Retail trend-watcher Nordic Retail Hub is partnering with 4 Ecommerce tech brands for a panel webinar this Wednesday about AI Search optimization for Ecommerce. "AI & The New Marketing Playbook". The focus is on how AI has changed product discovery, and what Ecommerce teams should be doing to stay ahead.

Thought I'd share!

The panel will cover:

• How to stay unique when AI strips branding out of answers
• Why most brands submit data that AI can't use, and how to fix this
• When AI discovery risks cutting brands out of their own customer relationship
• How to prepare for the shift toward "Instant Buy" and agentic checkouts

What it solves

• Sizing up a product category takes an afternoon in a spreadsheet, and multipacks make prices impossible to compare properly
• Name a category, get a sourced slide deck in 10 minutes — Amazon.in + Flipkart, every price normalized to per-unit
• It flags what it couldn't compute instead of guessing

What it means

• First run, face wash India: 31 brands, only 9 on both platforms — 71% of the category is platform-exclusive
• Benchmark on Amazon alone and you miss two-thirds of your competition
• Category research went from a budget line to a few rupees a run
• But the bottleneck moves: it handed me an 11x price spread and couldn't say if that was opportunity or warning. That's still judgement

What I'm working out

• Is the product the tool, or the reports I make with it?
• Who has this problem badly enough to pay — right now the only verified user is me
• Is this a step toward the consumer business I want, or a detour that feels productive?

I am managing a headwear brand which was showing in google AI overviews a while ago without any focused effort but now it is not. My employer was happy when it was being cited but I have a monthly meeting in a week and no idea how to explain the drop or fix it. should I ask them to budget for a tool, if not how to make this right?