From Data Analysis to Data Storytelling: Improving Product Experience at Chick-fil-A

For fast-food aficionados, there’s no question that Chick-fil-A has perfected the chicken sandwich. Now, we’re perfecting the digital product experience.

Our Chick-fil-A One app is our loyalty app that allows customers to order ahead, earn points, and redeem those points for food rewards. Not only is the purchase funnel a key KPI, but we also monitor how customers pick up their order (e.g. curbside, drive-thru, takeout) and whether or not users redeem their rewards.

As a user experience (UX) researcher, I use analytics and user testing research to determine how users interact with our mobile app and better understand how their customer experience leads to conversion. I then promote UX methodologies and collaborate with cross-functional teams in business marketing, engineering, product, and design to determine what works, what doesn’t, and what they should do next. We identify research objectives, and those objectives and activities in turn help guide us through our product roadmap.

A Lack of Analysis Leads to Unanswered Questions

I joined Chick-fil-A a little more than 18 months ago. I came from a web analytics background and wanted to move into the mobile space, but to be honest, Chick-fil-A was not on my radar. When a recruiter approached me about the position, I had an “A-ha!” moment. I always received impeccable customer experience from the company, and when I learned that the work culture mimics that customer experience, I was eager to join.

To understand your customers, you have to ask the right questions. To ask the right questions, you have to have the right data. Click To Tweet

When I first joined the organization, we were unable to answer some key questions about our mobile app users. We didn’t have any product UX tools, so any analysis had to be done looking at point of sale transactions and creating analysis using credit card hashes.

But to increase our order conversions, we needed to understand how users engage with the app: What were our users doing in terms of loyalty? Why weren’t they using their reward points? Why did users forget to scan when they used the app? If we knew the answers, we could consider modifying the app design. But we didn’t have the answers—only an abundance of questions.

Chick-fil-A is a big company, so I assumed a lot of their data research processes would already be solidified. But the technology side of the business is relatively young and operates much like a startup. When I started, they were at the beginning of their data-driven journey, and processes were still being developed.

Chick-fil-A had just purchased Amplitude, a product analytics platform that helps teams convert, engage, and retain customers. I was to be a data governor, acting as a point person for Amplitude and assisting other team members with use and access. I didn’t know anything about the platform, only hearing it described it as “Google Analytics on steroids,” and that was music to my ears.

Part of my role was to help develop some key data-driven processes. Some of these processes include identifying data sources, cleaning and organizing data, defining objectives, setting measurable goals, analyzing data, and presenting findings with actionable insights to stakeholders and across teams.

Our customer digital experience teams are broken down by app features. Within those teams, my role was to essentially socialize my UX research/data analytics framework, which included: Understanding user pain points, performing competitive analysis; deciding on new feature development; defining possible solutions; analytics; UI design; implementation; and review.

At the end of the day, we wanted to use data to guide all of our teams through the process of developing new features and improving our user experience.

Easing Everyone Into Data

Some people find data to be intimidating. When presented with a lot of information, they can get overwhelmed, especially if they don’t know what they’re seeing. When executives or stakeholders are uncomfortable with data, it can be a real problem for an organization; the intimidation factor can prevent them from asking the right questions and making the right decisions.

Sharing data across multiple teams makes it easier to make better decisions, faster. Click To Tweet

With new technology, there’s almost always a learning curve, and colleagues logged in with cautious optimism. But part of my role as an analyst is to make people more comfortable with data, and Amplitude helped with that. They worked with one of our developers to create internal materials that we could share across teams. These materials not only helped when onboarding new Chick-fil-A team members, but they also provided visualizations and explanations as to how Amplitude could help anyone answer their business questions.

Between those materials and Amplitude’s intuitive user interface, colleagues took to the platform pretty quickly. They saw the type of analysis that was possible—even if they didn’t quite know how to get there themselves right away.

Turning Data Points Into Actionable Items

I often think back to a customer experience issue we had within our app. Somewhere between the time a user selected “Prepare My Order” and the time they selected “I’m Here,” they got frustrated. After some analysis, I discovered why: roughly 8% of our users had trouble submitting their orders. The app dropped orders along the way because various systems weren’t talking to one another correctly.

What’s more, 60% of users were frustrated with wait times. Chick-fil-A built an Amplitude notebook “How many mobile customers are lost due to long wait times?” that included quite a few Amplitude funnel charts and other visualizations showing the conversion rates based on the various wait time ranges that were quoted to the customer. Then we analyzed conversions by time of day as well.

My team had to determine the percentage of mobile orders being placed on site and the number of mobile users opting for other pickup methods, because some of our restaurants can’t fulfill mobile orders with every method. Seeing these percentages prompted us to make modifications to the app to address those wait times.

I think about these stories of iterating with data because it shows just how far we’ve come in our data journey. Chick-fil-A could react to user frustrations within our mobile app because we do more than data research. We have become data storytellers, taking the information we uncover and turning it into a narrative that impacts the way we design, develop, implement, and measure success.

Empowering Teams with Self-Serve Analytics

Centralizing information with Amplitude means that now, not only can we answer questions such as how many of our users fall into each membership tier, but we can easily share that information across teams. All I have to do is send a link and anyone can view my charts within Amplitude. That makes the cross-team collaboration part of my job much easier.

The biggest change I’ve noticed since using Amplitude is that our feature teams now build their own dashboards, which allows them to create and add charts to keep track of different KPIs and monitor them for success. As more and more team members conduct their own research, I’m no longer the sole source for analytics, either. This means I’m not spread so thin and can spend more time with the data itself.

I constantly receive notifications of new user requests. It seems the more people learn about Amplitude and see what it can do, the more they want to use it. We also set up a monitoring feature to keep an eye on how people use Amplitude. This helps us determine how to further assist our team members and make sure they get what they need from the platform.

We also use other tools alongside Amplitude, including mParticle to send data into Amplitude, Bugsnag to understand app performance, and Taplytics.

As we connect more data, more teams can answer new questions. Integrating data from new sources is on the horizon for Chick-fil-A. We’re not quite there yet, but Amplitude’s investments in data integration and management tools reduce the friction for bringing new data in.

This year, we’ve had a lot of conversations about ways to integrate data from sources like DoorDash, Uber Eats, and Grubhub. Currently, we receive that data through various third-party apps like Amazon S3 and Google Analytics. We’d like to import that data into Amplitude so we can build more visualizations. We’re not quite there yet, but we are trying to strategize and think of other ways to get these different systems to communicate.

Seeing Data in Action

Amplitude has helped my team understand now how our customer feels about our product and how they engage with it. One example is how we have enhanced the Chick-fil-A delivery experience.

Restaurants were overwhelmed with delivery orders during the 2020 COVID-19 pandemic. The native delivery experience was already growing and with the increase in delivery orders, we saw an opportunity to focus more on creating a better experience for these new delivery customers.

We asked ourselves: How can we make it easier for customers to place and receive delivery orders? Why are users changing their destination selection during mobile ordering? Are delivery times too long that the user feels it’s easier to pick up an order via drive-thru or curbside? With strong user research, we were able to implement product decisions that spoke directly to customers’ pain points.

We added contactless delivery to the app to ensure social distancing. To promote delivery through both Chick-fil-A operator-led delivery and third-party delivery (DoorDash), we changed the flow for initial screens. This way, customers selected a fulfillment option first (pickup versus delivery). To monitor and measure our success, we defined clear key performance indicators and added necessary event tracking in Amplitude.

What did we learn? We learned which destination type was more preferred by our customers, the weekly frequency of operator-led delivery orders versus third-party delivery orders, which delivery option is more preferred when presented with a third-party versus operator-led option, and average distance to restaurant for third-party orders versus operator-led delivery.

We saw a 23% increase in third-party ordering which attributed to moving the delivery button to first initial ordering screen. Also, when users are presented with the option to choose third-party delivery versus operator-led delivery, 95% will choose operator led. With this information, we continue to enhance how we create better experiences for our customers through design.

We stand behind providing our customers with a personalized yet quick and efficient experience. Apart from the mobile app, we have begun to use Amplitude more for our catering business and personal web ordering. That means we’re going to do much more tracking on our email notifications and special offers. Within Amplitude, we can build on our early success with the mobile app, and build buy-in across the organization.

Great Analysis Leads to a Great Experience

Building a culture and processes around data doesn’t happen overnight. Even after researching and purchasing a solution, you can’t be afraid to make mistakes and learn through trial and error.

At first, people have to get comfortable with being uncomfortable. Each user has to explore the tool for themselves. The more everyone sits with it, the more confidence builds, and from there, it’s easier for everyone to see the story that emerges from the data.

Building a data-driven culture doesn’t happen overnight. The longer you persist, the more confidence you gain. Click To Tweet

Data is never perfect, but there are still so many valuable insights you can glean from it. Eventually, it becomes a matter of understanding your main data source. Once you understand that, you’ll know what questions to ask of your data itself. In our case, we’ve learned how we can better improve our experience for our customers. We can identify small issues before they become bigger issues, and keep our customers happy.