Retail · CPG · Loyalty
Retail and CPG margin is thin. Data-driven decisions are where it is recovered.
From perishable goods and food production to omnichannel retail and loyalty, we unify sales, inventory, production, and customer data into near-real-time analytics that sharpen inventory, margin, and merchandising decisions.
The engagement
A partner who understands Retail & CPG.
No one spends the first month explaining retail & cpg to us. The team arrives knowing the sector's systems, regulations, and reporting rhythms, then builds the data models, governance, and dashboards alongside in-house teams, against the metrics they already answer for.
- Online and in-store data unified into one near-real-time, governed foundation
- Inventory and perishables analytics that cut shrink
- Production, food cost, and logistics in a single view
- Customer and loyalty performance tracked alongside margin
What we stand up
The foundation for Retail & CPG
The capabilities we put in place, and how fast. The featured story below is a real automotive engagement, with its measured results.
Challenges we solve
What Retail & CPG teams are up against
The recurring problems we hear, and how we resolve them.
Stock and sales blind spots
We track stock against sales to sharpen inventory and replenishment decisions.
Online and in-store data split
We unify online and physical operations into one near-real-time view.
Opaque cost and loyalty data
We connect production and food cost with customer and loyalty analytics.
What gets delivered
Deliverables
Tangible outcomes engineered to move the metrics that matter.
Sales & inventory analytics
Stock-vs-sales visibility that cuts shrink and stockouts.
Omnichannel analytics
Online and in-store unified for near-real-time reporting.
Production & food-cost analytics
Production performance, logistics, and food cost in one view.
Customer & loyalty analytics
Margin-by-product insight and loyalty performance tracking.
Stack
Tools & technologies
The Snowflake-first stack we reach for in this sector.
Built for the regulators
Featured engagement
How we delivered for Automotive
A real engagement, start to finish: the challenge, the build, and the outcome. Client names are withheld to protect confidentiality.
AutomotiveAutomotive organization · Mexico
Governed, AI-ready data for automotive on Snowflake
A commercial-vehicle dealer group ran sales, service, parts, and the back office on separate systems, with no single version of a customer, vehicle, part, or supplier. Viewnear is building a corporate master data foundation on Snowflake, released domain by domain: a progressive multi-source golden record across eight business domains, using a Medallion architecture, Openflow ingestion, dbt transformations, and per-domain Snowflake CoWork agents.
3
Source systems unified
8
Business domains mastered
Medallion
Bronze, Silver, Gold
12 mo
Roadmap: three phased releases
Questions
Common questions in this sector
How does a retailer get one view of demand across online and in-store?
Retail and CPG teams get one demand view by unifying online and physical operations into a single near-real-time governed source on Snowflake, with stock tracked against sales. Viewnear delivers stock-vs-sales visibility that cuts shrink and stockouts, with online and in-store data unified for near-real-time reporting. Payment and customer data is handled PCI-aware and governed end to end.
Can Snowflake show margin by product and food cost for a food producer?
Margin-by-product insight and food cost sit on the same governed foundation on Snowflake: production performance, logistics, and food cost in one view, tracked alongside loyalty performance. Viewnear works across perishable goods and food production, unifying sales, inventory, production, and customer data into near-real-time analytics that sharpen inventory, margin, and merchandising decisions.
How does a multi-site sales, service, and parts network get one definition of a customer or a part?
One definition comes from a master data foundation on Snowflake: source data lands in Bronze, is cleaned and conformed in Silver, and resolves into governed Gold golden records, with master keys, matching and merge, survivorship rules, lineage, and audit designed in from the first table. Viewnear built that for a commercial-vehicle dealer group that ran sales, service, parts, and the back office on separate systems, mastering eight business domains from three source systems across three releases in a twelve-month roadmap. Per-domain Snowflake CoWork agents, grounded in each domain's governed golden record, let business users ask questions of master data in plain language.
Let's stand up a lasting data & AI practice.
Tell us where the organization stands (migrating, scaling, or shipping AI) and we'll map the fastest path to use cases in production, run by in-house teams.