The Challenges
Setting the Stage: Understanding the SaaS Industry’s Landscape and the Company’s Challenges Before Adopting AI
A fast-growing SaaS provider was facing pressure from rapid scaling. Their support team was overwhelmed with customer tickets, response times were long, and operating costs were rising. With customer churn on the rise, they recognized the need for a smarter, automated approach to stay competitive.
Before implementing TDWS AI, the company’s customer support relied heavily on manual processes. Live agents handled all queries, leading to bottlenecks during peak times. Customer satisfaction dropped as wait times increased, while internal teams lacked insights into recurring issues.
Challenges and Opportunities Before Implementing AI-Powered Support
- Rising customer expectations: Customers demand 24/7, instant support across chat, email, and in-app channels.
- High operating costs: Manual support is required for adding new hires each quarter, increasing costs without improving scalability.
- Data silos: Customer feedback and support tickets were scattered, making it difficult to identify recurring pain points.
- Inconsistent experiences: Resolution quality varied depending on which agent handled the request.
Missed growth opportunities: The support team was too busy firefighting, leaving little time for proactive customer success strategies.
Solutions Delivered
Strategy Implemented
- AI-driven chatbots: Introduced TDWS AI-powered chat assistants that handled FAQs, onboarding queries, and billing questions instantly.
- Smart ticket routing: AI classified and prioritized support tickets, directing critical cases to human agents while automating common responses.
- Customer sentiment analysis: Implemented AI-driven analytics to identify recurring complaints and track satisfaction trends.
- Knowledge base automation: Used AI to generate and update documentation, reducing repetitive inquiries.
Key Recommendations
Gnosys Digital and the SaaS provider partnered to design a holistic AI-powered customer support strategy. Together, we developed several key recommendations:
- Build scalable automation: Ensure AI handles at least 60% of incoming tickets without human intervention.
- Empower human agents: Utilize AI to surface suggested responses, enabling agents to resolve complex cases more efficiently and effectively.
- Unify customer data: Integrate all support channels into a centralized AI-powered dashboard for real-time visibility.
Continuous optimization: Use analytics from AI to refine FAQs, product documentation, and customer onboarding materials.
Technology Stack
- AI Engine: TDWS AI Platform
- Support Integration: Zendesk + Freshdesk API
- Knowledge Base CMS: WordPress
- Hosting: TDWS Cloud Servers
Analytics: Google BigQuery + Looker Studio
Results Delivered
10X
increase in accumulated traffic within one year
5X
increase in mobile-driven support interactions
- Increased customer retention: Faster response times led to repeat business and reduced churn.
- Enhanced customer satisfaction: Seamless support experiences across all channels boosted CSAT scores.
- Cost savings: Automation reduced reliance on hiring additional support staff.
- Increased brand trust: Customers perceived the company as responsive and tech-forward.
- Higher upselling opportunities: Support conversations became touchpoints for cross-selling premium plans.
