How Data Science Can Help QSR To Multiply Profits

Looking at it top down, multiplying profit entails two basic outcomes in the quick service restaurant (QSR) context. First, increasing the top line revenues and second, keeping the operating costs under control.  QSR Analytics can help you achieve both of these in a number of ways.

Operational costs are impacted mainly by the menu design, staff deployment, order fulfillment efficiency and inventory management all of which can be improved upon substantially through intelligent application of data sciences. On the revenues front, analytics can help you grow and retain customers and also boost the average realization per customer by enabling you to design personalized customer experiences that form the core of QSR branding.

Data Science multiply profits in QSR through QSR Analytics

Data Science multiply profits in QSR

Let’s have a look at each of these aspects in a bit more detail,

Optimized menu design

It can be tempting to include a large number of offerings that differentiate your menu from those of the competition. However, this can prove to be disastrous if it overburdens your staff and dents profitability in the process. The menu must be designed to strike the right balance between the offerings that are popular and drive volumes at a lower cost of operations and those that are high value but lower in demand. Analytics can help you do this by analyzing the vast amounts of electronic order data generated on daily basis at your QSR outlet and through ordering apps. It can also help you identify winning combinations and design menu pairings with corresponding discounts. Price sensitivity analysis combined with predictive analytics can help you forecast the performance of markdowns thereby eliminating the guesswork that generally leads to low-performing offers and promotions.

Analytics can help you do this by analyzing the vast amounts of electronic order data generated on daily basis at your QSR outlet and through ordering apps. It can also help you identify winning combinations and design menu pairings with corresponding discounts. Price sensitivity analysis combined with predictive analytics can help you forecast the performance of markdowns thereby eliminating the guesswork that generally leads to low-performing offers and promotions.

Lean and efficient operations

Prudent staff deployment is crucial to controlling operational costs. If a QSR outlet is handling home delivery orders along with in-restaurant and drive-through ones, it needs to maintain an optimum level of staffing to stick to its order-to-delivery time promises. QSR analytics can help your forecast the volume of orders by the time of the day or season so that you can align your staff deployment accordingly. This also enables you to predict inventory movements and make

QSR analytics can help your forecast the volume of orders by the time of the day or season so that you can align your staff deployment accordingly. This also enables you to predict inventory movements and make data-driven purchasing decisions to minimize food wastage.

High ROI marketing

Customers are interacting with QSR brands through social media, opinion websites, ordering apps and loyalty portals. Digital interactions are abundant and so are the opportunities to leverage the data generated through them.

QSR analytics can help you centralize this interaction data and unearth behavioral patterns and preference trends that can redefine your offerings strategy. You can segment and micro-segment your customers to offer correctly priced localized offerings along with targeted upsell and cross-sell recommendations for maximum revenue generation.

You can also track which marketing channels – online and offline – are providing the maximum reach and engagement levels for your brand at optimum costs. With advanced customer metrics such as lifetime value (LTV) and net promoter score (NPS), you are sure that you have your ears to the ground when it comes to managing the overall customer experience.

Effective loyalty management

Analytics helps you keep the cost of sales down by deepening your loyalty programs. This has a direct impact on the margins because the cost of acquiring a new customer is much higher than that of retaining one. Customers today, expect to be rewarded for their patronage and designing these reward programs in a personalized manner is by far the most effective way of driving loyalty.

Data sciences can help you understand what segments of your customer base are most sensitive to loyalty rewards and also what they value the most – straightforward discounts or perks such as reserved parking, secret menus or free entertainment add-ons. Also, QSR analytics can give you a comprehensive view of customer satisfaction levels and the sentiment around your brand which can enable you to take preemptive corrective steps whenever required.

Conclusion

The QSR industry is a highly competitive one and to stay ahead of the trend, it is essential to gain an in-depth understanding of your customer and align your operations in the most efficient manner to your customer experience strategy.

At Comtec, data scientists are not only proficient in statistical techniques but are also domain experts with relevant industry expertise. This makes it possible for us to contribute meaningfully by providing actionable business insights in line with the latest trends in the QSR industry. To get in touch, drop an email to rpa@comtecinfo.com.

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