Mastering Restaurant Data

By Ward Olgreen and Tim Tang, CFE

In a world where artificial intelligence routinely dominates the headlines, some restaurants still struggle to extract tangible business intelligence and, thus, value from their data. When “data is the new oil,” there is a tremendous opportunity to enhance customer experience, tune store operations, optimize profitability, and improve employee performance. Three steps for hospitality and retailers to master their data are to visualize existing point of sale (POS) transaction data, analyze credit card transaction frequency patterns, and optimize profitability with consumer purchasing behavior.??

Visualize Existing POS Transaction Data

POS transactions are the lifeblood of any customer-facing business. Each transaction provides insight into every aspect of the business, from operational effectiveness and recipe suggestions to customer satisfaction. The customer is most sincere about what they want when they pull out their wallet to make a purchase. Each transaction translates into valuable insights for the business. Yet, for decades, leadership has been sitting on enormous volumes of data without the ability to operationalize it quickly and cost-effectively. With improvements in processing capabilities and speeds, that has all changed.

The benefit of visualizing the data intuitively is to enable leaders to understand what they need to do––or what frontline workers need to do––without spending hours studying streams of seemingly meaningless numbers. That requires identifying “normal” versus “abnormal” incidents or patterns in the data. Common questions to suss out these insights include:

·???????? “Why is one store outperforming all of the others?” What best practices need to be shared with other stores? Are there unusual local events that warrant a reallocation of inventory periodically? Are the trade areas dissimilar? Variations in Guest Behavior? Employee service levels? In-Store Leadership?

Humans can only see so much, whereas the transaction data details everything.

·???????? “Why is one employee’s average transaction time so much longer than others?” (magnified when working the drive-thru) – Are they upselling more products? Despite the fewer transactions per hour, are they contributing more to profitability and/or customer satisfaction? Do they need more training on how to use the POS? Are they well-versed in the details of every menu item? Do they regularly have to call a manager over to help?

Dealing with fact-based data helps to solve this puzzle.

·???????? “Why is one store manager’s employee satisfaction scores so much lower than the others?” Are they routinely managing an understaffed shift? Are there specific employee issues that are affecting morale? Are there personal issues that are interfering with their professional responsibilities? Were they thrown into the lion’s den before being fully trained?

Analyze Credit Card Transaction Patterns

When monthly store transactions are down, is that bad or a reflection of market conditions? It all depends. If monthly sales from other businesses are down 10-15%, then being down only 5% means the store outperforms the competition. The location is doing something right rather than wrong. Consequently, the right strategy would be to maintain the current approach and expect profits to return when market conditions improve.

Not all businesses can access their competitors’ credit card performance patterns. However, much can be learned within your own four walls. When you analyze your data to determine the WHY behind the WHAT, you focus on what you can control. And on areas, you can impact regardless of external market pressures. The fact is we have all seen incredibly busy restaurants adjacent to empty ones. Try not to use a competitor’s lack of sales as a crutch to explain your own. Scrutinize the data to find the answers.

Optimize Profitability with Purchasing Behavior

While credit card transaction data provides a macro-level view for understanding transactional store performance, a micro-level view facilitates the understanding of itemized consumer purchases, enabling retailers to optimize and influence individual customer orders. By knowing what items commonly pair with others, retailers can increase not only the size of the basket but also the profit margins and guest satisfaction levels. When effective menu engineering is applied on a per store basis, the restaurant maximizes sales opportunities for the brand. When a server or cashier provides relevant recommendations, they nurture the customer relationship, garner trust, and boost loyalty.

Summary

In today’s challenging market, restaurants need the operational advantage that lies within their data. By properly visualizing the data to identify business anomalies, leveraging insights from credit card transactions, and analyzing customer purchasing behavior, restaurants can optimize operations and profitability while enhancing the customer experience.

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