Add a recommendation feature for products from different brands based on user search history
Seamlessly connecting them to a diverse array of products from different brands, tailored to their unique preferences and desires
Customers today expect tailored recommendations that align with their unique preferences and interests. To meet this demand, E-Commerce Express, an online marketplace offering products from various brands, aims to enhance the shopping experience by implementing a personalized recommendation feature based on user search history.
Introduction
Bewakoof is a popular Indian online shopping platform that offers a wide range of trendy fashion apparel and accessories for both men and women. Bewakoof has gained popularity for its trendy fashion offerings, quirky style, and seamless shopping experience. The app aims to cater to the preferences of young shoppers who seek fashionable and casual apparel and accessories.
The 48 Hours Product Design Challenge is indeed an intense and immersive experience that challenges participants to apply their design skills and creativity to conceptualize, design, and prototype a product that solves a real-world problem, all within a limited time frame of 48 hours.
The solution I came up with is below
Problem Statement : Add a recommendation feature for products from different brands based on user search history
Overview:
The goal is to enhance the Bewakoof app by providing personalized product recommendations to users based on their search history. By analyzing users’ previous searches and purchase behavior, the app can suggest relevant products from different brands that align with their preferences and interests.
Screen Expiation
The decision to use Collaborative Filtering with Matrix Factorization is based on its ability to provide accurate and relevant recommendations. By leveraging the collective wisdom of users with similar search histories Collaborative Filtering with Matrix Factorization is chosen as it allows me to analyze user search histories and identify patterns and similarities among usersThis technique enables me to match users with similar preferences and behaviors, and suggest products from different brands that have been favored by those similar users.
What are the pros and cons of implementing a recommendation feature
What factors should be considered when making a decision ?
The intention of the design was to use it as a form of branding. Updates to the app should include elements that relate to the brand. The product page should include offers, as well as advertising the tribe values. The design should be consistent with the branding already used in the app. The sorting feature allows users to customize their product experience by organizing and prioritizing recommended products according to their preferences. A button should be added to the Carousel so that users can easily view items in more detail.
How Will This Decision Impact the Business?
Improved Customer Experience: By providing personalized and relevant recommendations, the app can enhance the overall customer experience. Users will feel that the platform understands their preferences and can discover new products that align with their tastes. This can lead to increased engagement, satisfaction, and loyalty.
Increased Conversion and Sales: By suggesting products from different brands based on user search histories, the recommendation feature can drive higher conversion rates and sales. Users are more likely to make purchases when they are presented with items that match their interests. This can positively impact the bottom line and contribute to revenue growth.
Enhanced Product Discovery: Collaborative Filtering with Matrix Factorization can help users discover products they may not have come across otherwise. This can increase exposure for different brands and items within the app’s inventory, potentially driving sales for lesser-known products. It can also encourage users to explore a wider range of offerings.
Customer Retention and Engagement: Providing personalized recommendations can increase user engagement and retention. Users are more likely to continue using the app if they consistently receive valuable and tailored suggestions. Repeat visits and increased time spent on the platform can lead to higher customer lifetime value and brand loyalty.
Competitive Advantage: Implementing advanced recommendation techniques like Collaborative Filtering with Matrix Factorization can give Bewakoof a competitive edge in the market. By delivering accurate and relevant recommendations, the app can stand out from competitors and attract users who value personalized shopping experiences.
What key metrics should be tracked?
Conversion Rate: A high conversion rate indicates that the recommendations are effective in influencing user buying decisions and driving sales.
Average Order Value (AOV): Analyze the average value of orders that include recommended products compared to those without recommendations.
User Retention: Higher user retention indicates that the recommendations are enhancing the overall user experience and keeping users engaged.
The iteration process
Iteration 1
Design using the brand which is already being used in the app
By designing the recommendation feature based on the brand already being used in the app, you leverage the user’s existing familiarity and interest in that brand. This approach can enhance user engagement, encourage brand loyalty, and increase the likelihood of conversions as users are presented with products they are more likely to be interested in.
Let me show you how it looks like
Iteration 2
The sorting feature allows users to organize and prioritize the recommended products based on their preferences
The sorting feature is a functionality that allows users to organize and prioritize the recommended products based on their preferences. It gives users the ability to customize how the recommended products are displayed to align with their specific needs and interests
Let me show you how it looks like
Iteration 3
Add a button to the Carousel so that the products can be viewed in detail
By adding a button to the Carousel and linking it to the product’s detail page, you provide users with the ability to view products in more detail when they are interested. This enhances the user experience by offering easy access to additional information and allows them to make more informed decisions about the products they are considering.
Let me show you how it looks like
Aspects of construction
Strategies and adjustments can be implemented after each iteration
Final Flow
Key Learnings
- Personalization Matters: The significance of personalized recommendations in e-commerce apps. Tailoring product suggestions based on user search history can improve engagement, boost sales, and foster customer loyalty by creating a more personalized and relevant shopping experience.
- Data-Driven Decision Making: The value of leveraging data, such as user search history, to gain insights and inform design decisions. Analyzing user behavior patterns helps in understanding user preferences, improving the accuracy of recommendations, and driving effective personalization.
- Brand Identity and Tribe Values: The impact of incorporating brand items and highlighting tribe values in recommendations. Showcasing unique brand identities and aligning recommendations with shared values can foster emotional connections, increase user engagement, and cultivate a sense of belonging within the user community.
- Business Growth Opportunities: The potential impact of solving user pain points and enhancing the user experience on business growth. By providing personalized recommendations, increasing customer satisfaction, and fostering loyalty, businesses can drive sales, improve customer retention, and gain a competitive advantage in the market.
- Continuous Iteration and Improvement: The importance of ongoing iteration and improvement based on user feedback and market trends. By continuously refining the recommendation feature and adapting to evolving user preferences, businesses can stay relevant and maintain a competitive edge in the dynamic e-commerce landscape
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