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Amazon PPC
A PPC consultant audits a seller's Helium 10 Amazon Ads account live and argues that most wasted ad spend comes from correctable structural mistakes — overcrowded broad/auto campaigns, under-optimized budgets, and a failure to proactively harvest winning search terms into exact match — rather than from any single big miscalculation.
The first diagnostic step on any account is sorting all campaigns by spend, since most budget concentrates on the top five to 10 keywords.
Auto and broad match campaigns exist for keyword discovery and organic ranking research, not as the intended long-term profit driver, and get expensive fast if not optimized.
Putting too many keywords into a single campaign is a core mistake; high-search-volume keywords should be segmented into their own campaigns separate from low-search-volume ones.
Performance should be reviewed across three time windows — last week, last month, last three months — to distinguish consistent underperformance from temporary fluctuation.
PPC drops should be cross-checked against listing change history: title edits, image changes, price changes, and stock-outs can all affect ad performance.
Budget utilization percentage shows how often a campaign exhausts its daily budget; near-100% utilization on a good-ACOS campaign signals money left on the table, while low utilization on a mediocre-ACOS campaign signals bids aren't aggressive enough.
Broad and auto campaigns surface search terms with no obvious relation to the product (e.g., 'CBD cream' for a non-CBD product) that the listing would never be indexed for otherwise, because customers search that way regardless.
Winning search terms identified through broad/auto campaigns and the search term report should be proactively moved into exact match campaigns to concentrate budget and enable placement control.
Placement optimization means recognizing that a given keyword may convert well at top of search but not elsewhere (or vice versa), and allocating budget per keyword and placement accordingly.
The sales threshold for harvesting a search term into a manual/exact campaign depends on the seller's customer acquisition economics — high-LTV brands can harvest after one sale, while a general rule of thumb for most sellers is three to five sales before harvesting.
Branded search terms surfacing inside generic broad/phrase/auto campaigns should be segregated into their own campaign, since they indicate brand-aware demand rather than open discovery.
Order-by-spend audit — Sorting all campaigns by ad spend as the first step of any account review to see where the money is actually going. Apply: On any new account, sort campaigns by spend first to find the top five to 10 keywords consuming most of the budget and check whether that spend is converting well.
Budget utilization analysis — A metric showing how often a campaign's daily budget is fully spent, indicating whether ads run all day or get cut off early. Apply: Cross-reference utilization with ACOS: raise budgets on near-100%-utilization campaigns that already have a good ACOS, and raise bids on low-utilization campaigns with mediocre ACOS since that combination signals bids aren't competitive enough.
Three-window time analysis — Reviewing PPC performance across three timelines — last week, last month, and last three months — to separate consistent underperformance from temporary fluctuation. Apply: Check the weekly view for a fast recent snapshot, use the monthly view as the primary overview, use the three-month view to spot longer-term drops, and correlate any dip with the PPC change history or with listing edits (title, images, price, stock-outs).
Auto targeting campaigns — A campaign type where Amazon chooses which search terms to show ads against on the seller's behalf, without seller-picked keywords. Apply: Run auto campaigns to discover converting search terms — including ones that seem irrelevant to the product — then harvest the winners into manual or exact match campaigns.
Broad match campaigns — A targeting type where bidding on one term (e.g., 'in motion') exposes ads to many related search terms Amazon judges relevant (e.g., 'in motion hemp,' 'in motion roll-on'). Apply: Use broad campaigns for keyword and phrase research, then mine the search term report for winners instead of letting spend stay parked in broad indefinitely.
Exact match campaigns — A targeting type that bids only on a specific, already-validated search term rather than on variations of it. Apply: Move proven converting search terms out of broad/auto campaigns into dedicated exact match campaigns to concentrate budget and gain control over ad placement.
Search-term harvesting — The practice of pulling winning search terms out of the search term report of broad/auto campaigns and turning them into dedicated exact-match campaigns. Apply: Set a sales threshold before harvesting a term — generally three to five sales for most sellers, or as low as one sale for brands with high customer-acquisition budgets driven by lifetime value — then adjust the threshold up or down based on subsequent profitability.
Placement optimization — Adjusting bids and budget by ad placement (top of search vs. product detail page vs. rest of search) since a given keyword may convert well in one placement and poorly in another. Apply: Check per-keyword conversion rates by placement and dynamically allocate more budget or bid to the placement where each specific keyword actually converts, rather than applying one placement strategy account-wide.
Branded vs. generic keyword segregation — Keeping search terms that include the seller's own brand name separate from generic or category keywords within campaign structure. Apply: When a generic broad, phrase, or auto campaign's search term report shows branded queries surfacing, break those branded terms out into their own campaign since they indicate brand-aware shoppers rather than open discovery.
High- vs. low-search-volume keyword segmentation — Grouping keywords by search volume tier so that a handful of high-volume terms don't dominate a campaign's budget and starve lower-volume terms of impressions. Apply: Split high-search-volume keywords into their own campaign, separate from low-search-volume keywords, since Amazon's prioritization toward historically high-converting or high-volume terms otherwise crowds out the smaller ones.
Budget utilization is presented as ambiguous on its own: the same 100% figure means 'increase budget' when paired with good ACOS, but low utilization paired with mediocre ACOS is reframed as an aggressiveness problem with bids, not a budget problem.
The harvesting threshold (when to move a search term to exact match) is framed as an explicit economic calculation tied to allowable customer acquisition cost and lifetime value assumptions, not a universal best practice.
Auto/broad campaigns are justified mechanistically: since Amazon indexes and serves ads based on customer search behavior rather than literal product attributes, a listing can convert on a term (like 'CBD cream') it isn't even allowed to use in its own copy.
The account audit treats PPC data as a downstream symptom, explicitly instructing a cross-check against the listing's edit history (title, images, price, stock status) rather than diagnosing ad performance in isolation.
«this is something I would advise nobody to ever do, is putting too many keywords on the same campaign.»
— 02:16
«if you order by spend, you're going to find that usually most of your spend is going to be concentrated on your top five to 10 keywords.»
— 02:26
«That doesn't stop customers from searching it.»
— 06:16
«this is actually also a red flag because another day when this is also not close to 100% percentage is a very low, that means your bids are not aggressive enough.»
— 08:02
«Three to five sales is a good number, and then uh based on how that behaves in terms of if proactively three to five sales is making me profitable, I will keep it or increase it or decrease it and go from there.»
— 11:57
Reception
Viewers found the video insightful and valuable, with positive engagement and no negative pushback, though several replies read as spammy self-promotion rather than organic discussion.
The video functions as a live diagnostic clinic on one real account rather than a general-audience explainer, packing in named, actionable techniques (spend sorting, utilization-vs-ACOS cross-checks, harvesting thresholds, placement optimization) without quantifying the aggregate budget savings such fixes would produce.
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