Identifying churn & potential revenue increase for a leading QSR chain with 200+ outlets.

Business Overview

This F&B brand is widely known for introducing premium 'glass-bottled milkshakes' in India and operates over 200 milkshake restaurants and QSR outlets across the country

Challenges Before Storefox

Typical to large-scale retail operations, the brand faced significant challenges across its extensive footprint, including:

• Revenue Loss: Declining revenue across multiple stores often stemmed from challenges in identifying root causes and addressing them. For example, rising demand for out-of-stock products led to lost sales opportunities, while insufficient upselling efforts reduced the average order value.
  
• Unclear Operational Inefficiencies: Hidden inefficiencies disrupted store operations and negatively impacted customer experience, yet identifying these issues across a large store network remained complex. Common examples included delays caused by payment processing issues, malfunctioning equipment preventing the sale of star products, and poor store hygiene due to lapses in cleaning schedules.
  
• Customer Experience: A lack of visibility into customer interactions resulted in missed opportunities to enhance satisfaction and enable loyalty. Issues like inconsistent product quality due to insufficient training, unprofessional staff behavior, and long waiting times for order preparation frustrated customers. 

Enter AI-Powered Remote Monitoring & Observability Intelligence with Storefox

Storefox’s audio analytics solution was deployed across 40 high-priority outlets, introducing a game-changing approach to customer experience monitoring.

Our AI-driven platform analysed 35,000+ interactions, provided personalised improvement plans for each store, empowering the team to achieve their performance targets. These data-backed strategies focussed on addressing issues, identifying high impact opportunities, and driving outcomes.

The Impact

• Real-Time Conversation Analysis:  Storefox devices captured customer interactions with store staff across 40 stores, revealing patterns and anomalies at a remarkable scale for the team, with insights powered by advanced Large Language Models (LLMs). 
• ‍Dynamic Insights Delivery: Continuous monitoring and actionable insights allowed the team to act quickly on occurring trends and operational pain points.

The Results that Matter

Storefox didn’t just identify problems—it helped the brand with live monitoring to track the immediate impact of implemented changes. This visibility led to measurable improvements including:

• Customer Retention Risks: Identified 2700+ customers who were at risk of churn due to poor product quality experiences, making this pain point resolution a key priority for boosting satisfaction and loyalty.
• High-Impact Opportunities: Pinpointed the top stores that present the highest opportunity for driving the overall performance improvements, allowing for a more focused and impactful approach.
• Revenue Growth Potential: Recognised an opportunity to increase the average upsell pitch rate from 26% to 80% by continuously monitoring and tracking this metric to ensure progress & sustained growth. 
• Customer Experience Enhancement: Identified key areas under the umbrella of ‘Revenue Blockers’ and ‘Customer Experience’ impacting overall experience, including inventory gap, payment issues, product quality concerns, long waiting times, staff behavior, and store hygiene. 

By addressing operational and customer experience bottlenecks instead of investing heavily in product modifications, the brand achieved faster, more cost-effective results.

By bridging the gap between qualitative data and actionable insights, Storefox.AI delivered more than just a solution—it became a growth catalyst.