Darden Restaurants – Winning Customers with Data

Restaurants are looking to data to differentiate themselves in a rapidly changing competitive environment

Amid rising costs and competition, restaurants are employing data to execute strategic initiatives and differentiate themselves in the marketplace. Large players such as Darden Restaurants (“Darden”) are leading the way.

Darden operates a portfolio of eight recognizable brands such as the Olive Garden, Longhorn Steakhouse, and The Capital Grille. With over $7.2 billion in sales and over 1,700 restaurants, Darden has used its extensive scale to build data systems and conduct analyses to capture value in the market. In 2012, Darden, under the leadership of CIO Patti Reilly White, introduced its Check-Level Analysis as the first part of its digital transformation strategy.

Value Creation

Operational Efficiencies

Darden’s Check-Level Analysis tool accumulates information on every step of a guest’s experience at a restaurant. The Company can assess metrics such as wait times, items ordered, cook times, and pace of meal. According to White, “we can track what server is providing that guest experience, when the guest settled the bill, and how long they were there. We can trace all that to the satisfaction survey, if they decide to fill it out. Now we can understand the total guest experience within the four walls.”[1] This guest data gives restaurant managers and corporate leadership critical information they need to make decisions such as optimal menus and pricing, development and training, and fraud detection. Darden expects at least $20 million in cost savings from its data analytics program.[2]

Marketing Gains

Darden is also using data analysis in its marketing function to improve and extend the guest experience outside of its four walls. The Company has shifted from a mass marketing approach to a targeted marketing strategy with the help of its guest analytics platform. Data is used to continuously learn about guest preferences and behaviors, allowing Darden to segment guests and provide customized messages.[3] Under the leadership of the new CIO Christopher Chang, the team conducts tests to better determine what messages, timing, and frequency of outreach will provide the best results for each of the Company’s brands.[4]

The Company’s data strategy is based on four main pillars:[5]

  1. Robust data collection and solid platform foundation
  2. Emphasis on testing and learnings
  3. Data science capabilities to analyze and identify key insights
  4. Recognition of marketing as a cross-channel strategy

Together, these pillars allow Darden to capture unique insights and target the right customers at the right time with the right message. In doing so, the Company can influence the guest experience and find better ways to draw customers back into stores.


The US restaurant industry represents $799 billion in sales with over one million restaurant locations.[6] Barriers to entry are relatively low, and seven in ten restaurants are operated as single-unit businesses.[7] Given that most of Darden’s competition comprises mom and pop restaurants, the Company is well positioned to target guests and garner cost savings because it is able to collect and analyze data from over 1,700 locations. Although the portfolio represents different brands, Darden can distill general learnings from its large data database and apply them system-wide. While Darden has been at the forefront of data analytics among large chain restaurants, the Company should continue to monitor other chains to ensure it maintains its competitive advantage.


[1] https://www.informationweek.com/strategic-cio/executive-insights-and-innovation/darden-uses-analytics-to-understand-restaurant-customers/d/d-id/1141551?

[2] Ibid.

[3] https://www.cio.com/cio100/detail/2724

[4] Ibid.

[5] Ibid.

[6] http://www.restaurant.org/News-Research/Research/Facts-at-a-Glance

[7] Ibid.


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Student comments on Darden Restaurants – Winning Customers with Data

  1. Interesting post! I like your point on getting more targeted marketing – I wonder though, if customers will have a negative reaction to Olive Garden sending ads revealing it knows exactly what you had last time you went there without consent?

  2. Awesome to see that traditional businesses in the restaurant industry are starting to use data analytics to optimize their performance. I totally agree with your point around competition. Data collection and analytics, if implemented in the right way, can be a huge competitive edge. Since it is considerably easier for large companies to collect customer data and hire the right analytical talent, I wonder if this will cause a further divide between these big chain restaurants and mom and pop establishments, making it even harder for smaller restaurants to compete.

  3. It’s great that the data revolution has impacted so many industries, restaurants included. My one concern is that consumer tastes in food seem to change rapidly and the dataset that the brand is leveraging could ultimately not reflect the tastes of a modern or future consumer. I’d be curious how humans are introduced into the system in order to maximize the success of the larger program.

  4. Great post, M, thank you. While reading, I was thinking about whether the first CIO Patti Reilly White faced challenges when she introduced the Check-Level Analysis. There is little doubt that the data that Darden tracks with the Check-Level Analysis can prove useful, but I wonder how the implementation process worked – as we saw in class – when her team first received the data and proposed new ideas based on the findings? Were there operational changes to improve efficiencies or perhaps push-back from servers or chefs regarding food prep time? And perhaps the optimal menu based on the data was at odds to the chef’s knowledge of what may sell at a given location? Very interesting!

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