Amazon Accelerate Presentation Re-run: Are you making the most of Amazon data?

Introduction

Sreenath Reddy:
Hi everyone, and welcome! Thank you for joining this re-run of my Amazon Accelerate presentation, Are You Making the Most of Amazon Data?

This session originally received a lot of interest at Amazon Accelerate, so we’re bringing it back to share the same insights with our broader community. Before we get started, if you’re attending UnBoxed this year, do stop by our booth—we’d love to meet you in person.

Let’s dive in.

The New Reality of Amazon Data

Sreenath:
If we go back just two or three years, most of us complained about limited Amazon data. Vendor Central had no API access, AMC didn’t exist, and hourly data wasn’t available.

But fast-forward to now, and the situation has flipped completely. We’ve entered what I call a data deluge. There’s batch data, hourly data, retail data, advertising data, AMC, and shopper-level insights—more signals than ever before.

The problem is no longer data scarcity. The challenge now is data fragmentation—different APIs, disconnected sources, and a lack of visibility that creates blind spots.

The Five Core Buckets of Amazon Data

To make sense of the chaos, I like to break Amazon data into five key buckets:

1. Advertising – Campaign performance and spend data.
2. Retail – Sales, pricing, inventory, buy box, and organic rank.
3. Shopper Intelligence – Customer journeys, repeat purchases, and lifetime value.
4. Competitive Intelligence – Market share, share of voice, and share of search.
5. Custom Data – Brand-level inputs like product categorization and unit costs.

When unified, these data sets provide a complete picture of performance—but fragmented, they slow down reporting, create blind spots, and limit decision-making.

How Data Fragmentation Creates Blind Spots

Sreenath:
Many Amazon teams struggle to answer fundamental questions:

• What’s profitability by ASIN when ad spend and fees are factored in?
• Why are sales for a product down this month?
• Did my Prime Day deals actually acquire new customers?

Each of these questions requires connecting multiple data silos. Without that integration, teams spend excessive time collecting, cleaning, and analyzing data—time that could otherwise be spent on strategy and execution.

The Impact of Data Fragmentation

From our work with over 4,000 accounts across brands and agencies, we see the same pattern: teams spend too much time reporting and too little time optimizing.

Data fragmentation leads to four major time drains:

1. Collecting data from multiple sources.
2. Customizing data (e.g., product groupings, unit costs).
3. Building reports or dashboards.
4. Manually analyzing performance.

The future is about collapsing these steps—automating collection, unifying sources, and letting AI surface insights automatically.

The Rise of Generative AI in Data Analysis

Generative AI is already transforming how we work with data. Beyond the hype, it enables marketers to:

• Build dashboards in minutes instead of days.
• Interact with data using natural language.
• Automatically monitor and detect performance anomalies.

In one quick demo, I gave a generative AI tool a small dataset and a simple prompt: “Build me a dashboard with category-level breakdowns.” In minutes, it created a fully functional dashboard visualizing key metrics—proof of how accessible insight generation has become.

However, AI’s impact depends entirely on data quality and structure. Poorly organized data limits what AI can deliver.

The Path Forward: Building an E-commerce Data Foundation

There’s only one sustainable way to maximize the value of Amazon data:
Build a unified e-commerce data foundation.

This means:

• Comprehensive, automated data collection across all APIs.
• Robust error handling for reliability.
• Easy integration of your own brand-specific data.
• A well-connected data model that supports real-time analytics and AI applications.

With this foundation, you can create 360° product performance views—linking ads, retail, and inventory data for every ASIN.

How Intentwise Helps Brands and Agencies Accelerate This Journey

At Intentwise, we’ve already built this foundation. We collect and structure data across thousands of accounts, making it AI-ready from the ground up.

We help brands and agencies in three primary ways:

1. Reliable Data Pipes – Automated feeds into your data warehouse.
2. Advanced Visualizations – Pre-built, interactive dashboards that go beyond standard BI tools.
3. Smart Applications – AI-powered tools for diagnostics, optimization, and insight discovery.

We also layer in custom analytics services for brands that need tailored dashboards, AMC queries, or advanced modeling.

Examples of Next-Generation Visualization

• Path to Conversion View: Interactive AMC-based dashboards showing how each ad touchpoint contributes to conversions.
• ASIN Purchase Overlap Graphs: Network-style visualizations revealing which products are frequently bought together.
• Product360: Our observability agent that automatically detects performance anomalies, identifies causes (like pricing or buy box shifts), and provides root-cause insights—powered entirely by our connected data foundation.

AI-Ready, Future-Proof Solutions

Our ecosystem spans four key solutions:

1. Intentwise Analytics Cloud – Full automation from data pipelines to dashboards.
2. Intentwise Explore – Accelerates AMC adoption and first-party data uploads.
3. Intentwise Ad Optimizer – Smart automation for Sponsored Ads and DSP.
4. Product360 (Closed Beta) – AI-powered product performance diagnostics.

These are supported by our Analytics Services, helping clients build new dashboards, queries, and models quickly and cost-effectively.

Closing Thoughts

Sreenath:
Whether you build your data foundation yourself or with a partner like Intentwise, the key is to start now.

Connect your advertising, retail, and brand-specific data first—then expand across channels like TikTok or Shopify. Each connection reduces blind spots and compounds your competitive advantage.

If you’d like to discuss your data strategy or incremental roadmap, feel free to reach out at sreenath[at]intentwise.com or schedule a call via my Calendly link.

And before we wrap up, a quick reminder—we’ll be at UnBoxed, and we’d love to see you there. Thank you for joining, and I hope this session helps you rethink how you structure and activate your Amazon data.