Build a daily PPC waste agent before you automate anything else
Amazon sellers should not start with a giant AI plan. Start with one daily workflow: use Codex or Claude to review your Sponsored Products Search Term Report and flag wasted PPC spend before it survives another day.
This is the first lane worth building because it is narrow, repeatable, and tied to margin. You are not asking a model to run the brand. You are asking it to inspect one report, apply a fixed rule set, and prepare a decision table for the PPC manager.
The human still makes the call. The agent does the boring scan.
Key Takeaways
- Start with one PPC report, not a full account automation project.
- The best first use case is daily search term waste review.
- Codex and Claude are useful here because they can read structured data, follow rules, and produce repeatable outputs.
- Human judgment stays in launch context, margin tolerance, inventory risk, and keyword intent.
- Once the workflow works manually, connect it to APIs, schedules, MCP servers, or internal reporting tools.
Why should Amazon sellers start with PPC waste?
PPC waste is one of the cleanest places to use an agent because the work is repetitive and the cost is visible. A search term spends money, gets clicks, produces orders or does not, and creates a decision.
Amazon explains Sponsored Products as cost-per-click ads where advertisers choose products, set targeting, control budgets, and pay when shoppers click (Amazon Ads). That means every weak click has a cash cost. The faster a seller catches bad search terms, the less money gets burned.
The problem gets worse as the catalog grows. A brand with 10 ASINs can review waste by hand. A brand with 300 ASINs, several campaign types, and multiple marketplaces will miss things.
That is not a talent problem. It is a volume problem.
Decision: do not start by asking AI to manage Amazon PPC. Start by asking it to catch search terms a human should review today.
What report should the agent read every morning?
Use the Sponsored Products Search Term Report for the last seven days. It is specific enough to be useful and familiar enough that most PPC teams already know how to pull it.
Amazon's reporting docs describe campaign reporting as a way to review advertising performance and improve campaign decisions (Amazon Ads). For this workflow, the key fields are search term, campaign, ad group, match type, spend, clicks, orders, sales, CPC, conversion rate, and ACOS.
If you operate in several marketplaces, do not combine them on day one. Start with one marketplace, such as the US account, and run the workflow there for a week.
Marketplace blending is where a lot of sellers make the workflow messy. A query that looks expensive in Canada may be acceptable in the US because margin, CPC, reviews, price, and conversion rate are different.
Decision: one marketplace, one report, one daily review. Expand only after the first version is useful.
What should the daily prompt say?
The prompt should be boring on purpose. You want the same type of output every day, or the workflow will turn into another manual review.
Use this prompt:
Act as an Amazon PPC analyst for a 7-8 figure brand.
Review this Sponsored Products Search Term Report and find search terms that need action.
Do not summarize the full report. I only want the actions a PPC manager should review today.
Classify each recommendation as one of the following:
- Add negative exact
- Add negative phrase
- Lower bid
- Move to exact match
- Increase bid
- Monitor only
Use spend, clicks, orders, ACOS, CVR, CPC, campaign name, match type, and search term relevance.
Apply these rules:
- If a search term has meaningful spend and zero orders, flag it.
- If a search term has many clicks and poor conversion rate, flag it.
- If a search term has orders but high ACOS, suggest lowering the bid unless it appears to be a launch or ranking term.
- If a search term has multiple orders at acceptable ACOS, suggest moving it into exact match.
- If a search term is clearly irrelevant to the product, suggest adding it as a negative.
- If the data is too thin, mark it as monitor only.
- Do not recommend changes with high confidence unless the data supports it.
Return the output as a decision table with:
Search term
Campaign
Spend
Clicks
Orders
ACOS
Recommended action
Reason
Confidence: High / Medium / Low
After the table, give me the top 3 actions you would review first.
That prompt is not fancy. That is the point.
A fancy prompt tries to impress the seller. A good operating prompt makes the same decision easier every morning.
Decision: keep the prompt fixed for the first week. If the output is noisy, change the thresholds, not the whole workflow.
What should the PPC manager do with the output?
The PPC manager should treat the agent output as a review queue, not an instruction set.
Start with the top three recommendations. Check the search term, the campaign goal, the ASIN, the product margin, and whether the campaign is in launch mode or profit mode.
That context matters. A term with high ACOS may still be worth funding if the product is ranking for a priority keyword. A term with zero orders may still deserve another few days if spend is low and the search term is highly relevant.
The agent can flag patterns. It cannot know every launch thesis, inventory constraint, brand defense decision, or margin tolerance unless that context is added.
This is why ALFI does not frame AI as a replacement for Amazon operators. A good strategist should still own the decision. The agent should remove the row-by-row grind that makes good people miss obvious waste.
Decision: approve obvious negatives and obvious exact-match harvests. Hold anything tied to ranking, inventory, or margin for human judgment.
What rules should the agent use?
The rules should be simple enough that a human can audit them.
Start with these:
- Flag search terms with meaningful spend and zero orders.
- Flag search terms with many clicks and weak conversion.
- Flag irrelevant terms for negative exact or negative phrase.
- Flag converting terms that should be moved into exact match.
- Flag terms with orders but poor ACOS for bid review.
- Mark thin data as monitor only.
Do not hard-code universal thresholds unless your account economics support them. A $50 spend threshold may be too high for a small catalog and too low for a brand spending heavily across hundreds of ASINs.
Use account-specific thresholds instead. For example, a mature profit campaign might flag a term after 15 clicks with zero orders. A launch campaign may need a wider window. A thin-margin SKU should get stricter rules than a high-margin SKU.
The economic point is simple: the agent should not chase tidy media metrics. It should protect contribution margin.
Decision: set thresholds by campaign role and SKU margin. A launch campaign, a branded defense campaign, and a mature profit campaign should not be judged by the same rule.
How does this connect to Codex, Claude, MCP, and schedules?
The manual version proves whether the workflow is worth automating. Once it does, the same logic can move into a scheduled agent.
OpenAI describes Codex as useful for knowledge work, including data analysis, report generation, automations, and recurring work (OpenAI). OpenAI also shows Codex automations as scheduled tasks that can run on a recurring basis (OpenAI Academy).
Claude has a similar path through Claude Code, MCP, subagents, and hooks. Anthropic describes MCP as a way for models to connect to external tools and data sources (Anthropic docs).
For a seller, that means the daily PPC waste workflow can later become:
- a scheduled job that pulls yesterday's Amazon Ads data
- an MCP-connected agent that reads campaign and SKU context
- a report generator that posts the decision table into Slack or Discord
- a review queue that stores approved and rejected recommendations
- a weekly audit that checks whether approved actions improved spend quality
But do not build the whole machine first. That is how teams waste weeks designing automation around a workflow nobody has used.
Decision: run the workflow manually for five business days. Automate only after the PPC manager says the daily table is worth keeping.
What does a good daily output look like?
A useful output is short and opinionated. It does not explain the whole account.
The first table should show only the rows that need review. The agent should not include every search term because that recreates the original problem.
A strong output looks like this:
- Search term: "glass water bottle replacement lid"
- Campaign: US | Bottle | SP | Broad | Discovery
- Spend: $64.20
- Clicks: 23
- Orders: 0
- ACOS: N/A
- Recommended action: Add negative phrase
- Reason: The term points to replacement parts, not the advertised product.
- Confidence: High
That is useful because the decision is clear. The seller can approve it quickly.
Now compare that to a weak output: "This campaign may need work." That sentence helps nobody.
Decision: force the agent to make row-level recommendations with reasons. If it cannot explain the action in one sentence, the recommendation is not ready.
When should sellers expand the workflow?
Expand only when the first lane works.
The next step is not full PPC management. The next step is adding context.
Add SKU margin so the agent can separate expensive clicks from unprofitable clicks. Add campaign role so launch terms are not judged like profit terms. Add inventory status so the agent does not recommend scaling a product with low stock.
After that, add a weekly review:
Review every PPC waste recommendation from this week. Which approved actions reduced wasted spend, which rejected recommendations were correctly rejected, and which rules should change next week?
That weekly review is where the workflow gets sharper. It turns the agent from a one-time report reader into a working operating habit.
Decision: add one context layer at a time: margin first, campaign role second, inventory third.
Where does ALFI fit in?
ALFI's view is simple: AI should not replace the people responsible for Amazon growth. It should make them harder to blindside.
Most Amazon sellers do not lose margin because nobody cares. They lose margin because campaign data, SKU economics, listing issues, inventory, and marketplace differences sit in different places. A person can inspect them, but not all day, every day.
Targeted agents are useful because they watch the repetitive lanes. They find the spend leak. They prepare the report. They make the strategist faster.
That is the difference between generic AI noise and an operating system for Amazon growth.
At ALFI, the human still owns the brand context, campaign strategy, contribution margin logic, and client relationship. The agent supports the staff and the customer by removing blind spots and making daily work sharper.
Decision: do not buy AI theater. Build one workflow that improves margin discipline this week.
Should Amazon sellers let an agent make PPC changes automatically?
Not at first. Use the agent to prepare a review queue. Let a human approve negatives, bid changes, and keyword moves until the rules have been tested.
Can this work without the Amazon Ads API?
Yes. Start with a manual CSV export. The API is useful later, but the first version only needs a clean search term report and a repeatable prompt.
Should the workflow use Codex or Claude?
Either can work. Codex is strong when the workflow needs scripts, scheduled jobs, reports, and automation. Claude is strong when the workflow needs tool connections, MCP, subagents, and careful review of messy context.
What is the biggest mistake sellers will make?
They will try to automate the whole PPC account before proving one daily workflow. That is backwards. Prove the review habit first.
How often should the PPC waste agent run?
Daily is the right default for active accounts. For smaller accounts, three times a week may be enough. The key is consistency.
What should be automated after PPC waste?
The next lane is keyword harvesting. Once wasted terms are being caught daily, use the same search term report to find converting queries that deserve exact-match campaigns.
What to do this week
- Export your Sponsored Products Search Term Report for one marketplace.
- Run the PPC waste prompt above for five business days.
- Review only the top three recommendations each morning.
- Track which recommendations were approved, rejected, or changed.
- Add your SKU margin thresholds before automating anything.
- If the workflow saves time, connect it to a scheduled report.
- If you want a senior team to build this into your Amazon operating rhythm, start with ALFI's Amazon growth services.
