The 2026 e-commerce data stack: What winning brands are doing

Introduction

Sreenath Reddy:
Welcome everyone to another Intentwise webinar. I’m Sreenath Reddy, CEO and co-founder of Intentwise, and I’m joined by Kenton Snyder, Product Manager here at Intentwise.

This is one of the topics I’m most excited about because, before starting Intentwise, I spent nearly a decade running data teams at a large consumer internet company. I’ve lived through multiple generations of data stacks—and I’ve never seen change happen at the pace we’re seeing today.

What we’re going to talk about today is how the e-commerce data stack is evolving and what winning brands need to do heading into 2026.

The Traditional Data Stack (and Why It’s Breaking)

For nearly 30 years, the traditional data stack has followed the same basic structure:

1. Data storage – databases like BigQuery, Redshift, Snowflake, or even spreadsheets
2. Reporting tools – Looker, Tableau, Power BI
3. Dashboards – built for specific business users

In this model, domain expertise lives in people’s heads. Dashboards are hard-coded representations of that expertise, and humans interpret the outputs.

This structure has barely changed—but it’s now under extreme pressure in e-commerce.

Why E-commerce Data Is Uniquely Challenging

Marketplaces like Amazon and Walmart generate enormous volumes of data, but it’s:

• Fragmented across retail, advertising, and Amazon Marketing Cloud (AMC)
• Time-consuming to stitch together
• Slow to turn into actionable insight

Teams spend huge amounts of time and money just assembling dashboards, yet still experience blind spots, delayed insights, and incomplete visibility.

On top of that, channels are now deeply interconnected:

• TikTok activity impacts Amazon sales
• Amazon ads influence DTC performance
• First-party data flows into AMC and DSP

Most teams today are data-rich but insight-poor.

How AI Is Reshaping the Data Stack (Already)

AI is fundamentally changing how data stacks work—and this isn’t future state. We’re already here.

What’s changing:

• Traditional BI tools are being replaced by AI-driven development tools
• Static dashboards are being replaced by interactive, actionable applications
• Build times are shrinking from months to days

The idea of a static dashboard is effectively dead. What’s replacing it are applications that:

• Are interactive and collaborative
• Provide context
• Enable action directly from insights
• Can be built extremely fast

Real Examples of the New Data Stack in Action

Product Exception Monitoring

A client asked for a daily feed showing product-level exceptions like:

• Buy Box loss
• Inventory issues

We delivered a working prototype in hours and had it in production within days.

Advertising Audits

Use cases like:

• Missing keywords or ASINs
• Over-spend on branded terms

From idea to production took less than a week—and the result looked like an application, not a dashboard.

CLTV and Promotional Impact Analysis

During BFCM, brands wanted to understand:

• Changes in CLTV
• Acquisition cost during promotions vs. non-promotional periods

We built this analysis in days, showing 3-, 6-, and 12-month CLTV side by side.

From Insight to Action

Instead of just showing funnel drop-offs, users can now:

• Identify products with high abandonment
• Instantly create audiences
• Activate campaigns directly from the application

This is the shift from passive reporting to active execution.

What’s Coming Next: Agentic Data Stacks

Looking ahead into 2026, the next major shift is this:

Domain expertise will move from people into systems.

Today, diagnosing underperformance requires human analysis. In the near future:

• AI agents will proactively analyze performance
• Systems will diagnose why something changed
• Recommendations and actions will follow automatically

The future stack includes:

• A unified data foundation
• Embedded domain knowledge
• Interactive applications
• AI agents that analyze, predict, and act

This is not science fiction—it’s coming in the next 6–12 months.

What Brands and Agencies Should Do Now

1. Own Your Data

Relying solely on third-party tools is risky. When relationships end, data disappears.

Winning teams:

• Own comprehensive, connected datasets
• Control their historical performance data

2. Build AI Literacy

Experiment with AI tools now. Teams don’t need to become engineers, but they do need fluency.

3. Invest in Data + Knowledge

AI alone isn’t enough. Real advantage comes from:

• Clean, connected data
• Encoded business and domain knowledge

That combination unlocks true generative AI capability.

How Intentwise Helps

Intentwise’s mission is to build a commerce-ready data and knowledge foundation.

We help brands and agencies in three ways:

1. High-Quality Data Pipelines

Unified, e-commerce-centric data models across Amazon, Walmart, AMC, DSP, and more—without the burden of building and maintaining pipelines yourself.

2. Ready-Made Applications & Dashboards

A growing library of analytics applications, including white-labeled client portals for agencies, deployable in days.

3. Smart, Proactive Applications

Applications that:

• Detect issues proactively
• Explain why performance changed
• Recommend next actions

This enables teams to move from tactical execution to strategic impact.

The Road Ahead

This shift is already happening. Over the next 6–9 months, AI-driven, agentic systems will redefine how brands and agencies operate.

At Intentwise, we’re deeply investing in embedding domain expertise directly into our platform—and you’ll see more innovation rolling out as we move into 2026.

Closing

If you’d like to discuss where your current data stack stands—or explore what this evolution means for your brand or agency—we’re happy to connect.

Thank you for joining us, and we look forward to continuing this conversation in upcoming webinars.