# Mey Nenadic

Mey Nenadic writes about e-commerce, customer experience, and practical uses of AI. Their posts show how customer reviews can reveal business problems and how AI tools may help shoppers find products and commerce teams analyze data.

- Profile: https://b2binfluencer.marketing/creators/mey-nenadic/
- LinkedIn: https://www.linkedin.com/in/mey-nenadic
- LinkedIn followers: 1,354
- Topics: artificial-intelligence, ecommerce, ai-adoption, agentic-commerce, customer-experience
- Based on 11 dated posts, latest 2026-10-02

## Summary

Mey Nenadic is most useful for thought leadership on AI-driven commerce analytics and customer review insights.

- Best for: B2B e-commerce consultancies or retail teams wanting AI commerce analytics thought leadership.
- Not for: Consumer footwear campaigns, performance influencer work, or measurable revenue with discount codes.
- Check first: Confirm audience analytics, partnership format, deliverables, disclosure, and fees before contacting them.

### Takeaways

- AI ran across about 13,500 Trustpilot reviews for a PE-backed Nordic fashion brand in two hours.
- Return and refund friction was dominant complaint pattern; Trustpilot score was 2.7.
- Product data not structured for language models makes retailers invisible to AI shopping agents.

## Main ideas

- **Public reviews hold financial problems that dashboards miss**: Nenadic treats customer reviews as evidence for profit-and-loss questions, not a sentiment exercise. Complaint patterns such as return and refund friction push customers away and show up as revenue leakage, not as visible KPI failures. AI can read large volumes of reviews quickly enough to make those patterns usable. The argument spans a single distressed brand and large retailers that absorb the damage through brand awareness.
- **Customer experience matters most when you are not H&M**: Nenadic opens by saying customer experience does not matter, then narrows the claim: large brands can carry poor reviews because of what they call brand gravity, while most companies cannot. The provocative headline sets up the argument, which Nenadic puts plainly: the logic applies because your company is not H&M or Zara. Their advice is to look for revenue that disappears quietly through abandoned checkouts and lost repeat business.
- **Agentic AI shopping makes product data the new front door**: Nenadic argues that AI agents have started doing the searching, comparing, and stock-checking once handled on a brand's own site. Products not structured for language models effectively do not exist to those agents. The post connects the shift to readers' own experience, asking whether they have tried buying with AI, while noting that survey data shows most merchants report little effect so far.
- **AI adoption is infrastructure, not a prompt habit**: Drawing on the 25 years they say they have spent in experience design, Nenadic argues that asking a chatbot questions is not an AI strategy. It is like Googling in 2005 and calling yourself digital. Their priorities: access to real platforms, education before clients demand it, and treating AI as infrastructure embedded in how teams brief and deliver—not as a separate department.
- **Written for owners, agencies, and investors rather than shoppers**: The posts consistently address a defined commercial reader: people running commerce businesses backed by private equity, or agency and in-house teams behind on adoption. Closing questions and calls to action hand the argument to that reader, pairing claims about shopper behaviour with consequences for whoever owns the P&L.

## Work to read

- [Customer experience does not matter](https://www.linkedin.com/posts/mey-nenadic_customer-experience-does-not-matter-hm-activity-7437762643827769344-Td6Q)
- [A PE-backed Nordic fashion brand is sitting on a €20M operating loss](https://www.linkedin.com/posts/mey-nenadic_a-pe-backed-nordic-fashion-brand-is-sitting-activity-7437104274666541056-cVQo)
- [I just bought size 50 sneakers with ChatGPT](https://www.linkedin.com/posts/mey-nenadic_i-just-bought-size-50-sneakers-with-chatgpt-activity-7444632150001442816-phJD)
- [Stop asking questions in ChatGPT](https://www.linkedin.com/posts/mey-nenadic_stop-asking-questions-in-chatgpt-i-know-activity-7430152328608935936-DMOA)
- [Senior UI Designer - e-commerce focus, Vaimo](https://www.linkedin.com/posts/mey-nenadic_senior-ui-designer-e-commerce-focus-vaimo-activity-7298368071256195073-AJP8)

## Brand relationships

- **Vaimo** (employment)
- **Anthropic (Claude)** (mention)
- **Perplexity** (mention)
- **Trustpilot** (mention)

## Partnerships

Mey Nenadic's five LinkedIn posts cover AI-driven commerce, customer experience and review analysis, plus a 2025 design-team hiring post. None lists a partnership format, sponsor policy, rate card, inquiry route, sponsorship, paid collaboration or brand-partner arrangement. For a thought leadership collaboration, contact them through their LinkedIn profile and ask about available formats, deliverables and booking; agree scope, disclosure and commercial terms directly. Companies planning sponsored-post or affiliate campaigns should ask whether those options and pricing are available.

## Alternatives

- Juozas Kaziukėnas: Choose Juozas if the consultancy wants to focus on how AI shopping agents select products and how retailers can influence those choices. One post describes research in which agents favored cheaper, higher-rated products and tended to avoid items labeled “Sponsored”; another examines which retailers ChatGPT had integrated with and what that meant for brands. Those examples give a campaign a sharper agent-selection and commerce-distribution angle than Mey Nenadic’s review-to-revenue analysis.
- Amit Bachbut: Choose Amit if the consultancy wants a practical briefing for Shopify merchants on agentic checkout, measurement, and operational decisions. One post walks through eligibility, attribution limits, missing checkout features, and where to review settings; another frames AI commerce around discovery and product visibility rather than checkout alone. Amit is a better option for a retailer-facing implementation or readiness discussion.
- Sharon Gai: Choose Sharon if the consultancy wants a broader introduction to agentic commerce, including emerging payment protocols and how shopping may move from discovery toward transactions. Her post names several payments initiatives and frames agent readiness around storefronts, APIs, and product data.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/