In a recent episode of Talk Commerce, I had the pleasure of sitting down with Rochelle Thielen, CEO of Traject Data, to explore the transformative impact of retail data automation on the industry. While conversations about AI dominate headlines, our discussion revealed that the true revolution lies in how automated data collection and analysis are powering these solutions.
The Scale of Retail Data Automation Today
During our conversation, Rochelle revealed some staggering numbers about data collection in modern retail. “When we’re talking about quantity, we’re looking at 100 million data points per day for some enterprise users,” she explained. This massive scale of data collection is what’s enabling the sophisticated AI solutions we’re seeing in retail today.
As someone who’s been in the e-commerce space for years, I was particularly impressed by how this data is being put to practical use. The sheer volume of information being processed is mind-boggling, but it’s the application that really matters.
Real-Time Decision Making in Retail
One of the most fascinating insights Rochelle shared was about the importance of real-time data. “If you’re more than 24 hours old on data, you’re pretty far behind,” she noted. This is particularly crucial for:
- Dynamic pricing strategies
- Inventory management
- Customer experience personalization
- Competitive analysis
The Human Element in AI Implementation
Something I strongly agree with, and Rochelle emphasized, is the continued importance of human oversight in AI systems. She stressed that “humans are still controlling what the AI is doing,” with teams regularly verifying data samples to ensure accuracy. This human-in-the-loop approach is crucial for maintaining quality and preventing potential pricing or decision-making errors.
Transparency in AI Customer Service
We had an interesting discussion about chatbots and AI-powered customer service. Rochelle made a compelling point about transparency: “You need to be transparent. People don’t negatively look at interfacing with a bot as long as the bot is equal to or better than the human.” This approach to honest AI implementation is something I’ve always advocated for in e-commerce.
Looking Ahead: 2025 and Beyond
Looking to the future, Rochelle shared some exciting predictions. The focus is shifting toward true omnichannel experiences, with particular emphasis on:
- Integration of social media data (including TikTok)
- Enhanced visual and video data processing
- Democratized access to AI tools for smaller retailers
- Sophisticated fraud prevention systems
Real-World Applications
One of the most impressive examples Rochelle shared was how their data helps prevent fraud and unauthorized reselling. For small businesses, their systems can detect when purchased items are immediately listed for resale on platforms like eBay, helping protect inventory and brand value.
Final Thoughts
As we wrapped up our conversation, it became clear that we’re at an exciting intersection of big data, AI, and retail. What impressed me most about Traject Data’s approach is their focus on scalability and accessibility – making these powerful tools available to businesses of all sizes.
If you’d like to hear more insights from Rochelle and learn about the future of retail technology, I encourage you to listen to the full podcast episode. The rapid evolution of retail technology means there’s always more to learn and discuss.
Remember, whether you’re a major enterprise or a small retailer, understanding and leveraging data is no longer optional – it’s essential for staying competitive in today’s retail landscape.
Find more episodes about what’s on the forefront in retail innovation here
