Looker + ClosedLoop AI

Analytics & BI

Product intelligence as queryable, governed, dashboardable data

Looker turns raw data into governed, trustworthy business intelligence. ClosedLoop AI turns customer conversations into structured product intelligence. Together, customer feedback becomes a first-class data source — modeled in LookML, queryable by any analyst, and available in every dashboard across the organization. No more anecdotal evidence; feedback is data.

Looker is Google Cloud's enterprise business intelligence platform built on a semantic modeling layer called LookML. It provides governed data access, interactive dashboards, embedded analytics, and AI-powered conversational analytics through Gemini integration.

Data visualization SQL modeling Dashboards Embedded analytics

What You Discover

Product intelligence that only surfaces when AI processes every Looker conversation at scale.

1

Feedback as Governed Data

In Looker, data is modeled once and trusted everywhere. ClosedLoop AI feeds product intelligence into your data warehouse where it becomes part of your LookML model — governed, versioned, and consistent. Every analyst querying customer feedback gets the same definitions, the same metrics, the same source of truth.

2

SQL-Powered Feedback Exploration

Your data team thinks in SQL. ClosedLoop AI structures feedback data so analysts can query it the way they query every other dataset — joining feature requests to account revenue, filtering sentiment by product area, or building cohort analyses that combine behavioral and qualitative signals.

3

Cross-Dataset Intelligence

The real power emerges when feedback data joins your existing tables. Combine feature requests with ARR data to find revenue-weighted priorities. Join sentiment scores with usage metrics to find at-risk accounts. Overlay feedback themes with support ticket volumes to see which complaints drive the most operational cost.

4

Embedded Product Intelligence

Looker's embedded analytics let you surface product intelligence in the tools your teams already use — internal portals, product dashboards, executive reports. ClosedLoop AI data flows through Looker into wherever decisions are being made, not just into a standalone feedback tool.

Who's Talking on This Channel

The customer profiles you hear from on Looker — and the intelligence each one reveals.

Data Analysts and Engineers

Data professionals who model, query, and govern business data — now treating customer feedback as a structured dataset they can join, filter, and analyze alongside every other table in the warehouse.

Product Managers

PMs who need to pull their own feedback reports without waiting for a data team — using Looker's self-serve exploration to slice insights by segment, product area, or time period.

Executive Leadership

Leaders who rely on Looker dashboards for business decisions — now seeing customer feedback trends as a standard KPI alongside revenue, retention, and growth metrics.

Revenue Teams

Sales and CS leaders who need feedback data connected to account value and pipeline stage — understanding which product gaps impact revenue and which feature requests come from the highest-value accounts.

Example Signals

Real intelligence ClosedLoop AI surfaces from Looker conversations.

"A SQL join between feedback data and ARR revealed that 70% of feature requests by revenue weight came from just 3 product areas — the volume-based prioritization had been ignoring the revenue-weighted truth"

Revenue-weighted reframing

"A Looker Explore combining feedback sentiment with product usage showed that the most-used feature had the lowest satisfaction — a hidden retention risk in the product's core value prop"

Usage-sentiment divergence

"Embedding a ClosedLoop AI feedback widget in the internal account health dashboard surfaced that 4 of the top 10 accounts had escalating negative sentiment — before any formal churn signal appeared"

Embedded early warning

"Analysts querying feedback data by customer segment discovered that enterprise and SMB customers used identical language to describe opposite needs — the same word meant different features for different audiences"

Semantic ambiguity detection

Measurable Outcomes

How your life changes when you connect Looker to ClosedLoop AI.

Automate delivery of structured feedback data into your data warehouse where it becomes a governed, queryable Looker data source
Product intelligence modeled in LookML with consistent definitions trusted across the entire organization
SQL-native feedback exploration so data teams analyze customer voice with the same tools they use for everything else
Cross-dataset intelligence that joins feedback with revenue, usage, support, and pipeline data in a single query
Embedded product intelligence surfaced in internal dashboards and portals through Looker's embedded analytics
Self-serve feedback exploration for product managers without requiring data team involvement

Related Integrations

Other analytics & bi integrations that work great with ClosedLoop AI.

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Start extracting product insights from your Looker data in under 5 minutes.