What happens when your brand has a million different voices speaking to a million different customers? Is that the pinnacle of personalization, or is it just brand chaos?
Agility requires both the speed to personalize content for every individual as well as the control to ensure every one of those interactions faithfully represents the core brand.
Today, we’re going to talk about resolving one of the biggest paradoxes in modern marketing: achieving hyper-personalization at massive scale, without sacrificing brand governance and consistency. We’ll explore how generative AI is moving from a creative novelty to a core operational engine for enterprise marketing, enabling brands to craft unique stories for every customer, while ensuring they all sing from the same hymn sheet.
To help me discuss this topic, I’d like to welcome, Jason Ing, CMO at Typeface.
About Jason Ing
Jason Ing is the Chief Marketing Officer at Typeface, where he leads global marketing and drives the shift toward AI-powered content creation. Over the past two decades, he has built high-performing marketing teams and launched enduring, customer-obsessed campaigns at brands including Procter & Gamble, Xbox, Amazon Prime Video, AWS, and Gusto. Known for systematically scaling teams, programs, and go-to-market motions, Jason has a track record of delivering marketing strategies that not only drive impact in the moment but continue to perform years later. At Typeface, he helps modern marketers rewire how their teams work—so they can move faster, scale smarter, and unlock AI’s full potential.
Jason Ing on LinkedIn: https://www.linkedin.com/in/ingjason/
Resources
Typeface: https://www.typeface.ai
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Transcript
Greg Kihlstrom (00:00)
What happens when your brand has a million different voices speaking to a million different customers? Is that the pinnacle of personalization or is it just brand chaos? Agility requires both the speed to personalize content for every individual as well as the control to ensure that every one of those interactions faithfully represents the core brand. Today, we’re going to talk about resolving one of the biggest paradoxes in modern marketing, achieving hyper-personalization at massive scale without sacrificing brand governance and consistency. We’re going to explore how generative AI is moving from a creative novelty to a core operational engine for enterprise marketing, enabling brands to craft unique stories for every customer while ensuring they’re all on the same page. To help me discuss this topic, I’d like to welcome Jason Ing CMO at Typeface. Jason, welcome back to the show.
Jason Ing (00:48)
Thanks for having me. I’m really excited to be here.
Greg Kihlstrom (00:50)
Yeah, yeah. Looking looking forward to talking and you’re a you’re returning returning champion here. So good to have you back on the show. Always, always love that. For those that, you know, didn’t catch your other episode and to talk a little bit about what you’re doing now, why don’t you give a little background on yourself and your role at Type.
Jason Ing (01:07)
Certainly. So I am a career marketer, started my career at Procter & Gamble, cut my teeth marketing, Pampers and IAMS Petfood. Great place to start my career. But I realized, you know, I wanted to focus on areas, particularly technology, where I just had a lot of interest. So I spent nearly two decades almost equally between Microsoft and Amazon.
I worked on everything from the early days of online gaming ⁓ at Xbox to video streaming at Prime Video and helping drive mainstream cloud adoption at AWS. And AWS was really where I saw firsthand how technology can fundamentally reshape what teams and businesses are capable when remove the friction and make it easy for users to adopt technologies. When we last talked, I was at Gusto helping reaccelerate their growth across their suite of HR products from payroll benefits and so much more as we like to say, and just building the early brand and demand gen work that you may have seen in some of their national campaigns. And you know, now I’m really excited to be at Typeface. get the fun job of marketing to marketers and it comes at this rare moment where brand creativity and AI are all converging. My focus here is leading marketing through that major category shift, moving from a world of AI tools to AI teammates to fully AI augmented brand systems that help teams work faster and create better work overall. And it’s just a very energizing place to be right now.
Greg Kihlstrom (02:42)
Yeah, I love it. Yeah, let’s let’s dive in then. And so let’s we’re going to talk about a few things today, but want to start with from the strategic perspective here talking about brand voice and value. So you’ve talked about establishing a brand system of record and for a CMO at a large at an enterprise company who’s used to brand guidelines living in PDFs and PowerPoints and places like that, what does that concept mean in practice and why is building this brand system of record a foundational step before scaling personalized content with AI?
Jason Ing (03:20)
Yeah. So like, as you mentioned, a lot of these brand guidelines sit in, you know, what they refer to as a brand book, which is, you know, a really thick PDF or PowerPoints that sit somewhere in an intranet. And sometimes they get used or sometimes they don’t, but they generally say static and buried and quite honestly, not used as much as they ought to be. And what happens is people tend to do their best to interpret them if they can find them. But a lot of times, especially over time, these aren’t living, breathing documents per se. that interpretation naturally drifts, especially when you have dozens of creators working across different channels or different geographies. And so a brand system of record is really the opposite. It’s what we consider a living brand brain, for lack of a better word, and it captures your tone, style, examples, your language, terminology, visual ID layouts, all of the things that makes your brand distinct. And it turns it into something that AI can use in real time. So when content is created, it’s not about it being close enough. It’s actually checked and shaped by the brand agent to make sure that everything is consistent, safe, and on voice. And this is a critical foundation for scaling personalization. If you don’t have it, you end up with a lot of volume but you lose the identity and the consistency when you end up with just a ton of content that doesn’t match your brand. And so when you have this at the core of your system, AIs can finally trust that the AI will scale a lot of that content across all different creative and content types because the system is grounded in the brand’s DNA. And so that’s why we start there.
Greg Kihlstrom (05:09)
Yeah, yeah, that makes sense. And I want to talk a little bit about, know, we’ve been talking about personalization for years and I think there’s there’s a broad definition of it. And then there’s doing personalization a little in a little more advanced way, let’s say, you know, a lot of brands are calling it personalization, but really just substituting, you know, first name here or or things like that, maybe recommending similar products, some you know, technically personal personalization, but rather rather simple ways of of doing things versus how Netflix recommends shows to watch or Spotify recommends music to listen to. How would you recommend and how do you help brands cross that threshold from that? I would almost call it just substitution rather than personalization. But, you know, crossing that threshold from basic personalization to creating content that genuinely feels like a valuable and curated for the customer.
Jason Ing (06:07)
Yeah. So what you described is what I consider old school personalization is still personalization, but it’s more of what I consider deterministic. So if you like X, then you’ll like Y it’s very much functional and grounded in some rules based logic. And it doesn’t really reflect how a brand really understands and what it knows about you. And so the opportunity now is just much bigger. It’s about delivering content that feels like it was created with you in mind. So it’s human, it’s human, it’s reflective of someone’s preferences, cultures, behaviors, and needs over time. And that requires a system that understands both the brand and what it stands for as well as its audience. And so for us within Typeface, we have a suite of agents called Arc Agents, and that’s where it comes in.
And it takes your brand rules and your audience insights, and it generates variations across different channels and geographies in a way that feels very intentional, not like a template as you described. And it’s continuous. So you’re not manually creating version A and version B anymore. You’re running a system that can adapt that scale. So a great example is we worked with a national grocery retail chain and they use our ARC agents to produce localized culturally relevant campaign variations for different regions. So if you imagine a local supermarket, you know, what I see in Seattle might be very different than what someone should see in Texas because of, you know, different patterns in, in, food consumption, for example. And so in the past, that might take weeks of back and forth type of work, but they did it in hours. And the work not only just felt better and more relevant, but it was done at a much faster speed.
Greg Kihlstrom (07:58)
Yeah, yeah. And so in addition to the typeface arc agents that you mentioned, there’s also been some new Salesforce integrations as well. And with that, seems like the the AI is then getting even closer to the customer data and as well as some execution channels. How do you ensure that this automation, you know, that there’s a human in the loop and in other words, you know, that the automation doesn’t run amok and what kind of guardrails and human in the loop processes are essential for marketers to maintain control while still we’re doing personalization at scale.
Jason Ing (08:35)
Yeah. Well, I will say speed without governance and guardrails is just very dangerous and enterprises can’t afford to do that. And our customers are a lot more savvy, especially as AI content has become much more prolific that they can see something isn’t quite right. And so for us, we build that governance into our system from the start. Everything again, runs through those brand rules. That’s ground zero there’s compliance checks, permissions and audit trails. And so the brand agent enforces tone, voice, naming, and legal requirements without anyone having to manually police it. As long as you set those rules properly when you begin and you have that human in the loop, who’s always overseeing things to make sure that things are where, what they need to be. And so our Salesforce integrations content is created inside the
customers governed environments using approved data and approved workflows. And that means you don’t have ⁓ rogue messages or off-brand assets popping up somewhere in the system. And more importantly, marketers stay in control. So the AI drafts, people approve. So you get the speed, but you also get safety and consistency. And that balance is what makes the whole thing.
Greg Kihlstrom (09:54)
So let’s talk about measuring success here as well. so certainly investing in any platform, but investing in a platform like Typeface, it’s certainly a creative and a marketing decision, but there’s also, we’ve got to prove ROI in anything that’s invested in. what are some of the KPIs that marketing leaders should be tracking to measure ROI of AI and know, Gen AI and this personalization, you know, are we looking at things like content velocity conversion lift, you know, just what should marketing leaders be looking at?
Jason Ing (10:29)
There’s an element of all of the above, but I always tell leaders measure outcomes, not just outputs. So yes, you’ll produce 10 times more content and it may be 50 to a hundred percent faster, but production gains aren’t the KPI. Those are things that I consider enablers or input type metrics. The real impact shows up when you look at you know, incremental engagement lift or conversion lift or your revenue per message or how personalization performs better across different segments amongst the things that you would typically measure in a campaign. So start with a use case, a lighthouse use case and measure the before and after. Don’t try to boil the ocean, pick one workflow, run it end to end and capture those gains. The other piece.
that becomes really important as well is brand consistency. As content volume multiplies, drift becomes a real risk. So tracking consistency, which is how often content passes governance checks on the first try becomes part of your overall ROI story. And then there’s the operational impact. Faster approvals, fewer revisions, reduced dependencies on agencies and the ability to scale personalization without scaling headcount. Those are all material financial outcomes.
Greg Kihlstrom (11:53)
Yeah. And then, you know, beyond some of those, maybe a little more intangible, but still important. The idea with freeing up resources to not have to do maybe hyper repetitive work or or some of these things is that they’d be freeing up creatives to focus on higher level strategy versus, you know, again, repetitive roles or things like that. You know, how do leaders know if these tools are doing that.
Jason Ing (12:21)
One of the clearest signs you’ll see is a lot in the anecdotes of just what your team tells you. But more importantly, what they often will tell you is just how their priorities and their time shifts. when the tools are working well, teams spend less time on production tasks, be it ⁓ resizing, versioning, formatting, and more time on those, what we call higher bandwidth conversations around strategy, storytelling, and insight. And what we find is creative teams generally will get more cycles of ideation because the cost of iteration drops dramatically. You can try 10 ideas in the time it used to take to produce one, and that changes the culture and people start building that muscle of speed and experimentation again. And what you end up seeing is like better brace, tighter alignment,
fewer revision loops because the system is really enforcing that clarity as a mechanism upfront. And then there’s the human side to it as well. Burnout goes down. People aren’t stuck in menial mechanical tasks all day. They feel more ownership because they can shoot more work and that work tends to be of higher quality over time. And when teams shift from, you know, makers of assets or producers to shapers of ideas, you really begin to feel that shift in your culture and just how your team works and how people show up to their work.
Greg Kihlstrom (13:49)
Yeah, yeah. And I think all of this is touching on, you know, really the evolving role of of marketers versus not versus, but maybe marketers and the tools that they use, let’s say. So an AI becoming a tool, you know, it’s I’ve heard people say it’s almost like a team member. I’ve heard others saying it’s not almost like a team member. But depending on who you ask, they may have different versions of this, but it’s all it’s all part of an evolution of how the role of the marketer is is changing. So, you know, you’ve you’ve as you shared at the beginning of the show, you have experience across some really great brands, you know, AWS, Gusto and others that you mentioned. How do you see the role of the marketer evolving over the next few years and what skills become less important and what skills become absolutely critical?
Jason Ing (14:39)
think it’s very hard to predict the future, especially with AI progressing at the rate it is. What will happen exactly, but I’ll share my point of view in terms of how I’ve seen other shifts take place and how I would imagine things really changing knowing that the pace of and the acceleration of that innovation, like, you know, I was blown away with that Gemini 3 demo that I saw earlier today and what it’s capable of that I could never imagine was possible. But what I would say is, you know, in the past, marketers have always been structured by their function, like, or by their channel, for instance, like you were a search marketer, you were a comms person, you were a product marketer, you operated or marketers operated within their channel. I see
less of that, a lot of those silos between roles kind of breaking down and marketers having to adopt a much more systems point of view and being more of a systems orchestrator of these AI tools, as opposed to being a user of a point solution that does X for you. So instead of, you know, in the marketing context, manually executed campaigns, they’ll design the logic, the goals, and the audience strategy that the AI will or the agent will carry out. And the tools will handle the lift, but marketers will handle the clarity of thinking that goes into those workflows. And skills like taste, judgment, narrative craft will become the differentiator. So those who do that well today will only become more valuable. Not necessarily those that are just working on the production of it and natural language interfaces will change the job and you will be guiding agents, setting objectives and shaping stories instead of just, you know, pushing tools and turning dials across a number of different tools. And I see us ending back in a world of like old school marketing. So think of like, you know, David Ogilvy or Mad Men, the show and those type of skills mattering much more, which is taking human storytelling insight that just comes from lived experience and creative instinct. And as production becomes much more of a democratized motion, those fundamentals become the thing that will set brands apart.
Greg Kihlstrom (17:03)
Yeah, yeah, love it. So let’s let’s take it up then to the brand level. And, you know, given given everything that you’re saying there and and the increased use of generative AI and other tools in the marketing workflow, what do you think is the biggest opportunity for brands that get this stuff right versus, you know, the risk for those that fall behind?
Jason Ing (17:24)
I see the biggest opportunity is in marketing becoming very real time and dynamic. It’s multi-segment. It’s personalized in a way that feels very crafted and authentic, not some sort of template. And the brands that get this right will move faster. They’ll stay more relevant and create systems that are constantly learning and improving continuously. And you’re creating these loops, these systems where it’s not only the content, but it’s the data from how that content performs, where you will have sort of this self reinforcing flywheel of dynamic creative that optimizes itself. see the biggest risk is just being continually stuck in pilot or wait and see mode. lot of the companies that experiment experiment endlessly, but they never opera operationalized because they’re nervous or they’ll scale content without governance and end up with a messy inconsistent brand and they’ll just give up. Or this is probably the most common thing that I see as teams adopt change management practices to adopt more AI. And that is they’re not changing the way they work and how their workflows are designed. And I would see organizational inertia as the biggest blocker to realizing any kind of return from AI or any kind of technology. So.
This gap from being an early adopter to a laggard will widen fast. And this isn’t really a nice to have. This is a structural advantage. And that’s why it’s constantly talked about in the news media, because this is where we will begin to see the decisions and bets being made now separate who wins versus who doesn’t in this generational shift.
Greg Kihlstrom (19:10)
Yeah. Well, as we wrap up here, got a couple of last questions for you. If we were having this interview one year from now, what is one thing we would definitely be talking about?
Jason Ing (19:20)
Yeah. A year from now, we’ll be talking about the shift from when people used to prompt chat GPT to orchestrating agents. Marketers will set goals. The systems will create and adapt across channels without any kind of constant steering or tweaking. And these agentic workflows will become the standard. They’ll be autonomous, but governed and creative quality will become the main competitive differentiator since
content volume will essentially be unlimited. And so we’ll see a lot more of those, that closed loop marketing that I described where the content creates performance data, the AI uses that data to generate the next best creative and that cycle will get tighter and smarter. And brands will design not just for humans, but also AI agents that are increasingly consuming and interacting with that content. And websites is a great example where, you know, websites won’t
only be designed with humans and people in mind, but the agents that are crawling through the websites to determine how to surface metadata and information on answer engines. And I think that’s going to reshape a lot of the assumptions that we’re making about marketing today.
Greg Kihlstrom (20:30)
Yeah, yeah. Well, Jason, thanks again for joining today. One last question for you before we wrap up. What do you do to stay agile in your role and how do you find a way to do it consistently?
Jason Ing (20:41)
Well, for me, it starts with waking up every morning and recognizing that I know nothing and that I need to constantly relearn and re-educate myself and not let pattern matching or things that I’ve done in the past kind of weigh me down in terms of how I can learn, but staying very hands-on so that I can really bring in a beginner’s mindset to everything I do. And as it relates to AI, you know, I use it.
you know, personally in small everyday ways, I planned a family vacation, all in AI to Japan. And so it did a really good job of really telling me where I need to be, what I need to be watchful for and just helping show my kids and educating them on like, okay, this is how AI can be used across everyday things, except for cheating on your tests and homework. don’t, I don’t tolerate that too much. But you know, as a comes back to marketing, do always rely though on making sure I’m fundamentally sound on understanding my customers, knowing what great storytelling looks like and knowing that stories that really resonate with people and winning hearts as well as minds with customers is really the thing no matter what happens in technology is always going to be true in marketing. And so I go in trying to learn as much as I can while staying true to some of those principles that will never change.
