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Terra PPC is an advertising intelligence,
seller-business analytics, economics,

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and controlled automation platform for
Amazon sellers, brands, and agencies.

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Instead of looking at
advertising metrics in isolation,

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Terra PPC is designed to keep advertising
performance, seller-business context,

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product economics, automation controls,

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and auditability inside one
scoped operating workspace.

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The product is organized into
five connected capability areas:

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advertising intelligence, seller business
intelligence, economics and profitability,

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controlled automation and safety,
and AI, trust and control.

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

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demo.

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First, advertising intelligence.

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

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It starts from advertising data:

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ad spend, ad-attributed sales, ACoS,

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and ROAS for the selected
account and marketplace.

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

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Search-term views separate converting
terms from terms that only spend.

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When a term has spend but no attributed
sales, ACoS is shown as unavailable,

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not zero.

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Keywords and targets, n-gram
patterns, hourly behavior,

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and campaign architecture
each have their own view.

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Placement rules propose top-of-search
adjustments inside a policy,

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the budget planner compares
spend with the monthly plan,

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and the campaign funnel moves proven terms
from discovery to evaluation to scale.

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Next, seller business intelligence.

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Advertising performance is only
part of the operating picture.

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Where authorized, Terra PPC is designed
to use selected seller-business context:

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sales, financial activity, inventory,
listings, fulfillment, and retail analytics.

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Finance context supports
profitability and reconciliation:

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Amazon fees, refunds, and reimbursements
stay visible as their own lines.

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Inventory context supports
inventory-aware advertising decisions,

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and listing context explains when
an advertised product cannot sell.

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Seller revenue is business
context, not an advertising metric,

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and every value keeps its source label.

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Then, economics and profitability.

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COGS and other non-Amazon business
costs are customer-configured inputs.

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Terra PPC does not assume
Amazon provides those values.

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Landed cost, dated cost versions,

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

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When a supplier cost version is added,

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the impact preview recalculates
the product's cost share,

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its modeled break-even ACoS, and
the campaigns that advertise it.

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Here, a higher landed cost lowers break-even
from forty-two to thirty-nine point one

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percent while the campaign runs
at forty-one point eight percent,

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so scaling is held by the Cost Increase
Guard and a cost review is queued.

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In the modeled P&L, source
provenance stays visible,

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so users can distinguish Amazon advertising
data, seller context, financial context,

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customer economics, and
Terra PPC derived metrics.

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Next, controlled automation and safety.

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Rules, strategies, and recommendations
meet in the decision engine,

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which evaluates what should be considered:

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metrics, rules, strategy,
profitability, and eligibility.

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The execution planner determines whether
an eligible proposal can proceed safely,

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in what order, and under
which control mode,

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from scope and data readiness through the
circuit breaker and business guards to

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conflict resolution, global
guardrails, and audit.

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

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and held.

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Business guards hold scale actions when
days of cover are low or a listing cannot

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sell, and the circuit breaker stops
Auto actions when a cycle looks wrong.

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Manual, Review, and
Auto are distinct modes.

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Automation does not bypass scope,
policy, guardrails, conflict resolution,

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or the audit trail.

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The Action Center groups risk,
efficiency, growth, and maintenance,

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and every recommendation shows its
trigger, current and proposed state, rule,

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and guardrails.

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Then, AI and MCP.

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Natural-language workflows sit on top
of the same scoped product context,

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and answers name their sources.

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In the demo,

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asking why scaling is held returns the
same cost trace the COGS page shows,

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with scope, sources, and each step.

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AI-assisted interactions do not bypass
authorization, policies, guardrails,

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or control modes:

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a request to raise every bid by fifty
percent is limited to the configured maximum

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step.

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The Amazon Ads MCP Server
is Amazon technology;

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Terra PPC AI and MCP is Terra PPC's own
scoped interaction and governance layer.

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Authorization, scope,
provenance, and security.

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Advertising access and seller-business
access are separate authorization and scope

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contexts. Access to one does not
automatically grant the other.

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Advertising data supports
advertising operations,

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seller data supports business context,
customer-configured inputs drive economics,

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and derived metrics are
Terra PPC calculations.

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Every important number carries its source:

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ADS, SELLER, FINANCE,
ASSUMPTION, or DERIVED.

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Security is part of the design:

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authorized access, least privilege,
account isolation, data minimization,

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traceability, and a
defined data lifecycle.

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Finally, the interactive demo.

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Everything shown can be reproduced
from a reset, deterministic state:

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change a campaign's Target ACoS,

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run an evaluation,

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open a recommendation
and apply it in Review,

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then find it in the
change log and undo it.

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Changing an economic input
has visible consequences:

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after a new cost version is saved,

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the next evaluation holds the scale action
under the Cost Increase Guard and queues

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a cost review instead of
changing the advertising account.

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Demo actions remain inside
the Terra PPC environment.

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Terra PPC brings advertising intelligence,
seller business intelligence,

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economics and profitability, controlled
automation and safety, and AI,

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trust and control into
one scoped workspace.

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Explore the interactive
demo, or request access.

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Terra PPC is a software product
operated by ĐT ORGANIC COMPANY LIMITED.