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Snowflake Software / SaaS Tel Aviv, Israel

Optimove

Marketing Personalization

process every customer signal at massive scale so marketing AI could personalize campaigns better than human audience selection without capping data volume.

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19% Better campaign performance with AI-selected audiences
2 billion real-time events
33% Average increase in customer lifetime value
8.4 billion rows a day

Reported impact

Business outcome

Optimove improved campaign performance by 19%, increased customer lifetime value by 33% on average, and shrank long-running refresh and query workloads from days or hours to minutes or seconds.

  • Customer Experience
  • Productivity Improvement
  • Revenue Growth

Solution

Optimove uses Snowflake, Cortex AI, and Secure Data Sharing on Snowflake to process every customer signal at massive scale so marketing ai could personalize campaigns better than human audience selection without capping data volume. Behavioral histories, campaign interactions, and real-time customer events from more than 500 brands are processed on Snowflake at billion-row scale. Optimove uses the Snowflake foundation for large-scale AI audience selection and personalization, and keeps those models close to the data so it can score full histories instead of sampled subsets. The outputs feed campaign targeting and loyalty workflows for brand customers, giving marketers better audience selection and faster analytics without artificial limits on incoming data. Keeping ingestion, storage, transformation, and governed access on one platform reduces copying, simplifies administration, and makes it easier to reuse trusted data for analytics, reporting, and AI. Optimove improved campaign...

Data flow

behavioral histories and real-time customer events flow into Snowflake, Cortex AI, and Secure Data Sharing; curated data, reports, and model outputs are then served to brand marketers, loyalty workflows, and personalization models.

Solution architecture

3 components · 3 layers
  1. Compute
    • Cortex AI Provides in-platform AI functions used for summarization, classification, generation, or model-assisted analysis.
  2. Storage
    • Snowflake Provides the centralized data platform that stores governed datasets and serves analytics or AI workloads.
  3. Serving
    • Secure Data Sharing Shares governed data with partners or internal consumers without moving copies.

Architecture clues

  • Built to support more than 500 brands and millions of customers.
  • Combines Snowflake with Google Cloud to scale AI without limiting ingest volumes.
  • Processes complete behavioral histories directly on Snowflake.

Evidence from the source

19% Better campaign performance with AI-selected audiences
33% Average increase in customer lifetime value
8.4 billion rows a day, 2 billion real-time events
By processing complete behavioral histories on Snowflake, Optimove’s AI builds a fuller picture of each customer
Transparency Evidence & methodology 100/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

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 value100/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Snowflake

    Optimove customer story

    First-party
    https://www.snowflake.com/en/customers/all-customers/case-study/optimove/
    Source type
    Vendor-published 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

Date evidence

  • Sitemap last modified Aug 12, 2026 · Snowflake · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
  • Unverified extracted date Aug 12, 2026 · Snowflake · Unknown Legacy extracted date without source-page confirmation.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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