Nine Entertainment Co. Selects Domo to Build a Unified AI and Data Foundation — Replacing a Fragmented Analytics Stack Across Broadcast, Streaming, Publishing, and Digital With a Single Governed Platform Enabling Self-Service Insights and AI-Driven Workflows
Delivered in partnership with Altis Consulting, the initial migration produced nearly 50 dashboards in the first two weeks — a pace that exceeded previous tools — while natural language querying capabilities are enabling non-technical teams to explore data independently, and Domo Apps are now powering reusable, role-based data experiences that standardise logic and reduce duplication across one of Australia's largest and most diverse media organisations.
4 min read
Domo (Nasdaq: DOMO) has announced that Nine Entertainment Co., one of Australia's largest media organisations, has selected Domo's AI and data platform to consolidate its analytics tools, modernise its data stack, and enable self-service insights across the business. By standardising on a single, governed platform, Nine is creating a shared data foundation that supports faster decision-making and consistent metrics across a media portfolio that spans broadcast television, streaming, publishing, and digital platforms. The rollout is being delivered in partnership with Altis Consulting, one of Australia's leading data and analytics consultancies.
The Problem — A Growing Media Business With a Fragmented Analytics Estate
Nine Entertainment's data fragmentation is a product of success — and a pattern that is common across organisations that have grown rapidly through mergers and acquisitions. As the company expanded its portfolio through acquisitions and the evolution of its business units, each part of the business brought its own analytics tools, reporting environments, and metric definitions. The result was a patchwork of siloed systems in which the same underlying business performance could produce different numbers depending on which tool, which team, and which version of a report was consulted. For a media company whose advertising, subscription, and content decisions are all data-sensitive, that inconsistency has real commercial consequences — it slows decisions, creates audit overhead, and erodes trust in the data that is supposed to support strategic choices.
"As simplification and modernisation are central to our data strategy, consolidating onto a single analytics platform became essential. Managing multiple platforms created unnecessary friction and made consistent reporting harder than it needed to be."
— Barry Quinn, Head of Analytics Insights, Nine Entertainment
Why Domo — Intuitive UX, Cost-Effective Model, and Natural Language Querying as a Differentiator
After evaluating several options, Nine selected Domo for three primary reasons. The first was intuitive user experience — a platform that business users and analysts could both operate effectively within a single governed environment, rather than requiring separate tools for technical and non-technical stakeholders. The second was a cost-effective operating model, with Nine already seeing a meaningful reduction in overall analytics platform costs during the early rollout. The third — and described as a key differentiator — was Domo's production-ready natural language querying capabilities, which enable non-technical users across Nine's broadcast, streaming, publishing, and digital teams to explore data independently and ask questions in plain language without requiring SQL skills or analyst intermediation. This capability matters commercially: it means the cost and delay of analyst-mediated reporting can be reduced as more of the organisation gains direct, governed access to the data it needs.
The pace of initial delivery underlines the platform's accessibility. During the first phase of migration, Nine's data team delivered nearly 50 dashboards in the first two weeks — a velocity that the team indicated exceeded what had been possible with its previous analytics tools, and that demonstrates the platform's productivity profile in a real enterprise deployment rather than a controlled demonstration environment. Altis Consulting worked alongside Nine throughout this phase to rationalise a large volume of legacy reports into a smaller, higher-quality set, clarify reporting usage and ownership across the organisation, and convert existing datasets to the Domo platform in support of a governed self-service analytics environment.
"This project went beyond migrating dashboards. We helped Nine streamline reporting and fully leverage Domo to meet complex requirements and enable trusted, self-service analytics."
— Katrina Pilcher, Chief Operating Officer, Altis Consulting
Domo Apps, Shared Logic, and the Road to Automated AI-Driven Workflows
Beyond dashboard migration and self-service reporting, Nine is already using Domo Apps to build reusable, role-based data experiences across the organisation. By leveraging shared components and common calculations, the Nine team is standardising logic while reducing duplication and rework — a structural improvement that makes the data environment more maintainable and trustworthy as more teams and use cases are onboarded. Rather than each business unit building its own version of core metrics, shared components ensure consistent definitions are applied across the organisation, with updates propagating automatically rather than requiring manual synchronisation across dozens of siloed reports.
Looking ahead, Nine plans to introduce automated workflows that monitor data patterns and alert teams to emerging trends — moving from a self-service reporting environment toward more proactive, AI-assisted analytics in which the platform surfaces insights rather than waiting for users to query them. This trajectory is precisely what Domo's AI and Data Products platform is designed to enable: a progression from data consolidation through self-service access to automated AI-driven workflows, with each stage building on the governed foundation established in the previous one. For Nine, a media company for which audience behaviour, content performance, and advertising yield are all fast-moving signals, that automated alerting capability has clear strategic value. More information is available at domo.com.
Key Takeaways
- Nine Entertainment Co. — one of Australia's largest media organisations, operating across broadcast television, streaming, publishing, and digital platforms — has selected Domo's AI and data platform to replace a fragmented analytics estate that had accumulated across multiple tools and siloed reporting environments through years of mergers and business unit expansion
- Nine selected Domo for three primary reasons: an intuitive UX supporting both business users and analysts within a single governed platform; a cost-effective model that has already produced meaningful analytics cost reductions in the early rollout; and production-ready natural language querying capabilities that allow non-technical staff to explore data independently without analyst intermediation while maintaining governance and trust
- The initial migration — delivered in partnership with Altis Consulting — produced nearly 50 dashboards in the first two weeks, exceeding the velocity of previous tools; Altis rationalised a large volume of legacy reports into a smaller, higher-quality set, clarified reporting ownership across the organisation, and converted existing datasets to the Domo platform to create a governed self-service analytics environment
- Nine is now using Domo Apps to build reusable, role-based data experiences with shared components and common calculations — standardising metric logic organisation-wide, reducing duplication and rework, and ensuring consistent definitions propagate automatically rather than requiring manual synchronisation across siloed reports
- Looking ahead, Nine plans to introduce automated workflows that monitor data patterns and alert teams to emerging trends — moving the platform from self-service reporting toward proactive, AI-assisted analytics that surface insights automatically, a trajectory that positions the Domo investment as a foundation for progressively more automated decision-making as the platform matures within the organisation