In the Quick Service Restaurant (QSR) industry, customer interactions with Point-of-Sale (POS) operators play a critical role in shaping the customer experience.
A key activity during these interactions is upselling, which directly contributes to increasing the Average Order Value (AOV). However, brand owners often lack visibility into these last-mile conversations between customers and operators. This is where technology and artificial intelligence (AI) offer transformative potential.
A key activity during these interactions is upselling, which directly contributes to increasing the Average Order Value (AOV). However, brand owners often lack visibility into these last-mile conversations between customers and operators. This is where technology and artificial intelligence (AI) offer transformative potential.
Real-Time Conversation Analysis
To address this gap, a pilot program done with two QSR brands in Bengaluru introduced a simple yet innovative tool: a small, button-like microphone worn by POS operators. This device streams live conversations between customers and operators to the cloud, where AI analyzes the dialogue in real time. The AI evaluates key aspects of the interaction, such as:
- Whether the operator adheres to the prescribed script,
- Whether upselling techniques are effectively employed,
- Common exceptions or deviations in the conversation.
Pilot Results: Measurable Impact
Across multiple pilots, the technology delivered promising outcomes:
- **AOV Increase**: Stores using this solution saw a consistent 10% rise in AOV, driven by improved upselling.
- **Training Insights**: The success of the solution was closely tied to how well operators were trained to follow instructions, highlighting the importance of operator preparedness.
- **Customer Insights**: The AI uncovered valuable customer preferences and inquiries, such as frequent requests for "Diet Coke" or "bubble tea," providing brands with actionable data to refine their offerings.
Brand Reception and Revenue Challenges
Brand owners were initially enthusiastic about the results, appreciating the enhanced visibility and data-driven insights. However, establishing a sustainable revenue model for this solution in the QSR sector proved challenging. While the technology was feasible to implement and desirable for brands to adopt, it struggled to justify itself as a standalone service within the QSR domain for the technology provider .
Exploring New Horizons
To overcome these limitations, the focus has shifted to testing the solution in other industries, such as luxury products and high-value goods. These sectors may benefit from outcome-based revenue models, where the technology’s impact on sales, customer experience, and brand perception could command higher value. Current efforts are underway to explore these use cases and refine the business model accordingly.
AI-driven conversation analysis for retail offers a powerful tool for unlocking insights, boosting AOV, and enhancing operator performance in retail settings. While its potential in the QSR industry is clear, its long-term viability may lie in tailoring the solution to industries with higher margins and more complex customer interactions. The journey to discover business modles by refining and scaling this different use cases continues.
Do you have any insights ? Please do share .
Do you have any insights ? Please do share .