Customers of quick service restaurants (QSR) expect fast, efficient service and a seamless ordering experience, whether in-store, online, or through a mobile app. They also want customizable options delivered at a competitive price.
But delivering this level of service for an affordable price is more difficult than ever for QSRs, which have been hit hard by inflation in recent years. In particular, higher food costs have forced many to raise menu prices, which in turn can reduce order quantity.
As QSRs walk the tightrope between maintaining profitability while offering the value customers expect, data-driven marketing initiatives can help your business maintain customer loyalty and attract new patrons, even in a challenging economic environment.
What is QSR marketing?
QSR marketing typically involves a mix of promotions, loyalty programs, and targeted advertising, all aimed at enhancing the customer experience and encouraging repeat visits. Marketing initiatives may also leverage data analytics to understand customer behavior, enabling brands to streamline ordering processes and target customers with highly relevant offers.
Why does a data-driven approach matter in QSR marketing?
A data-driven approach enables QSRs to reach customers with greater precision, improving both engagement and return on investment (ROI). For an industry that operates on thin margins, it’s essential to craft highly targeted campaigns to optimize marketing spend and drive measurable results.
With rich data insights, your QSR can tailor promotions to specific audiences at the right moments and ensure consistency between national and local marketing campaigns. For example, using data analytics, you can leverage data during peak ordering times at a specific location, customers’ preferred menu items, and the effectiveness of previous promotions to customize an offer. This level of precision helps maximize the impact of each campaign while minimizing wasted resources.
3 data-driven QSR marketing strategies for overcoming key challenges
Third-party data signals around the web are fading as cookies become less prevalent, making it crucial to activate your first-party data to maintain effective customer engagement. At the same time, you need to be more strategic in how you collect, manage, and use customer data to comply with privacy regulations like CCPA.
Together, these privacy evolutions have resulted in several key challenges for marketers:
- Fragmented and siloed customer data
- Limited ability to measure cross-channel impact
- Difficulty scaling marketing efforts
Overcoming these challenges requires a robust data strategy that integrates first-party data with second- and third-party insights in a privacy-conscious way. The following steps are necessary to create a data-driven QSR marketing strategy that centers consumer privacy.
1. Create a comprehensive customer view
To be competitive, QSR brands need a comprehensive view of how customers interact across every touchpoint so they can appropriately tailor marketing campaigns. For example, your tactics for engaging with a frequent customer differ from how you’d market to a new or occasional visitor. But truly discerning how customers interact with your brand across various channels is difficult because data remains siloed in disparate platforms, such as loyalty programs, media networks, and email platforms.
Gaining a comprehensive view of your customer data allows you to deliver more targeted promotions and loyalty incentives. To achieve this, you need to build an enterprise identity foundation that consolidates your organization’s customer data from all available channels and assigns a consistent, pseudonymized identifier for each customer. From there, you can begin to build a truly personalized customer journey while keeping customer privacy in mind.
2. Measure campaigns across channels
Without a comprehensive customer view, it’s difficult to know which ads and campaigns actually resulted in a purchase. Picture this: a customer sees a social media ad for a new burger, receives an email promotion, and then places a mobile app order using their loyalty points. Each of these interactions is tracked in a separate, siloed channel, so it’s unclear which touchpoint actually led to the sale, or if it was a combination of two or three.
For instance, maybe they never actually opened the email promotion. Your email marketing platform will report that the customer didn’t convert — which is true for that platform. But that data lacks context for the customer’s whole journey.
That’s why establishing a comprehensive customer view with an enterprise identity is a critical first step. Without that person-centered identity, it’s extremely difficult to accurately measure full-funnel impact — from awareness to growth and loyalty — at the individual customer level.
A robust consumer data strategy takes measurement a step further by supplementing first-party data from your owned channels, including siloed franchises, with second- and third-party data from partner platforms and networks to provide a unified view of customer interactions across touchpoints. This approach enables you to see how individuals interact with your brand on media networks, including connected TV platforms, and delivery apps.
By capturing these interactions, you can understand each customer’s journey in its entirety, improving cross-screen measurement and identifying which channels and messages contribute to driving engagement and conversions. As a result, you can attribute sales accurately and refine your marketing mix to optimize budgets.
3. Enable scalability
A solid consumer data foundation unlocks countless possibilities to scale your QSR marketing efforts to build customer loyalty. We discussed how supplementing first-party data with second- and third-party data sources provides richer insights about your existing customers. As you add new channels to your marketing mix, you can use the customer intelligence you’ve already established to maximize outcomes with more personalized experiences right from the start.
Data collaboration between multiple platforms also makes it possible to engage new audiences more strategically. For example, if your QSR opens a new location, you can use lookalike audiences and predictive analytics to identify the local customers most likely to convert and engage them with personalized offers in a privacy-conscious way. You can protect customers’ personally identifiable information by ensuring all data collaboration among your partners takes place in a data clean room. That way, you can gain insights and reach audiences confidently without compromising data privacy.
Types of data essential for QSR marketing
In QSR marketing, you need to leverage diverse data types to create a complete picture of customer behavior and preferences. However, many QSRs have fragmented or incomplete first-party data that makes this difficult.
If you’re looking to augment your customer profiles beyond your own first-party data, your first move should be to gain access to your marketing partners’ first-party data (i.e., your second party data). The best way to do this is through secure data collaboration.
Data collaboration allows you to combine your own data with the first-party data partners like CTV networks, loyalty program providers, and social media platforms have about your customers. This enables you to combine various types of data like behavioral, attitudinal, and engagement data from multiple partners to fill information gaps, providing a fuller picture of customer interests and propensities beyond the “four walls” of your own business. Access to partner data is governed through clean rooms.
Let’s take a look at the types of partner data you can access through data collaboration and the role each plays in engaging customers at every stage of their journey.
Consumer behavioral data
Behavioral data captures customer actions, like purchase history, frequency of visits, and menu preferences. This data reveals patterns in consumer behavior so you can better understand what drives purchases and how to tailor offers to maximize relevance.
Attitudinal data
Attitudinal data provides insights into customer opinions, beliefs, and preferences, and is often gathered through surveys or feedback forms. By understanding customers’ feelings about menu items, service, and brand experience, you can create strategies that align with customer expectations and values.
Segmentation data
QSR brands can group customers based on shared characteristics like location, spending habits, or lifestyle. Tailoring marketing messages and promotions to specific audience segments helps increase campaign effectiveness by making messages more relevant.
Engagement data
Engagement data tracks how customers interact with marketing channels — from email opens to mobile app usage. Analyzing engagement data allows you to prioritize channels where customers are most responsive and optimize campaigns over time to generate stronger results.
Identity data
If you want to create a holistic view of customers across channels and touchpoints, you need identity data. This type of first-party data is essential for gaining visibility into customer journeys, strategically scaling marketing efforts, and ensuring attribution is accurate.
Create a better QSR marketing strategy with LiveRamp
LiveRamp’s data collaboration platform empowers QSRs to deliver personalized promotions and offers that consider the entire diner experience. We can help you improve your omnichannel marketing efforts with a robust consumer data strategy comprising an enterprise-wide customer view and secure data collaboration with external partners.
Whether it’s improving customer engagement, enhancing loyalty programs, or leveraging advanced data analytics, LiveRamp provides the tools QSRs need to succeed in today’s competitive restaurant market. Talk to a QSR expert today to get started.
