I’m thrilled to sit down with Zainab Hussain, a renowned e-commerce strategist with a wealth of experience in customer engagement and operations management. With her finger on the pulse of digital retail trends, Zainab has a unique perspective on how AI is revolutionizing the way we shop and sell online. In this conversation, we dive into the concept of agentic commerce, the critical role of data in modern online retail, and the innovative tools and partnerships that are shaping the future of e-commerce. We also explore how these advancements are helping merchants adapt to changing buyer behaviors and stand out in a competitive landscape.
How would you describe the idea of agentic commerce, and what sets it apart from the traditional online shopping experience?
Agentic commerce is a transformative shift in how transactions happen online. Unlike traditional e-commerce, where customers start on a homepage and navigate through menus or search bars, agentic commerce often begins with an AI prompt. Think of it as a conversation with a smart assistant that finds, compares, and even completes purchases for you. These AI agents, embedded in platforms like chatbots or search tools, act on behalf of the customer, making the process more personalized and efficient. It’s less about browsing and more about the AI understanding your intent and delivering exactly what you need, sometimes before you even fully articulate it.
What role do AI agents play in reshaping the way customers discover and buy products?
AI agents are like personal shoppers with superpowers. They sift through massive amounts of data in seconds to surface the most relevant products or deals based on your preferences, past behavior, or even a simple query. They’re not just reacting to searches—they’re predicting needs, offering comparisons, and guiding decisions. This changes discovery from a manual, time-consuming task to an almost seamless interaction. For merchants, it means the game is no longer just about SEO or flashy websites; it’s about being visible and relevant to these AI systems that are increasingly acting as gatekeepers to customers.
Why is the quality of data so important for merchants in this AI-driven shopping world?
Data quality is everything in AI-driven commerce because it’s the foundation of how these systems decide what to show customers. If a merchant’s product data—like descriptions, prices, images, or inventory—is incomplete, outdated, or poorly structured, AI agents might overlook their offerings or misrepresent them. High-quality data ensures products are accurately categorized, easily discoverable, and appealing when presented to potential buyers. It’s the difference between being recommended by an AI assistant or getting buried under competitors who’ve optimized their information better.
How can merchants improve their data to stay competitive in this new landscape?
Merchants need to focus on creating clean, detailed, and structured data for their products. That means ensuring descriptions are specific, images are high-quality, and attributes like size, color, or compatibility are clearly defined. They should also keep their inventory updated in real-time to avoid disappointing customers with out-of-stock items. Using tools that standardize and enrich data across platforms can make a huge difference. It’s also about understanding what customers are searching for through AI prompts and tailoring data to match those intents—think keywords, trends, or even seasonal relevance. Investing in this area isn’t optional anymore; it’s a survival tactic.
Can you tell us about the new tool Feedonomics Surface and how it supports merchants?
Feedonomics Surface is a game-changer for merchants looking to optimize their presence on major channels like Google Shopping or Meta. It’s a tool that integrates directly into the Commerce dashboard, allowing merchants to connect and fine-tune their product catalogs for these platforms. It helps ensure that product listings are formatted correctly, enriched with the right details, and aligned with the specific requirements of each channel. The goal is to maximize visibility and conversion by making sure products show up where customers are looking, with data that’s compelling and accurate. Early feedback suggests merchants are seeing better reach and engagement, which is a strong sign of its impact.
What’s the story behind the Feedonomics apps for Shopify users, and how do they help?
The Feedonomics apps for Shopify are designed to simplify the complexity of managing e-commerce across multiple platforms. There are two main apps—one focused on advertising and the other on listings and orders. They help Shopify merchants streamline their product catalogs, ensuring consistency whether they’re selling on their own store, marketplaces, or ad channels. They also make order management smoother by syncing data across systems, reducing errors and saving time. The broader vision here is to empower smaller or mid-sized merchants with tools that let them compete at the same level as bigger players, breaking down barriers to multi-channel selling.
Can you explain the partnership with PayPal and what BigCommerce Payments will offer merchants when it launches in 2026?
The partnership with PayPal is a big step toward simplifying payments for merchants. When BigCommerce Payments powered by PayPal rolls out in 2026 in the U.S., it will bring a suite of tools directly into merchants’ dashboards. We’re talking about features like balance tracking, payout management, multi-currency support, and settlement options. This integration means merchants can handle their financial operations more efficiently without juggling multiple systems. It’s about reducing friction in the backend so they can focus on growing their business rather than wrestling with payment logistics.
How does the agentic checkout with PayPal enhance the buying experience in AI-driven commerce?
The agentic checkout with PayPal is all about making purchases effortless within AI-driven environments. Imagine you’re interacting with an AI assistant, it finds the perfect product, and instead of being redirected to a separate checkout page, you complete the transaction right there in the conversation flow. PayPal’s integration ensures this process is secure, fast, and intuitive. It aligns perfectly with how agentic commerce works—keeping everything fluid and customer-centric. It reduces drop-off rates because there’s no break in the experience, which is a win for both buyers and merchants.
What makes Catalyst storefront technology unique for merchants launching new sites?
Catalyst storefront technology stands out because it’s built for flexibility and speed. It allows merchants to create highly customized, responsive online stores that cater to specific markets or customer needs without requiring heavy coding or long development cycles. For instance, it’s been used for diverse launches like Mountain Warehouse’s EU site or DriveDen in the U.K. It’s also designed to integrate seamlessly with modern commerce tools, so merchants can adapt quickly to trends or scale across regions. It’s really about giving them control over their brand experience while keeping the tech side manageable.
How do these recent launches demonstrate the ability to cater to diverse markets and regions?
These launches, from Mountain Warehouse in the EU to LCA Franchising across Australia, New Zealand, the U.K., and Canada, show a deep understanding of varied market demands. Each region has unique customer behaviors, regulatory needs, and competitive landscapes, and the ability to roll out tailored solutions—like B2B stores for F&C Distributors or auto-accessories sites for DriveDen—highlights a platform that’s adaptable. It’s not a one-size-fits-all approach; it’s about providing tools and tech that let merchants localize their strategies while maintaining efficiency. This global yet personalized capability is crucial in today’s e-commerce world.
What is your forecast for the future of AI-driven commerce over the next few years?
I believe AI-driven commerce will only accelerate, becoming the default way many people shop within the next three to five years. We’ll see AI agents getting even smarter, not just assisting with purchases but anticipating needs based on broader lifestyle data—think integrating with smart home devices or personal schedules. For merchants, the pressure to optimize data and integrate with AI platforms will intensify, as visibility will increasingly depend on how well they play with these systems. I also expect more seamless, embedded payment solutions and a rise in voice-based commerce as AI continues to evolve. It’s an exciting time, but merchants will need to stay agile to keep up with the pace of change.
