Case Study
Web Analytics Dashboard B2B Supersmart
Background
Supersmart is a B2B2C company that develops solutions for smart shopping in retail stores, primarily in supermarkets and convenience stores. Among their products are a scanning application, a tablet-based management system for store employees, inventory management systems, interfaces for scanning devices, a smart cart application, and more. Control over all these tools is remotely managed through a web-based dashboard accessed by managers and store administrators. The dashboard allows managers and store administrators to remotely control and oversee these tools.
Supersmart needs a dashboard to effectively manage its store operations, optimize workflow, and provide superior customer service.
The dashboard serves as a centralized hub for managing store operations efficiently. It provides real-time insights, facilitates inventory tracking, enhances customer service through the smart cart application, and streamlines overall workflow for store employees. By offering remote access and control, the dashboard enables managers to make informed decisions, optimize processes, and ensure smooth operations across multiple locations.
The Challenges
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Data should be persenolised per user persona. Flexible prioritization of visual data presentation according to diverse client needs.
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Quickly identifying and understanding patterns through a large volume of transaction data to find specific issues like: customer buying patterns and inventory turnover.
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Need for real-time insights to make proactive decisions. Accessing consolidated data across multiple stores.
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Providing seamless support for over 15 different languages.
Main Goal
Our main goal was to define personas, map and address their different needs from the system.
Empower administrators and users of retail companies, enabling them to create the most functional dashboard system for their daily busy work.
My Role
UX Design Lead (Hands-on):I led the UX of the project and collaborated with one other UXer. In addition, I worked closely with a Product Manager, alongside a UX Content Writer,
2 Full-stack Developer and 2 Front-end Developer, 1 data analyst and 2 computer vision engineers.
Architecture Design, sketching, workflow, UI, prototyping, dev handoff, design reviews, and support through development.
Research and user needs
In researching Supersmart’s web dashboard analytics, the product team focused on understanding user needs and identifying pain points in their journey. Our approach began with user interviews, targeting various personas using the system, such as store managers, cashiers, and IT personnel, to gather insights into their daily interactions with the system and their specific requirements. These interviews revealed key challenges, such as difficulty in accessing real-time data and navigating the dashboard’s interface.
To ensure our design solutions were aligned with real-world demands, we partnered with major retailers like Metro and H-E-B. These collaborations helped us specialize user goals, creating the fastest and easiest ways for daily call-to-actions, ultimately enhancing the overall user experience. Combining Competitors Analysis with our designed partners helped us
We made direct observations at actual supermarkets, where we closely monitored how users interacted with the dashboard in a live environment. This allowed us to see firsthand the context in which the system is used, uncovering issues like slow load times during peak hours and confusion caused by unclear data visualizations.
Additionally, we conducted a thorough data analysis on the system, examining usage patterns, error logs, and performance metrics. This quantitative approach helped us pinpoint specific pain points, such as frequent disconnections and inconsistencies in data reporting. The data collected by combining qualitative insights from interviews and observations with quantitative data analysis, played a crucial role in the design planning of the dashboard, fostering a deeper understanding of customer needs and more intuitive and efficient user experience insights.
The Solution
Use Case 1
Persona
Nir Hirsh
Data Integrity Administrator,
Persona on Retail / Store Level
Using Dashboard Analytics
Goal
Monitor and analyze override types for transactions that failed validation to maintain data accuracy and identify underlying issues.
User Flows Diagram
Wireframes
Missing Weight Widget Flow
Screens
1. Main Widget Screen
• Overview: Key performance indicators (KPIs): A high-level summary of all transactions validation.
• Widgets: Charts and graphs providing an at-a-glance view of trends and anomalies. Quickly identifying and understanding patterns in failed transactions that required overrides. The way to efficiently navigating through a large volume of transaction data to find and solve specific issues.
2. Table Screen with Items List and System Recommendations
A detailed table view of all failed transactions requiring overrides.
Columns for transaction ID, override type, failure reason, date, responsible personnel, and system recommendations for resolving issues.
3. Specific Item Detection Screen with Manual Actions
A focused view on individual failed transactions and their specific details. Visual indicators for detected issues, step-by-step breakdowns of the validation process, manual action options (e.g., revalidate, adjust data, escalate to a higher authority), and context-sensitive help.
Use Case 2
Persona
Vlad Reznik
Admin for a retail chain,
Persona on Store Level
Using Dashboard Analytics
Goal
To enhance store performance by leveraging key business metrics.
Optimizing inventory management and improve sales strategies.
Identify and adress any operational inefficiencies.
User Flows Diagram
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Wireframes
Profitable Item Flow
Screens
1. Main Widget Screen
The Real-time Revenue Monitoring screen now offers a more intuitive interface with simplified navigation. Real-time sales data is displayed through dynamic charts and heat maps, providing clear visuals of trends and peak periods. A comparative analysis feature helps Vlad quickly identify underperforming stores by comparing key metrics. Widgets offer at-a-glance revenue summaries. These enhancements enable Vlad to swiftly identify and act on revenue optimization opportunities.
2. Inventory Tracking Screen
The Inventory Tracking screen now features a centralized dashboard with color-coded alerts for low inventory on high-demand items. Predictive analytics forecast inventory needs based on sales trends and seasonality. Automated restocking alerts ensure Vlad receives timely notifications to prevent stockouts. Interactive elements allow Vlad to drill down into specific product details and statuses. This design supports proactive inventory management, minimizing sales loss and optimizing stock availability.
Key Enhancements
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Personalized Data Presentation:
Incorporate user-specific customization to allow different personas to prioritize relevant data, including personalized dashboards and tailored alerts.
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Smart Inventory Management: Provides insights into inventory turnover rates, helping users optimize stock levels and reduce overstocking and easily identify inventory that fails validation.
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Real-time data integration: Unifies data from different sources into one dashboard, offering users a comprehensive view of the store's performance in real-time and enabling simple actions to clean data easily.
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Sales Analysis: Analyzes sales trends and customer buying patterns, enabling all users to make informed decisions on product placements and promotions.
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