Current Sheetz App Excessive User Friction

  1. Repetitive, confusing, slow, buggy

  2. Favoring / recommendation function is lag(recommend in random; favoring never used in ordering process) (e.g. has to wait for long till reach sth related to me)

  3. can not adjust different customers’ need at different time(people in a hurry & just want reordering; when driving / walking)

Our Solution: Sheetz Voice Ordering

We proposal bundling Sheetz app with Siri and bring a frank new way of mobile ordering. After activating Sheetz’s app with Siri, the voice assistant will first check your location and the Sheetz store you are heading. Customers can then choose the way of ordering that best satisfies their needs: repeat a previous order, order from favorite items, or get Sheetz’s recommended sets. In each of the three cases, the voice assistant will provide a concise but informative overview of the items, and detailed display of ingredients if customers require to do so. At the end of this short voice ordering procedure, the user is either get settled and can directly head to the shop or is directed to a human representative if he wants more information.

INTRODUCING Sheetz Voice Ordering...

How Voice Ordering Reduces Friction

The key focus of the voice ordering is allowing customers to place order fast and comfortably bypassing the redundant screen interaction processes. One key feature of our voice ordering is that it frees the user’s eyes and hands. This completely hand-free procedure meets especially the biggest need for those who want to order on their way. Even though the procedure is meant to be only engaging the sense of hearing, we will keep some helpful information on the screen for our customers’ reference. We believe that our innovation is flexible of handling speed ordering under a variety of contexts.

Value and Co-Creation

Voice ordering through bundling with Sheetz generates value for both users and Sheetz. It provides users with greater flexibility by removing some of the constraints that are associated with the current app. For example, users who are driving are now able to place orders entirely through voice without lifting a finger. Voice ordering is also a more natural medium and done right can be an efficient way to place orders. As you saw in the video, placing a repeat order can be done in as little as 10 seconds. For the business, beyond generating more orders, voice ordering can help with increasing basket size and increasing customer delight through more personalized offerings. Most importantly, it helps Sheetz further it’s mission of being a customer-friendly brand.

Why Voice Ordering Through Siri Will Work

We chose Siri as a widely realized voice agent. Currently, there are more than 100 million iPhone users in the United States, accounting for about 45 percent of all smartphone users in the United States. Voice ordering is a proven success for other food chains. 20% of Domino's one-click orders come through Alexa. Moreover, Half a million orders through Dom.

 

Last but not least, voice commerce is the future, with customers increasingly embracing voice technology. According to our research, 74.2 million Americans use smart speakers every month, and 62% of speaker owners have bought items through voice commerce, only 7.9% of people use smart speakers for food and beverage shopping. (Lindberg, Voice Ordering the Emerging Restaurant Ordering Technology You're Not Quite Using Yet)

Feature Roadmap

We suggest a phased rollout of the voice ordering functionality, with an emphasis on continuous user testing. We want to ensure that we add features that both engage beginners and attract experts.

Design Process

 

Stage 1: 

Understanding the existing product-service system and selecting a focus area

Concept Mapping

This phase began with research into Sheetz and its offerings. When we felt like we had a comprehensive view, we modeled the different elements of Sheetz in a concept map. 

 

This design tool helped us keep track of everything that could be done at Sheetz and gave us a starting point for thinking about improving the Sheetz experience. The MTO process was particularly interesting to us at this stage. 

Insights

By making a concept map we realized that there are many areas in the Sheetz App that an be improves. We also found out that developing applications can be really expensive and Consulting firm Deloitte found that customers who order online at casual and fast casual restaurants tend to spend 13 percent more. Therefore, we narrowed our focus to finding service innovation opportunities on Sheetz App's ordering process.

PESTLE Analysis

We built a Pestle Diagram to model the industry as it currently stands.

POG

Projecting to the technological future, how might Sheetz make more profit leveraging the store's favorable personalized food ordering and smartphone technology?

Research Question

How might we innovate a personalized, profitable, and simple mobile ordering experience that mirrors the quality of an in-store Sheetz experience? 

User Journey Map/ Blue Print

To reframe our research question, we experimented with and modeled the mobile app to understand its current workflow and capabilities. We selected the mobile app as our focus area after seeing areas for improvement in the user experience

Insights

  • The app experience does not reflect Sheetz’s store’s fast and friendly experience with its taxing repetitive selection, ordering, and paying process 

  • The occasional technical failures might partially be due to the complex interactive touchpoints and pages. 

Conclusion

The current Sheetz App consists of many Excessive User Friction

Repetitive, confusing, slow, buggy

Favoring / recommendation function is lag(recommend in random; favoring never used in ordering process) (e.g. has to wait for long till reach sth related to me)

Can not adjust different customers’ need at a different time(people in a hurry & just want to reorder; when driving/walking)

Opportunities and Measurements of Success

By improving the Sheetz App, what might we be able to achieve? 

  1. Increase in profit (Larger basket size, more app orders, higher app usage)

  2. Better brand image (Efficient, helpful, and technology-forward)

  3. Personalized experience (Satisfy various needs, person-person interaction)

Stage 2: 

 

Opportunity and Ideation

Personas

We focus on analyzing the needs of the millennials, who are gradually becoming the main body of Sheetz digital apps' and store's customers. 

Jessica Brown

Millennial Female

MFA Student

“No time and low budget, so anything cheap and quick would be good for me.”

Jessica Brown is a graduate art student attending the college near a Sheetz Cafe. On school days, she stops by the Sheetz store to grab MTO sandwiches and coffee before and after classes. At times when she needs to fill gas, she would text and wait till the gas fills. 

Challenge/Pain Point

  • Limited time for filling gas and getting food

  • Tight budget

Joseph

Millennial Male

Junior Accountant

“All I want to do at the end of the day is to have a beer and hang out with my friends.”

Joseph is a 25 years old Junior Accountant at Pittsburgh. He lives with his parents and drives half an hour to work every day. He is constantly finding places to hang out with his friends.

Challenge/Pain Point

  •   Too little spare time

  •   Hard to find a place for relaxing during weekends

  •   Tired of complex services

  •   Eager to try new things

Timothy

White Collared Male

Real Estate Development Manager 

“I want to eat healthily and I like to plan things out so I am more time-efficient.”

Timothy is a 33 years old Real Estate Development Manager at Carlisle. He values the quality of the food he eats and he likes to plan his day out one day ahead.

Challenge/Pain Point

  • Dislikes waiting for the MTO order preparation in-store with nothing to do

  • Lack of MTO food during nights

Tim

Blue Collar Male

“My work requires me to get refreshment fast and often.”

Tim is a 30 years old Blue Collar Worker. He drives to nearby convenience stores for refreshment and food in between work breaks.

Challenge/Pain Point

  • Need somewhere to socialize and relax

  • Need a place for good food

  • Consistent cheap food

Amy

Working Mom

“I need something quick, but more importantly, something healthy and nutritious for my kids.”

Amy is a 42 years old mom with one 17 years old boy and one 13 years old girl. She has a very busy daily schedule that apart from her job she has to drive her kids from school to after school classes.

Challenge/Pain Point

  • No time to prepare healthy dinner and afterschool snacks between picking up kids from school to music class and sports practice. 

  • Need to find a better routine

  • Need a plan that will become an easy habit

Goals

  • Get what she needs fast

  • Save $

Attributes

  • Speed driven

  • Price driven

Goals

  • Some places to get high delicious food at a low price

  • A variety of choices

  • Constantly looking for places to hang out with friends & partner

Attributes

  • Own a car

  • Heavy internet & social media user

  • Love to try fashionable things & new tech

  • Easy to be influenced by online reviews

  • Value interpersonal relationship

Goals

  • Wants affordable but high-quality food

  • Bundled purchases - shopping for multiple needs in one trip

  • Moderately health-conscious

Attributes

  • Owns a car

  • Community Oriented

  • Short on time

  • Loyal to local and familiar brands

Goals

  • Grab food fast

  • Get food for low price

Attributes

  • Goes to Sheetz multiple times per day

  • Is friendly with the staff

  • Might interact with other regulars

  • Likes to sit outside

Goals

  • Feed her kids healthy food

  • Become more time efficient

Attributes

  • Time driven

  • Nutrition driven

Insights

The majority of the personas need the ability to order fast and care for nutritional intake (we also assume that they need to know the parking availability).

Provide a simple, streamlined, and “smart” mobile ordering experience that is attuned to the specific needs of the customer.

Solution

Reframing the findings

Ideation

We ideated for solutions that met the needs of each of our personas. We consolidated our proposed solutions that met the overlapping needs of these personas (Fast ordering, nutrition, and parking)

Different solutions encompass different parts of the ordering process

But each innovation impacts the amount of customization possible for the order

Potential Risk and Assessment

Stage 2: 

Stage 3: 

 

MVP and Prototyping Ideas

Storyboarding

We built storyboards for our most promising 5 ideas

User Testing & Field Research

We went to Sheetz and interviewed customers, but we also interviewed millennials on campus

Respondents at Sheetz:

  1. Male around late 20 to early 30 (App user)

  2. 20ish male (App user)

  3. Uber Driver middle-age worker (No app)

  4. Male around 30 years old (No app)

  5. Middle-aged woman (No app)

Respondents on campus:

User Testing Results

Ages 20 - 28, mix of men and women, mix of Sheetz customers and non Sheetz customers

Store interior

Risk Assessment

How we assessed previously identified risks

Conclusion

One-click ordering and voice ordering were both popular concepts, but each had a major drawback:

  • Many of the complaints about voice order were about its ability to understand something complicated and that the technology probably wasn’t there.

  • While one-click ordering for past orders was a very appealing idea, it turns out it exists! The problem is that people don’t realize it because you have to favorite items after you’ve ordered them.

So, we’ll be prototyping to see if we can simplify the repeat order process and make it more obvious and accessible by bringing in voice.

Ordering on Sheetz Mobile App

Ordering on Sheetz In-store kiosk

Stage 3: 

Final Stage:

 

Prototyping

After researching further, we decided to prototype on voice ordering for multiple kinds of quick orders, not the full menu and not just repeat orders.

Reasoning:

  • Sheetz had tried voice ordering with Alexa and online feedback indicated that people were unhappy with just ordering favorites.

  • Existing voice solutions at other restaurant chains were only using voice for only quick orders. Examples: Dominos, Pizza Hut, Denny’s

  • Prototyping subjects express doubt in the technology of full-menu ordering

  • Sheetz’s menu was too large and there were too many customization options for full ordering to make sense. 

Brain Storming on the Voice ordering flow 

Initial Voice Ordering flow chart

Final Voice Ordering flow chart

We modeled the logic of how voice ordering might work

We modified our voice order process to be more efficient

Voice Agent

We researched voice agents and decided on Siri

Reasoning:

  • Based on our storyboard feedback, ordering on the go was the actual barrier. If we were actually going to solve a pain point, we needed a solution that was available on the go.

  • Siri is the most popular mobile voice agent.

  • iPhones are the most popular smartphone in the United States.

  • Apple recently created Siri Shortcuts for third-party developers to use, and other companies like Caviar are already using this to voice order food. There’s precedent.

  • Sheetz already had an Alexa skill, but Alexa only had 10% of the mobile voice agent market share.

Service Blue Print

User Journey Map

App Mock-Ups

Wireframes

Hi-fi 

Onboarding and Home

The users are asked to select the personal preference on the type of food items for the Sheetz Voice Ordering personalized recommendation.

User are able to see their orders preparing progress, favorite items, and past orders on the home page.

Quick Reordering

Concept Video Development

Storyboarding the Frames

We made a video storyboard before committing to filming or voicing anything to think through the concepts

Final Video

We filmed the video to prototype the voice ordering process and to prepare to get feedback

Video Feedbacks

We showed our video to Millenials, white-collar males, and moms, and got very positive feedback. People re-validated the problem of ordering on the go and were excited about our solution. 

Risk Assessment

How we assessed previously identified risks

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