Amazon AdvertisingGlossary

Amazon's most common advertising type, appearing on search results pages and product detail pages, pay-per-click (CPC).

Exclusive to Brand Registry sellers, displaying brand logo and multiple products at the top of search results.

Display advertising appearing on Amazon and off-site, targeted based on user browsing behavior.

Also known as Sponsored Products, former name of Sponsored Products advertising.

Only triggers advertising when buyer search terms exactly match keywords, high precision, low traffic.

Triggers advertising when buyer search terms contain keywords or variations, moderate precision and traffic.

Triggers advertising when buyer search terms contain any part of keywords or related terms, highest traffic, lowest precision.

Exclude irrelevant search terms to avoid wasting advertising on invalid clicks.

Cost Per Click, fee per click, i.e., the fee Amazon charges when advertising is clicked once.

Click Through Rate, ratio of ad impressions to clicks, measuring advertising attractiveness.

Advertising Cost of Sale, ratio of advertising spend to advertising sales, calculation formula: advertising spend / advertising sales × 100%.

Return on Ad Spend, advertising input-output ratio, calculation formula: advertising sales / advertising spend.

Ratio of advertising clicks converting to orders, measuring traffic quality brought by advertising.

Campaign is the highest level of advertising management, containing multiple ad groups, setting daily budget and campaign strategy.

Ad group contains multiple keywords and products, each ad group can set different bidding strategies.

Words buyers use when searching, sellers select keywords for advertising.

Maximum daily spending limit for advertising campaigns, advertising stops displaying after reaching the limit.

whenAmazondeterminesAdvertisingunlikely to convert, automaticdecreases Bid, provinceAdvertisingCost.

whenAmazondeterminesAdvertisingmay convertincreases Bid, determinesunlikely to convertdecreases Bid.

Seller manually sets Bid, Amazon does not auto-adjust.

Sponsored BrandsAdvertisingoldname, atonenameforSponsored Brands.

Strategy: After new product launch, use Sponsored Products with broad match, $50/day budget.
Operation: Add core keywords, enable broad match, collect 7-day search term report.
Result: Discovered 30+ quality long-tail keywords, ACoS dropped from 45% to 28%, organic ranking improved by 5 positions.
Applicable: New product cold start, keyword discovery.

Strategy: Use exact match for core keywords with Dynamic Bidding - Up and Down.
Operation: Select 10 core keywords, set higher bids, enable dynamic bidding.
Result: Core keywords stably ranked top 3, conversion rate increased 40%, ACoS controlled below 20%.
Applicable: Mature products, core keyword defense.

Strategy: Regularly analyze search term reports, add irrelevant terms as negative keywords.
Operation: Download search term reports weekly, add terms with CTR<0.1% or no conversions as negatives.
Result: Invalid clicks reduced 60%, ad spend decreased 35%, ACoS dropped 15 percentage points.
Applicable: All advertising types.

Strategy: Use Sponsored Brands to display brand logo and multiple products, target category keywords.
Operation: Design eye-catching logo and slogan, select category and brand keywords, $30/day budget.
Result: Brand exposure increased 200%, store visits increased 150%, new product conversion improved.
Applicable: Brand Registry sellers, multi-product portfolio.

Strategy: Use Sponsored Display to target competitor ASINs and capture competitor traffic.
Operation: Select 10 competitor ASINs, set auto bidding, enable "Purchase Intent" targeting.
Result: Captured 30% additional traffic from competitors, 1.8% conversion rate, 28% ACoS.
Applicable: Products with price or differentiation advantages.

Strategy: Set different bidding strategies for the same ad group for A/B testing.
Operation: Ad group A uses "Dynamic Bidding - Up and Down", ad group B uses "Fixed Bidding".
Result: Dynamic bidding ACoS 24%, fixed bidding ACoS 28%, dynamic bidding saves 14% spend.
Applicable: Mature products with sufficient data.

Mistake: Raised bid from $1.5 to $4.0 to capture top position without considering product profit margin.
Result: Ad position reached top of first page, but ACoS soared to 78%, severe advertising loss.
Lesson: Bids should be calculated based on product gross margin: reasonable bid = margin × target ACoS × conversion rate.

Mistake: Launched ads without optimization for months, no negative keywords added, no bid adjustments.
Result: $8,000 wasted on invalid clicks in 3 months, ACoS remained above 50%.
Lesson: Optimize ads at least weekly, analyze search term reports, adjust strategies promptly.

Strategy: Increase ad budget 2 weeks before Prime Day, Black Friday and other major promotions.
Operation: Increase budget to 2-3 times normal, enable Bid+, increase bids for high-converting keywords.
Result: Holiday sales 5 times normal, ACoS controlled below 30%.
Applicable: Major promotion periods.

Strategy: Create dedicated ad group for long-tail keywords with phrase match.
Operation: Collect 50+ long-tail keywords, set lower bids ($0.5-$1.0), $20/day budget.
Result: Long-tail keyword ACoS only 18%, accounts for 40% of total orders, high profit contribution.
Applicable: Products with certain sales volume.

Theory: One Campaign + One Ad Group + One Product + Multiple Keywords
Operation: Create Campaign → Add Ad Group → Attach one ASIN → Add 10-20 core keywords
Applicable: New sellers, single product testing phase
Pros: Simple structure, easy to manage, convenient for data analysis
Cons: Keywords compete with each other, difficult to precisely control bidding

Theory: Multiple ads (variants/ASINs) in same ad group share keyword pool but have independent bids
Operation: Add multiple variants in same ad group (different colors, sizes), set different bids for each ad
Applicable: Products with multiple variants, significant sales differences between variants
Pros: Shared data, high optimization efficiency
Cons: Best-selling variant monopolizes exposure, other variants struggle to get traffic

Theory: Set up different ad groups based on keyword match types (broad/phrase/exact)
Operation: Ad Group A (Broad) + Ad Group B (Phrase) + Ad Group C (Exact), same keywords different match types
Applicable: Products with clear core keywords, need refined control
Pros: Precise control of each match type budget, easy to analyze keyword performance
Cons: Complex management, requires regular optimization

Theory: Set up multiple ad groups for the same product with different budgets and bidding strategies
Operation: Ad Group A (Auto bidding, $30 budget) + Ad Group B (Manual exact, $40 budget) + Ad Group C (Long-tail, $20 budget)
Applicable: Products with certain sales base, need refined budget allocation
Pros: Risk diversification, independent optimization per group, clear ROI tracking
Cons: Initial data scattered, need sufficient data to support decisions

Theory: Each product/variant has its own ad group with independent bid and budget control
Operation: Ad Group A (Black variant, $1.5 bid) + Ad Group B (White variant, $1.2 bid) + Ad Group C (Blue variant, $1.8 bid)
Applicable: Multi-variant products, large differences in profit or conversion rate between variants
Pros: Complete independent control, avoid internal competition, maximize each variant potential
Cons: Data scattered, high management cost

Theory: Use Campaign Budget Optimization feature to automatically allocate budget to better-performing ad groups
Operation: Set up multiple ad groups, give better-performing groups higher bids, let system auto-allocate budget
Applicable: Mature products, multi-ad group operations, need automated optimization
Pros: System intelligently allocates budget, reduces manual intervention, improves overall ROI
Cons: Need sufficient data accumulation, unstable during system learning period

Theory: Set tiered bids for different keywords based on conversion data
Operation: High-converting keywords (ACoS<15%): Raise bid 20% → Medium-converting (ACoS 15-25%): Keep status → Low-converting (ACoS>25%): Lower bid 30% or pause
Applicable: Ads running over 30 days, mature products with sufficient data
Pros: Optimized resource allocation, maximized ROAS
Cons: Requires regular analysis, high data sensitivity requirement

Theory: Use Sponsored Display or Product Targeting to target competitor product pages
Operation: Create competitor targeting ad group, select 10-20 relevant competitor ASINs, set bid at 80% of regular price to attract traffic
Applicable: Products with differentiation advantages, need to expand traffic sources
Pros: Proactively capture competitor traffic, reduce reliance on search keywords
Cons: Conversion rate usually lower than search ads, need continuous landing page optimization

Mistake: Put multiple products in same ad group with identical keywords, best-seller monopolizes exposure.
Result: Best-selling ASIN gets 90% exposure, other ASINs get almost no traffic, ad effectiveness unbalanced.
Lesson: Multi-variant products should have separate ad groups, or use "Bid Adjustment" feature to differentiate exposure.

Mistake: Stuff 100+ keywords into one ad group without distinguishing match types or bids.
Result: High-competition keywords raise average bid, low-competition keywords get no exposure, ACoS out of control.
Lesson: Group keywords by management, keep core keywords in separate groups, aggregate long-tail keywords.

Strategy: In auto campaigns, negate your own brand keywords to avoid wasting ad spend on traffic you already rank for organically.
Operation: Add brand keywords as exact match negatives in auto campaigns.
Result: Auto campaign ACoS dropped from 35% to 22%, saving 30% in ad spend.
Applicable: Brand Registry sellers with good organic rankings.

Strategy: Manual campaigns target competitor keywords while auto campaigns negate converted competitor terms to prevent ad cannibalization.
Operation: Manual ads target competitor keywords, auto ads add high-converting competitor terms as negatives.
Result: Clearer ad structure, ACoS reduced by 12%, avoiding multiple touchpoints for same user.
Applicable: Sellers running both manual and auto campaigns.

Strategy: Negate irrelevant ASINs from auto campaigns, then use them as manual targeting.
Operation: Analyze auto campaign reports, negate irrelevant ASINs, then create separate ASIN targeting campaigns.
Result: Precisely reach target competitor traffic, conversion rate increased 25%.
Applicable: Sellers with sufficient auto campaign data needing refined operations.

Strategy: Set negatives at Campaign and Ad Group levels respectively for refined management.
Operation: Campaign level negate brand keywords (general), Ad Group level negate specific irrelevant terms (specific).
Result: Clearer ad structure, negative keyword management efficiency improved 50%.
Applicable: Multi-ad group operators with some management experience.

Strategy: Before peak seasons, proactively negate seasonal terms irrelevant to your products to avoid invalid clicks.
Operation: Analyze last year's peak season data, add seasonal-related negatives 1 month in advance.
Result: Peak season ACoS controlled below 25%, 8 percentage points lower than competitors.
Applicable: Seasonal products, holiday gift sellers.

Strategy: In multi-variant products, negate non-main variants in main variant ads to concentrate budget.
Operation: Main push black variant, negate black ASIN in white variant ad group.
Result: Main variant ad spend concentrated, ACoS dropped to 18%, single item sales increased 3x.
Applicable: Multi-variant products with clear main push items.

Mistake: To lower ACoS, added too many keywords as negatives, including potentially high-converting terms.
Result: Ad impressions dropped 80%, although ACoS dropped to 15%, total orders severely declined.
Lesson: Negatives should focus on clearly invalid search terms, don't over-optimize.

Mistake: Added lots of negatives just 3 days after launching ads, blocking normal keyword expansion.
Result: After learning period, couldn't expand quality search terms, missed potential traffic.
Lesson: New campaigns should run at least 14 days before adding negatives to let system fully learn.

Strategy: Establish regular negative keyword optimization mechanism: analyze weekly, clean monthly, review quarterly.
Operation: Weekly add low-quality negatives → Monthly check for false negatives → Quarterly review negative keyword performance.
Result: Continuous ad optimization, ACoS stable at 20-25%, ad efficiency improved 40%.
Applicable: All sellers to establish long-term optimization habits.

Strategy: Choose appropriate negative type based on invalid keyword characteristics.
Operation: Phrase negate "iphone case" excludes all searches containing iphone case; exact negate only excludes exact matches.
Result: Phrase negatives more efficient, reducing negative keyword count by 80%, ACoS lowered by 10%.
Applicable: Sellers needing efficient management of large number of negative keywords.

Mistake: Set $5/day budget expecting large orders with minimal investment.
Consequence: Budget exhausted by noon, keywords lose exposure for rest of day.
Correct: Set budget based on keyword average CPC to ensure 24-hour effective display.

Mistake: Think auto ads are enough, only rely on Amazon's system matching.
Consequence: Traffic sources imprecise, spending on irrelevant search terms, ACoS stays high.
Correct: Auto ads for keyword discovery, manual ads for refined targeting, combine both.

Mistake: No data analysis, set all keywords at $1 or randomly set high/low bids.
Consequence: High-competition keywords get no exposure, low-competition keywords waste money.
Correct: Calculate reasonable bid range based on keyword competition, conversion rate, product margin.

Mistake: Think head terms have more traffic, only bid on generic terms like "phone case".
Consequence: Head terms highly competitive, CPC $2-3, ACoS hard to control. Long-tail keywords wasted.
Correct: Combine head terms + long-tail keywords, long-tail as profit source.

Mistake: Put 5 unrelated products in same ad group sharing keyword pool.
Consequence: Best-seller monopolizes exposure, other products get nothing, data messy.
Correct: Each product in separate ad group, or group by relevance for clear data.

Mistake: New products use "Dynamic Bidding - Down Only", new ads get zero exposure.
Consequence: Amazon thinks ad performance is poor, further reduces exposure, vicious cycle.
Correct: New products use "Dynamic Bidding - Up and Down" or "Fixed Bidding", adjust after data accumulation.

Mistake: Think top position converts best, raise bids 3x cost to capture #1 spot.
Consequence: ACoS soars above 80%, lose money on every sale, budget exhausted quickly.
Correct: Calculate reasonable bid range, positions 2-4 often have best ROI.

Mistake: Never check search term reports, never add any negative keywords.
Consequence: Ads spend on irrelevant searches like "free", "tutorial", "used" etc.
Correct: Analyze search term reports weekly, add low-quality terms as negatives promptly.

Mistake: Negate any irrelevant search terms including potentially high-converting ones.
Consequence: Impressions drop sharply, traffic cliff, miss potential customers.
Correct: Focus negatives on clearly invalid terms, avoid false negatives, give ads learning time.

Mistake: Immediately pause ads when ACoS hits 30%, think ads are losing money.
Consequence: Lose ad traffic, organic ranking drops, total sales decline, overall profit decreases.
Correct: Consider long-term value like organic ranking boost, keyword market share growth.

Mistake: Only focus on ACoS, think high ACoS means losing money.
Consequence: Ignore overall sales growth and brand exposure value from ads.
Correct: Comprehensive analysis of ACoS, ROAS, ad order ratio, organic ranking improvement.

Mistake: Launch ads with messy title, blurry images, incomplete bullet points.
Consequence: Traffic comes in but conversion extremely low, waste lots of ad spend.
Correct: Optimize listing first (title, images, description, reviews), then run ads.

Mistake: Start advertising product with 0 reviews expecting ads to bring sales and reviews.
Consequence: Buyers see 0 reviews and won't buy, conversion extremely low, wasted clicks.
Correct: Accumulate at least 10-20 real reviews before running ads, or use Vine program.

Mistake: Set same bid for $20 product and $50 product in same ad group.
Consequence: Higher-priced product has better margin but lacks exposure, lower-priced product overbid.
Correct: Set bids independently based on product profit margin, higher-margin products can have higher bids.

Mistake: Don't monitor competitor bidding and strategy changes, keep your bids unchanged.
Consequence: When competitors raise bids, your ad position continuously drops, traffic stolen.
Correct: Regularly monitor competitor dynamics and keyword bid changes, adjust strategy timely.

Mistake: Enable broad match without monitoring search term reports, let ads match to irrelevant terms.
Consequence: Ads match to "how to", "tutorial", "repair" completely irrelevant searches, severe waste.
Correct: Broad match must include daily search term monitoring, add negatives promptly.

Mistake: Think promotion traffic is sufficient, proactively lower ad budget to save money.
Consequence: Promotions are peak buyer activity time, lowering ads means giving up traffic opportunity.
Correct: Raise budget before promotion, pre-warm; maintain or increase during promotion to capture traffic.

Mistake: Think auto bidding is "fully automatic", no need to care about what search terms match.
Consequence: Amazon may match ads to completely irrelevant searches, ad spend wasted.
Correct: Auto bidding is just a targeting method, still need regular search term report checks and negative optimization.

Mistake: Run ads 3-5 days then judge poor performance and pause, or frequently change strategy.
Consequence: Amazon ads need learning period, 3-5 days data insufficient, frequent changes affect system learning.
Correct: New ads run at least 14-30 days before judging, optimize based on data.

Mistake: Completely rely on ads for traffic, don't care about organic ranking optimization.
Consequence: Sales drop to zero when ads stop, high ad dependency, long-term profit extremely low.
Correct: Both ads + organic ranking, use ads to boost sales and improve organic ranking, reduce ad dependency.