Instacart is a grocery delivery and pickup service app, connecting users with personal shoppers who handpick items from local stores and deliver them directly to the user's doorstep. The platform partners with various grocery chains, allowing users to shop from a wide range of products, schedule delivery times, and even chat with shoppers in real-time. Offering a convenient solution for busy individuals, Instacart emphasizes a seamless shopping experience from the comfort of one's home.
Why Instacart?
We aimed to select an application with a high rate of recurring usage, one that users return to every month or at least every few months. What could be more fitting than a grocery delivery app? An application that users consistently rely on and use repeatedly. The surging popularity of online grocery platforms, influenced by global shifts and an emphasis on convenience, renders Instacart a prime candidate for usability analysis. Ensuring its design meets evolving user demands is paramount.
We are targeting graduate students from the age group of 20-30 years. When we researched (desk research) before setting up a demographic, we found that most of the participants using the app fall in this age range and are graduate students.
User Personas
We carefully selected a diverse group of international students for our interviews based on demographic data. Our goal was to deeply explore how international students perceive and use Instacart, considering various factors that might influence their experiences. We engaged with international students with different levels of familiarity with Instacart, ranging from frequent users to newcomers, and considered their cultural backgrounds, academic majors, and the duration of their stay in the United States.
Check out the interview questions here.
Strengths:
Improvement Areas:
Affinity mapping is a collaborative technique used to organize and synthesize the vast amounts of unstructured data gathered from interviews. By visually clustering similar ideas and insights, it aids in discerning patterns, identifying overarching themes, and pinpointing areas of concern or opportunity. This method not only ensures a holistic understanding by combining different perspectives but also reduces individual biases, making insights more grounded and actionable. In essence, affinity mapping transforms raw, qualitative data into clear, visual representations that can guide subsequent decisions and strategies.
Codes in UX search are essential for several key reasons. They help organize and categorize large amounts of qualitative data, making it manageable. These codes also serve as the foundation for data analysis, allowing researchers to identify trends and insights in user behavior and preferences. Additionally, codes provide a standardized language for data interpretation and facilitate communication among team members and stakeholders.
We conducted a survey to understand the demographics of online grocery shoppers and found Instacart to be a predominant choice among them. Through Think Aloud sessions with 10 diverse users, primarily representing the 20-30 age bracket of graduate students, we delved into common challenges faced during their app usage. This targeted demographic was chosen based on our initial desk research, which indicated that a significant portion of the app's users were graduate students within this age range.
User Experience Issues with Instacart App:
We conducted SUS Rating with our 10 participants. We gathered the data and used that data to analyze and understand the perception of different users and how different users rate the application. The SUS rating refers to the System Usability Scale. It provides a quantitative measure of usability and user satisfaction. Higher SUS scores indicate better usability and user satisfaction.
In this study using the System Usability Scale (SUS), participants assessed Instacart-App’s usability, revealing a mix of strengths and areas for improvement. A key concern raised by multiple participants was the application's perceived complexity, which they found unnecessarily intricate. This indicates a need to simplify the user interface and interactions, as complexity can discourage user adoption and lead to frustration.
Participants also noticed inconsistencies in the application's design and functionality, highlighting the importance of design and interaction consistency for a smooth user experience. Inconsistencies can confuse users and inhibit efficient navigation. Furthermore, the participants expressed the need for assistance when using the application, suggesting room for improvement in the user experience to enable more self-guided navigation and reduce reliance on external help.
Check the complete calculation here.
1. Streamlined Interface: Simplifying the design can directly improve user experience and retention. Reduce design clutter and prioritize core functions to enhance user navigation and decision-making.
2. Design Consistency: Uniform design elements prevent confusion. Adhere to a consistent design language, including consistent icons, buttons, and color schemes across the app.
3. Performance Optimization: Slow app performance can deter users. Implement back-end and front-end optimizations, focusing on areas highlighted by user feedback, such as search and load times.
4. Enhanced Price Comparison: Comparative shopping is a key user expectation. Offer a feature that shows comparative prices from different stores for a chosen product, allowing informed decisions without extensive navigation.
5. Personalized Shopping Experience: Enhancing user convenience can foster loyalty. Introduce a "Repeat Last Order" option and use algorithms to suggest products based on user behavior and preferences.
6. Real-time Communication: Direct communication can improve user satisfaction. Integrate a chat feature for users to interact with delivery personnel, aiding in better order accuracy and coordination.
7. Prominent Promotions: Users seek value deals. Position offers and deals at strategic locations in the app, like the homepage, ensuring visibility.
8. Efficient Checkout Process: A simplified checkout can enhance conversions. Refine the checkout flow, reducing unnecessary steps and offering an express option for frequent users.
Next Steps in the Research and Evaluation Process:
1. Prototyping: Based on the recommendations, create low-fidelity prototypes to visualize the proposed changes. Tools like Sketch, Figma, or Adobe XD can be used for this phase.
2. User Testing on Prototypes: Conduct usability tests on the prototypes with a small group of users to validate the proposed changes. This will help identify any potential problems before development begins.
3. Feedback Integration: Analyze the results from the prototype testing and refine the design accordingly. Address any new pain points or challenges that emerge.
4. High-Fidelity Design: Progress to high-fidelity designs that incorporate detailed visual and interaction elements. These designs should be a close representation of the final product.
5. Development Collaboration: Work closely with the development team to ensure that the designs are implemented accurately. Regular check-ins will be crucial to align design intent with technical feasibility.
6. Beta Testing: Once the changes are developed, launch a beta version of the application. Invite a subset of users to test this version in real-world scenarios and provide feedback.
7. Iteration: Using feedback from the beta testing, make any necessary refinements to enhance functionality and user experience.
8. Continuous Monitoring & Feedback Loop: Establish mechanisms for ongoing user feedback collection, like analytics tracking and periodic surveys. This ensures you're always attuned to user needs and can respond with timely updates.
By following these steps, we'll ensure a thorough and iterative approach to refining and enhancing the Instacart user experience, grounded in real user feedback and rigorous testing.
