Conversational Analytics in Looker: Turning Data into Insights Through Dialogue

Reimagining How Businesses Talk to Their Data

In a world where data doubles every 12 months, speed to insight has become a competitive edge. Yet, most analytics tools still expect users to dig through dashboards, filters, and SQL queries.

Google Cloud’s Looker Conversational Analytics changes that - forever.

It transforms the analytics experience from “build and click” to “ask and answer.”
With it, anyone - from finance analysts to operations leaders - can simply talk to their data in natural language and get accurate, governed insights in seconds.

“Show revenue growth by region this quarter.”
“Which suppliers have invoices pending beyond 60 days?”
“What’s driving an increase in overdue balances?”

The answers appear instantly - as visualizations, summaries, or actionable insights. No technical skills, no filters, no friction.

The Power Behind the Conversation

At the heart of this experience lies Looker Semantic Model - the trusted layer that ensures every response aligns with your organization’s business definitions and data governance.

When users interact through Conversational Analytics, Looker interprets Natural language query analytics, generates governed SQL, and executes it safely against your warehouse - BigQuery, Snowflake, or any connected platform.

The result?
Real-time insights that are accurate, explainable, and enterprise-ready.

Conversational Analytics Architecture

This architecture bridges AI’s intuitive reasoning with Looker’s governance-first analytics - making sure every insight remains consistent, secure, and compliant.

Meet the Looker Data Agent

Think of Agents as your organization’s intelligent data companions.

They’re pre-trained on your Explores, KPIs, and business rules - ready to understand your company’s language.

An agent knows what “invoice exposure,” “aging bucket,” or “liability risk” means in your specific context. So when a finance analyst asks,

“What’s our vendor exposure above 90 days?”
the Agent knows exactly which dataset, metric, and filter to use.

Reusable, sharable, and governed, these agents bring true conversational intelligence into everyday analytics.

Reinventing Payables Intelligence: The AP Insight Agent

Now let’s see Conversational Analytics in action - inside one of finance’s most crucial functions: Accounts Payable (AP).

Everyday Scenarios Where the AP Insight Agent Delivers

1. Vendor Exposure Overview

Identifying vendors with high unpaid balances allows for better decision-making around collections and overall financial health.

By visualizing top vendors with the largest unpaid invoices, finance teams can quickly spot where cash is tied up and direct collection efforts accordingly.

Prompt:
Show top 10 Vendors by unpaid Invoice Amount including Vendor Name, Total Invoiced, Amount Paid, and Outstanding Balance.

2. Overdue Invoices (>90 Days)

The analysis brings attention to invoices that pose the greatest risk, allowing collections teams to act quickly and reduce potential losses.

By tracking invoices overdue by more than 90 days, AP and finance teams can prioritize recovery efforts and identify vendors requiring closer collaboration.

Prompt:
List invoices with Invoice Date between 2016–2024 where Age Bucket (Invoice Date) is >90 days. Show Invoice Number, Vendor, Invoice Date, Amount Paid, and Outstanding Balance.

3. Department Liability

This analysis identifies which departments have the largest accounts payable exposure, encouraging accountability among business units and budget owners.

Understanding which departments drive the highest payables allows finance leaders to manage budgets proactively and ensure spending discipline.

Prompt:
Show Outstanding Balance by Department and Business Segment including Total Invoiced and Distinct Invoice Count.

4. Payment Terms Impact

Understanding how different payment terms affect invoice aging helps optimize vendor agreements and enhance liquidity.

Analyzing payment term performance can reveal which agreements contribute to delayed payments and help teams optimize terms for improved liquidity.

Prompt:
Show Outstanding Balance by Payment Terms and Age Bucket.

Conclusion: From Data Reports to Data Dialogue.

Conversational Analytics in Looker turns every business user into a data expert - no training, no dashboards, no delays.

When paired with Looker agents like the AP Intelligence Insight Agent, it transforms how organizations understand, govern, and act on financial insights.

• A. From static dashboards to dynamic discussions.
• B. From reactive reporting to proactive intelligence
• C. From data collection to data conversation.

The future of analytics is conversational — and it’s already here.

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