Data and Analytics in QSR Delivery—Unlocking Personalization, Efficiency, and Growth

In the rapidly evolving world of quick service restaurants (QSRs), delivery has become a cornerstone of growth and customer engagement. As digital ordering and off-premise dining surge, the ability to harness data and analytics is no longer a competitive edge—it’s a business imperative. QSRs that leverage first-party data and advanced analytics are not only optimizing delivery operations but also creating hyper-personalized experiences that drive loyalty and sustainable growth.

The New Delivery Landscape: Why Data Matters More Than Ever

The pandemic accelerated digital adoption across all demographics, with digital restaurant ordering among older adults increasing by over 400% year-over-year at one point. This digital shift has generated a wealth of first-party data—information that QSRs can use to understand customer preferences, behaviors, and pain points. However, collecting data is just the beginning. The true value lies in integrating analytics into every aspect of the QSR business, from menu management and delivery logistics to marketing and loyalty programs.

The Power of First-Party Data

First-party data—collected directly from customers via owned digital channels like mobile apps, websites, and loyalty programs—forms the foundation for building direct, meaningful relationships. Unlike third-party delivery platforms, which often retain valuable customer insights, QSRs that invest in their own digital infrastructure gain access to rich behavioral and transactional data. This enables:

Personalized Offers: Tailoring promotions and recommendations based on past orders, preferences, and even time of day.
Menu Optimization: Identifying top-performing items, bundling opportunities, and emerging trends to refine offerings in real time.
Operational Efficiency: Forecasting demand, reducing food waste, and optimizing staffing through predictive analytics.

Frameworks for Connecting Data to Action

To unlock the full potential of data and analytics, QSRs should adopt practical frameworks that connect insights to business outcomes:

1. Connect Data to Action

Every data point collected should be tied to a specific business action—whether it’s a menu change, a new delivery option, or a targeted promotion. This closes the loop between insight and impact, ensuring analytics drive tangible results.

2. Value-Based Customer Segmentation

Move beyond generic demographics. Use analytics to segment customers by lifetime value, order frequency, and responsiveness to offers. This enables more precise incentive design and resource allocation, ensuring high-value customers receive the right attention and rewards.

3. Automate Experimentation

Leverage automation and AI to run rapid, low-risk experiments—such as A/B testing new menu items or delivery bundles—and use the results to iterate quickly. This test-and-learn approach accelerates innovation and helps scale successful initiatives across locations.

4. Invest in a Comprehensive Data Platform

A unified customer data platform (CDP) breaks down silos and provides a single source of truth for marketing, operations, and customer service teams. This is essential for delivering a seamless omnichannel experience and enabling real-time personalization at scale.

Optimizing Delivery: Balancing Third-Party and Direct-to-Consumer Models

Third-party delivery platforms offer reach and convenience, but they also create distance between QSRs and their customers. To build resilience and long-term value, QSRs should:

Balance Channel Mix: Use third-party platforms to acquire new customers, but incentivize repeat orders through owned channels where possible.
Negotiate for Data Access: Where feasible, seek partnerships that provide access to customer data from third-party platforms.
Differentiate the Direct Experience: Offer exclusive menu items, loyalty rewards, or personalized service through direct channels to encourage customers to order directly.

Real-World Impact: Data-Driven Success Stories

The business impact of data-driven decision making in QSR delivery is clear:

A major QSR chain unified fragmented data and marketing systems across more than 1,500 locations, enabling real-time personalization across email, web, and mobile. The result: a $470 million potential revenue uplift over three years, enhanced customer profiles, and the ability to anticipate supply-demand and launch new products regionally.
A global restaurant chain in Europe implemented a cloud-based analytics platform, enabling advanced segmentation and predictive analytics. By encouraging infrequent visitors to add just one more visit per year, the brand projected $35 million in additional revenue. This approach delivered a 5x increase in testing velocity, 75% reduction in reporting time, and up to 10% increase in guest count.
A leading Asian QSR brand built a full-featured customer data platform, enabling hyper-targeted offers and rapid test-and-learn experimentation. The impact: a 14% growth in sales, 5x increase in testing velocity, and a 500% increase in ROI.

The Road Ahead: Building Resilience and Loyalty

QSRs best positioned for the future are those that treat data and analytics as core strategic assets. By integrating intelligence into every facet of the business, QSRs can:

Respond rapidly to changing consumer behaviors and market conditions.
Deliver personalized, frictionless experiences that drive loyalty and repeat business.
Optimize operations for efficiency and profitability, even in the face of labor shortages and supply chain disruptions.

As digital transformation continues to reshape the industry, QSR leaders who invest in data-driven frameworks will not only survive but thrive—delivering value to customers, employees, and shareholders alike.

Ready to take the next step? Publicis Sapient partners with QSRs to design and implement data-driven strategies that unlock growth, efficiency, and customer loyalty in a rapidly evolving marketplace.