BI & Analytics
Looker integration with Feedback Analytics: from feedback to insight in your dashboards
Feedback Analytics captures feedback and turns it into insight and follow-up. Looker is where you show those signals next to revenue, operations, and CX KPIs: governed dashboards and explorations your leaders already trust. Feedback becomes part of the same narrative as the rest of your metrics: feedback, insight, action.
Why this integration
Feedback that stays outside BI is easy to miss in leadership cadences. Modeling Feedback Analytics data in Looker puts scores and themes alongside branch performance, conversion, or service metrics.
Definitions matter: what a score means, which segments count, and what follow-up already runs in Feedback Analytics. Looker presents the view; Feedback Analytics remains the system where feedback is measured and turned into action.
What you can do with Feedback Analytics + Looker
Feedback Analytics supplies trusted feedback and context; Looker turns it into dashboards and explores, typically on top of your cloud warehouse.
| Visualize feedback | NPS, CSAT, CES, and themes from open text in one BI layer: trends, comparisons, and filters aligned with how you report. |
|---|---|
| Blend sources | Join feedback with CRM, revenue, or operational data where policy and modeling allow. |
| Location performance | Track scores and volume by site, region, or team next to local KPIs. |
| Trends and sentiment | Surface time-series views and aggregated text signals for CX and operations priorities. |
| Executive reporting | One set of definitions for leadership: weekly snapshots to quarterly packs, consistent with your semantic model. |
| Technical shape | APIs, exports, and BI connectivity into your warehouse and Looker, aligned with ETL and governance. |
Practical use cases
- CX dashboard: NPS and CSAT next to funnel and retention for the same segment.
- Retail or franchise: scores by store or region compared to traffic or revenue where data exists.
- Support and ops: post-touch feedback next to handle time or backlog from operational systems.
- Leadership pack: fixed views with shared definitions, not manual exports from siloed tools.
- Themes and sentiment: aggregated open feedback signals to steer product and service priorities.
Who it is for
BI teams building a semantic layer for feedback next to other datasets. Management and line leaders steering by branch or segment. Operations linking throughput and quality to satisfaction. CX teams who want trends in the same cadence as the business.
How the connection works
Configure surveys and logic in Feedback Analytics; use exports or API access for downstream processing.
Land data in your analytical store via scheduled loads or pipelines, then model explores and dashboards in Looker. Feedback Analytics stays where feedback is captured, interpreted, and followed up before it enters the BI domain.
Why Feedback Analytics as the central feedback layer?
Feedback Analytics covers collection through action: flows and action lists, not one-off surveys.
The numbers you show in Looker then have lineage and meaning, not only charts.
Want to align this with your warehouse, access controls, and Looker models? Request a demo: we can walk through your first dashboard and data paths with BI and CX.
FAQ
Does Looker replace Feedback Analytics?
No. Looker is BI and visualization; Feedback Analytics is where feedback is captured and turned into follow-up.
Do we need a data warehouse?
You usually model Looker on warehouse tables (e.g. BigQuery). The right path depends on your stack and scale.
What about privacy?
Send only fields needed for analysis, document purposes and retention, and align Looker and warehouse access with roles and GDPR commitments.
Can we show NPS and CSAT together?
Yes, if both are modeled with shared time and segment fields for consistent comparisons.
