Terra PPC Product Tour

Terra PPC is an advertising intelligence, seller-business analytics, economics, and controlled automation platform for Amazon sellers, brands, and agencies.

Instead of looking at advertising metrics in isolation, Terra PPC is designed to keep advertising performance, seller-business context, product economics, automation controls, and auditability inside one scoped operating workspace.

The product is organized into five connected capability areas: advertising intelligence, seller business intelligence, economics and profitability, controlled automation and safety, and AI, trust and control.

Each capability on the public site links to working evidence in the interactive demo.

First, advertising intelligence.

The walkthrough uses synthetic demo data, and demo actions are never sent to Amazon.

It starts from advertising data: ad spend, ad-attributed sales, ACoS, and ROAS for the selected account and marketplace.

Every campaign is read against its own Target ACoS and its modeled break-even.

Search-term views separate converting terms from terms that only spend. When a term has spend but no attributed sales, ACoS is shown as unavailable, not zero.

Keywords and targets, n-gram patterns, hourly behavior, and campaign architecture each have their own view.

Placement rules propose top-of-search adjustments inside a policy, the budget planner compares spend with the monthly plan, and the campaign funnel moves proven terms from discovery to evaluation to scale.

Next, seller business intelligence.

Advertising performance is only part of the operating picture. Where authorized, Terra PPC is designed to use selected seller-business context: sales, financial activity, inventory, listings, fulfillment, and retail analytics.

Finance context supports profitability and reconciliation: Amazon fees, refunds, and reimbursements stay visible as their own lines.

Inventory context supports inventory-aware advertising decisions, and listing context explains when an advertised product cannot sell.

Seller revenue is business context, not an advertising metric, and every value keeps its source label.

Then, economics and profitability.

COGS and other non-Amazon business costs are customer-configured inputs. Terra PPC does not assume Amazon provides those values.

Landed cost, dated cost versions, and FIFO purchase layers set the unit cost that each day's sales carry.

When a supplier cost version is added, the impact preview recalculates the product's cost share, its modeled break-even ACoS, and the campaigns that advertise it.

Here, a higher landed cost lowers break-even from forty-two to thirty-nine point one percent while the campaign runs at forty-one point eight percent, so scaling is held by the Cost Increase Guard and a cost review is queued.

In the modeled P&L, source provenance stays visible, so users can distinguish Amazon advertising data, seller context, financial context, customer economics, and Terra PPC derived metrics.

Next, controlled automation and safety.

Rules, strategies, and recommendations meet in the decision engine, which evaluates what should be considered: metrics, rules, strategy, profitability, and eligibility.

The execution planner determines whether an eligible proposal can proceed safely, in what order, and under which control mode, from scope and data readiness through the circuit breaker and business guards to conflict resolution, global guardrails, and audit.

An evaluation runs the whole cycle and reports what it created, applied, skipped, and held.

Business guards hold scale actions when days of cover are low or a listing cannot sell, and the circuit breaker stops Auto actions when a cycle looks wrong.

Manual, Review, and Auto are distinct modes. Automation does not bypass scope, policy, guardrails, conflict resolution, or the audit trail.

The Action Center groups risk, efficiency, growth, and maintenance, and every recommendation shows its trigger, current and proposed state, rule, and guardrails.

Then, AI and MCP.

Natural-language workflows sit on top of the same scoped product context, and answers name their sources.

In the demo, asking why scaling is held returns the same cost trace the COGS page shows, with scope, sources, and each step.

AI-assisted interactions do not bypass authorization, policies, guardrails, or control modes: a request to raise every bid by fifty percent is limited to the configured maximum step.

The Amazon Ads MCP Server is Amazon technology; Terra PPC AI and MCP is Terra PPC's own scoped interaction and governance layer.

Authorization, scope, provenance, and security.

Advertising access and seller-business access are separate authorization and scope contexts. Access to one does not automatically grant the other.

Advertising data supports advertising operations, seller data supports business context, customer-configured inputs drive economics, and derived metrics are Terra PPC calculations.

Every important number carries its source: ADS, SELLER, FINANCE, ASSUMPTION, or DERIVED.

Security is part of the design: authorized access, least privilege, account isolation, data minimization, traceability, and a defined data lifecycle.

Finally, the interactive demo.

Everything shown can be reproduced from a reset, deterministic state: change a campaign's Target ACoS, run an evaluation, open a recommendation and apply it in Review, then find it in the change log and undo it.

Changing an economic input has visible consequences: after a new cost version is saved, the next evaluation holds the scale action under the Cost Increase Guard and queues a cost review instead of changing the advertising account.

Demo actions remain inside the Terra PPC environment.

Terra PPC brings advertising intelligence, seller business intelligence, economics and profitability, controlled automation and safety, and AI, trust and control into one scoped workspace.

Explore the interactive demo, or request access. Terra PPC is a software product operated by ĐT ORGANIC COMPANY LIMITED.