Artificial Intelligence (AI) is projected to reach $126 billion by 2025, and Machine Learning (ML) has become a key in personalization and automation. That’s why the integration of AI and ML into online 3D product configurators is revolutionizing how sellers and buyers interact with product designs on websites. Through AI and ML-empowered features, everyone can freely customize and visualize products in real time for a better experience.
This blog will explore how AI and ML level up the performance of 3D sales configurators to drive innovation and customer interest, leading to more business sales and revenues.
An overview of online 3D product configurators
What is a configurator? A product configurator is a visual tool or software that allows users to design, customize, and visualize products immersively to various specifications. With online 3D product configurators, everyone can view all variants and combinations in 360 degrees and work with more interactive visualizations for a unique shopping journey.
Here are some highlights about how a 3D sales configurator benefits your website:
- Product visualization: Customers can easily rotate, zoom in, and interact with designs from every angle more immersively than static, physical, and 2D visuals.
- Sales processes: Everyone can instantly visualize and see their product designs, reducing time spent communicating back and forth between parties.
- Conversion rates: By showcasing how customers’ designs will look in reality, 3D configurators help minimize their confusion about products and close deals faster.
- Customer satisfaction: With product configurators, customers can interact more with true-to-life designs, helping increase their engagement and positive feelings.
- Orders and revenues: More satisfaction with your products makes buyers feel more trustful about adding more items, leading to increased AOV and revenue.
Roles of AI and Machine Learning in Empowering 3D Product Configurators – 350w
Artificial Intelligence (AI) and Machine Learning (ML) have enabled sellers and buyers to achieve more dynamic online 3D product configurators that require less manual effort. However, AI and ML can not replace the old logic configuration; they are only the next generation of innovation adopted in sales configurators for more advanced performance.
Let’s check the 3 most significant aspects that AI and ML level up these configurators.
Drive a more customer needs-based configuration method
AI and ML can be used to analyze customer behavior, preferences, and historical data on your 3D product configurator for proper, tailored configurations. This personalization is effective in enhancing customer satisfaction and leading to higher site conversion rates. As an interesting recent point from WARC, “87% of online shoppers were comfortable sharing personal information with brands in exchange for better online shopping.”
Empower large datasets for informed decisions
ML excels at processing large, complicated datasets to ensure that online 3D product configurators can offer smarter recommendations for buyers when visiting your website. This seems similar to the first benefit, but ML focuses more on your business by listing practical and profitable configurations based on inventory levels and previous feedback.
Here is an example: When a product configurator recommends popular trim packages based on regional data, you can effectively optimize stock and reduce overproduction. This is key to making informed decisions in sourcing and manufacturing at your business.
Save time and effort for salespeople
AI-powered sales configurators can automate repetitive tasks, freeing the sales team to focus on relationship-building with stakeholders like suppliers or customers. These tools are designed to generate accurate 3D visualizations, prices, and quotes in real-time. Consequently, salespeople will spend less time and effort interacting with customers because each variant, combination, and customization is displayed quickly and clearly.
Best Practices when Adopting AI and ML in 3D Product Configurators
To succeed in implementing AI and ML into your online 3D product configurators, you need to have a proper, comprehensive strategic approach to maximize benefits. Understand that this section will list out some best practices that you consider carefully:
1. Solve real problems rather than just adopting new tech
Adopting AI and ML for the sake of trends can backfire. Instead, identify specific pain points—like slow rendering times or poor personalization—and use AI and ML properly. Indeed, the integration of AI and ML into 3D product configurators is not similar in niches; some products demand these technologies for a better experience, and others don’t. That’s also why successful implementations should ensure a higher return on investment.
2. Start gradually and allow for learning and adaption
Always begin a pilot project as testing, such as adding AI-driven recommendations to your existing sales configurators first. This is crucial to learning a new technology, gathering user feedback, and then scaling up gradually for comprehensive improvement. From that, you can reduce the risks of a one-time investment and make refining easier.
3. Look for proper AI and ML-driven features
If you are confused about what to start with AI and ML in your online 3D product configurators, below are some expert suggestions that you can consider for upgrades:
AR & VR
AI and ML significantly empower Augmented Reality (AR) and Virtual Reality (VR), especially transforming 3D visualizations in complex or tailor-made products such as furniture, kitchens and baths, or architecture. Both sellers and customers can walk true-to-life product designs in an immersive space, fostering a deeper understanding. This is also essential to boosting customer engagement, collaboration, and feedback.
Real-time rendering
When it comes to real-time rendering, the role of ML algorithms is much more important. These algorithms can instantly ensure accurate photorealistic visualizations, helping save time and effort compared to traditional rendering techniques. As a result, you can reduce the lead or waiting time for both sellers and buyers, leading to faster-informed decisions.
Generative & transferable design
While generative design allows for exploring design possibilities that your technical team established before, style transfer helps transform a simple 3D model more artistically. Both can be driven by AI, ML, and computational power for the best-finalized products. You will discover designs that are well-structured for functionality as well as aesthetics.
Conclusion
The fusion of AI and Machine Learning with online 3D product configurators reshapes e-commerce, offering personalized, efficient, and visually stunning experiences. Remember to adopt best practices for using AI and ML in sales configurators to keep ahead in a competitive market and optimize upfront investments into these technologies.
