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How ElevenLabs Turns Feature Launches Into a Growth Engine - Luke Harries

Sub Club by RevenueCat · 2026-03-09 · 17 min

0:00--:--

Key moments - from our scoring

Substance score

68 / 100

Five dimensions, 20 points each

Insight Density14 / 20
Originality12 / 20
Guest Caliber16 / 20
Specificity & Evidence13 / 20
Conversational Craft13 / 20

ElevenLabs approaches growth by treating launches as the heartbeat of its marketing engine, where new AI models and features unlock viral moments across earned and paid channels simultaneously. Rather than siloing launches from marketing, Luke Harries' team coordinates with product and research to create comprehensive launch campaigns: compelling creative assets (video, animations, social posts) paired with optimized landing pages and localized ad copy across Meta, Google, and TikTok. The company employs two dedicated AI creative producers using tools like Motion, ElevenLabs' own text-to-speech, and AI-generated imagery to rapidly test creative variants at scale. For its $100+ million annual ad spend, ElevenLabs treats each channel as its own growth engine, starting with Google search as the largest performer, then scaling through segmentation, localization, and incrementality testing. Rather than simply flooding channels with AI-generated creative, the team uses AI strategically - building custom GPT models to adapt X posts into high-performing Meta and Google copy, creating in-house localization infrastructure, and dubbing content across 70+ languages. The conversation reveals how marketers increasingly function as creative directors managing AI agents, setting brand direction while AI handles execution, iteration, and personalization at scale.

Key takeaways

  • →Feature launches should be treated as growth engines coordinating product, creative, and paid marketing simultaneously rather than siloed product announcements.
  • →AI-generated motion design, voiceovers via text-to-speech, and music layering enables rapid creative testing while maintaining quality across multiple ad variants and platforms.
  • →Bottom-up channel optimization (treating Google, Meta, TikTok each as separate growth engines with their own funnels) outperforms top-down budget allocation and shows where the next scaling bottleneck lives.
  • →Custom GPT models trained on high-performing vs. low-performing ad copy can adapt brand messaging into platform-specific variations (X to Meta/Google) at scale faster than manual copywriting.
  • →Building internal localization infrastructure with LLMs and custom GitHub actions dramatically reduces costs and speeds up adaptation of ads across 70+ languages compared to agencies and expensive SaaS tools.

In this episode

  1. 1Building Growth Engines Through Feature Launches
  2. 2From Earned Media to Paid Ads: Leveraging Creative Across Channels
  3. 3Video Production Strategy: Motion Design, UGC, and AI Creative
  4. 4Deploying $100 Million in Paid Ads: Channel Strategy and Localization
  5. 5Measurement, Incrementality, and Budget Allocation at Scale
  6. 6The Future of Marketing: AI Creative Directors and Autonomous Agents

Mentioned

ElevenLabsRevenueCatDavid BarnardLuke HarriesMetaTikTokGoogleChatGPTMotionGitHubScribe v2ElevenCreative

Guests

Luke Harries

Topics in this episode

Meta adsGoogle AdsElevenLabsAI-generated imageryTikTok AdsGitHub ActionsMotion (creative tool)ElevenCreativeText-to-speech technologyCustom GPT models

Questions this episode answers

How does ElevenLabs coordinate new feature launches across marketing channels?

When a new feature or model launches, ElevenLabs creates a comprehensive campaign that includes viral social content (tweets, threads with video), optimized landing pages, and coordinated ad copy and creative variants for Meta, Google, and TikTok - treating the launch as a growth engine across earned and paid channels simultaneously.

What's ElevenLabs' approach to creating ad creative at scale without losing quality?

They employ AI creative producers with motion design backgrounds who use tools like Motion, ElevenLabs' text-to-speech, and AI-generated images to rapidly produce variants of ads. They also built a custom GPT trained on high and low-performing Meta and Google ad copy to adapt core messaging from X posts into platform-specific variations.

How do you measure ROI on $100+ million in annual ad spend across multiple channels?

ElevenLabs treats each channel (Google, Meta, TikTok) as its own growth engine with direct channel ROI tracking. They run lift studies within platforms to measure incrementality, accounting for people who would have converted anyway, and update incrementality adjustments quarterly to allocate budgets.

What's the future of marketing roles as AI gets more capable?

Luke predicts marketers will evolve into growth directors who set brand taste and direction while AI agents handle research, messaging, creative storyboarding, motion design, localization, and adaptation across formats - with marketers approving or rejecting the outputs each day.

How did ElevenLabs reduce localization costs and speed?

Instead of paying agencies and SaaS tools, they built internal localization infrastructure using a GitHub action and thin library that extracts strings and automatically localizes them via LLM prompts on every PR, then applies the same approach to dubbing and ad copy across 70+ languages.

What our scoring noted

Our reviewer’s read on each dimension, with quotes from the episode.

Insight Density

14 / 20

The episode delivers moderately dense, actionable insights on growth marketing and AI-driven creative production - particularly around treating launches as growth engines, building custom GPT tools for ad copy, localization strategies, and incrementality measurement. However, it lacks deep technical specificity or surprising claims; much of the advice is sound but expected (test variants, optimize channels, measure ROI). The discussion of AI creative directors and autonomous agents is forward-looking but speculative rather than battle-tested.

whenever we do a launch, part of the big bit is, okay, how does this translate into our Meta ads, into our TikTok ads?
we built a custom GPT where we've analyzed what's all the top performing Meta and Google copy and what's all our bottom performing Meta and Google copy

Originality

12 / 20

The core insight - packaging feature launches as multi-channel growth moments - is useful but not contrarian or particularly novel in modern growth marketing. The specific execution details (AI creative producers, custom localization GitHub actions, incrementality lift studies) show thoughtful engineering but represent methodical optimization rather than original thinking. The speculation about AI creative directors is interesting but underdeveloped and somewhat predictable given the industry trajectory.

the heartbeat of the growth team is working hand in hand with our incredible product and research team, such that when they're launching new features, new models, new capabilities, we put it through this growth system
we ripped out all the localization infrastructure. We built our own GitHub action

Guest Caliber

16 / 20

Luke Harries leads growth at ElevenLabs, a high-profile AI company, and demonstrates hands-on operator credibility: he discusses concrete decisions (building custom localization tools, hiring AI creative producers, deploying $100M+ in ads), not abstract theory. His seniority and direct involvement in scaling growth and paid spend at an AI-native company make him relevant and credible. However, he is not a founder or C-suite executive, which slightly limits caliber.

Luke Harries, who leads the growth team at ElevenLabs
we're on track to spend over $100 million in paid ads by the end of the year

Specificity & Evidence

13 / 20

The episode includes some concrete numbers ($100M ad spend, 20% week-on-week scaling targets, 70+ languages) and named tools (Motion, After Effects, GitHub actions, custom GPT). However, it lacks specific examples: no named competitor strategies, no actual performance metrics (CTR, CAC, ROAS figures), no concrete revenue or user growth numbers, and no detailed case study of a specific launch. Most claims remain conceptual rather than backed by hard data.

we're on track to spend over $100 million in paid ads by the end of the year
we've really lent into AI. As a side note, we initially went down the route of you pay an expensive SaaS app for localization

Conversational Craft

13 / 20

David Barnard asks solid follow-ups (e.g., pressing on UGC vs. AI creative mix, how to spend $100M wisely, measurement approach) and shows familiarity with the topic. However, the conversation rarely challenges Luke's claims or explores tensions; Luke's responses are generally unchallenged and sometimes vague (e.g., the future vision of AI creative directors remains speculative). The host misses opportunities to probe specific numbers, competitive disadvantages, or failure cases. The tone is cordial but not particularly probing.

Are you still using UGC though? And how do you think about UGC in this mix of AI-generated creative or AI-assisted creative plus the in-house assets?
How do you think about where to deploy that money with this fire hose of creative?

Conversation analysis

Computed from the transcript - who did the talking, and the words that came up most.

Most-used words

luke14growth14david13creative13barnard12harries12different11apps9elevenlabs9product9video9motion9team8launch8feature7best6

Episode notes

On the podcast: how ElevenLabs turns every new feature launch into a growth engine, how they're deploying over a hundred million dollars in paid ads, and why directing AI agents is quickly becoming a core skill for marketers and solo founders. This conversation is shorter than usual and will be featured in RevenueCat’s State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators. Top Takeaways: Turn every feature launch into a full-funnel growth engine Don't just ship and announce. Coordinate each release across organic posts, landing pages, and refreshed ad creative simultaneously so earned attention compounds into paid efficiency. Train a custom GPT on your own winning ad copy Feed your top and bottom performing Meta and Google copy into a custom GPT, then use it to rapidly translate brand messaging into proven high-performing ad formats. It turns institutional knowledge into a scalable creative tool.

Full transcript

17 min

Transcribed and scored by The B2B Podcast Index.

David Barnard: Welcome to the Sub Club Podcast, a show dedicated to the best practices for building and growing app businesses. We sit down with the entrepreneurs, investors, and builders behind the most successful apps in the world to learn from their successes and failures. Sub Club is brought to you by RevenueCat. Thousands of the world's best apps trust RevenueCat to power in-app purchases, manage customers, and grow revenue across iOS, Android, and the web.

You can learn more at revenuecat.com. Let's get into the show. Hello, I'm your host, David Bernard.

Today's conversation is shorter than usual and will be featured in RevenueCat's State of Subscription Apps report. Each episode in this series will explore one crucial topic and share actionable insights from top subscription app operators. With me today, Luke Harries, who leads the growth team at ElevenLabs. On the podcast I talk with Luke about how ElevenLabs turns every new feature launch into a growth engine, how they're deploying over $100 million in paid ads, and why directing AI agents is quickly becoming a core skill for marketers and solo founders.

Hey, Luke, thanks so much for joining me on the podcast today. Luke Harries: Excited to be here. David Barnard: I wanted to kick things off with how you think about growth. You're at ElevenLabs, you guys are launching tons of cool stuff, working on amazing products, but you've also been in the industry a while and have been doing this for a long time working on growth.

So, how do you think at a high level about growth? Luke Harries: Yeah. With growth, we think about building growth engines. And what's a growth engine for us is, it's a system which we track and we optimize and we set ambitious goals and we repeatedly take this engineering approach to marketing where we try and level up every time we do it.

And so, one specific way we do this is through big launches. And something which is very unique about AI is that when you get a new model that unlocks a new capability, which gives you a new viral moment. And so, the heartbeat of the growth team is working hand in hand with our incredible product and research team, such that when they're launching new features, new models, new capabilities, we put it through this growth system, and that normally translates into what's hopefully a really viral moment.

For example, we have the world's best speech-to-text model. And so, when we release Scribe v2, it's like, "Okay, let's do an incredible video and tweet thread to really show the world how to do that and top all the benchmarks." But then that also translates behind the scenes into a world-class landing page, sort of time to update all your different Meta, your LinkedIn ads, your Google Ads. So yeah, the launches are really the heartbeat for us.

David Barnard: Yeah. I think this is really overlooked in the broader industry. And when you're working on a feature, ideally you're working on something that people are going to care about, and that wouldn't be just your users. It's a great opportunity to expand that messaging beyond just putting it in the app and putting it in app banner.

Although, some people don't even do that. A lot of apps don't even have a on launch open, what's new, and, "Hey, check out this new feature or a tool tip," or those kind of things to even hint at existing users that this new capability is there. Much less using all that engineering effort and the creativity that goes into this new feature as a moment to get more attention. And of course, people are going to be listening like, "Oh, well, look, earned media is so hard to get these days."

And it is, and ElevenLabs has an easier time than a lot will have getting that earned media, but you don't know until you try. And I think more apps should be trying. And then how do you think about taking those launch moments and using the ideas, the new features and things like that in your paid assets as well? Because it's not just about getting earned media, it's about using these new features and that creativity to get attention, even if it's paid attention.

Luke Harries: Yeah, 100%. So, whenever we do a launch, part of the big bit is, okay, how does this translate into our Meta ads, into our TikTok ads? And so, we have a ElevenLabs app, which has all the best creative models, whether it's speech, sound, effects, music. And as part of that we release, for example, the image and video feature within it.

As part of that, you then go, "Okay, what are the ads that we should do? What are the different hooks?" And as you're thinking and iterating on that core messaging for the X post, you're also thinking and integrating for the different ad copy. And one of the new things we've actually just built, which has been really cool is we built a custom GPT where we've analyzed what's all the top performing Meta and Google copy and what's all our bottom performing Meta and Google copy.

So, we normally take what's our brand X post and then we pass it through this custom GPT, which will then iterate on it into the high-performing and [inaudible 00:05:08] and Google copy. And then another big bit, which I'd be happy to dive into is also we want to create lots of different variants of images, of videos, of statics in order to see what will drive conversion. David Barnard: Yeah. I did want to dive more specifically into video.

I mean, between Reels and TikTok, and I mean, even a good X post with a video is going to generally perform better than just a thread without any kind of example. How do you think about in generating these assets, when to use AI creative, when to lean into UGC, and when to just team create assets? On your blog post you talk about, put the founder in front of a camera and loom showing off the product. People don't often do those kind of things.

But again, if you're building something worth attention, you can probably do a little video like that. So, how do you think about balancing all of those? Luke Harries: Yeah, 100%. I think this will change a lot in the next year or two, but now in Feb 2026, what we've found best is, normally actually you start with agencies.

So we started with agencies, you're testing lots of different formats, you work out what fits, but then you want to bring it in-house, like really optimize the quality, but also scaling up the quantity. And so, we have two people which have the job title, AI creative producers, and their task is every day they're just obsessed. They're using tools like Motion. They're obsessed with, "Okay, what's the data?

What's working so far? What are other companies in the space doing?" And then they're coming up with new creative ideas and then rapidly iterating and testing it. At the moment, what we found works really well for our core apps, our web app is they create with after effects really great motion design.

So, that's their background. They are motion designers, but then they layer in with text to speech, voiceovers using ElevenLabs with the music, and that enables you to do rapid testing because you can test different hooks with motion design, you can test different voiceovers, different music. So you get nice little variants, but you also are able to keep the quality bar really high. And other things we use to boost production is lots of the AI-generated images we also incorporate into the motion design.

David Barnard: Are you still using UGC though? And how do you think about UGC in this mix of AI-generated creative or AI-assisted creative plus the in-house assets and you have motion designers on staff? You've got a lot going on. Are you also working with UGC?

Luke Harries: Yeah, we do three main types of video production in-house. The first one is the motion design, and that's still the bulk of our ads and works really well. You can get the quick hooks and variants to really see what messaging resonates. And particularly with this AI abstract, UI-based flows, they're great ways to show it.

The other team we have is a motion design team, but focused on brand videos and launches. And so they spend longer amount of time, fewer variants. And then we also have a in-house creator called Alec who has a YouTube channel who just shows how do you get the very best out of these tools? And it's more like person in front of the camera.

I think there's definitely a world where we can try supercharging that in future for the educational side using the avatars. But for now, we really care about quality as well as quantity. And actually, a person in the studio making really fantastic educational videos is a great way to do that. David Barnard: Yeah.

You shared with me before the podcast that you're on track to spend over $100 million in paid ads by the end of the year. How do you think about where to deploy that money with this fire hose of creative? Because one approach and what a lot of people are doing is like, "Okay, AI is now helping us create so much more creative. Let's just throw money behind it and just see what sticks."

Is that what you're doing with 100 million or how are you approaching that? Luke Harries: Not quite, no. So, the way we view about money and spend on channels is we actually view, yes, we have the top down view, but we're mainly thinking bottoms up. And so, we treat each channel as its own growth engine, and actually our biggest one still is Google and Google search.

And so, what we're doing is like that, we're obsessed of, okay, how do we make really great ad copy? How do we localize it to all the GOs? How do we have really high converging landing pages? And then it's like, okay, week over week, how do you scale it 10%, 20%.

For Meta, it's a similar one where yes, you want great amount of creative, but you also want really high quality. And then when I think about scaling creative in order to unlock, what you actually want to do is more segmentation. So, you are maybe using AI to help before maybe if you just had a general like, here's how to make images and videos with AI, but now you can go that one level deeper, like here's how podcasters or here's how people making apps can create with image and video.

And you can use AI to do that like personalization segmentation. The other really big unlock for us has been the localization side, and that's where we've really lent into AI. As a side note, we initially went down the route of you pay an expensive SaaS app for localization, you pay for an agency to then who have people to localize it. But I kept on having our team just sending screenshots of ChatGPT being like, "Oh, we should use this phrasing instead is way better."

And I was like, "Well, if the LLMs are way better at translation than these agencies and expensive tooling." So, we actually ripped out all the localization infrastructure. We built our own GitHub action and there's a thin library which just extracts the strings or wraps all the strings. And then each time we make a PR to our repo, it just sends it with a prompt per language about the localization guide, and that means we're able to localize way cheaper and much faster.

And then once we've also localized the apps, you're then able to localize all the ads. There's stuff like our dubbing model, or again, just passing the copy with good prompts gets fantastic results. We think bottom's up, what's that next bottleneck for us to scale another 20% week on week, month on month? And then you start going through, okay, first of all, it's like funnel optimization, then it's probably starting to think about stuff like localization and so forth.

David Barnard: And how do you think about measurement? And are you mixing in brand and other things that are harder to measure? I mean, with $100 million to spend, there's a lot more room to experiment and potentially put money into things that will pay off more in the long run. But are you looking at dollar for dollar ROI?

Are you looking at for some channels, but not others? How do you think about measurement and effectively spending that? Luke Harries: Yeah. So, ElevenLabs, we have different bits of the business.

We have mobile, self-serve web and enterprise, and each one of those we think about brand and performance a bit differently. Where the bulk of spend so far, which is still like self-serve web, which has nice parallels to mobile, the way we think about it is like direct channel ROI, and you can be more direct response when you're dealing with consumers or prosumers. And so, there you're able to do ... Meta has lots of great tools.

They tell you about what the different conversions and so forth are. But the important thing to do is to run the lift studies within the platform, which actually do an A/B test with holdout groups to tell you ... Because for a brand like ElevenLabs where lots of people already know, you often end up with lots of people would have converted anyway. And particularly as you start doing stuff like retargeting ads, so that's able to give you, yes, you were saying that 500 people converted.

Actually, there was only an incremental 200 because 300 people converted anyway. And then our system so far is we pull all that data from the platforms, we then add incrementality adjustments, which we then update every quarter, and then that's how we use to allocate our budgets. David Barnard: Yeah, fascinating. You're doing it at scale, not a lot of companies are these days in this space.

The thing I wanted to wrap up on, and we kind of already touched on it, but are we headed to a future where marketers are more like AI creative directors? And how do you see this going moving forward with leveraging AI in marketing? Luke Harries: We actually did this exercise internally around what does the future of marketing look like? And our sense is probably each product will have a growth person who has really great taste and really great ideas.

And then you work with the engineering team and you go, "Okay, I'm going to launch a product." So say we're launching image and video creation in our app, you then chat with an agent and you're like, "Hey, we're launching this product." It then literally checks through your code base, it checks through online competitive landscape, it reads through all your internal docs and knowledge based on your personas, helps you craft the core of the messaging. Then it goes one step further of like, okay, let me help storyboard out what does this launch video look like, and how does that actually translate then when you put proper AI-generated motion design as the models get better, maybe you're incorporating some avatars to show how do you actually use the product.

And then that launch point goes to performance marketing and performance marketing creative. And the idea is probably you wake up every single day and you have 10 to 20 high performing ads where you can like, you've set that brand direction, you're that creative director of where we're going and apply your taste, but then you're like, "Yes, I like these. No, I don't like these or these need to be tweets. You're chatting with it maybe with voice."

And then it goes and takes that one concept and adapts it for the different screens, whether it's horizontal, vertical, it then localizes it into the 70 plus languages. So, this is ideally what we're going to build end to end with the ElevenCreative, good amount of work to do. I don't think anyone's there yet. I think people are saying that we'll be there close within the next couple of months, but yeah, should be a lot of fun.

David Barnard: Yeah, it's going to be a fascinating couple of years. I mean, it already has been the past couple of years as we've integrated more and more. And it does just feel like each person is able to do more and more with the aid of AI, and that's just going to continue accelerating. So I love that idea of one person in that kind of growth product position, managing a bunch of agents who help build those things out.

I think is the way a lot of this is going to go. I like that. Luke Harries: 100%. The other bit, which could be pretty cool is I imagine lots of your audience who are also like the solo builders, the ideal is maybe even you just have connect something to your GitHub.

Every new PR is just monitoring what you're shipping, and then you just go, "I have an idea." It builds the feature, it then takes the feature and runs it through the whole launch process and spinning up your ads. So, potentially the first billion-dollar startup could be built on that. David Barnard: Yeah.

Well, this is so much fun chatting through this. It's going to be fascinating to see how things go the next few years. And ElevenLabs is right at the center of it building a lot of this. So, as we wrap up, anything else you wanted to share, job you wanted to hire out?

I know y'all are working on some stuff with a product called Flows that'll come out later this year. Luke Harries: Yeah. I think main one, we're hiring lots of mobile engineers, which I know you have lots of fantastic audience. If you want to trot out, you can just sign up, use the ElevenCreative product or download any of our mobile apps, and hopefully you'll find it useful for your own growth and performance marketing, and excited to keep working with you.

David Barnard: Awesome. Thanks so much. Luke Harries: Cool. David Barnard: Thanks so much for listening.

If you have a minute, please leave a review in your favorite podcast player. You can also stop by chat.subclub.com to join our private community.

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