Normalized claim
Return on investment increase: 50% increase
driving a 50% increase in return on investment
Freshworks, a global SaaS company, built a Google Cloud data infrastructure to analyze and optimize customer touchpoints across marketing and sales. The company centralized CRM, website, analytics, and advertising data in BigQuery to create a full lifecycle view of customer interactions and support self-service reporting.
Reported outcomes
8x
campaign growthRevenue & growth
Strategic outcomes
Catalog median for revenue & growth deployments: +40% across 68 reported metrics. Compare benchmarks →
Normalized claim
Return on investment increase: 50% increase
driving a 50% increase in return on investment
Normalized claim
Database spend reduction: 40% decrease
we reduced our database spend by 40%
Normalized claim
Query cost reduction: 44% decrease
The teams reduced query costs by 44% in November 2020 relative to August the same year
Normalized claim
Compute Engine/BigQuery cost reduction: 70% decrease
drove down Compute Engine BigQuery costs by 70%
Normalized claim
Campaign growth: 8 x increase
Since 2016, the business has increased by eight times its number of campaigns
Normalized claim
Lead growth: 5 x increase
driving a fivefold growth in overall leads
No explicit deployment-stage evidence found.
Primary read
Showing 3 of 3
A Google Cloud marketing analytics architecture centered on BigQuery, integrating Google Analytics 360, Google Ads, CRM data, and Looker Studio; BigQuery ML was used for visitor scoring and audience activation in Google Ads, with Cloud Source Repositories and Compute Engine supporting production jobs and analytics workloads.
The same organization appears in newer AI deployment evidence.
Measures whether this deployment's public evidence persists — not whether the system is still in production.
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