Studies indicate that by 2026, 75% of organizations will adopt AI-powered Business Intelligence tools that support natural language queries and conversational interfaces. This kind of skyrocketing demand is exactly what Google Looker AI features are built to address. Conversational Analytics is more than just an answer engine; it acts as an accelerant for faster, smarter, and more collaborative decisions. Understanding user intent, handling multi-turn queries, and visualizing insights instantly within tools like Looker Studio enables self-service data exploration for all users, not just analysts. In this blog, we explore how Google’s Looker Conversational Analytics is transforming how businesses deliver insights, empowering teams, and elevating customer experiences.
Skip the dashboards, Start a conversation with your data now
Business intelligence recently transitioned from static reports to interactive dashboards and now enjoys useful, natural language powered insights. Current industry research suggests that 77% of scalable companies with data-driven CEOs view the ability to make decisions rapidly as a competitive edge. 23% of organizations work toward cloud enablement to innovate and signal their sustainability objectives, 22% of organizations focus on building digital trust, and 20% of organizations are making strategic investments in BI platforms. These are key trends that show the need for making insights accessible, secure and actionable throughout an organization.
Looker allows anyone in the organization, even non technical users, to explore data with confidence. This is made possible by a single semantic model, which makes for consistent, trusted insight across the organization. Gartner identifies that for an organization to be using a top BI platform, that platform must include automated insights, visualization, usability, data prep and manageability; Looker includes all of these items.
What Is Conversational BI with Google Looker
Conversational Business Intelligence allows teams, internally, to discover and engage with data in natural language versus straining through complex dashboards. A sales rep looking to finalize a deal would potentially require some specific comparative data about the product and its competition. According to industry research, organizations that have adopted Conversational BI have seen efficiency gains up to 25%, particularly in sales, service, and field teams that needed instantaneous access to data.
The Looker natural language queries allow them to interact with the chat via everyday dialogue, requesting their required info through a chat window. Google Looker powers this shift by combining Looker natural language queries, a semantic data model (LookML), and the ability to share reports and alerts through tools like Google Chat and Slack, integrating data into daily workflows without disrupting context. Independent studies have shown that combining cloud data platforms with modern BI tools can deliver up to 205% ROI while saving thousands of analyst hours annually, over 5,000 in some cases.
Core Components:
- Natural Language Query Engine: Requires querying in natural language and getting real-time insights from the dashboard.
- LookML Semantic Layer: Keeps data consistent across teams by providing common rules and definitions.
- Integrated Sharing: Provides simple sharing of dashboards and alerts directly into your team collaboration tool such as Google Chat, Slack, and email; includes insights into your daily flow.
Figure 1: Core components of Conversational BI with Google Looker
Key Benefits of Conversational BI with Google Looker
Conversational BI with Google Looker brings together intelligent analytics, ease of access, and operational efficiency to unlock business value at scale. It includes:
- Real-Time Visibility from Connected Data: Looker supports an extensive list of SQL dialects which natively connects to a broad deployment of enterprise data sources. This negates the complexity of data prep and manual integrations, allowing for crank out faster and more relevant insights without waiting from similar time that is usually lost with traditional BI tools.
- Enhanced Collaboration with Embedded Analytics: Looker improves the potential for internal teams to collaborate in a much broader way by embedding important dashboards and reports, alerts into the tools they already know, such as Google Chat, Slack or email. When internal teams are able to share governed insights in real time, teams from across departments can align on metrics, analyze performance, and make significant actions even faster.
- Consistent Definitions with a Shared Semantic Layer: A common issue in large organizations is the fact that people in different departments refer to the same thing in slightly different ways. For instance, OTP in BFSI refers to One-Time Password, whereas OTP in transportation refers to On-Time Performance. Looker’s semantic layer (LookML) converges a shared, consistent definition of important metrics and terms across your organization, so when teams ask for “revenue” or “conversion rate”, they can be assured they are all getting the same, accurate answer with respect to what they mean, regardless of department, dashboard, or report.
- Enterprise-Grade Scalability and Security: Looker on Google Cloud offers row-level security, role-based access controls, and scalable compute for multi-team deployments of business intelligence with enterprise requirements of security and strict compliance.
- Time and Resource Optimization: Organizational efficiency is improved when teams act upon rather than interpret insights in results. This is achieved when dashboard training is eliminated alongside a reduction in ad hoc queries.
Figure 2: Key Benefits of Conversational BI with Google Looker
Our Work
At Niveus, we believe that data should benefit users, not hamper their process. That’s why we help internal business teams access the data they need faster for everyday decision-making through conversational BI. Whether it’s building Looker conversational analytics or integrating insights into tools your teams already use, our solutions are designed to be simple, smart, and scalable. We focus on making data easier to access, so your teams can focus on what they do best.
We build secure Conversational BI solutions using Google Looker AI features and AI-powered analytics. Whether it’s building conversational analytics interfaces or enabling report/alert sharing into collaboration tools, we make data work smarter.
Case studies
Enabling Data-Driven Decisions with Looker and BigQuery: Niveus worked with one of largest healthcare networks in India to modernize their analytics infrastructure using Google BigQuery and Looker to overcome problems including segmented data, manual reporting, and insufficient access controls. Niveus delivered a scalable, cloud-based data warehouse, automated the extraction, transformation, and loading of the CRM data stored on AWS, and developed over 15 custom Looker dashboards configured with predictive analytics and row-level security. After the implementation, the organization accessed real-time, secure and self-serve data access for over 200 users. This modernization transformed lead quality insight, removed manual reporting burden, improved data governance, and accelerated data-specific decision making for internal teams and external vendors.
Better Insights with a Unified, AI-Powered Retail Data Analytics Solution: Niveus collaborated with Gobi Cashmere, a leading Mongolian retailer, to create a unified, AI-driven, retail data analytics platform that eradicated data silos, and enabled real-time, data-driven decision-making across global locations of the company. Using Google Cloud technologies of BigQuery, Cloud Composer, and Looker Studio, Niveus provided Gobi with a serverless, low-code ingestion, modeling and visualization solution. The platform enabled the automation of ETL workloads, better forecasting and predictive analytics capabilities using BigQuery ML algorithms, and collaborative situations through the stitching together of data and databases from their e-Commerce systems. This created efficiencies, and Gobi was able to leverage the efficiencies to formulate better sales strategies and have a scalable and secure foundation of data to power their global retail business.
Conclusion
Business is being transformed by Conversational Business Intelligence. Google Looker AI features empower teams to bypass cumbersome dashboards and monthly reports insights are simply a question away. Studies show that organizations using conversational analytics experience up to a 24% faster time-to-decision, offering a clear edge in today’s data-driven landscape.
Using Looker’s natural language query capabilities, business users can connect with and interact with data directly. And together with sharing dashboards and real time alerts in Google Chat and Slack, insights become embedded in your team’s existing workflows. At Niveus, we bring this transformation to life securely and expertly. As a trusted Google Cloud partner, we help businesses design and implement conversational BI solutions that are smart, scalable, and tailored to your goals.
