Challenge: Burned by its previous foray into data science, Freddy’s needed a new partner and approach to bring its data science initiative to life.

Solution: Freddy’s incorporated the Domo Data Science Suite into its Domo instance, gaining the ability to model things like menu mix and prices.

Impact: Thanks to the Domo Data Science team, Freddy’s gained the education it needed to finally accomplish its goals.

Freddy’s feeds its hunger for data science with Domo.

In less than two decades, Freddy’s Frozen Custard & Steakburgers® has grown from a single location in the heart of the Midwest to nearly 400 locations across the US. While the restaurant chain is known for its classic fast food fare, the company has a decidedly modern approach to data science. However, when Freddy’s first began its data science journey, it not only struggled with a lack of technology, but a lack of perspective.

“Our first journey down the path of machine learning and artificial intelligence was not very well thought out, not by myself, my team, or our implementation partners,” remembers Sean Thompson, IT Director at Freddy’s. “In our pilot engagement with another platform, our lack of planning and understanding kept us from getting any real value or return on investment. We were too focused on accomplishing a goal, and not on the quality of the journey.”

After evaluating their experience with the pilot engagement, Thompson knew Freddy’s would need both a different partner and a different approach to sell the initiative to his leadership team. “I basically said to them, ‘Remember that thing you gave us a lot of money for, and we got zero ROI out of? I want to try it again, but I promise to do it differently this time.’ That was a really hard conversation to have.”

Ordering insight with Domo Data Science.

As a long-time Domo customer, Freddy’s believed that Domo would be the right partner for the restaurant’s next attempt at data science.

Working with Domo’s experienced data science consultants, Freddy’s set out to understand their restaurant quality data and make is easily consumable. This required the evaluation of 18 different data sets spanning over 100 different columns of information created for each of the Freddy’s locations at multiple points in time. With so many individual columns of data to consider, store quality was difficult to understand and assess—it simply was not feasible to look at over 100 columns of data to figure out what a restaurant was doing well and which areas needed improvement.

With Domo, Freddy’s created a statistically sound data reduction process to automate and make their store quality data easy to understand. Domo’s data science team worked with Freddy’s to fully understand business practices, their restaurant quality indicators, incentives for restaurants in managing restaurant quality, etc. After comprehensive discussions about both business practices and data, Domo worked with Freddy’s to develop an exploratory factor analysis to identify the complex interrelationships among the 100+ columns of restaurant quality data. After understanding these relationships, Freddy’s and Domo moved forward to develop a custom confirmatory factor analysis pipeline explicitly accounting for the unique attributes in Freddy’s data and business model. This process was then automated in a data science production pipeline that facilitates full automation of Freddy’s data science solution.

By focusing on the journey of the data, Freddy’s was able to gain the confidence needed to know they were on the right track. “We made sure that we took our time, stepping through the product, the project, and the process piece by piece so that we were learning along the way. With the Domo Data Science team, we were able to ask questions and get into sidebar conversations, all while using the data to drive the discussion.”

Scoring super-sized wins.

Thanks to the Domo Data Science Suite, Freddy’s quickly achieved several immediate wins. The company launched and optimized a new Guest loyalty program so it could effectively incentivize its most high-value Guests. In addition, it also gained the ability to accurately score locations so it could conduct A/B testing initiatives like price optimization and menu mix modeling.

“Before, we would just pick two restaurants that looked similar, but now that we have a true understanding of the relationships that are inside of our data, we can find exact comparisons. This has helped everyone from IT to our R&D team to our marketing and purchasing teams when we’re trying something new,” said Thompson.

For Freddy’s, Domo didn’t just provide the software needed to access these insights, but the indispensable partnership to make it all work seamlessly.