For years, marketers and business analysts have struggled with a frustrating gap in data analysis: they have more data than ever, but less clarity. The problem doesn’t come from the data itself; it comes from the interface between the user and the information. Many marketing professionals know what they want to learn—such as which campaigns drive qualified leads or which audiences convert best—but they don’t always know how to build the complex filters, queries, and segments required to get those answers.
Table of ContentsThe Evolution of BI Toward Conversational AnalysisThe Leading Conversational BI ToolsDatabricks BI/AI GenieDomoGrowKnowiMicrosoft Power BISigma ComputingSisenseThoughtSpotYellowfin BIZoho AnalyticsFeature Comparison TableKey Benefits for Marketers and BusinessesThe Future of Conversational Measurement
Traditional BI dashboards and analytics platforms rely on structured data models, manual drill-downs, and pre-built reports. While powerful, they often force non-technical users to depend on analysts or data teams to surface insights. As a result, the data retrieved can be delayed, misinterpreted, or biased by the limitations of the query logic itself. The next generation of measurement tools aims to remove that barrier by enabling marketers to converse with their data directly, transforming business intelligence into a more intuitive, collaborative process.
This new class of platforms combines advanced visualization and integration with AI-driven natural language querying. Users can now ask questions in plain English—Which campaigns had the highest ROI last quarter? or How did customer churn compare year over year?—and get accurate, contextual answers instantly. These conversational BI platforms mark a shift from manual reporting to true data dialogue.
The Evolution of BI Toward Conversational Analysis
In the past, BI tools focused on dashboards and predefined queries. Data had to be modeled, cleaned, and structured before it could be used effectively. While this made insights reliable, it often limited flexibility. Marketers wanting to explore ad spend, email performance, or regional sales trends had to navigate multiple SQL queries or rely on IT support.
Conversational BI changes that equation. Using large language models (LLMs), machine learning (ML), and natural-language processing (NLP), these tools allow users to ask free-form questions. The platform interprets intent, applies relevant filters, and delivers visual insights without requiring technical expertise.
This new model helps prevent one of the most common pitfalls in analytics: query bias. When users don’t know how to structure their questions correctly, they often apply incomplete or incorrect filters. Conversational systems, on the other hand, use AI to clarify and validate the intent behind each question, improving accuracy and reducing error.
For marketers and business leaders, the result is a democratization of insight—data becomes accessible, interpretable, and actionable for everyone on the team, not just data analysts.
The Leading Conversational BI Tools
A new generation of BI tools has emerged to make analytics approachable for everyone, allowing marketers and executives to interact naturally with their data. These platforms connect to dozens or even hundreds of data sources, support natural-language queries, and use AI to guide decision-making. The following solutions represent the most advanced conversational BI tools available today, listed alphabetically.
Databricks BI/AI Genie
Databricks, best known for its lakehouse architecture, recently introduced AI Genie, a conversational interface layered over its BI and analytics environment. Users can interact with large, live datasets through natural-language queries that are translated into SQL or Spark commands.
For data-heavy marketing organizations already using Databricks for data engineering or machine learning, AI Genie bridges the gap between technical depth and user accessibility, providing conversational analytics on top of enterprise data infrastructure.
Domo
Domo is a cloud-native BI platform known for its robust integration ecosystem and intuitive dashboards. It supports AI-driven insights through its Domo.AI framework, which includes conversational analytics, anomaly detection, and predictive modeling.
Domo’s visual interface and strong data connectors make it a versatile option for marketing executives who need to unify campaign metrics, sales data, and operational KPIs into one coherent view.
Grow
Grow targets small to mid-sized businesses seeking a straightforward BI environment with minimal setup. While its AI chat capabilities are not as mature as those of enterprise-grade tools, it provides smart insights, trend detection, and simple text-based exploration of key metrics.
For marketers managing omnichannel dashboards on limited resources, Grow offers a simple entry point into AI-assisted measurement.
Knowi
Knowi specializes in unifying data from multiple systems—including APIs, databases, and third-party applications—without requiring rigid modeling. Its natural-language BI interface enables users to ask questions in plain English, which are translated into complex queries in the background.
Knowi’s conversational layer works across disparate data sources, making it ideal for marketing organizations that rely on dozens of cloud tools. It’s particularly effective for agencies or enterprise teams needing cross-platform visibility across campaigns and clients.
Microsoft Power BI
Microsoft Power BI remains one of the most widely adopted BI solutions for organizations of all sizes. Its native integration with Excel and Azure services makes it a familiar environment for marketing teams. The Power BI Q&A feature allows users to ask natural-language questions and automatically visualize results.
AI capabilities extend through Copilot, Microsoft’s generative assistant that can explain results, recommend metrics, and identify trends across datasets. Power BI connects seamlessly to hundreds of systems, including CRMs, ad platforms, and databases, making it one of the most flexible solutions for omnichannel marketing analytics.
Sigma Computing
Sigma Computing brings a spreadsheet-like interface to cloud BI, allowing marketers to manipulate data visually without SQL. Its conversational module, Ask Sigma, interprets natural-language queries, automatically building charts and tables based on user questions.
Because Sigma connects live to data warehouses such as Snowflake or BigQuery, it delivers real-time answers, ensuring that insights are current and verifiable. It’s particularly popular among marketing operations teams that want flexibility without maintaining separate data pipelines.
Sisense
Sisense focuses on embedded analytics, helping organizations bring interactive insights directly into their products or internal systems. Its Simply Ask module uses natural-language processing to allow conversational interaction with dashboards.
Sisense’s AI layer goes further by recommending new queries, detecting anomalies, and even surfacing insights users didn’t explicitly request. For marketing teams managing complex data ecosystems—like web analytics, CRM, and sales systems—Sisense provides flexibility without requiring deep technical configuration.
ThoughtSpot
ThoughtSpot was designed from the ground up for search-driven analytics. Instead of navigating menus or dashboards, users type or speak queries into a conversational interface. Its Sage AI engine understands context, recognizes entities such as “customer churn” or “ad spend,” and produces real-time visualizations.
ThoughtSpot integrates with major data warehouses like Snowflake, Google BigQuery, and Databricks, enabling live queries on massive datasets without additional modeling. For marketers, this means the ability to instantly analyze campaign performance, lead quality, and sales attribution across platforms with minimal setup.
Yellowfin BI
Yellowfin BI combines classic BI dashboards with modern storytelling and natural-language query (NLQ) features. Users can type or speak their questions, and the system dynamically builds relevant charts and narratives to explain the data.
Its Signals feature continuously scans for statistically significant changes in key metrics, such as engagement rates and cost per acquisition, and alerts marketers when anomalies occur. For organizations seeking both automation and human-readable explanations, Yellowfin offers an appealing hybrid model.
Zoho Analytics
Zoho Analytics offers a balance between accessibility and intelligence. It features the Zia AI assistant, which interprets user questions and generates answers in both visual and textual formats. Zia can also identify outliers and forecast trends automatically.
The platform connects easily with advertising tools, email systems, and CRMs, making it a strong choice for mid-market marketing teams looking to centralize campaign measurement and automate insight discovery.
Feature Comparison Table
PlatformConnects to Multiple SystemsNatural Language QueryConversational ChatAI InsightsReal-Time Data AccessPredictive AnalyticsDatabricks BI✅✅✅✅✅✅Domo✅✅✅✅✅✅Grow✅✅❌✅✅❌Knowi✅✅✅✅✅❌MS Power BI✅✅✅✅✅✅Sigma ✅✅✅✅✅✅Sisense✅✅✅✅✅✅ThoughtSpot✅✅✅✅✅✅Yellowfin BI✅✅✅✅✅✅Zoho Analytics✅✅✅✅✅✅
Key Benefits for Marketers and Businesses
The rise of conversational BI represents a fundamental shift in how organizations interact with data. For marketers, this shift means:
Faster decision-making: Users can instantly ask questions and receive insights without waiting for analyst support.
Reduced bias: AI interprets intent and clarifies context, minimizing errors in query design.
Democratized access: Data becomes accessible to every team member, from executives to campaign managers.
Improved storytelling: Visual and narrative responses make data easier to communicate and act upon.
Real-time insight: Live connections to data warehouses and marketing systems ensure information is always current.
The Future of Conversational Measurement
The next frontier in analytics will not only answer questions but anticipate them. As generative AI continues to advance, BI tools are evolving into decision partners rather than static dashboards. The ability to converse with data—asking, refining, and challenging results—ushers in an era of measurable intelligence where marketers no longer need to be analysts to be data-driven.
For businesses, this means decisions can be made at the speed of conversation, supported by data that listens, understands, and responds.
©2025 DK New Media, LLC, All rights reserved | DisclosureOriginally Published on Martech Zone: Conversational Business Intelligence: The New Era of Measurement Analysis