The Value of Data-Driven Insights for QSRs

Diners’ perception of value is shifting; while convenience still matters, rising food prices mean cost is playing a bigger role than ever, Patrick Klein, RVP of QSR & Retail at LiveRamp, told Modern Restaurant Management (MRM) magazine. This means QSRs need to use their data to constantly understand what value really means for their customers right now.

"QSR sales data (POS) is crucial here. Identifying which menu items offer the best perceived value lets the QSR move beyond generic discounts and instead focus on smarter, more compelling offers like 'add-ons' or family meal bundles that help customers manage their spending while still feeling like they are getting a treat. Of course, different customer groups respond to deals in unique ways – for instance, families might be more deal-driven than single diners. A complete view of QSR customer data allows precise tailoring of these offers, turning reactive discounts into proactive strategies that build lasting loyalty."

QSR loyalty programs and mobile apps provide powerful signals for keeping diners coming back, Klein pointed out.

"By analyzing order frequency, offer response, preferred bundles, favored locations and social brand engagement, QSRs can create effective segmentation to focus their marketing efforts, such as identifying at-risk customers and sending them the optimal retention offers to entice them back. To truly measure the incremental lift of these efforts and optimize future media spend, QSRs can securely combine this loyalty data with broader consumer behavior data from partners in a privacy-preserving environment like a clean room."

What data points should QSRs prioritize to reach different value-seeking demographics? What is the role of personalization in reaching each segment?

While Point-of-Sale (POS) systems show what customers buy, they don't always tell you why they choose those options. To get the full picture, you need to combine the transactional data with demographic information (who your customers are, like their age or household size) and psychographic insights (their interests, values, and lifestyle). But the most powerful insights often come from behavioral data, which tracks what customers actually do, such as their ordering patterns, how often they visit, how often they use deliveries, and their preferred selections. 

In today’s crowded market, personalization helps QSRs cut through the noise, delivering relevant messages that maximize marketing ROI and build lasting customer loyalty.

Once these different pieces of information are collected, the key is to connect them all through a unified identity. This comprehensive view, potentially enriched with second- or third-party data from partners, is critical for scaling marketing efforts, measuring impact, and creating precise audience segments. This enables targeted campaigns, lookalike modeling, and cross-brand loyalty strategies.

Of course, personalization today is no longer a nice-to-have; it's what QSR customers expect. A majority of diners prefer discounts tailored to their past orders over generic offers, with QSRs offering personalized recommendations seeing a much higher chance of customers returning. For example, if a customer shows a preference for vegetarian options via the app, this can be used to serve them relevant ads on social media or Connected TV. Even fun elements like gamification in loyalty programs can be personalized to encourage specific behaviors, turning casual visits into consistent habits and deepening customer loyalty.

In today’s crowded market, personalization helps QSRs cut through the noise, delivering relevant messages that maximize marketing ROI and build lasting customer loyalty.

What are some examples of offers and data partnerships that are driving traffic and what can other operators learn from them?

Successful offers in the QSR space go beyond simple discounts; they focus on delivering perceived value and encouraging specific purchase behaviors that build long-term loyalty. Innovative approaches like Taco Bell's "Taco Lover's Pass" (a daily taco subscription) or low-cost monthly beverage passes have shown significant increases in customer lifetime value. These offers aren't just about immediate sales; they're designed to drive consistent, profitable habits.

To amplify reach and gain deeper insights, QSRs should embrace strategic data partnerships. Programmatic advertising, for example, uses location and search intent data (often from partners) to make real-time media buying decisions that drive foot traffic. A collaborative data ecosystem, facilitated by secure data clean rooms, is essential for combining QSR's first-party data with partner data — for example, ad exposure from publishers, purchase data from third-party delivery apps, co-marketing data from refreshment and event partners, and even cross-dining signals across a parent company's different restaurant brands.

This enables precise lookalike audiences, measurement of incremental lift from co-marketing, and accurate attribution of sales to specific media touchpoints, leading to more efficient media spend and better campaign effectiveness. 

Besides value, what are some issues data is suggesting is important to guests now?

Beyond just price, QSR diners consistently prioritize speed, convenience, and accuracy. Customers expect quick service, and common frustrations include long wait times and incorrect orders. Data from your Point-of-Sale (POS) systems, video analytics, and AI tools are crucial for optimizing operations, managing staffing, and streamlining kitchen workflows to meet these fundamental expectations. By leveraging technology to improve speed and accuracy, QSRs can significantly enhance the customer experience and build trust.

To amplify reach and gain deeper insights, QSRs should embrace strategic data partnerships.

Modern QSR consumers are also increasingly focused on quality, transparency, and healthier choices. They expect fresher ingredients, sustainable practices, and clear information about what's in their food. Additionally, experiential dining and globally inspired flavors are becoming more important, with QSRs redesigning spaces and offering exciting limited-time menu items.

Attitudinal and behavioral data are crucial for identifying these evolving priorities, directly informing menu development decisions, sourcing strategies, and marketing campaign themes. For example, if data shows a segment values sustainable packaging, QSRs can make a decision to invest in it and then use that as a marketing message, measuring the incremental loyalty it generates.

How can operators leverage data from loyalty programs and their POS to identify value-seeking guests?

For identifying value-seeking guests, POS data directly shows what customers consistently buy, such as dollar menu items, value meals, or family bundles, and what "extras" they might skip, providing clear behavioral indicators of a value-driven mindset.

Loyalty programs offer a direct channel for communication and provide deep insights into customer engagement, including visit frequency and average transaction value. However, fragmented data across POS, online ordering, and loyalty systems can hinder a complete customer view. Integrating these sources into a unified data warehouse, supported by identity resolution and powerful analytic and AI platforms, creates real-time 360-degree customer profiles that form a baseline for audience optimization. For example, if a customer's loyalty score shows a drop in frequency, this signal can trigger a personalized win-back offer as well as inform media plans to deliver new messaging on key channels.

Attitudinal and behavioral data are crucial for identifying these evolving priorities, directly informing menu development decisions, sourcing strategies, and marketing campaign themes.

Secure data collaboration with loyalty program providers, other restaurant brands in a parent company’s portfolio, third-party delivery apps and even various co-marketing partners such soft drink or sports brands via clean rooms can further enrich these profiles, allowing QSRs to benchmark their value-seeker segments against broader market trends and refine their media targeting decisions for acquisition and retention.

What is the best way to measure the success of an offer?

Measuring the success of QSR offers goes far beyond just looking at sales figures; it requires a deep understanding of Return on Investment (ROI) and accurate messaging attribution and incrementality measurement.

While basic analytics track overall performance, sophisticated attribution determines which specific marketing touchpoints actually lead to a conversion, like an in-store visit. Without precise attribution, QSRs risk misallocating their marketing budgets because they can't tell which parts of a campaign are truly effective, making it hard to optimize spending for the best results.

To get a comprehensive readout, QSRs need to track a variety of Key Performance Indicators (KPIs). Some commonly used KPI categories for QSRs include Financial Performance (e.g., Return on Investment, Average Order Value), Customer Engagement (e.g., Conversion Rate, Foot Traffic Lift) and Marketing Effectiveness (e.g., Cost per Acquisition, Customer Satisfaction)

A critical component for creating and analyzing these KPIs is leveraging data collaboration, where partners can contribute to a unified customer journey as a foundation for accurate cross-channel measurement, even for channels that are traditionally hard to measure, ensuring smarter budget allocation, personalized offer generation and more effective marketing.