Navigating the measurement gap: A guide for QSR analysts

With inflation on the rise, consumer spending is down and many QSRs (quick-service restaurants) are seeing declining customer traffic. 

The pressure is on analysts to support effective AI-driven personalization, track disjointed consumer behavior across channels and prove campaign ROI.

In this article, I’ll cover how: 

• 54% of consumers say they plan on cutting back on non-essential spending including eating out.

• QSRs require sharper diagnostics to understand customer behavior across channels and location.

• QSR brands have access to extensive customer data to support more effective AI personalization, which puts additional pressure on analysts to turn raw data into effective campaign strategies that demonstrate clear ROI. 

• Data is siloed across platforms—leading to fragmented measurement and preventing analysts from understanding customer behavior across channels, prohibiting them from gaining the holistic view of customers that’s required for effective personalization. 

• Zappi delivers diagnostic depth with 60% more predictive accuracy than legacy pre-testing. 

• Zappi overcomes the limitations of cross-channel measure gaps—centralizing insights, offering AI-powered verbatim analysis and category benchmarks that illuminate consumer behaviors. 

Consumers are spending less on eating out, especially at QSRs, as the result of rising restaurant prices, inflation, industry-wide layoffs and worries over tariffs. As a result of the current economic climate, 54% of consumers say they plan on cutting back on non-essential spending—including eating out. 

A recent Conference Board survey shows that food away from home is the top expense consumers are planning to cut back on or eliminate in order to manage rising costs. For the sixth month in a row, QSRs report a net decline in customer traffic—with 46% reporting that they’ve had fewer customers than they did in July 2025. Even McDonald’s saw a 3.6% decline in same-store sales in the first quarter of 2025—marking its biggest decline since the pandemic. 

Despite consumer spend trending downward overall, some QSR brands and locations are showing strong performance while others are seeing a drop in customer traffic—highlighting the need for sharper diagnostics to understand granular customer behavior across stores and locations. 

For example, drive-thru visits are down 5% to 8% year-over-year in 2025. The percentage of total QSR orders placed through this channel has dropped from 83% in 2020 to 65% in 2025. In comparison, digital and mobile-app orders are up.QSR takeout traffic increased by +15.5% YOY (versus +9.5% in 2024), showing consumer preference for cost-savings, flexibility and app-based convenience.

As a result, QSRs require sharper diagnostics to understand granular customer behavior across stores and locations to help them create effective, data-driven campaigns and promotion strategies. Currently, there is increasing pressure on brand analysts to help brands quickly and reliably identify which products, campaigns and promotions work best for different customer segments across locations.

82% of companies are using AI personalization to improve the customer experience and 70% of restaurants send personalized offers to customers. 

In the QSR industry, personalized offers and recommendations lead to a 8-12% jump in average order value. AI-based personalization is a big buzzword in QSR in 2025, putting pressure on brand analysts to turn raw data into a strong ROI-driven strategy that justifies AI investment. 

But despite the wide-spread availability of extensive consumer data that can help support effective personalized customer experiences, cross-channel measurement gaps prevent analysts from accessing this data and creating the 360-degree customer profiles necessary for effective personalization. 

Data is typically soiled away across platforms, while each channel measures and reports on data differently—blocking effective measurement and insight generation. This data is often fragmented, incomplete and lacking in quality. In addition, traditional tracking methods such as third-party cookies are declining—making it harder to track individual or consumer households across channels. 

These cross-channel measurement gaps make it difficult to gain visibility into the full customer path and prevent brand analysts from developing a unified, holistic view of customers' behavior across channels. Without a holistic view of the customer journey, it can be difficult to justify marketing spend and prove campaign ROI. 

To help bridge these gaps, you need to break through silos and centralize your data and analysis. That's where Zappi can help you overcome these barriers by centralizing insights, offering built-in, powerful AI-based verbatim analysis and providing category benchmarks to help you assess consumer behaviors and reactions. 

Zappi integrates your channel insights, providing a centralized dashboard for data collection, storage, testing and analysis across channels—including digital, social and OOH. 

 Going beyond basic metrics and delivering diagnostic depth, Zappi offers 60% more predictive accuracy than legacy pre-testing—allowing you to more accurately forecast an ad’s potential impact on ROI. The Zappi platform also provides detailed insights into how your concepts and creative is received by customers, giving an in-depth look into their perceptions and reactions. Ultimately, Zappi allows you to develop a detailed picture of consumer’s responses to your brand and outputs, from emotional range and intensity to purchase intent and brand appeal. 

You can even use Zappi's subgroup analysis feature to get an understanding of how different segments respond to your inputs, segmenting your results based on demographics, behavioral data and psychographics. This segmentation can provide vital performance insights and help you justify ad spend. For example, it may highlight that while a campaign underperformed across segments, it directly drove sales among Gen Z consumers in inner city branches. 

Agility is essential in the fast-moving QSR space. Beyond depth, Zappi also provides speed with a suite of agile and fast tools—allowing you to rapidly test your ad concepts and creative with your target consumers at the earliest stages of development. Zappi can provide insights in as little as six hours, with an average of twelve hours from idea to insight—allowing you to make fast, data-informed decisions that keep pace with changes in customer behavior and preferences and rapid market shifts. 

Additionally, Zappi’s AI Quick Reports help to automate and improve the efficiency of your research analysis. Use this feature to quickly turn raw data into actionable insights and create comprehensive, custom research reports. Our AI-powered verbatim analysis provides in-depth insights, scored against industry benchmarks in the QSR space, allowing you to quickly assess your creative's performance on factors such as emotional impact, purchase intent and brand appeal.

Zappi allows you to efficiently balance speed with rigor throughout high-pressure promo and ad cycles. 

Delivering speed, agility, and impact—it’s an essential tool for unifying your customer data across channels and delivering the data insights needed to guide strategic thinking and decision-making. This helps you effectively navigate variable consumer behaviors across locations and segments, competitor strategies, any decline in consumer spending and seasonal variations.