Belkin's Senior Director of E-commerce tested AI chatbots for customer service beyond basic order tracking, then deliberately pulled back to human agents for relationship-critical moments. Jyoti Malik explains why most omnichannel strategies fail (teams treat digital as a retail add-on instead of rethinking the entire operating model), shares her phased approach to channel expansion, and reveals the three-part assessment she uses before investing in first party data infrastructure.
The practical takeaway: before chasing martech solutions or agentic commerce readiness, map your business outcomes two years forward and audit whether you can actually act on the data you collect. Jyoti's team experiments with AI for content creation (a non-creative team member now generates banner assets in ChatGPT), but she's cautious about where automation creates value versus where it damages customer relationships.
Topics discussed:
- A phased path to omnichannel that starts with shared business pain, not a channel wishlist—pilot narrowly, prove outcomes, then scale.
- Why “connected” ≠ context. Without a clean, governed data foundation, AI agents guess; with it, they deliver explainable answers you can act on.
- A 3-part first-party data check before you buy (or build): quality, quantity, and actual utility in your business flow.
- How to prevent tool sprawl by writing the business requirements first—then selecting (or sunsetting) tech accordingly.
- Where AI helps—and where it hurts. Chatbots struggle with complex service; creative helpers can speed up production for non-designers (e.g., quick banner variants) when guardrails are clear.
- Agentic commerce readiness starts with data hygiene and friction audits, not another dashboard.
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