How BlossomFlower Delivery achieved $266,000+ in annual customer support savings

Balancing exceptional customer service with cost efficiency is a challenge for many businesses, especially in industries with high customer interaction volumes. For BlossomFlower Deli very, a leading online florist known for its nationwide delivery services, rising customer support costs became a growing concern.

To address these challenges, the company partnered with Pointai, a leader in AI-powered customer support solutions, to streamline operations, reduce expenses, and enhance service efficiency.

BlossomFlower Delivery is a dynamic US-based service offering fresh, exclusive bouquets with fast ordering and nationwide delivery. Its quality products and innovative logistics drive steady growth.

About company

Rising costs and operational inefficiencies

BlossomFlower Delivery’s nationwide success in delivering fresh flowers came with a significant operational burden: an overstretched and costly customer support system. Managing a daily influx of 1,000 customer inquiries, the company relied on a 60-agent support team, incurring an annual operational cost of $432,000.

This expense stemmed from a monthly salary of $500 per agent, along with an additional $100 per agent in service-related costs. Despite this investment, response times ranged from 15 to 30 minutes, leaving customers frustrated and resulting in a low CSAT score of 1.9 out of 5.

These inefficiencies made it clear that a more scalable, cost-effective, and responsive customer support model was needed to sustain growth while enhancing service quality.

Challenge

Harnessing AI for automation

Pointai introduced a transformative AI-driven approach to streamline BlossomFlower Delivery’s customer support operations. The premise was clear: a significant portion of customer inquiries were repetitive and predictable, making platform prime candidates for automation.

To validate this assumption, 5,000 customer support tickets were analyzed, revealing that 92% of inquiries could be efficiently handled by AI. This insight laid the foundation for an AI-powered support system designed to automate routine queries, reducing agent workload and allowing human representatives to focus on complex, high-value interactions.

By implementing this data-driven automation strategy, the company aimed to reduce operational costs, improve response times, and enhance customer satisfaction without sacrificing service quality.

Solution

A strategic and gradual integration

The deployment of Pointai’s AI assistant followed a phased, data-driven approach to ensure seamless adoption and operational stability.

The process began with the introduction of Luna, an AI-powered virtual assistant, initially tasked with managing 10% of incoming customer inquiries. Weekly performance assessments evaluated Luna’s accuracy, resolution rates, and customer feedback, allowing for incremental workload increases. As the AI system demonstrated consistency and reliability, its scope expanded to handle 82% of the daily ticket volume — significantly reducing agent workload while maintaining service quality.

This dual-layered strategy — blending AI automation with human expertise — ensured that routine queries were resolved instantly while high-value interactions received the necessary human attention. The result was a balanced, scalable support model that optimized response times, reduced operational strain, and maintained customer satisfaction.

Implementation

To further enhance efficiency, Pointai implemented an AI co-pilot designed to assist human agents with complex cases.

This tool provided:

Concise summaries of customer inquiries to streamline issue resolution.
AI-generated response suggestions to enhance agent productivity and consistency.

82% of daily tickets were successfully resolved by Luna, demonstrating AI’s ability to handle high inquiry volumes with accuracy.

Ticket automation

AI-powered queries achieved response times of just 2.1 seconds, compared to the previous 15–30 minutes for human-handled cases.

Response time

Annual operational expenses dropped by 61.6%, decreasing from $432,000 to $166,000, significantly reducing financial strain.

Cost reduction

The overall CSAT score increased from 1.9/5 to 3.7/5, marking a 94.7% improvement, indicating a significantly enhanced customer experience.

Customer satisfaction

Additionally, the AI co-pilot further improved agent efficiency and response consistency, leading to a CSAT increase for human-handled complex queries to 2.5/5. Given that Luna managed 82% of inquiries, an analysis suggests that AI-handled cases likely achieved a CSAT score near 4/5, reinforcing the effectiveness of AI in managing routine customer interactions.