Sainsbury's
Client: Sainsbury's
Sector: Design, Interaction
My Role: Entire product design from research to conception
Project Time: 1 month
Here’s a clear overview of our project roadmap, from secondary research to design limitations and future plans. We began by researching one of Sainsbury's major challenges—substitution. Through secondary research, we gained a better understanding of online packing processes, followed by primary research to identify user pain points. After generating insights, we conducted prototype testing. Finally, we developed our concept, defined its limitations, and outlined the next steps.
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What is the problem of Sainsbury's substitutions?
- Sainsbury's has one of the lowest satisfaction ratings for substituted items in the UK's top supermarkets.
- Substitutes often fall short of customer needs and expectations leading to customer dissatisfaction and poor overall shopping experience.
Hunt Statement
'We are going to research the substitution practices of Sainsbury’s pickers to identify opportunities to improve the quality of these decisions, increasing customer satisfaction and strengthening customer-colleague interaction.'
Assumptions & Research Methods
We made assumptions to improve the substitution process by
1. enhancing personalisation to better meet customer needs
2. providing colleagues with clearer guidance for making more appropriate substitution choices
Data Analysis
In total, we interviewed two customers and two colleagues as our target users for the research. In addition, we received 13 responses from local participants. The data from the interviews were analysed through an affinity diagram.
Affinity Diagram
Findings from interviews and observations
Unexpected Items - Customer 01
Users are receiving replacements for their items that are either unusable, dissimilar, or in incorrect quantities. This creates inconvenience for customers (e.g., requesting refunds), ultimately resulting in a poor user experience.
Lack of Transparency - Customer 02
Users often lack the time to check delivery information, leaving them unaware of substitutions until the delivery arrives. This inconvenience forces customers to accept unsuitable replacements.
Lack of Customer Insight - Colleague 01
Colleagues lack insight into the customers they pick for, often making substitutions based on intuition or general recommendations. As a result, customers are more likely to receive items that do not meet their personal standards.
Business-driven substitutions - Colleague 02
Colleagues may substitute items based on business objectives, such as prioritising products with shorter expiration dates. This leads to customer dissatisfaction when they receive items with reduced freshness or shorter shelf life.
Empathy Map
To understand the feelings of customers and colleagues, we analysed them through an empathy map.
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Pain Points
Customers
1. They can not inform Sainsbury's of their personal substitution preferences.
2. They receive goods they don't want with insufficient quantity, lower quality or shorter shelf life.
3. It's easy to miss out on delivery info about substitution.
4. Difficulty in being flexible with unsatisfactory substitutes after accepting items.
5. They were confused and dissatisfied with the price of substitutions.
Colleagues
1. They are unaware of customer preferences such as type, price, quantity and quality.
2. They use intuition to choose substitutions when recommendations fail, which is time-consuming.
3. They don't have a clear picture of stocked goods. There is a lack of system support.
4. They cannot tell if users will accept substitutions, or receive feedback on past choices.
5. Long-distance picking affects picking time and IPH.
User Journey Map
To understand the customers' feelings, pain points and colleagues' points of view during the whole process.
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Design Opportunities
After creating journey maps, we developed "How Might We" statements to generate ideas for enhancing customers' and colleagues' interactions and experiences.
01 HMW - Customer
Enable customers to efficiently and easily choose their ideal substitutions through flexible options and user-friendly interfaces?
02 HMW - Customer
Optimise the substitution recommendation system to ensure recommended substitutes better meet customer needs and expectations?
03 HMW - Customer
Improve pre-delivery communication and provide guarantees for returns and exchanges to ensure customers feel confident in their substitution choices?
04 HMW - Colleague
Reduces time for colleagues to select alternatives?
05 HMW - Colleague
Provide tools and techniques to help employees quickly assess the suitability of potential substitutes based on customer preferences and product attributes?
06 HMW - Colleague
Provide better support to employees to avoid them being forced to provide substitution when no suitable substitutions are available?
Design Concept
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Low-in-stock Notification: A notification system that alerts customers when an item is about to go out of stock.
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Customised Substitution - based on the AI system: 1. Users can apply "tags" to filter substitutions for items likely to be out of stock, ensuring replacements better match their specific needs. 2. The AI system will match the customer's tags with the original item to provide a more suitable substitution. 3. Customers are presented with three substitution options, offering greater flexibility and convenience.
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Tracking the process: Users can view which items have been substituted during the 'tracking process.'
Customer and Colleague Journey Improvement
To identify potential improvements, we combined the two user journeys to analyse their pain points collectively.
Prototype-Customer
After developing the "how might we" statements, we used a matrix to identify the best opportunities to address the problem. Once we selected the design concepts, we created wireframes and prototypes to conduct user testing.
Prototype-Colleague
Usability Testing
We conducted testing of our final high-fidelity prototype with 4 customers and 2 colleagues to gather insights on how our design delivers value to users. We evaluated the prototype's usability by guiding users through a series of tasks and asking them to rate their experience using the System Usability Scale (SUS). Overall, we received a SUS score of 75.9, indicating a solid user experience.
Measuring Success
To measure the success of our prototype, we established three key metrics:
1. Substitution Acceptance Rate
To what extent are customers accepting substitutions?
2. Customer Satisfaction Rating
How satisfied customers are with their online purchasing experience?
3. Colleague Satisfaction Rating
How happy are Sainsbury's colleagues with online picking?
Limitations & Challenges
1. Customer completion
If too many items are tagged as ‘likely to be out-of-stock’, customers may become frustrated and decide to abandon their shopping session altogether.
2. Low tolerance for error
Our concept hinges on precise stock monitoring, where every item must be meticulously tracked.
3 .Previous data
The AI substitution system must integrate seamlessly with existing technology and processes, leveraging historical data to accurately predict stock levels.
4. Substitution Error
If the AI system fails, customers may receive an incorrect substitution item.
Future Directions
1. Introduce complementarity as a metric
Introducing complementarity as a recommendation metric to enhance the acceptance rate of substitutions.
2. Enhance AI System Accuracy
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Precision of Recommendations
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Stock Monitoring Reliability
3. Cross-Store Inventory Synchronization
Implement real-time shelf monitoring to facilitate substitutions across stores.
4. Broader Application in Business
Expand the system's application to various scenarios, such as stock monitoring, to enhance commercial profitability at Sainsbury's.
"Our Next Level Sainsbury's strategy is about giving customers more of what they come to Sainsbury's for - outstanding value, unbeatable quality food and great service.”