Creating an Innovative and Intuitive Interface for Furniture E-commerce Platform

DBB Software has recently developed a highly intuitive interface and 3D-visualization design technology, providing photo-realistic renders of interior and exterior settings for a global furniture e-commerce platform. More information about the incredible potential of AI to transform e-commerce and interior design can be found in our previous article. The client’s task was to create a fully automated, AI-based interior design virtual stylist that could completely change the way people shop online and add in the required context for a confident purchase. Below, we’ll trace the project’s stages and evaluate the results that were achieved.

Challenge

The client was an e-commerce company that primarily focused on the sale of furniture.

The challenge was to develop comprehensive solutions for an e-commerce platform to accommodate various interior design preferences and options for different needs. It had to be an online marketplace with an intuitive, user-friendly interface and a virtual stylist for the immersive experience of choosing the furniture for a customer’s interior.

The general solution involved creating a user-friendly interface with the virtual stylist for a furniture e-commerce platform. First, we need to complete a questionnaire and several slides on the website on which the client will answer questions. The next step was to develop an algorithm according to the results of the questionnaire that would choose furniture for the room. After that, we must build a 3D room design with selected furniture.

Business needs:

• The client’s company provides several interactive widget solutions for online furniture stores all over the world
• Each solution should have the ability to be integrated into the vendor’s website
• Data for these widgets should be fetched from vendors in different ways.

Challenging Tasks:

• The large number of furniture pieces that we need to synchronize with the databases of customer stores (vendors)
• Integration with different clients, which have their stores, and various technologies are used. Therefore, integration was simplified in several stages.
• Implementation of sampling algorithms and performance optimization for them - the algorithm is quite complex and involves many queries to the database that are difficult to combine, and the requirements for the speed of building a design are 4-5 seconds

Tech stack

The process is built on the agile methodology:

1. Sprint is scheduled for two weeks
2. Tasks are added to the monday.com board
3. Tasks are divided into three main groups
   • current sprint
   • next sprint
   • backlog
4. Once every two weeks, the team estimates tasks from the backlog and the product owner creates the next sprint
5. Twice a week 30-60 minutes the team meets with the customer (sprint planning, retrospective, demo)

Our software development team leveraged a blend of cutting-edge technologies and frameworks to execute this project.

• Angular 13
• React
• Node.js
• Express
• Next.js
• NestJS
• Python (Django) for the admin panel
• Google Cloud for deployment
• Jenkins
• AWS for deployment
• PostgreSQL
• Redis
• Knowledge Graph
• GoLang
• Azure

Implementation and Features

We began the development process with the tech stack and solution design in place. The team worked in an agile manner, developing and integrating the technologies. Practical tips for easy navigation of the process and optimal results when creating realistic room designs with 3D rendering can be found in Leveraging 3D Room Design and Cloud Platforms for Realistic Rendering.

The UI/UX team ensured that the virtual design was translated into an intuitive and user-friendly interface. Python was used for integration with the machine learning model.

Product features:

1. Easy and seamless integration with vendor sites is implemented through GA scripts
2. Analytics from vendor’s sites are collected using the Facebook Pixel approach
3. Based on this analysis, user-oriented designs are created (different for each logged-in user)
4. The design creation algorithm prepares a list of recommended furniture items and up to seven alternatives for each of them based on the single selected item

Results

We gave the client technical solutions that met their current business ideas and needs. Four products were developed:

• CTL: collage with images of furniture items
• STR: photo of 3D-designed room with 3D-designed furniture
• Virtual designer: a questionnaire that prepares designs based on users' answers (CTL or STR is configured on the vendor’s side)
• 360-degree iFrame with one furniture item with the ability to rotate it

The developed technologies made a platform for online shopping more convenient and feature-rich, with benefits such as a wide furniture selection, interior stylist options, and a user-friendly interface.

Correlated Deep Tagging hyper-personalizes the shopping experience by making products more discoverable and improving the tagging accuracy with computer vision AI. The created methodology elevates and inspires online experiences, creating visually appealing interactions throughout the funnel.

Correlated deep tagging improves filtering based on the categories shoppers want to explore by adding context when creating a match. It delivers the most accurate results for both small vendors and marketplaces with large inventory sources. This solution works on multiple visual discovery cues that shoppers can select, combine, or remove until they find exactly what they want. In a way, it turns a product catalog into a tailor-made one. Filtering out items that do not fit the exact criteria for a more accurate search alleviates shopper frustration and focuses solely on effective product discovery and personal style, enabling personalized style-based recommendations like similar items and a full look.

We provide the technology that bridges product discovery and purchase, providing the ultimate tools for increasing conversion and AOV and cementing brand loyalty.

Client values:

• We are currently working on a new microservice architecture for an existing solution
• Training Chat GPT collects parameters for existing algorithms of design creation from users through on-site chat
• Using graph-oriented DB (Knowledge Graph) to optimize the performance of the design creation algorithm
• Preparing storybook for React component reuse across all features

Summary

In this project, we developed an innovative, user-friendly interface for an e-commerce platform with an easy-to-use virtual stylist, multi-functionality, and a high degree of usefulness. Explore our case study and see how partnering with DBB Software can propel your business to new heights in digital healthcare solutions. To explore more about the paramount importance of an optimized UI tailored specifically to the needs of e-commerce businesses in the interior design space, look at Reimagining Interior Design E-Commerce: The Power of Intuitive UI.