OpenPromo
Redefining how businesses and creators manage and amplify their content.
Social Media Dashboard Mockup
TL;DR
Problem
Businesses and creators spend excessive time managing multiple platforms with little clarity on growth. Current tools like Buffer or Hootsuite focus only on posting.
Solution
OpenPromo unifies scheduling and publishing across platforms and introduces AI-driven boosting to amplify reach.
Impact (anticipated)
• Save hours weekly
• Drive higher engagement through AI promotion
• Scale from solo creators to agencies
Context
The social media management market is saturated with tools that solve only part of the problem. While platforms like Buffer and Hootsuite excel at scheduling, they fail to address the fundamental challenge: helping content creators and businesses actually grow their reach.
Frustrated creator illustration
Small businesses and creators struggle to manage multiple platforms effectively.
Small businesses and creators often lack ad expertise or budgets, making boosting and promotion inaccessible. They're forced to choose between expensive agency services or DIY approaches that rarely deliver results. Current limitations include:
Fragmented Workflows
Users switch between 3-5 different tools for scheduling, analytics, and promotion.
Limited Growth Tools
Existing platforms focus on posting, not on amplifying reach or engagement.
Expensive Ad Management
Professional ad services cost $2,000+ monthly, beyond most SMB budgets.
Complex Analytics
Data scattered across platforms makes it difficult to understand what's working.
OpenPromo addresses this by embedding AI-driven promotion into everyday workflows, making growth accessible to creators and businesses of all sizes.
Goals
Streamline Content Management
Provide a unified dashboard for scheduling and publishing across all major social media platforms, reducing workflow complexity.
Empower Growth with AI
Deliver smart recommendations and auto-boosting capabilities that help users expand their reach without requiring advertising expertise.
Support Diverse Users
Create scalable workflows that work for both individual creators and marketing teams, with appropriate permission levels and collaboration features.
Build Trust
Design a transparent, intuitive experience that feels approachable and builds confidence in AI-driven recommendations and automated actions.
Approach
Discovery & Research
Understanding the competitive landscape and user needs
Actions Taken
- • Competitor analysis (Buffer, Hootsuite, Later)
- • Interviews with 15 small businesses & creators
- • Survey of 100+ social media managers
- • Analysis of current workflow pain points
Key Insight
Users don't just want scheduling — they need help growing reach. 73% of respondents said their biggest challenge was "not knowing how to make content perform better."
Competitive analysis matrix
Competitive landscape showing gaps in AI-driven growth features.
Information Architecture & User Flows
Mapping workflows for different user types
Actions Taken
- • Defined workflows for creators and SMBs
- • Mapped scheduling dashboard journeys
- • Created user journey maps
- • Designed information hierarchy
Outcome
Clear separation between "Schedule & Publish" and "Boost & Analyze" workflows, with seamless transitions between modes.
User flow diagrams
Early user flows and information architecture explorations.
Prototyping & Testing
Iterating on usability and clarity
Actions Taken
- • Created wireframes in Figma
- • Ran usability tests with 12 users
- • Iterated on scheduling clarity
- • Refined dashboard navigation
Key Learning
Users needed more control over AI recommendations. Added manual override options and transparency features showing why suggestions were made.
Wireframe iterations
Wireframe iterations based on user feedback and testing insights.
Visual Design & AI Concepts
Creating the final design system and AI interfaces
Actions Taken
- • Built scalable design system (shadcn/Tailwind)
- • Explored AI-boosting UI concepts
- • Created high-fidelity mockups
- • Designed component library
Innovation
Introduced "Smart Boost" cards that show predicted performance and budget recommendations in an easy-to-understand format.
High-fidelity dashboard mockup
Final dashboard design with integrated AI boosting recommendations.
Impact
Save Time
Centralized scheduling expected to cut weekly workload by 60% based on early user testing feedback.
Boost Reach
AI-driven promotion can help users expand audience without ad expertise, targeting 2-3x engagement increases.
Scale Easily
Designed to support both solo creators and agencies with flexible pricing and team collaboration features.
Early Validation
"This is exactly what I've been looking for. The AI suggestions actually make sense and save me hours of research."
- Sarah, Content Creator (10K followers)
"Finally, a tool that helps with growth, not just posting. The boost predictions are incredibly helpful for budget planning."
- Mike, Small Business Owner
Reflection
What I Learned
Users value simplicity over advanced features at first; trust is built with clarity. The biggest insight was that AI recommendations need to feel collaborative, not automated. Users wanted to understand the "why" behind suggestions and maintain control over final decisions.
What I'd Improve
Balance dual audiences (creators vs SMBs) with modular workflows. The current design tries to serve both audiences equally, but future iterations should offer more customized experiences based on user type and business size. I'd also invest more time in micro-interactions to make the AI features feel more magical and less mechanical.
Next Steps
• Further usability testing with larger user groups
• Deeper AI integration with platform-specific optimization
• Refining analytics dashboard with actionable insights
• Building team collaboration features for agency use cases
• Exploring integrations with e-commerce and CRM platforms
Key Takeaway
Designing for AI-powered tools requires a delicate balance between automation and user control. The most successful features were those that felt like having a knowledgeable assistant rather than a black-box algorithm. This project reinforced the importance of transparency and user agency in AI product design.