Reducing Cognitive Load and Enhancing Delight in PLG

Kailey Raymond: Everyone approaches growth differently, but whether your PLG or SLG or a little bit of both, your cornerstone is designing the right processes in creating moments of delight for your customers. Dialpad's Morgan Norman kicks off his PLG strategy by trying to reduce friction in their experience as much as possible so that users can make decisions without feeling overwhelmed. Morgan designs dopamine hits throughout the user journey to ensure that they feel confident in reducing friction and enhancing delight. You unlock paths to revenue. In today's episode, Morgan and I discuss the importance of onboarding product flood growth models and marketing AI products in a saturated market. I am very excited today. I have Morgan Norman here. He is the Chief marketing Officer at Dialpad and has also held executive roles at Copper, Zora, NetSuite and Microsoft. Morgan, thank you so much for being here.

Morgan Norman: I'm so excited to be here. There's so many amazing guests you've had, so let's take it away. Let's have some fun.

Kailey Raymond: Let's take it away. Softball for you first. Morgan, I wanna learn about how you got to where you are today. You've been in Tech in the Bay for quite a while, but in your own words, what's your career journey?

Morgan Norman: Yeah, so it's a pretty wild one and one that I don't think I would've figured out it ended up here. I was raised by artists in New York City. I was a bi-coastal kid a little bit. Decided to come out here for college, trying to be a struggling writer, was unable to make a living. This is the before the days where you could be a content writer in blogs. And one day a friend said, why don't you come up here and try this tech job? It's in inside sales. You're great at actually speaking with people, people like you. Then you could go back to actually writing the novels you wanna do. So I took this job 25 years later, I ended up being here, but there's a twist in the middle is throughout that I ended up finding a love because I was in inside sales for a while and ended up eventually doing early marketing stuff.

Morgan Norman: There was like events and demand generation really early on, but none of the tools worked for us in inside sales. None of the marketing materials worked because we could only convey things over the phone. So I started building materials that would work for us. So those were presentation decks that I could just send over via email and they would understand what the story is we were trying to say or the value we were trying to make. And from there I started creating these corporate decks across the whole company. Everyone was like, oh, everyone started using these decks and this was a pattern that happened within every company.

Morgan Norman: And eventually I didn't want to be in sales. I was actually okay at it. I'd run some big scale sales teams both in the field and inside, but I always had this love for creativity. I always was a creative. And then eventually it just fully pulled me over where they said, Hey, how about you take over all the messaging? How about you take over all the branding and the strategy and next thing you know, you're sitting in one of these lead marketing chairs, which has been fantastic. It's one of my favorite jobs in the world.

Kailey Raymond: I love that story. So you started out like Creative Brain, went into sales, tried to find your pocket there and ended up in a place where you can actually expand on that creativity and being in inside sales probably gives you a whole lot of empathy for what marketers are telling you to do.

Morgan Norman: Yes.

Kailey Raymond: And what it's actually like to be in front of customers every day. Any like quick insights from your sales days that you've brought into your marketing roles?

Morgan Norman: I think the sales job, and I was originally like a sales development rep is probably the hardest job in the company.

Kailey Raymond: Impossible.

Morgan Norman: And I really do mean that, it's just rejection all day long, like an eighth grade dance and you have to have like perseverance. The challenges with marketers is we don't have to deal with that. We actually can just say, oh, here's the materials this customer should like and we have these really strong points of view. They're dealing with a completely different world. So one of the things I think that's really important and where I've had some success is to understand that many times they can't pitch so many products, they can't pitch to too many different user types. So you have to figure out how you simplify that and then also watch what they gravitate towards and what they gravitate towards is what's more comfortable for them. And then eventually bring in some things that's a little less comfortable and kind of push them. Marketing, were always ahead of sales. We're like six months, sometimes years ahead of sales, but it's like how do we pull them along and allow them to weave their self into the story versus dumping work off? And that's what I think a lot of marketers do. It's like, this is the story we've agreed about corporate, everyone learn it and then they're really struggling to adopt to it.

Kailey Raymond: That is so insightful. Starting small, making sure you can iterate. So you have seen a lot of different roles in organizations mainly go to market, customer facing roles, really telling stories in tech for over 20 years now. Tell me about some of the trends that you're seeing in today's market that's different than the other times that you've seen. What is it like to be in marketing today?

Morgan Norman: It's such a tough question. The first piece that was really transformative for all of us is just dealing with product-led models and growth models and what does that do for changing the way you think about experience? You think about data, you think about systems and then how do you coach a team where you're in uncharted worlds, whether you might actually be good at growth with one product line. What happens when you add another product line and another self-service? What are the learning paths of users and how do you kind of coach the team without overwhelming them because it's so ginormous. It's like this incredible Tetris game if you will. So there's managing that on a product-led growth side, but there's also the sales-led side. So you have to service this conflict in the middle where it's like you wanna drive online business, you want to hand off the top opportunities and leads or MQLs [0:06:55.6] ____ or PQLs to sellers.

Morgan Norman: And at the same time you've gotta create all these sales tools to help the sales team be effective. So that transition just from a growth model to a sales side model has been around for a while. The complexity of it in this new world is like nothing any of us have seen before. There's very few experts I worked with this one gentleman, his name was Nid Shaw, he did Figma and Zendesk, he's got a PhD in electrical engineering and even he will talk about how complex this can get from a formulary perspective. You have to have real strong principles and growth, but you have to experiment a lot and have a lot of freedom. The other piece I would say is the biggest challenge that we're seeing now, and I'd say in the last six months you're probably seeing is, we're an AI company.

Morgan Norman: We've been an AI company for over five years. We have about 4 billion minutes of AI conversational data we've been looking at for that amount of time. But marketing AI where everyone is in a fearful state and they don't understand the value and trying to give them clarity and not to give them clarity about your solution, but give them clarity about how can they begin this new journey for themselves. How can they transform their company into an AI company, but also reinvent their career and reinvent what they wanna play with. That's so complex right now 'cause they're so many fake products that people are talking about or high products. It's like the internet in 1999.

Kailey Raymond: I love that you just called this out. Absolutely. I was having a conversation with the head of product for Airtable the other day talking about these two exact topics. I was like, yes, this is exactly what is happening in marketers worlds right now. AI being able to actually use it instead of just talk about it. I think that we're at this crucial moment where a lot of people are saying, yeah, we're an AI company or you...

Morgan Norman: Yes.

Kailey Raymond: We're gonna start these AI use cases. So can you just tell me a little bit about how you're helping your customers to implement AI use cases? What does that look like?

Morgan Norman: Well, it has a lot to do with data, which I think you folks talk about in all the parameters around data. So what Dialpad originally started as, it's the folks that built Google Voice. They had this vision of building business collaboration for everyone, all types, whether that's meetings, voice, contact center, sales, it didn't really matter. And then they got lucky in a way with this acquisition that came to them and they figured out like, could conversational data be the most valuable data in the world? And data's the new currency suddenly that happened this year. So one of the pieces I think from an AI perspective is it's one thing to say you're an AI company. It's one thing to actually have AI data. It all comes down to usage and adoption. We can all talk about it. You've launched a feature, there's a press release, the salespeople have presentation decks, but are people really using it?

Morgan Norman: And what I love about working for a company that has Google DNA and design and self-service DNA is from a contact center perspective, those who are dealing with customer engagement, 96% of all customers on our customer engagement side use AI. It's shocking. We didn't even know it was actually true. We're like, this can't be accurate at first. The other piece now is this next wave of AI is how do you get everyone to adopt it and start to tinker with it? It doesn't mean that it's gonna work perfectly for them, but they're going to push the envelope of what it is getting back to you of what those features might be or how it would work better for their workflow. So the difference that I see a lot of AI companies is yes, you have an AI feature, but the truth is we all know you don't have capacity If you're in the AI market, you know, you don't have capacity to offer it to a lot of people.

Morgan Norman: It's just the nature of the space right now. The next flavor is really dealing with users that are very passionate about this and actually do they want to kind of adopt some of these features and kind of coach you in because it is uncharted worlds. If you will, the other piece of AI is we have a lifecycle team that's constantly educating the individuals on what features might be interesting for them. Is it a meeting summary, is it a recap? Would they like a coaching moment or a playbook? And so if you think about your AI features, not just like did they turn on AI? What are the different features and functions you want folks to adopt? And then how is that gonna provide data for you and different parameters for you?

Kailey Raymond: That's so right. And I think that there's, everybody gets wrapped up in this because there's like AI features and then there's like choose your own AI adventure, which is the realm of probably predictive modeling. And then...

Morgan Norman: Yes.

Kailey Raymond: Like a lot of the gen AI use cases, you can put it in a box but it can really go anywhere. And it's like...

Morgan Norman: Yeah.

Kailey Raymond: How do you make sure that people are fully understanding the full capabilities of what this can do? So when you say 96% of your contact center customers are actually using AI, walk me through what some of those actual use cases are.

Morgan Norman: Yeah, so the use cases for us is we deal with anywhere from a 10 person customer engagement contact center to tens of thousands. And they're typically scattered everywhere in the world. The difference is if you go to an old world model, a supervisor, whether it's on a service side or a sales side, would have to like listen to calls and say, are they actually following the exact adherence we want them to? Are they asking the right questions? And then how did they actually score? Did someone say service was good, yes or no? So we have a couple different things that folks do. One is they can get immediate signals on if someone's actually following a playbook or if they've deviated from it. So instead of looking at thousands of calls, it's prompting the supervisor, here's the one immediately to look at.

Morgan Norman: And it might be a new hire because generally people are doing the best they can. So maybe you need to update a playbook or it's not prompting the right information for us. The other side of AI, which is very unique that we've been leveraging since we do transcriptions as well, and it's real time. And this is a whole nother facet of AI, which people are not really diving into as much and need to, it'll coach the individual, they're speaking too much. Change your tonality. This person's actually upset with you right now. Speak about this specific offering. If they mention a competitor, a billing user can actually set up a playbook that says, speak this about these different value points. And all that's designed around business users versus an army of PhDs. So I'd say coaching is one aspect that's really easy to understand. Playbooks is another, there's another piece we launched last year, which is AI CSAT. So we can predict your CSAT from all your calls without you doing anything.

Kailey Raymond: Wow.

Morgan Norman: And without you sending any surveys to anybody. And it's so accurate when we did it ourselves, what we thought our CSAT was, it was 15% higher than it really was. But it also told us what exactly to solve. And our chief customer officer started solving those things in about, I think it was probably six to 12 weeks. And suddenly the real CSAT is now best in class. But we didn't even realize these were some of the insights customers were talking about. 'Cause you'd have to listen to every single call.

Kailey Raymond: That's so interesting. So you're basically taking...

Morgan Norman: That's crazy.

Kailey Raymond: Taking call summaries and then you're saying like, here are the top trends, let's action against this.

Morgan Norman: Yep. In real time. Yeah.

Kailey Raymond: Brilliant.

Morgan Norman: Yeah.

Kailey Raymond: And so yeah.

Morgan Norman: Yeah.

Kailey Raymond: So you're on a call with an agent and you're literally listening to the tone, what the person is saying and then prompting them with these playbooks in real time.

Morgan Norman: Yeah.

Kailey Raymond: Blown away.

Morgan Norman: It's gonna get even more advanced than that. This is just the beginnings and it will give you a summary. It will tell you exactly the call purpose and you'll be able to design different call purposes. And normal ones are like there's a refund or there's a technical issue. But if you're in healthcare, it's like there's an insurance issue or it's Medicare and those are very different protocols than a tech company that's saying you might have this specific issue or a luggage company sending out a new piece of luggage to something that broke. So all of those need to be designed by business users who understand the workflow and business problems versus let me draw some schematics, go to an IT person, build an AI model that meets this it's just so illogical and this is where really folks need to dive into and this is why we wanna get products in people's hands so we can build these next generation workflows.

Kailey Raymond: That is so interesting. Very, very cool that you're building. I'm wondering, since you've been doing this AI for five years way ahead of the current trend, when everybody just decided to say that they're an AI company overnight.

Morgan Norman: Yeah.

Kailey Raymond: So how are you starting to think about marketing AI products in this now very saturated market?

Morgan Norman: Yeah. Yeah, this has probably been the most interesting time in my career and the most challenging in my career. And what I noticed is that you can have a lot of differentiation in a market and you'll see people, if you've been in the AI space for a while, people borrow from you very quickly. The first problem we ran into, and I'll go into the larger scale of how we think about marketing, is people can rip off your content overnight suddenly. And this was a really difficult challenge because we're heavy into content, we're heavy into thought leadership, but suddenly some someone's just mimicking this and Google doesn't recognize if you, they were really savvy. They were on top of that. The big piece that I think about from brands that I've always broken down to a system called basis is how do you tell the story? How do you see the product?

Morgan Norman: Or how do you show the product? How do you prove it? And then what do you want the user to do? Or what are the actions? In most companies, if they're really concise, they can tell the story pretty well. If they have a pretty strong vision and it's real, they can tell the story not in just a feature function way. They can tell a bigger story how they're transforming the world. We always have focused there. AI that works for you. We've always thought about the good AI, we did a Super Bowl commercial about it before. People were thinking about it. AI doesn't have to be scary and there's a lot of principles around those areas. The next is how do you make it relevant to the users where they can see themselves in the product? And what I mean by that is just like you insert yourself into a movie, they can see themselves using the product and saying, oh, I have my own prompts I wanna configure.

Morgan Norman: I have my own use cases and I don't need an admin. No, this is your own specific, sales center. You can do whatever you want with it. Oh wow. Oh I have my own sales methodology. So suddenly you wanna relate to them and get them excited enough and get that energy. The proof part, most companies do well, it's "Validation analysts" whatever it could be. But going back to it, it has to be authentic. And this is where I'm a little disappointed with a lot of marketers and it's just marketing spam. It's not authentic and you can see it, you can feel it when you go to their sites. They're trying to force what their desires are versus maybe what ultimately might help users. So what we also do, and we focus heavily on brand, is it's a big video play.

Morgan Norman: It's very clear in terms of their simple messaging at the top. And then you can go down all the way down to product detail as deep as you want to. There's PhD papers if you wanna even get down to that level. And then they can tell that story without us. And this goes back to the first question that you asked me about how did I start my career? And I tell this story a lot. I'm dyslexic and the way I designed presentations was if I could drop the deck on the floor could someone pitch it without me? Because I knew sellers couldn't tell the story and get all the pieces. And this is the same way we market at Dialpad.

Morgan Norman: There's a clarity, there's a simplicity. It's about easy use, easy deploy. It's also about trying the product. Those same and beautiful design, all those Google principles and it's real, right? So we believe be authentic. It's okay if you have gaps in the product, but market at those levels. And we do push the envelope pretty far. We are on the edge of what folks are comfortable with with AI. We do some things that people are like, I dunno if this is for my company. And so, so be it. When you're ready for it, let us know and go do what you need to do to be successful.

Kailey Raymond: I love that insight and I think it's so brilliant. It's something that's so, it can be so hard in the day-to-day to remember, the enablement session's really important. Yes. But the 10 slide deck that anybody could pick up and immediately speak to, that's exactly what everybody needs and wants. They don't wanna have to think about it.

Morgan Norman: That's right.

Kailey Raymond: They don't wanna have to read a million documents to fully grasp onto the concepts. If any takeaway from today make a 10 slide deck that anybody can latch onto and pitch, that is absolutely brilliant. And.

Morgan Norman: And make it highly visual.

Kailey Raymond: Yes. And one of the things I think is interesting too is you're talking about really showing value and allowing people to discover on their own. And I think that's the way most people buy this. The way that a modern buyer is coming to you. They probably know a lot more about your products than they would've 10 years ago. They are doing tons of different research that's also kind of forcing this PLG motion as well. So is there a little bit of interaction there as well? How is PLG kind of inserting itself into the way that you're educating these users and the way that you're building your marketing programs from the ground up of like being really granular with what you're sharing?

Morgan Norman: Everyone has a different approach to growth. So sometimes growth folks are very data-centric and then sometimes you'll have growth individuals that are very much design-centric and then there's process if you will. And then there's moments of delight. The way I really think about PLG at the top level is cognitive load, is are you overwhelming the user? Now think about it, we're all multitasking. Something else is gonna happen to them in the middle of this and what's the cognitive load? How many decisions are you asking them to make? And what you'll find with most growth models, when you're going through a setup, it's literally like 80 to a 100 decision points and they don't realize that you're like, there's so many buttons and you have to learn what this is and what do you do here? So the first thing is to reduce the cognitive load as much as possible from a visual perspective and also a step perspective.

Morgan Norman: The next piece on that is user confirmation. Confirming to the user that they've done the right thing and that they feel successful. We all wanna know like, oh I might come back to this but I went through the first milestone. Another factor for us and we're just really into design, is just delight and design. And there's some amazing companies that you just mentioned. You're talking about Airtable earlier. They have beautiful design. And I think if you can delight users in a growth model, 'cause only so many are gonna go through, the abandoned users will go, what an amazing experience. And then there's that experience part of what are those different triggers in app off of app, back to the data pieces, what device are they on? Are they on mobile, is it tablet, what type of browser? And then you know like how technical they are, where are they located From a geo perspective, International's very different than stateside.

Morgan Norman: So I feel you need a baseline of those. And then also a baseline with what your resources are in growth. And growth is always underfunded. It just always is. It's a fact unless you're a founder that says I love growth and it's the model or Atlassian who did it, perfectly well, you're underfunded. It just is. And so the other piece is to understand what's capable with your team. We have an amazing growth team. It's a very lean team but it's a very effective team and they come up with really insane ideas. So I think it's understanding your resources, understanding actually how you can dedicate engineering, what kind of learning paths, how you really think about the user and then how you educate the teams to think about the users as well. And then from there, once they're in the product, that's a whole different piece in terms of like once they've dropped in, I really think about that first couple minutes. Then I think about, okay, how do I get 'em set up first day? And then I think if they don't hit the first day I'm like okay, how do I work with them over the next couple weeks?

Kailey Raymond: It's like dopamine hits. It makes perfect sense when you say it. Like I'm thinking about onboarding onto some tools and how many buttons I needed to click to do the things that I needed to learn how to do and I didn't get that reward and that pat on the back that I so deserved and that I so wanted, especially in a virtual world, like you're just doing it by yourself pretty hard.

Morgan Norman: That's right.

Kailey Raymond: You don't have a ton of resources that are looking over your shoulder or that are training you on these apps nowadays. So I love that idea of like making it the steps really clear, making sure that they know they did a good job and packaging it in that way that they can say like they feel good. I did something today. So many of the things that we're talking about right now you've mentioned a couple of times are these are data problems. These are things that require a whole lot of data for you to be able to make decisions to build these programs against. So I guess kinda first question is at Dialpad do you have a definition around what you consider good data?

Morgan Norman: It's a good question. I wouldn't say it's defined written down, but what I would say is the first piece that I look at is, is the data, does it have relevancy? Is it relevant to what I'm specifically looking at? Is it isolated in those areas? Because crossing over those areas like an ad team's, very different than a growth team. And then you have like a demand gen team that's very different than a field events team sometimes. And all of them have different parameters they're looking at and how they're looking at the user in a very different way. The next piece that I really need to look at, and this causes immense problems for marketers, is consistency and quality. Is it consistent? Is there consistent timeframe where folks are actually looking or a cadence that they're looking at this data and is the quality strong? Are you always going, oh we need to update it.

Morgan Norman: Could I get another view this way? And marketers just generally don't have the bandwidth for that. So I'm really looking for, it's got some baseline consistency, it's gonna give me some directional quality. It doesn't have a lot of noise in it. There's another factor that I think is important, which is just uniqueness and is it unique to each specific team? Like a billing team which we deal with in PLG, it's a very different set than a content marketing team. So I've never gotten a point where it's like this holy grail and it's this NSA dashboard of here's all the demographics and what everyone's doing. But I will tell you that uniqueness part, it has to work down to the individuals and it has to give them insights without having a meeting with them. It has to prompt them. It even has to prompt someone on the data side to say, oh I'm seeing this pattern.

Morgan Norman: Are you folks thinking that way? And most of the time data's not there. And most of the time you're actually going, okay, I'm seeing this. And because you have a lot of pattern recognition, you're saying okay look here. So that goes back to relevancy, right? So all those pieces have to tie together that relevancy, consistency, that quality and that uniqueness down to the end user. That's how I think about good data and actually break it apart by teams. I don't need this team to look at all this data over there. Don't confuse them, right? They don't need social media data, it's just a different world.

Kailey Raymond: It's interesting though because I think some of the principles that you're sharing right now kind of echo back to what you were saying earlier, which is have a deck that anybody can pick up and understand. Have a dashboard that anybody on this team can look at and understand and is relevant exactly to them, right? Like you don't need to get on a call to be able to say, can you tell me what this actually says? [laughter] Like you need to be able to action on it.

Morgan Norman: It drives me crazy actually. So we have a Friday marketing metrics meeting. I love the meeting because we do deep dive areas and it just gives me a pulse of how the instruments are. But first is, are you able to collect the data and are you going to transform it into something meaningful? So visual if you will. And can they tell that story back to a broader team? And so what I love about that is they're telling the story to the team of what they're seeing, they're giving their insights and from there, if they can't do that, they can't get other teams to activate around it. So back to the good data part is it needs to coach others, it has to be a learning for other marketers to understand what this group is doing and whatever they need to get done in this next horizon. It requires others to activate around that. Like growth requires design, it requires web, it requires content, it requires video, all those things. But there's that lack of understanding. So that data kind of helps them kind of tell that story and kind of transform what they're looking for.

Kailey Raymond: Here he is the storyteller at his heart. Is coming back. I love it. So we've talked about AI, some of the use cases that a lot of your customers are using, which are really powerful. I'm wondering how you're using some of the data that you're collecting at Dialpad to transform it into customer experiences, customer engagement programs, marketing campaigns. Do you have any examples that you wanna share?

Morgan Norman: Yeah, so a couple ways we use data, I'll go back to the growth piece and then we could go broader. What I've always wanted to get down to is like really heavy demographic data. You've had some amazing marketers on here who come from consumer side and they actually are light years ahead of all B2B and B2C companies, which is what we are, I've never fully gotten there, but from a data perspective we actually look at a lot of the profile information of how a user's first interacting with us. And that comes across from obviously if they touch us specific campaign, that's one part, but let's ditch that for a second. How do they interact with you from the web? Once again, what devices are they specific using? What demographic might you know about them from a specific campaign? What industries do you know about them which we get into a little bit, personalization.

Morgan Norman: From there I'm starting to look at behaviors, right? So and this is actually in our system and these behaviors will say if a user slammed through, more steps than general trigger this specific prompt or pull them over to an admin section. So the growth team is constantly configuring different triggers, different motions, different campaigns based up of what that user behavior is or lack of. Back to that data, if the user is logged out and is not logging back in the system, you gotta get 'em back in app as fast as possible. So all of that is really designed at that baseline customer data footprint. The other piece is just more foundational and I would say marketing basics, which is been around for years, is how do you look at your cost per pipeline? How do you look at your cost per campaign and how do you get more predictive to see what can drive in period in quarter revenue. So net new. So in examples of that, I'm constantly looking at data and say what's the fastest time to revenue from like zero to win? And then you're doubling down in that area and using that data to try to teach the team to experiment more as well. And once you find those sweet spots is where you can drive very fast, rapid in period revenue. You have the secret sauce to kind of grow the company whenever there's gap.

Kailey Raymond: Wait, I love this. You were talking about really onboarding but also kinda like educational assets and you're segmenting them based off of what they're actually doing, the channels that they're actually coming in from, how is that increasing conversion? Walk me through like how you're measuring that all the way to the end of a customer life cycle.

Producer 1: So when we think about onboarding, there's a variety of different ways users engage and you first have to figure out what type of user it is and what segment, what industry. So we deal with very small business all the way to the biggest enterprises, hundreds of thousands of employees. And they will sometimes go through a trial. So what do you do with that? You have to know what to do. So a VSB, you can't onboard them. You need to go through as much self-service as possible. So you want the billing campaigns, you want everything to kind of be really seamless, prompt them, the right actually product skew. And then you're pointing 'em over to just online resources as much as possible. And then if it's a specific account you can trigger them to engage with a CSM, you give 'em a choice there.

Morgan Norman: But then there's the other piece of onboarding where a large scale enterprise or a top brands going through your trial and you've gotta alert the team that it's a PQL. So Product Qualified Lead that they need to pounce on. And that's another area where they might not wanna engage with your team actually. So they still might wanna tinker on the product, they're doing more exploration, but it's, so it's a careful balance there. So we do on the onboarding side is we partner with our CSM and our professional services teams. We actually build a lot of content for them. It's built by our PMM team. They build a variety of different videos. They build everything from very high level videos to just learn about a feature down to detail. So once again, the learning path is different. So the learning path for someone who runs sales is very different from someone who runs customer engagement or customer service versus someone who's actually just setting up some sort of collaboration system.

Morgan Norman: Those are very different types. So we will typically take them actually into a little bit of high level videos. We'll take 'em down a layer, we'll give them a choice if they wanna interact with CSMs, if they wanna eject out a different pathway. And that's a really key element if you're managing growth in sales led and all those signals are also prompting the reps at the same time. You're talking a hundred thousand of these at a time, which ones do I look at? So you've gotta have the right signals in the right prompts where they don't waste their time or they're so frustrated with marketing, they're like, oh this is all garbage. Give them the right ones there. And then also ghost the reps communication based off of the data. That's how we roll.

Kailey Raymond: I love it. You also mentioned, well the importance, first of all, of speed to lead. I love that. Making sure that you're, getting in front of somebody, they're literally in your app, they're clicking in a million things, they're yeah, you should probably alert your sales team that this is somebody that they should talk to right now. Probably a good idea. And I'm wondering that kind of relates to something that you mentioned, which was what are the things that I'm gonna do in quarter that are going to produce revenue this quarter? Do you wanna give any trade secrets? Any thoughts there on things that you're doing well that are working?

Morgan Norman: I would tell you this, I'd love to give away secrets to do this, but believe it or not, it's always a surprise. What actually worked for me ages ago is not what works now and even what's happening even in this last quarter, it's not exactly what I would've predicted. So what it's teaching me is to be more uncomfortable with the team. And what I mean is I have an immense sense of trust that they will make a decision that sometimes I won't make because they're on a frontline. And this is an example, this one woman ran a tactic, her name's Rachel Flood. She ran a tactic where I was like, I dunno if this is gonna work. But what was good is she has this mindset of experimentation and she pushed it out there and it just fired and it was just starting to print, print pipeline.

Morgan Norman: And the piece that I would say in quarter is, if you don't have a variety of testing items and fallback plans around that, you're never gonna get there. And those have to be net new business. And it also has to be within your install base expansion. And you have to split those teams, split those motions and allow a freedom of it not working. But when it does work, they see the rewards of it, everything kicks in a different way. It's not rocket science. I think the rocket science is trust your team really empower them to do the things that they have a gut feel. Watch where they're drawn to. If they're drawn to something and they're really passionate and they're pushing back on you, step back, listen to them, do what they're telling you to do. And that's kind of how I operate with them.

Kailey Raymond: I love that. That's what makes marketing so interesting, right? Is like, yeah, what worked for you five, 10, whatever years ago. Like it's probably a little bit different today. Like every company is an AI company. That was not true five, 10 years ago. Right? So like that's gonna change your tactics. I wanna know, we've talked about a lot of the campaigns that you're running internally. Are there any companies that you look to that you think are doing it right?

Morgan Norman: I'm really follow a lot of top tier companies, which might be a little bit unfair. I think they're probably resourced a lot better than a lot of companies. But I'll put it out there. I have followed Airtable, I have followed Monday. Definitely Asana I think really gets experience in design, but they also really drive loyalty from their specific users. But I also follow some odd ones that, I might not love their product design but they have a good go-to-market model. And the way I approach marketing is I'm constantly trying products. I'm constantly saying like, okay lemme see what their self-service sign-up's like and what you can kind of tell is they have a point of view of something that we might not be doing. The other ones I do follow, I mean everyone's following like the real large scale LLM players And you could see, just watching from an outside, you could see 'em struggle, they'll launch something and then the CEO's saying, well this didn't work and now we're doing this.

Morgan Norman: There's a wonderful part of that where you're watching transparency start to happen where it didn't happen. And I empathize with any of those marketers 'cause it's a little bit like crisis management. So I do follow the AI market. There's so many articles you can't even keep up with and I ended up doing a newsletter myself about it. But it's very interesting to watch this crisis management side 'cause anyone who is in that world that is a third party system or using these third party systems, you're gonna be in crisis management if you're not already, it's coming. You're gonna have to explain this to your customers. You're gonna have to explain where this data is. You're gonna have to explain is there any leakage of this data? Is it noisy? What's happened? I do not wanna be on that side of the fence. And that's why I think Google was so cautious originally, and now look at this. They just announced like the founder's coming back to, that tells you how crazy this market is. And I'm coming outta retirement to fix the world.

Kailey Raymond: Yeah. I mean the number of people that are in the market that are saying that we need to push pause and that congress needs to come in and pass some laws, like this is a strange time that we're living in, in tech it's pretty unique to watch this happen while. For the most part, the gas is just being put on the grill and people are throwing those matches on. And we're trying to see what's gonna come out of it, so it's this tension that's that's happening right now.

Morgan Norman: Yeah. It's exciting to see. I hope it'll settle down. But I think for the marketers out there, I think our life's gonna get a little bit easier with copy. It's gonna get a little bit easier with imagery and design. So I think we're gonna benefit in a very big way. Experiences with all the world of chatbots out there is gonna be, help you with like delivering a better level of service. So I think, if you're on the marketing side, you're at a real advantage. And I would jump into, I'd really look at the technology before you jump into a company that says they're an AI company. I don't fall for it.

Kailey Raymond: I love it. Don't fall for the tricks. Do your research.

Morgan Norman: Yeah.

Kailey Raymond: Is there a trend, and it could be AI, I know we've talked about it a lot, but is there a trend that you're watching out for that's on the horizon as it relates to data marketing in the next year or so?

Morgan Norman: The problem with marketing data truthfully is you can either have it like in BigQuery in a variety of systems and it's siloed, right? So you might have your customer behavior in one set of tables and then how do you turn that into insights for everyone else that's more on the visualization side. I've really always wondered why someone hasn't been able to pull this all together and how to make it usable. How to make the intelligence more usable for marketers that might not have the SQL background or don't wanna go to a BI person all the time. So I feel that the tools do work. That's the struggle with marketing technology. It does work for like technical audiences, but then when you're really dealing with the business audiences, they kind of get outta tune or everyone's kind of send me this report. So I think there's some things that will come out with AI and that is gonna be fascinating with how people can look at data use. Probably those chat bots will be baked on top of it to give people the very specific insights they need to, and to think about predictive modeling, which you can't do without really a big rev ops team or analytics team. That's probably the, even though I've tried to play with it in some areas, I haven't been able to get where I wanted to go. That's the most interesting thing that I would like to see cracked in the next like six months or some basics towards that could be game changing for all of us. Yeah.

Kailey Raymond: I love it. Yeah. And it's like leveraging probably like reverse ETL in there. Take all that information out and pipe it into some AI built dashboard that's giving you these insights. I like it.

Morgan Norman: That, imagine if there's a chatbot on top of that and you're asking specific questions like, I think Google tried to do this with Explorer and you'd really have that intelligence. Then furthermore, they're pushing on document AI. I think Microsoft is as well. Imagine that it's gonna pull up other reference materials for you to back up what that could be and says, oh, have you looked at this across your entire network of docs? That's interesting to me. And you're like, okay, I know what I need to do.

Kailey Raymond: I think LLMs, a lot of people are gonna be able to probably replicate that for their own purposes. Let's feed data and make sure that it's specific to our use cases, cool. But what you're talking about on the predictive side of things and then having a tool actually tell you exactly the insight that you wouldn't have been able to pull out or you would've taken months for some sort of BI team to be able to like build this dash for you. Like that's really the thing.

Morgan Norman: So if you think... Our other holy grail was also too, it's like could you really break down users by their potential? Their potential is obviously limitless, but are they high usage, medium usage, low usage? What type of loyalty programs would you wanna offer to them? What's some of their purchasing behavior? What ads do they react to? And then if you could get that B2C data in there, like that demographic data, wow, that could be mind blowing.

Kailey Raymond: Automated segmentation, Yeah.

Morgan Norman: It'd be insane. It'd be absolutely insane. And then your advertising dollars could get cut into a fraction, I mean, overnight because you know exactly what to do. Your win rates are gonna go through the roof, your cost per pipe, cost for deal's gonna go down dramatically. And I don't think anyone's cracked this, but I actually do think some companies will crack this that aren't even existing yet and they will crack it in years, like overnight.

Kailey Raymond: I love it, the future's bright. Okay, now I'm back. I'm excited about AI again. This is good. For a while we were, apologizing for it. A little bit nervous. A little nervous. And now we're back on. Yeah. This is good. Last question for you.

Morgan Norman: Yeah go.

Kailey Raymond: What steps or recommendations do you have for somebody that's looking to uplevel their customer experience strategies?

Morgan Norman: I think the piece on customer experiences is gonna be more challenging in this next phase than anything we've ever seen before. And the reason is because there's going to be this appetite to wanna try products, and I think the GPTs out there and the other ones that are coming out are barred or whatever you wanna say. I think this is gonna cause a huge flux that you're going to have to deliver a self-service experience in AI. And the next piece on an experience is, I don't think you can be very successful selling your AI frameworks to a subset of users and think that's gonna drive adoption within the company. So thinking about who are your primary users, of course you have to pay bills and make a business, but then how are you educating other folks on what are those other elements of AI or value points you're driving?

Morgan Norman: If that's data or if you're basically querying specific information, great. Really think about that self-service experience even if you can't get there now, the next piece is going to be more of a like express onboarding. How do you actually help a business user set this up and see immediate value back to that confirmation of, oh wow, I did this right? Or pretty soon. If you don't have like Google collab, you're gonna be setting up your own models, right? So I think those are probably the most important, that first user experience that we think about. Then simplifying, you're not gonna be able to do all the learning paths you want, but what is that one basic one that explains what you're doing, the value you're trying to drive, and then also the steps you believe someone should take and why you should be part of their AI strategy.

Morgan Norman: If there's now tens and tens of thousands of products out there, whether they're real or not, why should you be part of this small collective of AI? Why should you be part of that AI step? Why do you deserve that right? And then can you basically, instead of thinking about just on your business end, can you do it in a more altruistic way of saying, are you really benefiting these people or are you just a feature you're just having fun 'cause it's like a Y Combinator thing. So try to consolidate. The other thing I would say in experience is if I was on the company side, acquire some real companies, I mean, now's the time where you're gonna need both the teams, you're gonna need the resources, you're gonna need developers and AI marketers. You think you can fake it. It's very complex. There's gonna be a shortage of people who really know this stuff.

Morgan Norman: So I would think about people who have a passion. I would think about actually how you partner across all areas of the business as you're doing this experience. And then also let some of this go. Marketing can't do everything and we get a huge burden right now in this AI space. So what can the CSM teams do to help you or your chief customer officer or find one? And then equally, what can the sales team do while they're selling that's gonna help sell that experience and partner with you for what you are today. And then let's build, let's make sure this is future-proof. So are you enabling those materials that also give them that delight even if they don't go with you?

Kailey Raymond: I love it. I really think it's all about building simplicity, right? Into everything that you're doing and making sure that the right people have access to the information at hand to make the best informed decisions. Morgan, I learned a lot today. Thank you so much for being here.

Morgan Norman: It was a great dialogue. I had a ton of fun. Thank you so much for having me.

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