Role
Product Designer
Team
1 Product Owner
1 Product Designer
1 Business Analyst
3 Data Scientist
3 Software Engineers
Duration
5 Months
Background
The increasing complexity and volume of sales operations necessitated an innovative solution to streamline processes and enhance performance. By leveraging AI technology, we sought to automate routine tasks, allowing our sales team to focus on higher-value activities.
Problem Statement
Challenges: Our sales team faced several challenges, including managing a high volume of customer inquiries, generating personalized sales content, managing sales data privacy and maintaining consistent follow-ups. These tasks were time-consuming and often repetitive, leading to inefficiencies and missed opportunities.
Target Audience: The primary users were our internal sales team for this MVP, consisting of sales representatives, account executives, managers, directors, and support staff.
Defining the user problem Statment
Goal
The goal was to provide tools that would automate routine tasks, improve response times, and enhance overall productivity up to 60%.
Interview & Findings
We conducted 1-on-1 detailed interviews with our sales team to understand their pain points and requirements. Key findings included the need for quick responses to customer inquiries, personalized follow-up messages, generation of pre-sales and post-sales notes, access to company’s private sales data while maintaining the privacy for every user as per their role, and efficient management of sales leads.
User Interview and Findings
Business Process Diagram
The sales workflow starts with lead generation and moves through the following stages:
1. Lead Generation: Acquire potential leads.
2. SDR Engagement: Sales Development Representatives (SDRs) contact leads, answer queries, and arrange calls.
3. AE Meeting: Account Executives (AEs) hold meetings, understand client requirements, and take notes.
4. Proposal and Contract: If the meeting is successful, AEs send a proposal and secure the contract.
After the contract is signed, engineers begin working on the project.
End to End flow of acquiring a lead to project handover to development team
Functional Architechture / Features Configuration
The architecture integrates conversational and generational AI agents into the sales workflow through a user-friendly interface. Key MVP features include an AI assistant, presentation generator, data input, user profiles and notifications, user management with role assignments, and a performance dashboard with system stats.
Feature Configuration on user level
Design
Lo-Fi Dsigns
I created the app's basic concept using wireframes inspired by ChatGPT's UI, focusing on customizable conversational agents like chatbots. For generational agents, we implemented steppers to collect the necessary information for generating content.
Hi-Fi Designs
High-fidelity designs involved extensive iterations. We divided the main navigation into two categories: conversational agents and generational agents. Conversational agents function as chat assistants with smart search options, while generational agents serve as artifact generators for various scenarios. After continuous improvements and consultations, we achieved an impressive and simple design.
Results and Impact
The product was launched internally with customized AI agents for each department, doubling work velocity. Continuous feedback led us to make significant improvements.
User Feedback:
- High Satisfaction: Sales and HR team appreciated time saved on routine tasks.
- Efficiency Gains: Automated responses and content generation boosted workflow efficiency.
Learnings:
- User-Centric Design: Highlighted the importance of user involvement.
- Iterative Improvement: Continuous testing and iteration were crucial for refining the AI agents.
- Personal learning: I habitually document new insights and discoveries on Notion in every project. This practice not only enhances my understanding of the product but also serves as a valuable glossary for onboarding future designers.
End to End flow of acquiring a lead to project handover to development team
Future Work
Our aim is to evolve this tool into a SaaS product, addressing the growing AI transformation needs of all organizations. Key innovations will include enabling users to create custom AI agents, incorporating advanced analytics, and enhancing customization options to meet evolving requirements.