Reported impact
Business outcome
ServiceNow achieved measurable business impact on Databricks, including 8x Faster lead scoring; 2x Increase in reply rate; 1.5x Boost in deal velocity.
- Customer Experience
- Productivity Improvement
- Revenue Growth
DatabricksSoftware / SaaSData Lake / Data Warehouse ModernizationMarketing PersonalizationSales AutomationData PlatformGenerative AI / LLMCustomer ExperienceProductivity ImprovementRevenue Growth2025 DatabricksDB#ff3621Software / SaaSUnited StatesHowever, the path to growth was mired in inefficiencies such as siloed data, disconnected systems and time-consuming manual workflows.1.5x Boost in deal velocityAug 22, 20256Data Lake / Data Warehouse Modernization|Marketing Personalization|Sales AutomationDelta Lake · Lakeflow Jobs · Unity Catalog0 2025-08-22 6
ServiceNow
Data Lake / Data Warehouse Modernization · Marketing Personalization · Sales Automation
However, the path to growth was mired in inefficiencies such as siloed data, disconnected systems and time-consuming manual workflows.
1.5x Boost in deal velocity
2x Increase in reply rate
8x Faster lead scoring
But behind their GTM engine was a maze of disconnected systems, slowing the decision-making of their 2,000+ sellers, impacting sales processes and stalling growth.
Solution
ServiceNow helps thousands of enterprises streamline digital workflows across IT, employee and customer experiences. But behind their GTM engine was a maze of disconnected systems, slowing the decision-making of their 2,000+ sellers, impacting sales processes and stalling growth. By adopting the Databricks Data + AI Platform, they unified data and deployed AI models in real time. Databricks powers their Lead Scoring, Outreach Assist and Demo Assist solutions, cutting processing times from hours to minutes and doubling email reply rates. “Databricks helps us go from idea to production faster,” Mili Merchant, Senior Product Manager at ServiceNow, said.
Data flow
Operational, customer, and transactional data lands in Databricks and is transformed through managed pipelines stored in Delta Lake under Unity Catalog governance
Solution architecture
- Storage
- Delta Lake Stores ServiceNow's curated datasets for analytics, machine learning, and operational use cases.
- Orchestration
- Lakeflow Jobs Orchestrates recurring ingestion and transformation pipelines inside ServiceNow's lakehouse.
- Governance
- Unity Catalog Provides access control, governance, and lineage across ServiceNow's shared data products and AI workloads.
Architecture clues
- Cloud: Azure
- Key product: Delta Lake
- Key product: Lakeflow Jobs
- Key product: Unity Catalog
- Real-time or streaming data processing
Evidence from the source
1.5x Boost in deal velocity
2x Increase in reply rate
8x Faster lead scoring
But behind their GTM engine was a maze of disconnected systems, slowing the decision-making of their 2,000+ sellers, impacting sales processes and stalling growth.
To support ServiceNow’s ambitious goal of reaching $15 billion in revenue by 2026, the company’s go-to-market (GTM) teams, which include over 2,000 global sellers, needed a more scalable and intelligent way to operate.
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
How scores are calculated
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Customer reference value95/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth20/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity20/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact25/254 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/205 direct source quotes retained.
- Date provenance10/10The publication date comes from the source page or publisher.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity10/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.databricks.com/customers/servicenowDatabricksFirst-party
ServiceNow customer story
Supports- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
Date evidence
- Published on source page Aug 22, 2025 · Databricks · First-partyOpen date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.
Related
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