The fastest way to build world-class analytics and make engineering the heroes is to stop treating analytics as a side project and embed it as a native product capability using AI-first analytics tooling.

Modern users expect to ask questions in plain English, explore live dashboards, and get clear explanations without leaving your app. Trying to custom-build all of that internally pulls engineers away from your core product, slows delivery, and creates years of technical debt.

Embedded analytics flips that equation. Engineering teams deliver a polished analytics experience quickly, customers stay in-product, and the team earns credit for shipping something powerful without sacrificing speed or quality.

What “World-Class Analytics” Really Means Today

World-class analytics is not a collection of charts bolted onto a product. It’s an experience; one that feels as natural and intuitive as the rest of your application.

Modern analytics share a few defining characteristics:

1. Natural Language Querying (NLQ) for everyone.

Your users should never have to become a BI tool techie. They know that AI should be able to get them answers by simply asking a relevant question. They should be able to ask:

“How many of my enterprise customers renewed last quarter?” – “Which accounts are at risk and why?” – “Show revenue by region compared to last year.”

And then keep the conversation going. World-class analytics remembers the context of the question. Users shouldn’t have to re-enter or restate their original request every time. The system should understand follow-ups like:

“Now break that down by industry.” – “Exclude churned accounts.” – “Turn this into a dashboard.”

This incremental, conversational flow is how humans think and how analytics should work.

2. Self-service dashboards and reports (no technical skills required).

Analytics should not require an analyst, SQL, or a ticket to engineering. Modern users expect:

• Dashboards they can build themselves
• Reports they can customize on the fly
• Filters, groupings, and comparisons without spending weeks or months training and learning a tool

The goal is simple: answers without friction.

When analytics is self-service, your users stay in your product instead of exporting data and asking someone else to make sense of it.

3. Prompt once, then switch to intuitive UI.

AI is powerful, but prompting should not be the entire experience.  World-class analytics combines the best of both worlds:

• Prompt first using natural language to generate an initial dashboard or report
• Then switch to an intuitive UI with drag-and-drop, filters, and layout controls

This allows a non-technical user to tweak a chart, rearrange a dashboard, add or remove metrics or columns, and save and share results all without repeatedly prompting the system.

AI gets you started fast.  But great UI gets you finished quickly.

4. Persona-based analytics experiences.

Executives, managers, operators, and individual contributors don’t want the same views.  World-class AI-powered analytics understands who is asking and how to format their view.

• Executives want high-level KPIs and trends
• Managers want operational performance and exceptions
• Practitioners want details and daily execution metrics

Dashboards and reports should adapt to the persona. They should automatically position the metrics and recommend more.  This is how you create analytics that feel “designed,” not generic.

5. Intelligent insights. Not just charts.

Charts show what happened.  AI should help explain why. Modern analytics goes beyond visualization to deliver:

• Automated insights
• Plain-English explanations
• Ability to trace and detect data quality problems.

Instead of forcing users to hunt for meaning, analytics should proactively surface it.

Data Integration is Non-Negotiable

None of this works without reliable, integrated data. World-class analytics platforms must connect to:

• CRM systems (Salesforce, HubSpot)
• Financial systems
• Product and usage data
• Data warehouses and data lakes

Clean, fresh, well-modeled data is the foundation. Without it, even the best dashboards fail.  That’s why modern analytics includes built-in connectors, data pipelines, and observability. So insights are trusted and current.

The Hidden Cost of Building Analytics from Scratch

This is where many B2B SaaS teams struggle. Your engineers are experts at building your core product, the thing that differentiates you in the market. But analytics is a different discipline entirely...

When engineering teams are asked to design dashboard builders, build report editors, manage data modeling, support NLQ and AI, AND maintain analytics infrastructure, they pay a heavy price:

• Roadmaps slip
• Features get watered down
• Maintenance becomes a long-term tax
• Analytics UX lags behind user expectations

The result often pushes users to waste valuable time trying to get their answers with Excel or external BI tools - when indeed there’s AI-Powered embedded analytics available that is native to your UI and delivers what your users are expecting.

How Embedded Analytics Makes Engineering the Heroes

There’s a better path. By embedding a purpose-built analytics platform into your SaaS product, engineering teams can:

• Ship world-class analytics faster
• Avoid years of maintenance and rework
• Focus on core product innovation
• Deliver a polished, professional analytics experience

From the customer’s perspective, analytics feels native.  From engineering’s perspective, it’s a massive acceleration and easy lift. Instead of spending months reinventing dashboards, reports, NLQ, and data integration, teams can deliver it in a fraction of the time, saving the company money.

• Shipping faster than expected.
• Delivering features customers love.
• Keeping the roadmap intact.
• Avoiding long-term technical debt.

That’s how to make your engineering team look like heroes. 

The Future of B2B SaaS is Embedded, AI-first Analytics

Modern SaaS users expect answers, not exports. They expect insight, not complexity.  They expect analytics that feel as intuitive as the rest of your product.

World-class analytics is no longer optional. It’s part of the product experience. The companies that win will be the ones that:

• Keep users in-app
• Empower non-technical users
• Leverage AI for insight, not just automation
• Enable engineering to move fast without sacrificing quality

Build world-class analytics into your product—and let engineering be the heroes who made it happen.