Skynar
Advertising performance means more when you can see inventory, margin, and marketplace conditions alongside it. Skynar is VeriVal's managed commerce intelligence platform, turning those signals into trusted metrics, forecasts, and recommendations your team can review before acting.
Connect the data you own to understand performance, evaluate tradeoffs, and guide the next action. Give marketing, operations, and finance a shared basis for deciding where to invest, where to protect margin, and when to adjust.
The problem
Amazon Marketplace teams often reconcile advertising reports, inventory feeds, marketplace portals, and finance spreadsheets before they can decide what to do. A campaign can show strong returns while stock is running low or fees are eroding margin. The missing context can change the right action.
Pain points
The same gaps show up whether you sell on Seller Central or ship as a vendor. The connected model helps teams investigate these operating problems with a shared view of performance.
Value across teams
Skynar is designed to help marketing, operations, and finance evaluate the same opportunity together. Shared product identities and business definitions make it easier to see where growth is worthwhile, where inventory needs protection, and which action best supports your priorities.
Identify where additional spend may earn a better return and where budget could be redirected.
Bring stock coverage and replenishment timing into promotion and advertising decisions.
Assess profit after advertising, fees, and other available costs before supporting further spend.
Review priorities and tradeoffs against an agreed baseline, with a clear reason for each proposed action.
Unified commerce intelligence
A useful recommendation starts with a clear understanding of performance. These questions guide the product, from reviewing results to weighing the next action.
Read governed metrics with a clear period, definition, and source.
Investigate changes across advertising, pricing, availability, and margin.
Use forecasts with uncertainty and the assumptions behind them.
Review recommendations ranked against the business objective.
Evaluate budget allocation, pacing, and bid suggestions.
Compare estimated revenue, profit, and inventory effects.
Apply inventory, margin, budget, and risk constraints.
Review the supporting evidence, confidence, and assumptions before choosing an action.
Review monitoring criteria and changing conditions that may call for an adjustment.
How the model connects
The architecture is designed to connect source records to shared business definitions, then to metrics, forecasts, and recommendations. Your team can trace a suggestion back to the data and assumptions behind it.
Advertising, sales, inventory, pricing, fulfillment, finance, and behavior data.
Signals resolved into meaningful events, with lineage preserved.
A canonical model of products, campaigns, orders, customers, and marketplaces.
Governed metrics with one trusted definition across every team.
Priority entity health scores with reasons and confidence.
Demand, sales, spend, inventory, and profit, looking forward.
Explainable action options with evidence and expected impact.
Actions ranked against the goals you choose.
Reasoning across domains — not isolated tips.
Connected business context
Intelligence modules
Understand performance, anticipate changes, and evaluate the next action. These connected engines use your data and business rules to bring the relevant context into each decision.
Consistent definitions for advertising, sales, inventory, and profitability metrics, with documented formulas and a traceable source for each number.
Product, campaign, creative, listing, and marketplace health with contributing signals and confidence.
Budget allocation, campaign pacing, bid suggestions, and diminishing-return analysis within agreed business limits.
Bring stock coverage, stockout risk, sell-through, and sales velocity into advertising and replenishment decisions.
Explore how demand, stock coverage, and profit may change as spend changes, with forecast ranges and assumptions made clear.
Explainable recommendations ranked by objective, checked against constraints, and presented for human review.
Spend intelligence
Budget allocation, pacing, and bid suggestions should account for diminishing returns. Skynar is designed to assess the expected impact of a spend change alongside inventory availability, margin thresholds, budget caps, and risk limits.
Health scoring
Health scores are designed to help teams prioritize products, campaigns, and listings that need attention, with contributing signals and confidence visible alongside the score.
Example score
Illustrative only: a score combines available campaign, inventory, pricing, listing, and financial signals. Its explanation shows the inputs, gaps, and confidence.
Recommended action: protect inventory before scaling ad spend.Metric context
Seven views connect current and historical values to a forecast, target, benchmark, variance, and recommendation. Illustrative values below show how that context can support a decision.
Illustrative metric
Recommendation for review
Review ad spend and replenishment together.Coverage is below the agreed range and forecast to decline. Consider reducing selected spend, then reassess when replenishment restores coverage.
Explainable guidance
The reasoning engine is designed to show the evidence, assumptions, and tradeoffs behind each suggestion, so your team can review it with confidence.
Your business priorities
Choose a balanced, profit, growth, or efficiency focus. Recommendations reflect your objective while respecting inventory, margin, budget, and risk constraints.
Reasoning across domains
These illustrative scenarios show how connected signals and business priorities can change the recommended action.
| Situation | How the model reasons | Recommended action |
|---|---|---|
| ROAS is strong but inventory is low | Media returns look healthy, but stockout risk may limit growth | Review a spend reduction until replenishment improves. |
| Inventory is high but paid traffic is weak | More demand may help if margin and expected returns support it | Consider increasing budget or bids on selected campaigns. |
| ROAS is falling and the Buy Box is lost | Offer availability may be contributing to the decline | Investigate the Buy Box before increasing spend. |
| Margin is thin and storage fees are rising | Holding the product may be increasing costs and tying up cash | Compare selective promotion or clearance against margin limits. |
| Search terms spend without profitable conversion | Some traffic may be consuming budget without enough return | Review negative keywords or lower bids. |
| Creative performance is declining | Asset fatigue is one possible cause to investigate | Test refreshed creative or shift spend to stronger assets. |
The foundation
Skynar Data Bridge provides the ingestion foundation: source setup, scheduled data collection, monitoring, and a record of each run. Data lands in storage or warehouse destinations you control, with source identifiers retained for traceability. We agree the sources and destinations for your implementation before building the modeling layer.
Campaign, search-term, targeting, creative, and performance data from the Ads reports you connect.
Orders, inventory, pricing, fees, returns, and catalog context from the seller data you connect.
Vendor sales, purchase orders, shipments, inventory, and demand forecasts from the vendor data you connect.
Data lands in cloud storage and cloud warehouses you own and manage.
We confirm the sources, platform compatibility, and access required for your implementation. Your warehouse remains the system of record for modeled commerce data.
Managed delivery
VeriVal manages the technical foundation while your team retains control of its data and business decisions. We confirm integrations, data requirements, and acceptance criteria together.
VeriVal manages the dbt and Python code, deployment, schedules, monitoring, and upgrades within the agreed service scope.
Source and modeled data reside in your storage and warehouse. You control the access granted to operate the service.
Recommendations support your team's decisions. Execution requires a separately agreed workflow with explicit permissions, approvals, and monitoring.
Shared definitions and source lineage connect each metric to its underlying records, giving your team a clear basis for review.
Common questions
Skynar is VeriVal's managed commerce intelligence platform for Amazon Marketplace sellers and vendors. It connects advertising, inventory, sales, finance, and marketplace signals into trusted metrics, forecasts, and explainable recommendations. Analyses draw on the data and integrations your organization provides.
Skynar is designed to add shared business context across specialist tools. For example, a campaign with healthy returns may still need lower spend if inventory is constrained. Connecting those signals helps teams evaluate the tradeoff before acting.
Data Bridge is the ingestion foundation of Skynar. It is designed for governed connector onboarding, scheduling, monitoring, run history, auditability, and lineage-preserving handoff into customer-owned storage or warehouse destinations.
Skynar is designed to work with customer-owned storage and warehouses, including BigQuery, Snowflake, Redshift, or Azure SQL where configured. We confirm compatibility and service access for your implementation. Source and modeled data remain in your environment; any additional processing is agreed as part of the service scope.
Yes. Skynar recommendations are designed to carry evidence, root cause, expected impact, confidence, risk, alternatives, and rollback conditions, so they are transparent and auditable.
Both. Governed KPIs describe performance, while business objectives guide how recommendations are ranked. A balanced, profit, growth, or efficiency focus helps align guidance with your priorities, subject to the inventory, margin, budget, and risk limits supported by your data.
Recommendations do not themselves authorize campaign changes. Your team can review the guidance and decide what to implement. Any execution workflow must be explicitly included in the agreed scope, with permissions, approvals, monitoring, and recovery controls defined before it is enabled.
Yes. Advertising analysis can use Amazon Ads data on its own. Inventory-aware guidance requires connected inventory data, and profit measures require the relevant cost and fee inputs. Total advertising cost of sales (TACOS) also needs total sales, while incremental return needs a suitable measurement method. The available data determines which analyses can produce meaningful results.
VeriVal manages the Skynar dbt and Python modeling code, deployment, monitoring, and upgrades within the agreed service scope. Customers retain ownership of their warehouse data and control the access they grant. Available sources, warehouse compatibility, and acceptance criteria are confirmed before rollout.
The architecture separates source ingestion in Data Bridge from warehouse modeling in dbt and advanced analytics in Python. It retains source identifiers and lineage, uses shared product and account definitions, and checks the required inputs for each analysis. We review source contracts, metric formulas, access boundaries, model tests, warehouse compatibility, and acceptance criteria with your team.
We discuss the decisions you want to improve, the data you own, and your measures of success. Together we confirm the integrations, data definitions, and access requirements, then validate the configured solution with your team.
We begin by understanding your business priorities and reviewing the data and systems you already have. Together, we identify any gaps in coverage, detail, or quality and outline the steps needed to support your goals.
Work with VeriVal
Tell us where advertising performance, inventory, or margin leaves your team with an uncertain next step. We can help bring those signals together in Skynar.
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