Unleashing the Power of Data-Driven Storytelling in QSR: 5 Signs Your Data Needs an Overhaul

As society leaves COVID behind, food services are beginning a new era.

Juggling inflation, supply-chain issues, and higher customer expectations, many restaurants have embraced technology to tackle the current QSR climate. In fact, 71% of respondents saw digital transformation as the leading driver for business agility.

While embracing technology and learning new ways to operate is shaping the industry, most companies struggle to manage their data effectively. Many are drowning in a sea of data, unable to use it to improve customer loyalty and increase sales. Worse, many don’t even realize they’re not using it effectively.

In an industry as highly competitive as QSR, the effective use of data is paramount to success and keeping an edge over rivals. However, many leaders fail to understand exactly what data can do for them and settle for disjointed, complex, and slow data insights. Recognizing when your data infrastructure needs an overhaul is crucial to unlocking your QSR’s full potential.

Here are the five signs you need to reassess and revamp your data strategy. By identifying these signals, you can proactively transform your data approach to ensure you remain agile, responsive, and primed for growth in the rapidly changing industry.

Sign #1: You Can’t Make Informed Decisions Quickly

In the QSR industry, timing is everything. Hesitation or poor split-second decisions means you miss out on customers in real time—you need the right data in the moment. You may have access to endless data, but if it doesn’t have real-time implications, it’s not working as well for you as you may think.

Effective data management helps transform raw data into predictive insights, enabling you to respond swiftly to changing market conditions, customer preferences, and operational challenges. If you can’t make quick and informed data-driven decisions, it’s a sign that your data infrastructure needs an overhaul. It could be due to data silos, inadequate analytics tools, or a lack of real-time data processing.

Chipotle is an excellent example of how fast data-driven decisions can help sales even in the direst of environments. The chain leveraged its social media analytics to guide its initiatives during the pandemic. Armed with insights, it pivoted to free delivery and emphasized employee safety. By 2021, digital orders made up almost half of the chain’s total charges. Because it was agile and quickly implemented changes across the organization, it remained profitable even as other fast-casual restaurants struggled to stay open.

Sign #2: Your Customers Surprise You

What would be the impact if you knew why a customer chose a competitor over you, and what would be the impact if you could find that out in real-time?

Translating data into actionable insights requires more than volume. You need a holistic understanding of the business context too. Understanding customer behavior is critical to a QSR’s success in today’s competitive landscape. If your customers’ actions or preferences seem to come from nowhere or surprise you, it’s a sign that your data analytics are not providing the insights you need.

Understanding your data from the right storyteller perspective will give you a more accurate view of your target patron’s likes and dislikes. A data overhaul can help you better understand your customer’s needs and preferences, allowing you to tailor your offerings and improve customer satisfaction.

Knowing your customers is critical to overall sales, and McDonald’s is the perfect example of that. In the wake of bad publicity and an increase in a health-conscious public, McDonald’s tried to introduce healthy items to its menu. However, the chain struggled to make its healthier offerings popular and ended up taking them out completely. While the company understood the general public sentiment, it failed to track what its customers wanted accurately.

Learning from these mistakes, McDonald’s has slowly transformed its strategy to reflect its customer base. Instead of trying to venture into new markets, McDonald’s focus on improving its core menu items led to a boost in sales at the end of 2022, while other businesses saw declines. With a better understanding of what customers want, McDonald’s only needed to tweak favorites instead of making significant investments trying to break into new markets.

Sign #3: You Don’t Know Where to Expand

Retail expansion is an exciting part of QSR growth. However, deciding where to open new locations is a make-or-break decision that will impact its overall success. Companies long relied on traditional statistical models to aid site selection. Today, depending on these outdated methods can lead to a costly failure. Even with a proven business, the wrong area will signal doom for a QSR.  

If your data is not helping you identify promising locations or market segments, it’s time for an overhaul. The right data will give you more than traffic patterns within the target area. You also need to uncover trends, patterns, and opportunities that will guide your expansion strategy by integrating and analyzing data from various sources. Your data needs to answer all the vital questions that one-dimensional data analysis cannot provide, like:

  • What are the local tastes and preferences?
  • How does your business fit with complementary companies in the area?
  • What is the growth potential of the area?
  • Are there any potential challenges or risks associated with the location?
  • How does digital commerce trends in the area influence success of offline locations?
  • How much penetration do my competitors already have in the region?
  • Is there a shortage of delivery options in the area?

Choosing and researching the right location is more than just visibility or foot traffic. QSRs that fail to understand the nuance of the area they’re moving into risk flopping. Instead, you need a data solution that will answer your deepest questions. It will not only guide location selection but enhance insights to deliver targeted messages to the selected consumers nearby.

Sign #4: Your Sales Are Hurting

If you’re experiencing a downturn in sales, you’re not alone. In fact, 85% of operators reported that their restaurants were less profitable in 2022 than they were in 2019, according to the Restaurant Association. However, just because it’s normal doesn’t mean there’s nothing you can do about it.

Even as some QSRs experience a downturn, others are still performing well.  As we mentioned above, McDonald’s is experiencing a resurgence in sales. Likewise, many other restaurants are experiencing growth as they respond to the current demand.

Declining sales or stagnant growth signals that your current data analytics are not providing the insights needed to optimize your operations, marketing, and product offerings. If your current strategy fails to resonate with customers’ needs, your sales will continue to decline. A more effective data infrastructure will help identify the root causes of these issues and provide actionable insights for improving sales and profitability.

Sign #5: You Struggle to Get a Unified View of Your Restaurant

QSRs gather critical data from disparate data sources and systems in today’s restaurant systems. Just a few include:

  • Point-of-sale systems
  • Online ordering platforms
  • Customer feedback
  • Loyalty programs

On top of internal data, restaurants rely on a large number of external data sources to learn more about their competitors and the industry at large. It can quickly grow complicated and confusing, which makes it ineffective. If you can’t understand your data or it seems to be telling different stories, it’s a costly waste of time.

If you’re having difficulty getting a holistic view of your restaurant performance and customer journey due to the number of data sources, you’re not getting as much as you could from data. Integrating and standardizing the information will provide actionable, easy-to-use data to identify areas for improvement, streamline operations, and enhance the customer experience.

What You Don’t Know Can Hurt Your Restaurant

Accurate storytelling is the most vital aspect of data analysis. It simplifies and distills complex data into an easily digestible narrative, making it more accessible and actionable. Instead of focusing on raw data, investing in a solution that provides the story behind the numbers is critical. The right perspective will provide answers and insights derived from comprehensive data analysis. It’ll empower your QSR to make informed decisions, stay competitive, and drive growth.

If you’d like to learn more about how Pyxis can give you answers to your most critical QSR questions, reach out to one of our experts today!

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