What challenges did Lighthouse face before AI implementation?

Customer demand for flexible self-service analytics was increasing, and building custom reporting in-house risked long delays and engineering bottlenecks. Lighthouse needed to model complex hotel metrics such as pace curves consistently so customers could trust the numbers. The company wanted a scalable analytics foundation that could support future conversational analytics.

What was the impact of the AI solution?

Lighthouse reported increased margins by 25%. The BI Pro tier added new revenue streams. Net revenue retention improved by as much as $100,000. The company expanded market reach and won deals it previously would not have been in. Customers that had struggled for years with Power BI were able to model complex hotel metrics like pace within weeks.

Rank#64of 3,117

Source

GCP

Lighthouse — Semantic modeling and conversational analytics-ready BI with Looker (BI Pro)

Use case typeConversational analyticsUpdated Jul 9, 2026

Lighthouse, a global hospitality technology company, needed to move from prescriptive custom reporting toward flexible self-service analytics for hotel chains and management companies. The company used Looker with LookML semantic modeling and embedded dashboards to launch BI Pro, a premium analytics tier with custom report building, visual metric galleries, templates, and personalized scheduled reporting. Lighthouse positioned the platform as AI-ready and conversational-analytics-ready, with the semantic layer serving as the trusted metrics foundation for future natural-language insights.

Organization: Lighthouse
Industry: Consumer & Food
Location: United States
Published: July 2026

Reported outcomes

+25%

marginsOther quantified impact

100,000 USDretained annual recurring revenue

Strategic outcomes

New product / capabilityLaunched a premium analytics product tierMarket & geographic expansionExpanded market reach and won new dealsCustomer experience & trustEnabled self-service reporting for hotel customersSpeed & agilityAccelerated complex metric modelingOther strategic outcomePrepared the product for conversational analytics

Primary read

Use case focus

Showing 2 of 2

1Conversational analytics
2Executive analytics

Customer demand for flexible self-service analytics was increasing, and building custom reporting in-house risked long delays and engineering bottlenecks.
Lighthouse needed to model complex hotel metrics such as pace curves consistently so customers could trust the numbers.
The company wanted a scalable analytics foundation that could support future conversational analytics.

Lighthouse chose Looker after RFP and proof-of-concept testing because of its semantic modeling capabilities.
It used LookML to centralize business logic and build trusted metrics on top of existing data.
The company launched BI Pro with embedded dashboards, custom report building, visual galleries of KPIs, editable templates, and personalized scheduled reporting.
The product was sold by hotel property rather than by user license to align with how hotel customers buy.

Technologies

Looker LookML

Lighthouse reported increased margins by 25%.
The BI Pro tier added new revenue streams.
Net revenue retention improved by as much as $100,000.
The company expanded market reach and won deals it previously would not have been in.
Customers that had struggled for years with Power BI were able to model complex hotel metrics like pace within weeks.

Sources & evidence1

Groundedness: 4/5Type: Customer StoryPublished: Jul 9, 2026Publisher: Google CloudEvidence: PrimaryConfidence: High

Primary source

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