This article is from a submission and does not represent the views of ChainCatcher, nor does it constitute any investment advice.
Marketing is always chasing the latest AI tools.
The rapidly changing market and continuously evolving platform algorithms demand that teams have extremely fast response times. The traditional marketing approach of 'slow burn' can no longer keep pace: the long chain of research, modifications, and testing not only slows down promotional efficiency but also gets directly eliminated in competition. Today, AI-assisted tools allow marketers' capabilities to be infinitely expanded, strategies to be adjusted in real-time, and efficiency to increase exponentially. However, simply relying on basic tool automation is not enough, as users are no longer willing to pay for one-way information bombardment.
Truly effective promotion must create emotional resonance between brands and users. This is exactly the philosophy conveyed by Vibe Marketing: by creating an atmosphere, enhancing participation, and delivering real value, users are willing to engage voluntarily rather than passively accept. This user-driven social signal is the communication power most favored by algorithms.
“Vibe Marketing” originated from a tweet by Andrej Karpathy, a member of OpenAI's founding team and former AI director at Tesla, which described a new programming experience called "Vibe Coding": "I was completely immersed in this vibe, enjoying an exponential explosion of productivity, even forgetting about coding." This was later transformed into a widely circulated meme by internet users who edited a picture by legendary music producer Rick Rubin with accompanying text. Vibe Coding quickly evolved into Vibe Everything. After being borrowed by the marketing community, this emphasis on atmosphere, “Vibe Marketing,” represents a brand new marketing approach—quickly validating by leveraging the efficiency magic of AI, creating “resonance” with users, and conveying brand value.
For project parties and users looking to build personal brands, X (Twitter) is an important battleground for market promotion and establishing voice. Whether at the initial stage of a project launch or during the early operation of a social account, large-scale exposure is needed through various means. Current common promotion methods include KOL publicity, advertising placements, event collaborations, etc., but these methods generally face the same problems: high costs, declining reach rates, rampant fake interactions, weakened user trust, and difficulty in measuring ROI.
It has been proven that only by relying on the genuine interactions of a large number of real users can algorithms be effectively leveraged and user trust won. Recent analytical reports have also confirmed this conclusion: compared to traditional methods, promotions realized through real user participation are not only more efficient and credible, but also significantly reduce costs, making them an ideal choice for project parties and individuals in the early stages of building social media influence.
The following are key indicators of effective content promotion on the X platform:
Account credibility and real interactions: Accounts with high-quality followers, genuine historical interactions, and no signs of bot activity are more trusted by algorithms.
Interaction type and quality: For example, comments and shares (especially Quote Retweets) have higher value, rather than just the measurable like count.
Duration of stay: User behaviors such as clicks, expansions, and time spent on content are increasingly becoming important signals for algorithms to evaluate quality content.
Content relevance and tag matching: The match of keywords, hashtags, topic relevance, etc., also significantly affects recommendation scores.
In such an environment, if you want to win? You can only use magic to combat magic—train a dedicated AI agent for real users, utilize the AI agent to find the right rhythm, and create resonance through real user interactions, building a dissemination loop that has both traffic and trust for projects and individuals.
Mojo GoGo: Real Users × AI Agents × Reward-Driven Social Media Promotion
Mojo GoGo is an intelligent platform that combines AI technology with social interactions, allowing brands and users to engage together. It uses a dual engine of AI agents + real user interactions to help projects and individuals break through the bottlenecks of social media promotion. On the same platform, brands can:
Automatically execute repetitive tasks with AI to easily handle complex operations;
Combine real user interactions to make every like, comment, and share more valuable;
Utilize AI to analyze data, quickly iterate strategies, and grasp the rhythm of dissemination.
Twitter Tasks is a core feature of Mojo GoGo that allows brands to customize AI agent tasks, operated by real users interacting with the AI bot on the X platform. As a result, brands obtain high-quality dissemination at low cost, while users earn rewards by completing tasks, creating a win-win cycle.
Through Twitter Tasks, brands can:
Customize AI interaction tasks that meet business needs
Engage real users in likes, comments, shares, and other social tasks to enhance content dissemination
Collect AI-driven data analysis to optimize task strategies and decisions
In simple terms, Twitter Tasks enable brands to drive dual interaction with AI and real users. This task-incentivized marketing (Task-to-Earn) model achieves low-cost, high-trust dissemination through real users completing tasks. Participating users can earn multiple rewards by completing tasks.
Comparison of different advertising channels: Personal KOL, KOL agency, and Twitter Tasks
Currently, personal KOLs and KOL promotion agencies are common choices for project parties and personal brands when promoting on the X platform. However, as mentioned earlier, these mainstream promotion methods have many problems, such as opaque ROI, interaction data filled with fake followers and bots, and difficulty tracking real user conversions. These issues undermine the reliability and measurability of promotional effectiveness. In contrast, Mojo GoGo's Twitter Tasks mobilize real fan groups for promotion through a Task-to-Earn incentive model, significantly improving dissemination efficiency and effectiveness, bringing higher ROI and user conversion rates for project parties and personal brands.
Let's illustrate with a specific case. Suppose a project or individual plans to promote on the X platform, and there are three options to choose from: personal KOL, KOL agency, and Mojo GoGo's Twitter Tasks.
Personal KOL: Suppose a KOL has 50,000 followers on the X platform, it is optimistically estimated that their real reach may only be 30,000 (60% reach rate), and their actual engagement rate is usually below 2%. Additionally, personal KOLs often lack professional data tracking tools, making it difficult to provide complete data from clicks to conversions, resulting in challenges in ROI assessment.
KOL agencies: Promotions through KOL agencies may involve more bot operations, making it harder to verify the authenticity of interaction data (such as clicks, impressions, and engagement). For example, a report released last year by Influencer Marketing Hub pointed out that some agencies inflate their data performance by purchasing fake interactions, undermining the credibility of ROI.
Twitter Tasks: Mojo GoGo's Twitter Tasks adopt a community-driven promotion model, recruiting 1,000 ordinary users (with an average of 100 followers each) within the community to utilize personal AI agents for content interactions (such as likes, shares, comments), theoretically reaching 100,000 followers. Compared to KOLs, the follower groups of ordinary users are more authentic, and their engagement rates are higher (according to Hootsuite's 2025 social media trends report, micro-influencers typically have 5,000 to 50,000 followers, with engagement rates ranging from 3% to 7%, far exceeding KOLs' 1% to 2%. The “ordinary users” utilized by Twitter Tasks are similar to micro-influencers, and their follower interactions are more likely to be genuine). Moreover, Mojo GoGo optimizes user selection and interaction management through AI-driven automation tools, ensuring the precision of content distribution and the transparency of data tracking, thereby enhancing ROI and user conversion rates.
By comparison, it can be found that Twitter Tasks not only outperform a single KOL in reach (100,000 vs. 30,000) but also have greater cost-effectiveness. The decentralized promotion model of Twitter Tasks significantly enhances the organic dissemination potential of content through real interactions by a large number of ordinary users. More importantly, Mojo GoGo's AI tools support real-time data analysis and conversion tracking, effectively addressing the issues of data opacity and difficult tracking of conversions in KOL promotions.
For marketing professionals familiar with marketing, it is evident that shifting budgets from expensive KOL promotions to Twitter Tasks for ordinary user promotions can not only effectively enhance dissemination but also establish stronger user trust through higher participation rates and authenticity, providing brands with a more efficient and transparent promotional choice.
How users can promote Roam through Twitter Tasks
For example, by promoting Roam's official Twitter content, users can complete real interactions through Mojo GoGo's task system, assisting in brand dissemination while earning dual rewards.
The operation process is as follows:
One-click access to the task platform
Directly jump to the Mojo GoGo task platform within the Roam App, where users can register to create their personal AI agent (bot). Users can customize the bot's username, avatar, and choose to have the AI generate an avatar, linking it to their personal X account.
Receive tasks
On the task page, users can see the designated promotional tasks for Roam X. Each task clearly labels the type of interaction (like, comment, share) and reward level. Users can manually select or one-click claim all tasks. After clicking 'Execute,' the AI bot will perform automatically.
Get rewards
After completing the task, users will receive dual rewards of Roam Points and Mojo GoGo Points:Like → Bronze Level → 10+10 Points
Comment → Silver Level → 30+30 Points
Share → Gold Level → 50+50 Points
Multiple tasks can be stacked, for example, completing “like + share + comment” will earn 180 points (90 Roam Points + 90 Mojo GoGo Points).
Roam Points can be redeemed for rights within the ecosystem, such as burning points for ROAM tokens, and in the future will unlock rare stickers and tokens for Mojo GoGo and other collaborative projects.
Furthermore, users can train the AI bot to associate with platforms like X, Telegram, and personal websites, customizing the number of tweets, topic tags, automatic replies, etc., making every interaction more valuable.
Roam × Mojo GoGo: Amplifying every interaction with Roam's global network
Mojo GoGo is the engine, while Roam is the fuel that drives this engine across the globe. As a leader in the global open wireless network, Roam has over 3 million registered users and more than 10 million WiFi node networks. Through collaboration with Mojo GoGo, the model of real user interaction + AI agent promotion is deeply integrated into its ecosystem.
When users complete social tasks, they not only help Roam expand brand influence but also accumulate various rewards such as Roam Points, Mojo GoGo Points, and future token rights. This is just the beginning; Mojo GoGo, as one of the collaborative projects of Roam Discovery Phase 1, will continuously expand the promotional matrix, teaming up with more quality projects to bring users more opportunities and incentives. Roam community users will also have priority access to multiple incentives, including Mojo GoGo and other collaborative project token rights, making every interaction more valuable.
With Roam's vast global network, these interactions not only amplify brand voice but also create a continuous stream of benefits for users. Roam transforms user participation into visible returns, making every user a key force in the growth of the ecosystem.
