A keyword-research framework for structuring Amazon PPC campaigns: instead of treating a product's full keyword list as one undifferentiated pool, keywords are clustered by the buyer's underlying purchase motivation (e.g., decorative vs. heavy-duty use for the same product), and one campaign is built per intent cluster.
The payoff is diagnostic, not just organizational: each intent-segmented campaign's CTR, conversion rate, and impressions become a proxy for whether the listing's assets (main/secondary images, title, A+ content, brand story, top reviews) actually communicate to that specific buyer segment. An underperforming intent cluster signals a listing-asset gap (e.g., missing decorative-use imagery) rather than just a bidding problem, turning PPC data into a listing-optimization diagnostic.
Some search terms indicate storefront/browse intent (shopping a brand generally) rather than intent to buy one specific unit — these should be routed to a Sponsored Brand/Store campaign rather than a Sponsored Products campaign.
Feeds into the broader Master Keyword List & Listing Scorecard and Six-Campaign PPC Launch Structure workflows, using Cerebro Filtering Protocol (Organic / Competitor Rank / Number of Competitors) output as its raw material. Buckets are typically assembled via AI-Assisted Intent Clustering (ChatGPT Two-Prompt Method) rather than manual tagging.
A Performance-category example: group several exact-match keywords that share the same shopper intent (e.g. gift-related, mom-related, pain-related) into one campaign aimed at profit. Default to Dynamic Bids Down Only (Default Steady-State Bidding Strategy); switch temporarily to Dynamic Bids Up and Down (Amazon PPC Bidding Strategy) if the campaign isn't getting impressions.
Group phrase-match keyword campaigns by semantic core / shopper-intent family (e.g., 'capsules,' 'powders,' 'muscle gain,' 'pain') rather than by search volume — one ad group or campaign per intent family. Because each family isolates a distinct shopper intent, CTR measured per family becomes a diagnostic: a family with unusually low CTR flags a mismatch between the main image/listing and that specific search intent, fixed by adjusting the primary image rather than the keyword targeting. Used as one of four campaign types (alongside category targeting, brand defense, and auto targeting) in a launch that reached $100K revenue in 90 days at 14% average ACOS.
Phrase match (see Keyword Match Types (Exact / Broad / Phrase)) is the match type used for semantic/shopper-intent-family keyword campaigns: exclude generic category keywords from these groups, and add only curated keywords sourced from keyword research or PPC search-term reports. Because campaigns are grouped by intent rather than by volume, per-group CTR becomes a listing diagnostic: an intent segment with unusually low CTR (e.g., a "powders" intent family) signals that the primary image or title doesn't visually match that search intent — fixable by changing the main image rather than the keywords themselves.
When branded search terms appear inside generic broad/phrase/auto campaigns' search term reports, they should be pulled out into their own dedicated campaign rather than left mixed in with open-discovery traffic. A customer searching your brand name is already brand-aware demand, not organic discovery, so it belongs in the same buyer-intent-segregated structure as other branded/non-branded splits — see Search Term Harvesting into Exact Match for the harvesting mechanics.
Из тем: PPC Campaign Structure & Bidding