Analytics Friction Impacting Agility
Bloomreach maintains a modern data stack anchored on Google BigQuery, managed by a highly capable Business Intelligence (BI) team. The team’s mission is to enable data-informed decision-making across the organization.
Historically, the company relied on Tableau for visualization and insights delivery, with much of the data modeling done directly in dashboards. While this approach is standard in the industry, it comes with known limitations. Business users often face hurdles in translating dashboard views into actionable insights, especially in time-sensitive scenarios. Moreover, the exact data needed may not always be available, leading to delays and increased demand on the BI team for custom, ad-hoc analyses.
For Bloomreach’s GTM and Finance teams, speed and precision are essential. Yet, their ability to act on data can often be slowed by analytics friction.
The common thread: decision-makers need fast, flexible, and intuitive access to data—but the existing analytics tools and workflows weren’t designed for this level of responsiveness.
Iris as a Low-Lift, Self-Serve Insights Layer
The BI team began evaluating solutions that could scale their capacity and improve self-serve access for business users. Tableau Pulse was among the tools considered, offering a natural language interface. However, it still required data models to be built and maintained within Tableau and struggled to handle higher-order business questions without explicit data syntax.
Iris stood out immediately.
Frictionless experience for business users: Iris allows users to ask natural business questions—like “Which accounts are at highest churn risk this quarter?”—and instantly receive analysis-rich answers grounded in the company’s data warehouse.
No need for pre-built dashboards or models: Iris connects directly to BigQuery, eliminating the need for BI teams to pre-model data or define logic within a visualization layer.
Context-aware insights delivery: Whether a CSM is prepping for a customer renewal, or a finance leader is evaluating margin trends during planning, Iris tailors the insights to the user’s specific role and data needs.
Use cases unlocked by Iris include
- Analyzing churn and health scores by customer without exporting data manually
- Instantly surfacing a customer-360 with relevant data for live conversations
- Summarizing product usage across Bloomreach’s suite in a personalized, contextual view
A New Paradigm for Insight-Driven Decisions
Iris is currently being rolled out within Finance. Early feedback has been very positive, with business users describing the experience as significantly more intuitive and actionable compared to traditional dashboards.
The BI team anticipates that usage of Iris will surpass Tableau as the primary method of data access for many teams. With broader adoption, Bloomreach expects measurable outcomes in areas such as:
Improved upsell opportunities through better identification of customer expansion signals
Reduced churn by enabling faster intervention based on health indicators
Increased decision velocity as teams reduce reliance on ad-hoc BI support
