E-commerce brands operating on marketplaces like Amazon, Walmart, and TikTok are
By sreenathkreddy · September 9, 2026 · Curated by George's Blog
E-commerce brands operating on marketplaces like Amazon, Walmart, and TikTok are paying a hidden data fragmentation tax.
Critical questions you care about often lie at the intersection of siloed datasets.
For example, getting a view of the LTV-to-CAC ratio requires combining sponsored ads DSP data from Seller Central or Vendor Central with Amazon Marketing Cloud.
Understanding product-level profitability requires stitching together ads data, organic sales, retail/ops data, and your own unit costs.
The tax shows up as manual reporting and analysis, hours of troubleshooting and diagnostics, and often a flat-out inability to answer key questions.
At Intentwise, we classify these data silos into 6 buckets:
🔸 1. Advertising
🔸 2. Retail/Operations
🔸 3. Shopper Insights (think AMC for Amazon)
🔸 4. Competitive Intelligence
🔸 5. Cross-channel
🔸 6. brands own specific data such as product unit costs, product categorizations etc.
While we all race to adopt AI in our daily lives, AI also shines a bright light on this data fragmentation problem through inaccuracies and hallucinations.
In fact, while the data fragmentation problem predates the Gen AI wave and has always been important to address, it's even more important now because with AI, it's garbage in, garbage out.
If you want to prevent revenue and margin leaks and shift your team from tactical to strategic work, a well-organized, AI-ready data foundation is a necessity.
What does AI-ready mean? Data must be well-organized, but it also needs meaning (a semantic layer) and domain knowledge for AI tools to integrate effectively.
The question is, how do you get there? The mistake is to embark on long-range technology projects that will not see the light of day for a long time.
The most critical next step is to create a prioritized list of important questions that are either critical for the business or take too much time today (10 or less :-) ). I would then prioritize the shortest paths to solving those problems, while incrementally moving towards the ideal end state.
At Intentwise, we've done this exercise with numerous brands. I'm happy to share what we've learned. If this is a critical topic for you, reach out.
#amazonadvertising #walmartconnect #retailmedia #genai