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Snowflake Retail Paris, France

Etam

Marketing Personalization · Supply Chain Optimization

give business teams a central platform for retail data so they could forecast better, optimize inventory, and use AI without a large engineering staff building custom connectors.

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50-100% less engineering effort for data users
8-15% improved forecasting accuracy
moved ~70% of its data into the Snowflake AI Data Cloud

Reported impact

Business outcome

Etam moved about 70% of its data into Snowflake, improved forecasting accuracy by 8-15%, cut engineering effort for data users by 50-100%, and enabled broader self-service analytics.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Etam uses Snowflake and Cortex AI on Snowflake to give business teams a central platform for retail data so they could forecast better, optimize inventory, and use ai without a large engineering staff building custom connectors. Etam centralizes business data from core systems, emails, spreadsheets, and retail operations on Snowflake using built-in connectors instead of custom point integrations. The shared platform handles transformation and analytics centrally, while Cortex AI helps extend insights and data access to users who do not want to depend on engineers for every request. Style, purchasing, retail, logistics, and other teams use the data for forecasting, customer recommendations, inventory optimization, and bespoke dashboards built on the governed retail data set. Keeping ingestion, storage, transformation, and downstream access on one governed platform reduces data copying, simplifies operations, and gives teams a single trusted operating view for analytics and AI. Etam...

Data flow

retail operations, business systems, emails, and spreadsheets flow into Snowflake and Cortex AI; curated data and model outputs are then served to style, purchasing, retail, logistics, and business teams.

Solution architecture

2 components · 2 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.

Architecture clues

  • Relies on prebuilt connectors to link Snowflake to core systems.
  • Supports forecasting, recommendations, and inventory use cases from one platform.
  • Uses Cortex AI to expose data and insights more broadly to business users.

Evidence from the source

Etam quickly moved ~70% of its data into the Snowflake AI Data Cloud
improved customer recommendations, optimized inventory levels and provided new insights to business users through AI-powered tools like Cortex AI
up to 15% improved accuracy in forecasting estimates
uses prebuilt connectors to link that data back to all its core systems
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

    Etam customer story

    First-party
    https://www.snowflake.com/en/customers/all-customers/case-study/etam/
    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

  • First archived Mar 22, 2025 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Jul 11, 2026 · Snowflake · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    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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