Sana: AI-Powered Engagement Assistant
An AI-driven assistant that automates customer engagement and enhances small business interactions on Facebook Pages.
Problem Statement
How might we help small business owners using Facebook Pages increase their customer engagement and streamline interactions using AI-driven automation?
Problem Background
Since the rise of e-commerce and social media marketing, small business owners have increasingly relied on Facebook Pages to connect with their audience. However, many struggle with:
- Delayed responses to customer inquiries, reducing trust.
- Inconsistent engagement due to lack of content strategy.
- Lack of analytics tools to track engagement performance.
AI-powered solutions like Sana can automate engagement, provide smart content recommendations, and track user interactions to optimize performance.
Research Insights
User Pain Points
Based on five qualitative interviews and five survey responses, we identified these challenges:
- Delayed Responses: Business owners take too long to reply to inquiries, leading to missed sales opportunities.
- Content Strategy Challenges: Users struggle to create engaging content and maintain consistency.
- Sales & Tracking Issues: Difficulty in linking engagement metrics with sales performance.
- Lack of AI Tools Awareness: Many are interested in automation but are unsure how to leverage AI effectively.
Supporting Data
- 90% of users expressed frustration with handling frequent customer inquiries manually.
- 80% of respondents found it difficult to track engagement and its impact on sales.
- 60% showed interest in AI tools for content generation and automated responses.
Feedback
Our research found that small business owners in Ontario and Nigeria were particularly interested in AI-powered chatbots to streamline customer interactions, reduce workload, and improve response rates.
Landing on the Solution
Based on our target users’ pain points, we focused on these features:
- AI-Powered Customer Inquiry Automation:
- Automatically responds to FAQs and escalates complex inquiries to the owner.
- Content Strategy Recommendations:
- AI suggests optimized post timing, hashtags, and engagement techniques.
- Engagement Tracking & Insights:
- Analytics dashboard for monitoring interaction trends and refining strategies.
Explanation of Solution
After testing our prototype with business owners, we found that:
- Automated responses improved response time by 60%.
- AI-generated content increased engagement by 40%.
- Personalized recommendations helped maintain consistent posting schedules.
User Flows/Mockups
User Flow Visual Representation
The flowchart illustrates how Sana, an AI system, automates responses and content management within Facebook Business Suite,:
- 🟠 User Action
- 🟢 AI Process
- 🟡 Decision Points
- 🔴 Escalation to Human
- 🔵 Notification Sent
Mockup
Low Fidelity Design
Sana Entry point at Facebook Business Suite Dashboard
Sana Dashboard – Screen Description
Sana is integrated as a dedicated tab within Facebook Business Suite, providing businesses with AI-driven tools to enhance engagement and streamline operations.
Hi Fidelity Design
Sana AI - AI-Powered Engagement Overview
The Sana AI dashboard provides an intuitive interface for small business owners managing their Facebook pages.
The AI Performance Overview section highlights key engagement metrics, including response rate (98% automated responses within 5 minutes), engagement increase (25%), and peak interaction hours (2 PM - 6 PM).
Below, the Recent Activities section logs AI-handled interactions, such as customer inquiries, content suggestions, and engagement spikes.
Users can take Quick Actions like configuring auto-responses, generating content, or viewing insights to optimize engagement.
The left-side menu allows seamless navigation through automation, content, analytics, and settings.
This dashboard empowers business owners with AI-driven automation to enhance social media engagement efficiently.
Future Steps
- Enhance AI customization by allowing businesses to train the assistant on their tone and branding.
- Integrate with Instagram & WhatsApp for multi-platform support.
- Improve AI recommendations by incorporating machine learning-based engagement predictions.
Learnings
Product Manager Learnings:
Muhanad Mukashfi Hagelamin Abdelrahim
This project reinforced the importance of user-centered AI development. The biggest challenge was balancing automation with human oversight, ensuring small business owners retain control while benefiting from AI efficiency. I also learned the significance of iterative feedback loops in improving AI-driven user experiences.
Designer Learnings:
Designer Learnings:
Jo Sturdivant
- Adapting to an Established Team: Joining the team in week 6 of 8 was challenging, as I had to quickly adapt to existing workflows, dynamics, and goals. This mirrors real-world situations where you often integrate into teams mid-project, and flexibility is essential.
- Work-Blocking for Efficiency: With only two weeks to complete the project, I learned the importance of a structured work-blocking system. This approach allowed me to manage my time effectively and meet deadlines under pressure.
- Making Data-Driven Design Decisions: Unlike my past projects, I had to rely on research conducted by others. This was a valuable experience in using pre-existing data to guide design decisions, helping me focus on the core insights without starting from scratch.
Developer Learnings:
Developer Learnings:
Vanady Beard
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As the back-end developer, I learned how important it is to create efficient and reliable systems that support the entire application. This experience also taught me the importance of optimising the database and ensuring the backend is scalable and easy to maintain.
Developer Learnings:
Stephen Asiedu
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As a back-end developer, I've come to understand the importance of being familiar with various database systems and modules. This knowledge enables me to build diverse applications and maintain versatility in my work. I've also learned that the responsibility for making the right choices rests on my shoulders, guided by my best judgement.
Developer Learnings:
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Developer Learnings:
Maurquise Williams
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- Process of Creating an MVP: Developing a Minimum Viable Product (MVP) taught me how to focus on delivering core functionalities balancing between essential features and avoiding scope creep.
- Collaboration in a Real-World Tech Setting: This experience taught me how to collaborate efficiently in a fast-paced tech environment, keeping the team aligned and productive, even while working remotely across time zones.
- Sharpening Critical Thinking and Problem-Solving Skills: This experience honed my ability to think critically and solve problems efficiently. By tackling challenges and finding quick solutions, I sharpened my decision-making and troubleshooting skills in a dynamic, real-world setting.
Developer Learnings:
Jeremiah Williams
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All in all this experience was very awesome I learned that in coding with others being transparent is key
Developers Learnings:
Justin Farley
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I learned how important communication is when working with a team. Communication provides understanding, advice, ideas, and much more. While working with the product team, I’ve found that communication keeps everything flowing smoothly. Working with a team also showed me that every member brings something different to the table and we all have to work together in order to align and meet our end goal.