for AOL in the evenings and on weekends and I used to be a support agent helping people set up AOL on their computers. And even if I think back to that, like they had CDs to install. So now it's like even just thinking of a CD and trying to put it in and, and it just like at the time that was, that was normal. Right. That's how everyone did anyone. Like the cloud didn't exist back then. Everything was mainframes, it was local. And so yeah, it was, it was an interesting job because I would have people, I couldn't see them. So now we're all used to video calls. That feels really normal to us. Like it was literally just me talking to someone and then trying to describe their problem to me and me try to describe steps for them to do. And so even if I think back to that and where we are now, just on this call. Right. Or I think about my son and he uses, you know, FaceTime to call home to my grandparents in Ireland. Like, it's just amazing the change in technology that we've seen in that timeframe, both in our personal lives and also in enterprise, commercial and our ability to.

[Lauren Wood]

Support customers as well. Like if you think about being on the phone, walking them through a physical action of putting a CD into a computer to download, now it is just a whole other level of automation and ease as well. And so I'd love to hear, you know, AI agents is the big conversation. We're going to talk about AI agents a lot today because of AgentForce and all the incredible work that Salesforce has been doing. What makes you excited about AI agents, especially as we look at it in the context of where we've been even in the past 10 years.

[Bernard Slowey]

Yeah, I think we have like these moments in time with technology, like every 20 years or something. There's just something that transforms it. Like if you think about the service industry, it started face to face. You had to walk into a physical store or whatever it was and so you were limited in the hours of operation of that store, right? Then we had tele service, right. All of a sudden you could phone someone, right. And that was a big transformation in technology, Right. Seems kind of weird to think about that now. But it was, it meant people could be available longer hours. It wasn't just the opening hours of the store. Then we had the Internet, right. And then, so then it all became very much self service. Like every single company in the world has a portal that you can go to and try and find out about their product. And everybody starts in Google, everyone searches, they go to YouTube, they try and figure it out themselves, probably before they even come to you or come to your company. And so now we have this moment in time which like Anyone who used ChatGPT, that first moment you used it, you kind of went, wow. You know, it's these moments in times where it just transforms technology. And so now you have this way these agents that are going to enable you to have 247 availability. You know, it's always there, it's always available, it's trained on all of your content. You don't have to like predefined these specific scenarios. It has access to everything that you want it to have access to and it's incredibly accurate. And the other thing that's amazing is like today a lot of our interactions are text based, but voice is coming at us fast, you know, so you're going to be able to deal with these AI agents. And it's not like a robocall. It's actually, you know, natural human language. It feels very, very natural. So you think about that in the service injury space, it's like I'm going to be talking to an agent that's going to be helping me solve my problem or help guide me on onboarding, whatever that. So it's just, it's this transformational moment that I think every company is like, wow, how do I enable this and how can I use this for my customers?

[Lauren Wood]

I think it solves so many of the problems that we've been seeing in the customer experience space. For example, when we call, I mean this is still to come, but when we call a company and we have to then choose the button or choose, choose who we want to talk to and go through all of this. It's so laborious and now we are just easing so much of that friction through AI and I'd love to just take a quick step back to make sure everyone understands what we're talking about when we talk about AI agents. Because this is still new. Can you define it for us?

[Bernard Slowey]

Yeah, I think people still trip up a little bit on like chatbots and agents and kind of what's the difference? And I think we've all had an experience with a chatbot on a company's website and generally it tends to be a bad experience. Chatbots, historically, like, like you had to define the logic that was in the chatbot. What I mean by that is you would write a dialogue, you would literally say, if this, then that, if this, then that, if this, then that. And if you ask that specific question that that chatbot was trained on, it did an okay job. It had no emotion, no intelligence. It just helped with that thing. But if you went off script, if you asked it something that it wasn't trained on, it was a terrible. It is a terrible experience. Right. So now with these AI agents, something like ChatGPT is trained on the Internet, right? So it's incredible the access it has. But what we do at Salesforce forces. We give you the capability to train agent force on your content corpus. So instead of me having to suddenly like write all of these dialogues, I can literally give this large learning model access to whatever content I want to give it access to. And so now we can answer any questions straight out of the gate related to that content. But where it gets much more powerful is that's called unstructured content. At Salesforce, we also have a lot of structured content. So a lot of information about our customers that's stored in something called our C 360. Right. So you start to use that structured content and you can personalize the experience. I know who Lauren is. I know the product she bought. I know she just recently became a trailhead ranger. And so you can really personalize this into the agent experience while it's given answers. That's just something you could never ever do before. You know, it's pretty incredible when it.

[Stephanie Postols]

Comes to AI agents. I hear the pieces around adding in the customer data and you've got your own LLMs that you can work with. But to me, how I understand them is they're more goal oriented. Like they have somewhere like a problem they can solve and they can head that way without building out chatbots and adding in information. Like it's really built off. Like you said, if this, then that only the scenarios that you built out. But is it correct to understand that AI agents is more just like goal oriented?

[Bernard Slowey]

So today with our implementation of AgentForce, it's Q& A conversational, where you ask it a question and it comes back with an answer. And that's kind of how most of us have experienced ChatGPT. But where we're moving to is the agent can actually action on your behalf. And that's super powerful. So if you think about the example where you ask it, how do I reset a password? Right. Generally it will come back where you do steps A, B, C and D. But imagine when we can actually do that on your behalf, right? So there's information we can get just to verify you are who you are, and then we reset the password for you. That's just a very simple example. Like in banking worlds, it's like issuing a refund on your behalf. A retailer could be as well. So they can actually do action as well as just conversational Q and A. And that. That's a game changer.

[Lauren Wood]

It's like having an employee, it's an AI employee. And I think that that's the big shift that I'm seeing when we talk about agents is it's no longer just a tool, it's actually capable of so much more and making decisions on its own. Which is also wild to think about.

[Bernard Slowey]

Yeah, yeah. We think about it a lot as like, it's a digital employee. Just the way that we have human employees, we now have a digital workforce that we need to empower and that will augment our human workforce. Right. Allows us like a good example as well, is these. These models have language capabilities in them, right? So suddenly we can go to all of these other languages that we might not be in today because we just wouldn't have the budget to invest in headcount to do support in these languages. Now you have it in English and you can use these large learning models to do real time translation. So, you know, Lauren could be in Japan as an example. That's going back and forth with our agent. That agent was trained in English, but it's able to translate and go back and forth with you and, you know, no difference. You know, that's pretty incredible as well. Is these real. These language translation models just open up so many avenues for companies.

[Lauren Wood]

Yeah, it's wild. I actually, a quick example of that is Airbnb. I'm an Airbnb host and I've had guests from other countries come and stay at my place and I talk to them in English and sometimes I get an email in another language, but in the chat it shows up as English. And so I've been like, what is this? And then I went in to look at it and I was like, oh, that's what they're doing is real time translation between the guest and the host and it's like, wow, that opens up so many more possibilities. So when we think about agentic AI and bringing this into businesses, what is the opportunity at stake for companies to start using agents as soon as possible?

[Bernard Slowey]

It's interesting that I meet with companies a lot to talk about what we're doing and like everyone's really interested and everyone wants to get started. But in a lot of cases companies are afraid to get started. A lot of cases they want to do internal implementations before external. When I say internal, what I mean by that is like maybe you have an agent beside your support rep that's helping your support rep, which is a great use case. Right. But they're nervous to go external because they're worried about things like hallucinations or is it going to say something that like oh no, my company's going to be associated with this. And so that's one of the things I've really been helping companies and customers with is like I showcase what we did to say, hey look there's, there's, there's rules, there's guardrails you can put in place so that it only answers certain things. And so I definitely, I see people want to get into it, especially companies, but I do see an apprehension and nervousness on like what happens if it goes wrong. And for us, for that is like we have in Salesforce. It was, it was a design principle for us was that Agent Force is backed by humans. And so it's if it can't solve you easily go into the conversation with a human. It's actually pretty slick. It like Agent Force Force leads the conversation. Lauren, the support engineer joins the conversation. She can see the history of the conversation with Agent Force. She gets an AI summary of it so she can quickly start with, okay, I'm going to continue on from here. And so I think that's an important design principle to help companies is it should always be backed by humans. Otherwise you're going to dead end, you're going to dead end people and frustrate them.

[Stephanie Postols]

What kind of company is this for? I'm thinking at least as like a small business owner. Is this something that a small business owner can use or is it right now really for enterprise companies who do have a lot of data and a lot of things that they're trying to.

[Bernard Slowey]

To automate, I think it's the full spectrum, Stephanie, which is kind of what's amazing. Like if you're a small business company Today like you probably can't have like a support phone number, right? And like, you know, because you're not going to invest in that headcount, you've other things you need to be worrying about, right? And so suddenly you have the ability to have support. Right? You could have a digital agent on your website that's maybe answering some of your top questions from your FAQs. And if it can't answer, maybe it submits like an email, a case where one of your humans can come back afterwards. But I think it goes all the way from like SMB to massive enterprise. Now obviously the use cases are different than how enterprises are going to think about it, but I actually think it helps give SMBs a leg up because suddenly now you have this digital workforce that you can leverage to help you go faster.

[Stephanie Postols]

It seems like companies will be built off of this model like of agent force and having a bunch of agents, it's like a whole different way of building a company. But even when thinking about these different marketing leaders that I talk to and the teams that they have, like they're thinking about team structures different. And I think actually startups might have a really great advantage of like I have no employees currently, but I can have some digital ones. And now all of a sudden I have five or 10 departments that are all, you know, these digital employees.

[Bernard Slowey]

Yeah, yeah, totally. It's, it's crazy. Like it's, you know, it's often sometimes that you, you know, you have that advantage when you're new is that you can build around this technology that's there versus having legacy hold you back a little bit.

[Lauren Wood]

I see this a lot in my consulting work. Cause I work with a lot of startups who are in that position where we kind of have a blank slate or it's not too us to take a step back and redesign how we're approaching AI, especially AI and cx. And then I also work with organizations that are much larger who it's, it's challenging. Like we have to really change our fundamental structure in order to now work with this AI and bring it into our existing system. It's just more complex and it takes more time and intention. Although I will say I think the intention is important no matter where you're implementing AI and really how you're doing it and what you want it to be doing. But there's definitely an opportunity for earlier stage companies to start off with AI as a foundational principle.

[Bernard Slowey]

Totally agree.

[Lauren Wood]

So I'd love to talk a little bit or a lot actually about salesforce's agentic AI journey. Because Salesforce dove into agentic AI quite early on and developed Agent Force, which I know you were lucky enough to be customer zero of. And I want to get into that story and understand one what was it like really bringing in an agent workforce into your team? And then we're going to get into the lessons and the learnings and all that good stuff. But first, tell us just what was it like starting to use them?

[Bernard Slowey]

Yeah, it's kind of crazy to think about. Like, we have our big sales conference, Dreamforce, around September every year, and we had Dreamforce last year, which we pivoted to Agent Force as a company. Like, Agent Force just kind of happened like this pro. Like, you know, as I said, this technology exploded. We were very lucky that we were working on an incredible product that could leverage that. So our whole Dreamforce conference was pivoted to Agent Force, and. And I was kind of standing there, I was in that conference, and I was like, wow. If anyone should be an amazing use case of this, it's what me and my team do, because we're responsible for our help portal at Salesforce, which is where customers go when it gets like 60 million visits a year. It's like the second biggest portal at Salesforce, and it has a lot of content. It actually has 740,000 pieces of content. And it does a good job. People find what they need. But we always heard two common pieces of frustration. It's too much content. I can't find what I'm looking for when I need it quickly. And so that was the opportunity with Agent Force, right, is you can now have this conversational experience, ask it a question, get the answer you want, and go back and forth. So I challenged my team. I came back from Dreamforce and I said, let's get this up and running in October. So that was four weeks it took us to. That shows how easy this product is. Because if you think about Salesforce, right, It's a massive B2B enterprise. Hundreds of products. You know, it's complicated. And we. We launched on October 11th. So it was just over. I think we were four and a half weeks that we got it up and running, and we launched it on our help portal, which was pretty incredible. I've been in. You know, I worked for Microsoft for 15 years. I worked for GitHub. I've been in lots of technology companies. And to get something like this launched so quickly just showed the flexibility in the product.

[Stephanie Postols]

Did you tell anyone that you were doing this or did you, like Run on the down low where you're like, I'm just going to see what I can make. And surprise, no surpr.

[Bernard Slowey]

Guys, we're live. Here you go, Mr. Benioff, here, a great example for you now. No, we did tell people we were doing it. I, I felt like we were the perfect use case. I think service is a great use case, right? Like, because there's a, there's a, there's a clear roi, right? It's like, hey, if we can have customers solve with this agent, then, you know, more of them are getting the solution, what they need, etc. So you're seeing a lot of companies as they look at these agents. Service is kind of the number one use case. And it's not to say there's like, marketing's use cases, sales, there's hundreds of other ones. But I think companies are kind of honing in on like, okay, service. Something where I could really see this thing having an impact. And so that's why I felt we, we should be, you know, my leader, Jim Ro, I know you had on the show before, he always challenges us on to be customer zero. You know, use our own products, be a showcase for own products so that I can go talk to customers and say, here's how we're using it. Here's the mistakes we made, here's the impact we're seeing from it. And so we really wanted to be the customer zero of aging. For us, that was our goal, which.

[Lauren Wood]

I think is generally, if, if you can be your first customer, you always should be. Just as a principle when it comes to customer experience, because that allows you to really learn deeply what your customer is going to experience.

[Bernard Slowey]

Totally. Totally.

[Lauren Wood]

So, like, launching in four weeks is insane, especially if you think about how new this technology is and how complex the Salesforce system and help center is as well. Can you give us a bit of an insight into, like, what you launched? I'm assuming it wasn't like, the whole thing. I'm assuming you kind of took off a piece and said, okay, we're going to launch this.

[Bernard Slowey]

Yeah, it's interesting. So, like, if I reflect back to that, like, I was so nervous. Like, I was so nervous. Like, I had major anxiety because this was like, it's going to be available for people to use. And, you know, once people have access to something, they're going to tell you what they think about it. And so we, we went live. We started small, actually. We went live to what we. A cohort of authenticated custom. What I mean by that was a small Percentage of customers who are logged into our help portal could see the experience. So they kind of saw like an Ask Agent Force kind of on our documents. So we felt comfortable doing that because we wanted to see, well, how does it perform, how many people click on it. Like all your classic, it's like a funnel, right? You're seeing who lands on your portal out of that number. Who engages with Agent Force? How much did Agent Force resolve? How many went through to the human? So you had all of these metrics that were measuring and. And so we started pretty small. But then we actually, as we started to have reviews internally in Salesforce, we realized we were actually going too slow and that we just needed to get out there and open it up so that we could start to get feedback and learn. I'm going to screw up this quote. But Reid hoffman who started LinkedIn, he has this great quote on like, you should never be happy with the first product you release, but you should release it. And so that was the mindset. I was like, it's not going to be perfect. It's going to be things that people aren't going to like. But because it's out there and because it's live, we're going to quickly iterate and improve on them things versus if we keep it back here forever, we're probably going to be too slow. And so that was our mindset was like, it's good enough, it's not perfect and it will never be perfect by the way. We're going to have to constantly keep iterating. It's good enough. Let's get it out there. So then we exposed it to everybody. So anyone who goes to help.salesforce.com, you'll now see this beautiful full screen experience of Agent Force. You can access it, anyone can access it. Whether you're logged in or not. You can go ask it a question and it will help you on a question related to Salesforce.

[Stephanie Postols]

So I'm thinking about a lot of these big companies who probably listen in to this show. Marketing trends. I'm wondering how like did you have people pushing back on you being like, do not launch this. Here's why this is a terrible idea. Like where they're seeing the risk being like so large that they were like, bernard, this is a terrible idea. Cause I'm sure in other companies this would be happening and like how to push back against that risk adverse.

[Bernard Slowey]

It's interesting is that the hardest part actually came was Marc Benioff tweeted about it and posted on LinkedIn that we were live and he got a lot of comments. There is LinkedIn and his Twitter post. And I was literally like going in, reading every comment. Every day I'd get up and have my morning coffee and I'd open it to see what new comments were.

[Lauren Wood]

I can't imagine the anxiety you were feeling in that moment.

[Bernard Slowey]

Some of them are brutal. Some of. Honestly, I didn't feel great about my Salesforce career that first day because we had a lot. Like, we have a very engaged community at Salesforce. We have our trail blazers, our MVP program. Like we, we are incredibly lucky. The engagement we have from comm. From our community. But with that, they'll tell you what they think. And I like that. Right. But there was times they were asking it questions and the answer coming back wasn't a great answer. Right. And you know, there was, I'll give you one example which is like someone had tweet, put a screenshot underneath them. They asked a question about integration with a competitor product and we kind of said something about the product and then had a. A link to that company's website, which is not a great situation. Right. I was like, okay, I'm definitely gone. This is the end of my career. And I'll just. This is like one of the learning moments of agents, by the way, is like what we did then is you go into. We have something called Agent Builder, which is where your prompts live. So this is like you teach Agent Force. There's something called the Global Instructions, which is like a topic where you teach Agent Force the world it lives in. So you tell it you're part of Salesforce, no code, right. It's all in natural language. And you tell it. I want you to speak in this voice and tone. These are the things like don't want you to speak about so you can set guardrails. Like maybe you don't want it to ask questions on your CEO as an example. So you put all of this inside the Global Instructions. So when we saw that happen, we were like, oh crap. Jumped into our Global Instructions and said, do not talk about our competitors and listed every competitor was problem solved. Great. The very next day, and I don't mind, the very next day we saw a case where someone asked, how do I integrate this competitor's product with Sales Force? We have great content on that. But what happened? Agent Force didn't answer right. Because we'd given it this strict guard rails of what not to do. So this was the learning moment for us. We went back into Agent Force and We coached it just like you would coach a human employee. We told it, we deleted that guardrail and we said, listen, you're a Salesforce employee, you're a customer service agent. Put the best interest of Salesforce in everything you do. That was what we wrote. And so we taught it. We taught it to think. We were treating it like an old school chatbot. Don't do this if that do this, this right. Instead it was like, no, no, you're smart. We just need you to think this way. And that solved that problem. And so that was a huge learning for me and my team. It's like this prompt design, this prompt engineer. And it's a discipline now that's in the industry. And it's like it's really, really need to think through it on what you write and how you write it.

[Stephanie Postols]

This is like such a new space we're in where people are still just trying to like figure out prompt engineering for ChatGPT. And they're like, oh, maybe instead of just like, give me the answer to this. It's like I should say, pretend you're this and think about it this way. Like the more context. And so it's no surprise that of course you're like, oh, yeah, maybe we should do that here too. But it's such a fast paced world right now to keep up with. Are there any other funny moments like that that came up or just things that happened while you were rolling this out that probably are relatable to other people who would be going through this process?

[Bernard Slowey]

I think maybe coming back to Lauren's question, which I didn't do a good job of answering on of risk averse versus pushing. We definitely had people internally. I used to, we obviously, obviously Slack Salesforce, it's a massive product for us and so we all live in Slack. I would get slacks every single day from people in the company giving me examples of where it didn't do a good job. A lot of the times they were people that were very knowledgeable in Salesforce products asking it a very detailed question. And a lot of the times the problem wasn't agent force. The problem is the content in the back end that it's trained on. If you don't have good content, right, if you like, it's only as good as the knowledge it has access to. And so like, and people will go, and they try it with Chat GPT and they go, ChatGPT gives me this answer. I said, yeah, but Chat GPT has access to the whole Internet so it can pull an answer From Reddit, it can pull an answer from some blog somewhere. And the risk of that is hallucinations, right? That's what scares companies on, on these agents is like, so ours is one of the one mentioned this earlier on. But Agent Force, you limit it to your own content set. So with that, sometimes if it didn't have the right content, it didn't do a good answer. So we had to work on updating our content. I think it actually exposed to us areas where we didn't realize we didn' content.

[Lauren Wood]

I mean, that's such an important factor, which I actually think a lot of people who are approaching or rolling out AI, building it into their, their systems, we all need to do it and people are taking different approaches. But the thing I keep hearing time and time again is that your data is critical. The information that you're feeding to the AI is critical. And it's a very large and complex, complex thing to think about because we have, it's almost like we have like a. All of our stuff is like strewn everywhere and all of a sudden we have to organize it in a way where someone can come in and actually like intake it and use it. And I'm curious to know your thoughts on that piece. And like, how did you go about organizing your data so quickly to then allow Agent Force to use it? Or had you already had a totally clean house and none of that had to happen?

[Bernard Slowey]

No, no, I don't think anyone has a clean house. We have had. We have an advantage at Salesforce that we have this other product called Data Cloud. And with Data Cloud, like people always ask me where we started with agentforce and what I tell people is like, it's like when you have a new employee start, what do you do? You give them access to data, right? You give them content, you train them so that they can start to be upskilled and be able to do their job. And so Data Cloud allowed us to take all of these different data sources, right? These knowledge articles, these products, and actually hydrate them all into Data Cloud. And then that gave Agent Force, this foundation, it's able to access all of this data in Data Cloud. That's the unstructured data. And as I mentioned earlier on, we're now going to give it access to structured data as well. So I think I had a bit of an unfair advantage where I had access to Data Cloud because I work in Salesforce, but when I talk to customers, I'm like, this needs to be part of the solution. Like, you can use it without Data Cloud. But if you can have a repository that can contain all of this data and can bring it all in, it can normalize it, it can standardize it, then you have a huge advantage as you go live in these agents.

[Lauren Wood]

I mean, it's really the strength of your agent at the end of the day. Like, as you were saying, it's not going out into the Internet to find answers. It's using the information that you provided to it. And that's the beauty of it. And also it means we need to do that extra legwork to make sure that the agent has what it needs.

[Bernard Slowey]

We learned this kind of the hard way. So we're a couple of months in now, and our, our Agent Force implementation still feels a little bit robust. Like it responds to you, it gives the right answer. And so what we learned is what else do you do when a new employee starts in a service world? Right. Yes. You train them on the hard skills. Right. Like, do they have the information to answer these problems? But you also train them on the soft skills. Right. The way that you deliver a difficult message. Right. If you're a support engineer. Like, we spend a lot of times on that soft skill training. And so what we forgot to do with Agent Force is we trained it on the hard skill, but we didn't focus on the soft skills. And we talk about this as the head and the heart. We were very much focused on the head, the brain element of it, and not enough on the heart. So now we're doing a lot of work where we're actually taking the training that we train our support engineers on, and we're using that around some of the prompts for Agent Force. So just think about it as we're giving Agent Force access to that training so it has much more of the soft skills on how it delivers its message. It's kind of crazy when you think about that, but that was been a big learning for us.

[Lauren Wood]

Yeah. The thing that I'm like kind of mind blown by is you're taking a training that you give to humans about soft skills and you're able to train an AI agent on the same content.

[Bernard Slowey]

You're just teaching it in certain ways. Like, like, like we always have this good example. Like if, if someone comes to us, let's say with a severity, one issue, right. Like, let's just say Salesforce is down. Doesn't happen very often, but some companies can have. Things are down. The last thing you want is the agent going back and forth with you on potential ways to solve that problem. You want it to go, oh my goodness, you a sev1 I'm so sorry to hear that. We're going to get you through to one of our support engineers and they're going, you know what I mean? Like that's an example where Agent Force needs to get out of the way quickly but it needs to have a lot of empathy in that situation. Right. And so that's the example of what we mean. You don't want it to be like kind of robotic and try and answer that problem. It's like, no, no, get out of the way. Be very empathetic to it. And that's how you would teach a human employee to also react in that situation.

[Stephanie Postols]

One thing we haven't talked about yet is like the success that you saw once you implemented Agent Forest. I mean one, I'd love it if you like if you had a before and after. Because I'm trying to visualize what it was like before when customers would go on there and ask a question, what it's like now to really understand what it looks like and then what happened after. How many cases are getting solved with AgentForce? Tell me a bit of the stats.

[Bernard Slowey]

So this visual that you can see, this was our health portal in I guess September last year. Right. And so it looks like pretty much every single company in the world has some portal like this. Right? You can come to it, you could search on it, you could access our content, it has videos, places to learn, etc. And you can go in and create a case from it. So that's kind of what it looked like back then. And so as I said to you earlier, unfortunately the problem with this is people struggled to find what they were looking confirm. Right. Especially if you are having a problem, you need an answer quickly. You know we hear that in all of our research with customers is like, hey, if I'm having an issue, you need to be able to answer me quickly. Right. And so let me now show you what this looks like now. So this is help.salesforce.com now. And so what you can see is it's a completely different experience. It's a full screen experience of Agent Force. So you can go in and ask it any question. As I mentioned earlier, it doesn't matter whether you're logged in or not. You can engage with agents, Agent Force. And what we've done as well is you asked me like how do we determine the success? Right. We believe transparency is key for trust. So what we've done is down the bottom, you can see down here we actually have A live ticker to show how many Agent Force conversations. So since launch, you know, we've had 450,000 conversations with Agent Force. So since October 11th, that's a pretty huge number. And then you can see we also try and show our human tickets as well, because we want to try and show people. But what I want to show you is just something a little bit cool here now. And I go, you can click on this, here's how and what that will do. It's going to show you all of our metrics and how we measure success. So this is our customer zero page. And you'll actually see there's a video there that some of me and my team are in to talk about our implementation. But what we show you is you can actually look at all of our data and you can go back to any date since we launch. What you asked earlier on is like, how do we measure success? Right? And so what we look at that is think about this as a funnel, right? Someone has a conversation with Agent Force, right? It comes back with an answer and you go away. And we consider that resolved, right? So you asked it a question, you came back with an answer and you go away. You don't. When I say go away, you don't want to create a case with a human. And so you can see our resolve metric is like mid to high 80s, right? But we also get asked questions, but is that really resolved? Like, how can you determine that was resolved? Like maybe the question I just went away. And so what we've implemented now is we have something called customer confir resolution, which is in the flow of the conversation. We ask the question at the end of the conversation, hey, did this resolve your issue? Yes or no? And on that customer confirmed resolution, right now we're about 76%. So that's a really good data point for us that like all of these conversations that you're having at the highest level, it's probably about 80 something. And then customers are telling us it's about 76 when they answer that question. The other two metrics I just wanted to show you so I can help explain it, is we also look at this thing. This is the Agent Force conversation handoff. So you can see that for percent. So that is that week, 4% of customers who engage with Agent Force got handed off to a human support engineer. So that was that kind of flow that I was telling you about. Like, it's really critical to us that it's an easy flow. The other metric, which is interesting for us is we have this thing called Abandon. And let me explain what Abandon is, is you can kind of see the Ask Agent Force in the bottom right hand corner. So certain percentage of customers click Ask Agent Force, they open it up, up and they don't ask it a question. And we're really interested on this and why is that happening? And we think some of this is to do with kind of UX UI where people are like, oh, that's one of them old school chatbots. I don't want to engage with that. Right. And so they don't ask it a question. And so that's something that we're working on is how do we kind of pull more people into the experience. But that is kind of the metrics that we measure today. And what's pretty cool on this site by the way, is we have lots of blogs on how we did it. You can. There's Jim Rote up there, you all know very well. And so we're very transparent. Here's all of our information, here's how we launched it. Go look at it and see what you think yourself.

[Stephanie Postols]

Yeah, that's. This is awesome. I love the ticker numbers on the homepage. I just feel like it's kind of gamified. I'm like, I just want to sit here and watch it go up and see how many humans are involved and. Yeah, that's fun.

[Lauren Wood]

And can we also talk about the sales, the sales strategy here? I mean, you're literally showing like, we are using this and here's the results that we are getting in real time time. I think it's something like this point about transparency is so critical. It's always been critical. But when we talk about AI, it is ever more important because customers, whether they're B2B or B2C will trust you more if you are transparent with when you are using AI versus when you are not. And we see that in the data. And I just want to. I just think it's a really great, really great website. You did a great job, dude.

[Bernard Slowey]

I gotta admit to Ticker was not my idea, but I love it. And at first I was like a ticker. Why would. Because like it's going to hit like half a million soon, you know, and you're like, wow, like that's a pretty incredible number. And then, yeah, to your point on transparency, Lauren, like if we're not using our own products and we're not showing like, why would a customer buy it? You know? So it's this like this trust piece of. Okay, Salesforce is Using it. Here's all the metrics we measure. And like, we debate the metrics as well. Like, people are like, well, is that really a resolution rate? And like, yeah, you're right, we need to do better there. And so we introduced that customer confirmed resolution, which is people actually telling us, yes, you solved my issue, you know, and so we're just like any support leader in the world, I have the same pressures they do to kind of show ROI and all of that sort of thing. And so we're transparent. Here it is, here you can see it.

[Stephanie Postols]

I love that you guys are like, you're like the original case study and companies can just come in and like copy paste your strategy. And by you doing all this legwork, I mean, I think about back when I worked at Google, we were always trying to figure out metrics of like, which ones mattered. And we used to get excited about ones. And then people would come in and be like, actually you don't want that metric to be high, that's bad. That means you're having a problem. And like, there was always so much debate. And so the fact that you guys did this first and you already have like a whole entire, like, basically you can copy this entire strategy and just do it with another company. But I'd love to hear who else has done this, like, who else has copied this.

[Bernard Slowey]

I love what you said there, Stephanie, because one of the other things that we like had these long debates on is that handoff to human. Internally we call that escalation rate, which is a real support mindset metric. And you say that to people externally and like they're like, what's escalation? Is that a bad thing? And so at that whole page you saw, our marketing team built that page. So we partnered heavily with our marketing team on like, how, how can we tell this story easily to customers so they can go use it? And kudos to our marketing team. Handoff. The customer is way better than our human, is way better than escalation rate. But the thing I want to tell you about, like, we had a long debate that escalation rate was down at like 1% and sometimes it was 2% and now we're at 4% and people are like, oh my God, what's going on? And it's actually a 4 because it was too hard to get from agent force into a support engineer with too much friction in the process. And so we want it, we simplified that process. You can literally come and go talk to a human, talk to an agent, whatever that might be, and it will create your case and send you through. And so we think that escalation rate will probably get a little bit higher. And we're okay about that because that means it's a good experience for our customers, which is the most important thing we're doing. But it's interesting as people can get driven by metrics. You know, it's like, oh no, it's at 4%. It's like, yeah, but that's a good thing, you know. And so, so that's just like, as you talk about that Google and that like debate and metrics, we do that a lot internally as well.

[Lauren Wood]

I think that the, this piece is something that so many companies struggle with, especially from. As a CX leader, I would always say let's make the experience best for the customer, but it's not always the most cost efficient way because it's better if we don't have a human talk to them. If we just make the customer figure it out themselves or if we just have the AI do it, it's a cheaper option, but it's not the best experience. And we all know as consumers that when you want to speak to a human and you can't speak to a human, there is probably nothing more frustrating.

[Bernard Slowey]

So I share this story with my team all the time. Like when I was kind of earlier in my career at Microsoft in Dublin and Ireland, we had this project that was literally called Automate and Eliminate. And if ever there was a name on a project that tells you you're doing the wrong thing, Automate and Eliminate was that. And like I remember I won like a gold star or some monthly award at Microsoft for driving up this number of Automate and Eliminate. And what we do, we just made it really hard to get to the human. We put lots more clicks in the flow and so we saw people drop off and we were high fiving each other. So it's my example of like whatever leadership defines is like these are the metrics, these are the things. Sure you can do things to do that, but it can have terrible, terrible impacts.

[Stephanie Postols]

I think it'd be fun to hear maybe some lessons that you've gotten from either Microsoft or any previous companies that have influenced what you're doing with AgentForce and how you're thinking about like we were talking about with metrics or building out a team or really anything you're working on. I'd love to hear a bit about that.

[Bernard Slowey]

Even if I think about my role, I'm the SVP for digital success and someone called me recently in A webinar, a unicorn, which I didn't know how to think about that. But like what it is is that not many companies have a leader on a team that are 100% focused on the digital experience when you think about service, right. A lot of the times like I got passionate in this in my career because like I used to lead Windows support from Microsoft, massive support footprint, thousands of support engineers. But I always say like no one gets up in the morning and says I want to contact support, right? They're all going to go online. And so like I started to really kind of hone in on digital and spend a lot of time there. And then kudos to Jim Ro. He created a function and I joined to come lead it. And my team wake up every single. We wake up in the morning thinking about how can we improve the digital self service experience for our customers. That's our day job. It's not an ar. Like I find in many companies they have people that run functions and then like it's like, oh, and also you should think about digital, you know. And so, so that's the big thing for me is you have to have people that are invested in it. You know, I have a team of over 100 people now that are working on like Agent Force is one thing we work on, we have other things. But they're all waking up in the morning thinking how do we improve the digital experience for our customers? Whether that's, you know, that's not just support motions, we also think about success motions, right? You've bought our product. How do we help you onboard? How do we make sure that you're getting, you're getting the value from that product so you renew, right? Like that's critical. Like support's kind of that moment. Something goes wrong and I need help. But we also need a great digital journey to help you on. And that's what my team 100% focuses on and that's been a big learning in my career is like you need people that, that's their day job, that's all they worry about.

[Stephanie Postols]

So I'm naive. Is this not normal to have this kind of role? Like is this role not. Oh, okay, I'm like this sounds like perfectly like, yes, it makes sense. We should have it.

[Bernard Slowey]

Yeah, yeah. No, it's funny like there's, there's a, there's a LinkedIn community now for digital success and there's like digital success webinars and like that didn't exist and a while ago, you know. And so, so I get asked to attend these things and talk a little bit about my role and Salesforce, that's where the unicorn thing came up because I think I'm the only SVP that's on digital success, which made me, made me laugh. But no, it's not. It's not something that unfortunately for a lot of companies, it's on top of someone's curve. Current job.

[Stephanie Postols]

Yeah. I just heard a quote in my interview the other day where someone's like, the things that look contrarian and crazy today will be commonplace in the future and so this will probably be very common, I would assume in the next year or two.

[Bernard Slowey]

Yeah, I love that.

[Lauren Wood]

The way that we can utilize AI in customer success is still yet to be seen in many use cases. And Salesforce is really, I mean Salesforce has pioneered customer success period. So it makes sense that you are getting to lead that function, the new wave of what customer success really, really means. I'd love to hear some examples of other clients that you've been working with other than Salesforce yourself to really utilize agentforce and how that's been taking place.

[Bernard Slowey]

Yeah, it's actually interesting that site I showed you. If you scroll down to the bottom of that site, you'll also see other customers that are using it as well. So I feel like a majority of my job now is going talking to customers about what we do. So that wasn't my job a couple of years ago, but we have some great examples. Like OpenTable is a big company that's using AI agents now. So we share with them what they're doing and they kind of share. Cool. I also want to learn from these other companies by the way, like how are you implementing and what are you doing? What learnings can I take from you? So OpenTable is a huge one, Vivint. I actually have to my house their security alarm system, camera system. If you go to their website, you're going to engage with an agent. Remarkable. Which probably behind me somewhere literally have.

[Lauren Wood]

One that I'm using right now.

[Bernard Slowey]

They're the best. Incredible. Incredible. In the best. Amazing. You go to their website to engage with support and you'll engage with agent force. And so they're just kind of three top of mind examples. Like there's huge companies that we're working with right now. I can't kind of get into the names of some of them that are getting ready to do implementations. And so that's where me and my team come in a lot because we share what we did, our lessons learned and our mistakes. And so that they can get ready to go live. So you're going to see a lot of companies going live with Agent Force over the next couple of months. A lot.

[Stephanie Postols]

Are there any key questions that you keep getting asked, especially among these, like larger companies coming in? Are there themes where people are like asking similar questions?

[Bernard Slowey]

Yeah, well one of them you all touched on earlier, which is a kind of around the data hygiene. Right. Like we actually there's this new, new terminology, my team are talking about it recently, which was a new one for me called data collisions, which is like you have data that, you know, content is a good example where maybe you've couple of articles on something that's similar and maybe you're using like an acronym name or something and the agent can't pick the right piece of content. It's a collision of that content. And so, so that comes back to this kind of data hygiene piece that you asked about earlier. It is really important that you have the right data. You're, you know, we, we've spent a lot of time actually culling older articles. Right. Stuff that's not relevant anymore so that the agent's not trained on it, you know, so that's definitely a very, very common one. One, the other one I would say is the experience from agent to human. We talk about that a lot like, because in our experience it's like you have a choice, you can have the human join the chat so you know, they come in, it's a seamless experience or maybe you don't have the time at that moment so you can create a case to like have someone come back to you at a time that works for you. And so we spent a lot of time designing that experience. And so a lot of customers are like, how did you do that? Show me how it works. And so that's another one that we spend a lot of time on as well.

[Stephanie Postols]

Do you have to go through expectations with them? I know when we talked previously you were kind of talking about how a lot of people come in and they just expect AI to work right away, this better be perfect, I better fix all my problems. And you had a good analogy around like would you treat your employee that way in week one? Be like, what did you do? Why'd you mess that up? You got that thing wrong.

[Bernard Slowey]

I can't remember the name of the bias but as humans we have a bias for machines, that machines should always be correct. And the example, the great example is like self driving cars. Right? Right. Like we're afraid to let them onto motorways because there's like 000 whatever percent chances that we'll have an accident. Humans have accidents all the time. Right. So self driving cars are actually a safer option than a human. Right. But we don't want that to happen until it's near perfect. Right. And so it's similar with some of these agents. It's like people expect the answer to be perfect all the time. And it might not be and it might not be for a multiple reasons. Like we talked about content, if the agent doesn't have access to the right content, if that content's wrong, then your agent's going to be wrong. You know. And so, so there's so many reasons like, like there's so many reasons behind it. Like I gave you the example earlier on of like if you don't like the prompts aren't positioned the right way then it might respond in a different way than you want it to. And so there is that expectation setting and that's why I think that experience agent to human is critical because you need to make it easy that someone can go oh actually you know what, I just want to go true to the human.

[Lauren Wood]

How have you gone about creating the guardrails beyond just the here's the content to pull from. But especially as we think about the more like empathetic skill set of the agents. How do you like set values in place with the agent and how have you made those decisions around what to train it on?

[Bernard Slowey]

It's interesting actually. We spent a lot of time as a team just thinking about, about like what do we not want it to answer questions on. And so one example is we have a simple guard rail that you should only answer questions on Salesforce products, which I think every company would do. Right. Like it's funny, I look at, I look at our conversations every day. I go in and read some of the ones and I can see like we have a sediment analysis that runs on our conversations that tells me whether they're positive, neutral or negative. And I can go look at the negative ones and see what, what it was. And so like some of the negative ones people ask like how do I cook pasta? And so like agent Force didn't respond and I'm like wow. Like, and I think it's because like people think ChatGPT and so they want to go ask it anything. And like no, we've confined it into the world of please don't answer anything, just answer questions related to Salesforce. You know, so that was one. It seems obvious but like that's a, that's a design choice. If you want, you could give like these things access to the Internet and say, hey, go, go answer all of these things. Other things. It was funny like we were sitting down going, God, we don't want it to try answer questions on Mark Benioff. Like, we don't want people to be asking it questions about our CEO. And it comes back and says, you know, like, because, because that's not ours. It's a support Persona. It's a support site that's not what it should be for. So we set guardrails. If someone asks about one of our leadership team, it will point them to our investor relations page. You know, so it's really interesting. Like it's, it's an exercise you need to do at your team. Where do I want it to answer? And then probably more importantly, where do you not want it to answer?

[Lauren Wood]

And I think that that's, you know, it's one of those steps that has to be talked about before implementing. So many companies want to just dive right in. But yeah, this is one of those things. It's like make sure your data is clean and then also be aligned on where you want this agent to play and where the boundary is. Where's the fence to the playground?

[Bernard Slowey]

Totally. And the other thing I'd say, Lauren, is like companies kind of treat it like a traditional software release, right? Like, hey, we're going to go do all this work, I'm going to bang release this thing. And like it's not a one and done. It's a constant refinement. It's a constant looking at the performance. Why was it doing things this way? Like, did we not have content for that? Do we need to adjust our prompts? Because like we said earlier, it's an employee, right? And it's grown, it's getting better all the time. Like ours is far from perfect right now. It'll get better and better and better over time. So you got to be thinking like that. It's not an old school traditional software release. It's a digital employee. And you gotta be constantly refining it.

[Stephanie Postols]

I feel like this is a perfect segue, knowing the timing that we have left into more of that. Like the closing the loop between sales, marketing, cx. Cause right now it feels like we're entering into a different world when it comes to businesses. And it used to just be, you know, you've got your awareness top of funnel. Your customer comes in, you sell to them, hopefully retain them. Customer support is sometimes, you know, either in the middle of that or at the end depending. Now it feels like everything's kind of merging together and more conversations have to be happening between these teams like you just mentioned. Bernard, when people have an issue, you might want to come back and change the model. Okay, this happened over here when someone was coming into the flow. This now needs to be adjusted. How do you see the world going forward with this cross functional collaboration space that we're in?

[Bernard Slowey]

Every company in the world has this problem of they show their silos to their company customers. You know, you have marketing, that's all about lead gen and like how are we driving the pipe? Etc and okay, now you have sales, we're going to create that and we have a customer. Now you kind of have your post sales function support success and they tend to be siloed and suddenly you now have this agentic layer that goes across all of them. Right. And so like an example of that is like I see with companies that they struggle to pass the relevant information between the different departments. Like I'll give you a very simple example. Example. Sometimes a success team doesn't have the relevant information of why the customer bought the product. What do I mean by that? Sales sold it for a certain reason. Right. They sat in a room and said, hey, you buy this product and it's going to give you this feature, it's going to give you this roi. They sell and they're gone. I'm not, this is not Salesforce, by the way. I'm just saying this is what a lot of companies tend to think about it. Right?

[Lauren Wood]

Seen it many times.

[Bernard Slowey]

Yeah, yeah, right. And then suddenly it's like customer, customers are okay. Like, and so your success team needs that information. Right. So that they can now figure out how do I do a tailor onboard for Lauren to make sure that she gets that value of why we sold it. Right. Or why we marketed it originally. Right. And so now you have this agentic layer across the mall that's able to see all of this data. It's able to see what did marketing do, why did we sell it, what was the business outcomes the customer said they wanted and now I can tailor. Like we get really excited with agents is that today our agents really about the support Persona, but we're going to light up these other Personas like a success manager. Right. It would help you with your onboarding. Right? It would. Even today our agents text, we're getting ready to launch voice. Right. Which is pretty incredible. Our agent would ring you and say, hey, you know, I see you, you just signed up for Salesforce. I See, you bought it for these reasons I'm here to help you on board. Let's schedule an onboarding session. You know, like that's something today that not every customer might get because maybe they're a smaller customer or something like that. So suddenly these agents gives you this ability, this digital workforce to do all of that. A huge scale.

[Stephanie Postols]

It seems like too this is an amazing time for CX leaders and marketing leaders all to also be at the product leader table to be able to influence products that are being developed because they have a lot more intel and everyone's going to know more about the customer and more about what sold them and why they're excited about that than ever. And so it seems like there's going to be a lot of collaboration opportunities that bring marketers and CX and other leaders to a table that maybe they were not really at previously.

[Bernard Slowey]

Totally. And one of the conversations we've been having Stephanie is like the. I think the danger with some companies is you could go create agents for all of them divisions. You could have a sales agent, a marketing agent, a support agent. And for us we want to make sure on our customers experience it's agent force, right? So it's one agent but it might be behind it. You have an army of agents that are skilled in certain things. You could have a renewals agent, a success agent, a sales agent, a support agent. But the depending on what you ask it it brings the relevant agent into the conversation. So for the customer, I'm just talking to agent force. In my world like companies will call it different things. I'm just talking to that company's agent. I don't realize there's all these different agents behind it. So you suddenly, because what companies do today is like they show their organizational seams, right? I always like my example with this is portals, right? Companies will have a support portal, they'll have a, you know, sales portal and they've already in Salesforce. We did it and we're working to try and bring all of them together. The danger is you do that with agents as well is you build all of these separate agents versus leveraging the capability that it can work across it all.

[Lauren Wood]

So then we have to train our agents to be cross functional.

[Stephanie Postols]

That's I'm wondering how like how Lauren, do you train these agents and people to think differently about building this structure when you're like okay, don't learn, don't think about anything I've ever learned before. Now think different, do different. Like how do you know you can.

[Bernard Slowey]

Still have so you still have like your, your subject matter expertise and your company should still build your sales agent, you know, and your support team should. But what you have with Agent Force is we have this agent to agent transfer. And so what it should do is based on the question Stephanie asks it. So let's say like you ask it like maybe you have a licensing question or a pre sales type question. In that scenario, Agent Force is able to recognize that question is related to this domain. I'm going to bring in this agent to answer that question. It's more about the technology recognizing what the customer's intent is and then bringing the relevant agent into that conversation.

[Stephanie Postols]

Okay, that, yeah, that feels a little easier. So instead of me being like, oh, I have a. This feels like it's a customer support question. I don't need to know that as the customer, I just need to go be like, help sos, this is what I need, blah, blah, blah. Like I'll just voice it into the system and then behind the scenes they'll know like, oh, actually that's a finance thing. She's having billing problems.

[Bernard Slowey]

Coming back to if we're using structured data and let's say you are a customer, right. And you're logged on, we're then able to start to use some of this information as well to know what we should come back with. Right. Like maybe we can see, okay, Stephanie's day two with our product, right. She's, she's onboarding, right. We need to use our onboarding aids. Like, so there's, there's ways we can use our structured data as well, like to help us and understand where you are in your journey and what you're trying to do.

[Lauren Wood]

I just wanted to bring it back to a real life example here that this is sol. This is a pro, A real life problem that this is solving. When we call up a number and we wait on hold and then we get through and we end up being on the, the wrong number. And then they're like, oh, let's transfer you to this other place and you can wait on hold over there again, which is the most frustrating thing in the world. And this is the beauty of agentic AI is that we, the consumer or the customer no longer needs to deal with that because the AI knows what it is that we're asking for and can directly put us in touch with the right agent where we don't have to wait on hold because totally.

[Bernard Slowey]

And it knows who you are, Laura. That's the most important. Knows who you are. And it's Tailored that experience based on who you are.

[Stephanie Postols]

I'm very excited by this. I was just on a chat line with Adobe trying to cancel my, like, crazy enterprise account that I accidentally signed up for two years ago. And it. I still don't even know if it's canceled. I was on with, like, four different chatbots and they kept being like, but actually, do you want to buy this? This thing? I'm like, no. And then I'd come back to it and be like, oh, that never got canceled four times. And I think it's still a problem. And they didn't know enough information about me and they kept asking me stuff. I'm like, I don't know. I think you should know this. I think I'm your customer. You should know this about me.

[Bernard Slowey]

So they probably do, but they just don't want you to cancel.

[Stephanie Postols]

They just don't have Agent Force yet. It's a problem.

[Lauren Wood]

So I wanted to talk a little bit about the impact on the humans in the loop here and how this is. I mean, obviously AI is having a huge impact on business. And with new employees, these AI employees, it's going to impact the existing employees. And the thing I keep coming back to is what are the skills we need to be learning to really work with AI now that we have these. These new types of friends that we're working with day in and day out?

[Bernard Slowey]

It's interesting. So one of the things. I'll come to your question in a minute, but just I think one of the other things is this, like, fear of what's it going to do for my job, et cetera. And so one of the things we've been really trying to do is, like, with our support engineers is making sure they're part of our Agent Force launch. So we use our support engineers to look at the performance of Agent Force to help go. Actually, what would you have done in that scenario? Because they have more expertise in our products than anyone else in the company, maybe outside our engineering team. So since day one, we've included our support engineers so that they feel really part of it. And, you know, hopefully it takes away some of the volume that's probably easier for them, and they're left with the more complex scenarios. We're always going to need, like, incredible support engineers. So that's the first thing I'd say on your question. It's been interesting. As I was having this conversation with my team the other day, we just hired a prompt designer slash engineer. And, you know, that role. I don't know how far back you'd go, but it didn't exist. There was no such thing. Right. Like, you know, and so, and I was even laughing because I was super curious on what type of applicants we will get. I was like, God does really have a know when people put like 20 years experience or something and there's no possibility of 20 years experience. So I was like, I wonder like who's going to apply for this? We actually got a rock star. I can't wait for her to start. But like to your point, there's these new roles starting now. We have a director of our LLM operations. You'd have told me two years ago I'd have a director of LLM operations. I'd be like, what are you talking about? Is this English you're speaking? And so I do think it's up to people to be start training on some of these like depending on what your interest is. Like, you know, UX designers. There's now this prompt design which is a new flavor of UX design, you know, and then there's understanding these models and more about them. So I think it's, it's really exciting. And I said it to my team, it's like, wow, look at us. We're blazing a trail. We're creating these new opportunities. There's opportunities for existing people in my team are getting more deeper into it. It might create new roles for them. So it's kind of cool to be honest with you on some of these roles that are opening up.

[Lauren Wood]

Yeah. I mean with any technological innovation, new roles have been created and of course right now a lot of people are afraid, oh, is AI going to take my job? And as you know, your job to be today probably in some cases. But there's going to be whole new jobs, whole new careers, whole new departments maybe that are even created. I know I've been talking to a lot of people about the new role of the AI manager, the agent manager, like as a human needs to now manage this team of agents and train them and guide them and coach them.

[Bernard Slowey]

Yeah. And I think the, I think the organization point is I feel in a lot of situations they augment the human. You know, I was just on a call earlier today. I have a, a team, a video production team. So we have a Salesforce support YouTube channel and it's an amazing news, like the second fastest growing YouTube channel in Salesforce. And we have a lot of things happening in Salesforce which shows you like how much it's grown. But they were talking to me now about how they're Using AI for their video scripts, you know, and something that would have normally taken, you know, hours and days is now taking minutes, you know, so it's not that it's replacing their role, it's allowing us to go faster and to implement more videos at a more, you know, quicker time frame. And so that's great because it means we're getting more out there for our customers to self serve on. So I think you'll see more examples like that where it's like it's augmenting my job, it's allowing me to be more efficient at my job, and then.

[Lauren Wood]

It frees up time for more valuable activities as well. I mean, I think about, especially in the realm of customer success, if we can spend more, more time listening to and thinking about our customer instead of doing operational, you know, even scheduling meetings and things like that, that just like eats up our time, we are much better off thinking about our customer, spending time with our customer, listening to our customer, and then bringing that insight back into the organization. Because those human to human interactions, that is what AI will definitely never be able to replace. Right. So let's lean into that.

[Stephanie Postols]

So one of my favorite questions that I ask of all my marketing trends guests who are all normally CMOs of the Fortune 500, Fortune 1000, is what's something that you believe that very few agree with you on?

[Bernard Slowey]

I love this question, by the way. I'm going to steal this question and I'm going to use it with people when I'm interviewing them because then I think you'll see how their brain thinks. I have to think about this a lot, by the way. So kudos to you. You had me kind of like, oh my God, what will I say to this one? The thing I learned that on is like I don't think data is everything. And I think a lot of leaders in marketing support whatever it is, they just live in data. Now I live in data. I look at data all the time, but sometimes I think the best decision goes against what data tells you. And so like I always push my team is just because our data is telling us something like, is that really what's happening? Doesn't often tell you the why, the why someone chose to do something, the why they made that decision, the why they went that way. And so I challenge people. Of course you should have data. Data is foundational to everything you do. I live in scorecards and metrics, but I really challenge people sometimes. It's about going with your gut instinct, you know, and saying, hey, no, I think this is the right idea. I've been doing this for a long time. I'm going to go against the data and I'm going to try to do something myself.

[Stephanie Postols]

Have you done this recently? I'd love to hear a story if there's is something that comes up around this.

[Bernard Slowey]

I don't know if I have a perfect example, but even coming back to Agent Force, like, you know, Data probably should have said don't release Agent Force to the whole world at once, right? Like it's, it's doing an okay performance. Our resolution rate is X or whatever. You know, you look at the data and you're like, let's just continue to go slow. Let's just iterate and over time we'll get it better and better and better and then we'll go large. And if I'd have made that decision, I don't think we would be where we are now now because we went big. Even when the data told us it wasn't doing an amazing job, it was doing a good job. It meant that suddenly it was exposed to more people and there was more pressure on me and my team to make it better, faster. And so that's like, that's an in. Like where it was like it forced us to go faster by going against the data and releasing it to everybody.

[Lauren Wood]

I think about this often. I'm so glad that you share, share this take or this opinion, Bernard, because going back again to what AI will not be able to replace, it's our intuition. And it is so important that we hold onto that intuition and if anything, strengthen it. Now that we have AI doing a lot of the logical thinking for us where we can say, is this right? Just because the data says it doesn't mean that we need to do it that way. It is insight, it is information. We can take that, but we still need to use our human critical thinking skills to decide is this the right way to go?

[Bernard Slowey]

Totally. And your intuition is built up over years of decisions, bad decisions, you know, things that went wrong, you know, and so like AI doesn't have that, you know, and so sometimes your human instinct is the best way to go. It's the best way to go.

[Stephanie Postols]

Yeah. AI probably a lot of times has all the risks that have ever happened in how many years it's been tracking data. And I think what's amazing about humans is being like, I'm going to do it anyways. And that's actually where most of the breakthroughs have happened, the biggest companies, the most life changing things is like, yes, it's showing me this might be a terrible idea to do based off these things. And I'm going to send a rocket to space anyways and then it happens.

[Bernard Slowey]

Yeah, exactly.

[Stephanie Postols]

Right.

[Bernard Slowey]

No, it's a great. No, you're crazy, right? Why would you do that? People are going to die.

[Lauren Wood]

Have you changed how you lead your team team at all now that AI is such a big part of your day to day?

[Bernard Slowey]

I think it's a lot of my focus right now and I actually kind of worry a little bit that I spend so much time here. Like, my team has lots of other elements like I talked about, like our YouTube channel. I manage all of our email campaigns for onboarding. And it's just like a ton of things to my team. And I worry actually a little bit that I'm so much of my time as an agent force that people that aren't working on it in my team feel like they're not working on the big shiny thing. And so it's about prioritizing my time and making sure I'm still spending times in other areas so that they can see that it's still. Because it's not all agent force, you know, we've lots of other things we do that's super important.

[Lauren Wood]

I think that the AI hype cycle definitely has a lot of people's attention at the moment, but it's really important to remember that it's not everything. It's the shiny. Everything is the shiny new thing. But there's, yeah, still a lot else.

[Bernard Slowey]

Although I do tell my team, I think everything that we do today will change. Like, even like, if we go in that example of like, you know, we send emails to customers, you know, and like, hey, you know, you bought Salesforce. You should do these things. Like, and it feels so 1980s now, you know, and. And like, you can imagine a world, like I said earlier, a proactive agent, right, that's looking at signals and saying, oh, Stephanie hasn't turned on this feature yet, you know, and it either reaches out in text or voice or like, you know what I mean? And so, like, it all becomes automated. So, like, I do think everything we do today will change. I think some things will change completely. Other things will augment, other things will be a little bit different, you know, and. But I think everything will change.

[Stephanie Postols]

It's kind of similar to that quote where it's like, if you have a hammer, everything you see is a nail. And that's kind of what I see with everything right now where I'm like, I do think AI will be in many of these things and they will be completely different. And so I'm kind of like seeing everything as a nail of like everything can be disrupted and it's amazing. And what a great future we get to live in with like all the things we don't have to do anymore when this comes to me.

[Bernard Slowey]

Yeah, like how much do we use ChatGPT now in your daily life?

[Lauren Wood]

You know, I mean, on that point, I actually have a question for both of you, which is what is your favorite personal use case of AI?

[Bernard Slowey]

Yeah, no, I have a good one because someone actually shared it with me was we're going on spring break vacation in a few weeks and someone shared to me about like actually putting into chat GPT where you're going on vacation, who you're going with. I have an 8 year old son. These are the things I like, etc. Etc. Etc. Here's how I'm going to be here. Here's the food we like to eat. And it gave me a tailored inventory of what I should do on my holiday. And like, I was like, wow, like some of this is really cool. Not saying we're going to do everything on it. I want to relax at some point as well. But like, what a cool use case, you know, of like being able to get that inventory of what to do.

[Lauren Wood]

Yeah.

[Stephanie Postols]

Oh, that one's way more fun because I'm like, I think about the stuff that I'm in now and I'm still, it's still so work related, but I love having it just like poke holes in anything I'm doing. So if I'm for example, coming up with some questions for an interview with Bernard and uploading the whole document and being like, pretend you're a top podcast host and tell me which questions are gonna result in a lame answer and which ones are gonna go nowhere and which ones are more thought provoking and contrarian and like, and I keep making it poke and then I get a new one and I'm like, now look at this one and tear it apart and pretend you're a cmo. What won't resonate with you? What parts don't you care about? Basically be really aggressive with everything I'm giving you. And it just, I feel like, gives.

[Bernard Slowey]

That's very cool.

[Stephanie Postols]

Such good output. By saying pretend to be this like cutthroat killer in the podcast industry, I'm like, ah, okay, this is great.

[Bernard Slowey]

I'll give you a good one, Stephanie, because I know you have kids that someone shared with me recently is they were at home and it was a rainy day in Seattle, and they asked ChatGPT and it gave them games to play in the house with their children that they had never played before.

[Stephanie Postols]

Ooh, I love that. Especially if I could say, like, here's the things that I have. I've got this random tree you can climb. I have, you know. Oh, that's a good one. I love that. I'm stealing that for all four of my kids.

[Bernard Slowey]

There you go. Parent in 101 here. There you go.

[Stephanie Postols]

I'm taking it. It's hot tips.

[Lauren Wood]

Well, Bernard, we have one question that we ask all of our guests on this show to close it out. And that question is, what is one piece of advice that every customer experience leader should hear?

[Bernard Slowey]

Oh, that's an easy one for me because I talk about this a lot is I don't think the word customer obsession. I find people say them words and they don't really mean it. Like, it's like, it sounds good. It's a nice thing to write on a wall. But like, you gotta be spending time even in the digital space, right? Like Agent Force. A good example. Like, I read every day some transcripts from AgentForce, the ones that were bad, right? I'm meeting with customers, I'm meeting with our MVPs who give very critical feedback on, like, what should we be doing different? How do we make it better? And so, like, I think to be truly customers, customer obsessed, you have to be looking at your calendar and going, how many hours a week am I actually talking to customers or reading something that was interaction with them? That's what it means. And I just think if you're in the world of cx, that is critical to anything you do.

[Lauren Wood]

And it goes back to the data point you made. It's not just the data. We have to actually have those conversations, really be there with our customer, listening to them, understanding what's the need behind their need, and digging deeper with our question questions. So I could not agree more. Thank you so much.

[Stephanie Postols]

This was awesome. Thank you all for letting me jump in and be in this conversation. Super fun and excited to run it on marketing trends as well. Thanks, Bernard.

[Bernard Slowey]

Yeah. Great to meet you both.