See how this GenAI trailblazer used Koah to drive conversions with relevant, native, and user-first ads.

TL;DR

• DeepAI needed a monetization program that drove conversions—without compromising its UI

• After several new and traditional providers couldn’t deliver, DeepAI began serving users Koah’s contextual, LLM-native ads

• Today, DeepAI seamlessly balances predictable ad revenue with a best-in-class user experience 

About

DeepAI is one of the most comprehensive creative AI platforms on the market. Based in San Francisco, it provides a wide array of tools, spanning text-to-image, video, music, chat, and web-connected voice interfaces, that users can leverage without relinquishing the rights to their creations. Since its founding in 2017, DeepAI has partnered with leading innovators, including OpenAI, Wolfram Research, Undetectable.ai, Exa.ai, Fal.ai, and Prodia.com, and has been ranked #26 in A16Z's 100 GenAI Apps.

Challenge

DeepAI Needed a Monetization Model as Premium as its AI Tools 

Thanks to its savvy SEO strategy and first-of-its-kind text-to-image generator, DeepAI quickly attracted a lot of organic traffic. While plenty of these visitors became paid subscribers, Founder and CEO Kevin Baragona knew generating revenue from the app’s many free users was key to unlocking the next level of scale.

Kevin began running traditional banner ads alongside AI conversations. These ads yielded steady revenue, but ate up too much space on the page. Kevin worried that users wouldn’t be able to focus on DeepAI’s helpful answers with these irrelevant ads distracting them.

“A lot of professional and amateur artists use our platform to support their creative pursuits. Conspicuous ads could easily break their flows.”

To preserve the integrity of the in-app experience and keep retention strong, Kevin began experimenting with contextual ad providers. Although the first two solutions he tried integrated more naturally with the LLM interface, neither yielded the conversion lift he was hoping for. And they couldn't be adapted to real-time user intent because they relied on static revenue models optimized for predetermined monetization.

Just when Kevin had started to accept that answer engine marketing would always require a tradeoff between UX and conversions, he discovered Koah. As soon as he learned of its ability to balance both priorities—while also protecting user data at every step—he had to try it out.

“It can be hard to market your solution as ‘premium’ when you rely on ads for revenue. Koah helps us seamlessly balance our customer experience and revenue goals. ”

Solution

LLM-Native Placements That Convert Without Breaking the Flow

Kevin describes onboarding with Koah as his “fastest implementation to date.” After just an hour of pair coding, he and the team were able to integrate Koah’s context-native ads into DeepAI.

Before long, the Koah ads were generating as much revenue as the previous networks had—only this time, the gains didn’t come at the expense of user engagement or retention.

That’s because every prefix, suffix, inline, and image ad Kevin runs via Koah is carefully rendered to embed into AI conversations. Beyond aesthetic relevance, both the placements and the ads themselves are chosen based on the intent of the query and past performance data.

Take a user who asks DeepAI for help with a video editing project. They might receive a high-performing inline ad for a video editing class, alongside the organic answer. With Koah, relevance isn’t a barrier to conversions; it’s what drives them.

“Koah has solved the elusive conversion problem that all GenAI publishers face.”

Koah’s precise ad optimization ensures resonance with each user, but never at the cost of privacy. Koah collects the minimum amount of data needed from users, anonymizes and aggregates it, and never sells or shares it with other publishers or advertisers. 

Best of all, if Kevin ever has any questions about data privacy or ad formats, he can easily run them by Koah’s hands-on support team. The team is always available to answer quick questions over Slack, hop on a Zoom call to review performance metrics, and even ship new ad formats Kevin wants to try. With Koah by his side, he can iterate on his ideas almost as quickly as he dreams them up.

“The Koah team moves fast. They adapted their SDK to our user experience at record speed.”

Results

A Perfect Balance of Ad Revenue and Powerful UX 

Koah is the ideal supplement to DeepAI’s robust SEO strategy. Today, Kevin effortlessly converts user traffic into hard revenue, without compromising on the best-in-class experiences that attracted those users in the first place.

The results:

• 90% reduction in p90 response latency in 4 months

• 30% monetization fill rate, and growing

Kevin can’t wait to keep testing ad formats with the Koah team. They’re already collaborating on novel sponsored experiences that enable advertisers to integrate directly into AI conversations. With this unlock, users will get value without even leaving the DeepAI interface. Kevin is also eager to test out new surface areas, including placements on the DeepAI homepage and in the mobile app.

“When you’re building a nascent channel like sponsored AI ads, you can’t afford to place your trust in old-school solutions. LLM-native ad networks like Koah are the only way forward.”