Racecar
Programmable Social Changes How Growth Works
Traditional social media was designed for broadcasting, not structured experimentation. Every user sees the same post. Testing requires publishing multiple variants manually, estimating split traffic, and piecing together partial analytics from external dashboards. Personalization often means sending users to separate landing pages, where drop-off increases and attribution becomes unclear.
This model limits serious growth experimentation inside the feed itself.
Base Frames changes that architecture.
Built on Base and running inside Farcaster, Frames allow dynamic, programmable content to render directly within a social post. The same post can display different variants to different users. Engagement signals are programmatically accessible. Reward logic can be automated.
Racecar exists because this infrastructure makes structured experimentation possible inside the feed itself.
Turning Frames into a Growth Operating System
Racecar transforms programmable social into a disciplined growth engine.
Within a single post, teams can render controlled A/B variants to different audience segments. One cohort may see a blue background. Another may see a white version. Instead of guessing performance, teams compare results within a structured experiment environment.
Because Farcaster identities are wallet-linked and interactions are accessible at the protocol layer, user behavior can be scored meaningfully. Likes, comments, replies, and shares are not just vanity metrics; they become signals that feed into segmentation logic. Different actions can carry different weights, allowing teams to identify high-value participants rather than treating all engagement equally.
Racecar also introduces leaderboard-style scoring. Users accumulate points based on interaction quality and frequency. This allows teams to segment customers dynamically and prioritize their most engaged audiences without exporting data to separate analytics systems.
Experimentation, Segmentation, and Personalization - Inside One Post
Racecar does not treat experimentation, segmentation, and personalization as separate workflows. They operate together.
The same post can render personalized content based on user score or segment membership. A top-ranked participant may see a "#1" badge inside the mini app and become eligible to claim a higher reward amount. Another user may see a different incentive tier or variant experience. All of this happens without redirecting users away from the feed.
This eliminates friction between discovery, interaction, and reward. Campaign logic, user scoring, and personalization remain native to distribution rather than layered on top of it.
Built Specifically for Base Frames
Racecar is not a generic analytics tool adapted for social media. It is designed specifically for the Base Frames environment.
On traditional platforms, rendering different content to different users inside the same post is not possible. Behavior signals are limited. Reward automation requires complex off-platform integrations.
On Base Frames, these capabilities are native. Racecar organizes them into a structured system: segmentation logic, controlled experimentation, weighted scoring, leaderboard mechanics, and personalized rendering - all operating inside programmable social.
Recognition
Racecar won Best Overall Prize at the Base Frames Hackathon in Singapore, highlighting strong product direction and execution quality in a competitive builder environment.
From Broadcast to Structured Growth
Social media has long been a distribution channel. Base Frames turns it into programmable infrastructure. Racecar provides the structure to use that infrastructure intentionally - enabling controlled experiments, meaningful segmentation, and dynamic personalization directly inside the feed.
For teams building on Base and Farcaster, growth no longer needs to rely on guesswork. It can be designed, measured, and continuously improved.