ElevenLabs · AI voice and audio tools
Drop the translation agency; have an LLM translate app text on every code change
Much cheaper and faster than the agency and paid tool it replaced
What they did
What happened
- Stage
- scale
In their words
How ElevenLabs Turns Feature Launches Into a Growth Engine – Luke Harries
Luke Harries… 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.
Luke HarriesThe 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."
Luke HarriesSo, 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 BarnardAnd 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?
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More from this episode
- Turn every feature launch into a video, thread, landing page and fresh adsCalled the heartbeat of growth; no numbers given
- Feed your best and worst ad copy into a custom GPT that writes new adsNewly built; guest calls it really cool, no results yet
- Test ad formats with agencies, then hire motion designers to make variants in-houseMotion-design ads are the bulk of ads and work really well; no numbers
- Hire an in-house creator to make YouTube videos teaching the productChosen over AI avatars for quality; no results given
- Use AI to make ads for each audience, like podcasters or app makersDescribed as the way to scale creative; no results given
- Treat each ad channel separately and grow its spend 10-20% a weekGoogle search is still the biggest channel; no spend or return numbers
- Translate ads into other languages with AI dubbing and prompted copyGuest says it gets fantastic results; no numbers
- Run holdout tests in each ad platform and discount reported sales by the resultsExample: 500 reported conversions were only 200 incremental
Tags: llm-translation, github-action, ai