# PPC Analytics {% hint style="info" %} **Difficulty:** ๐Ÿ”ด Advanced ยท **Reading time:** \~15 min {% endhint %} {% hint style="success" icon="rocket" %} **Open this page in your dashboard:** [**Go to PPC Analytics \[BETA\] โ†’**](https://dashboard.sellermagnet.com/ppc/analytics) {% endhint %} {% hint style="warning" icon="triangle-exclamation" %} **BETA:** The PPC Manager is currently in beta. Some features may behave unexpectedly or change based on user feedback. Please report any issues at . {% endhint %} ## ๐Ÿ“‹ Overview The **PPC Analytics** page is your central hub for understanding how your Amazon advertising campaigns are performing. It combines **8 key KPIs**, **interactive charts**, and **detailed data tables** to give you a complete picture, from high-level trends to individual keyword performance. Whether you want to know which keywords are burning cash, which products deliver the best return on ad spend, or what time of day your ads convert best, the Analytics page surfaces all of this in a single view, no spreadsheets required. *** ## ๐Ÿ“Š Key Performance Indicators > **Quick Benchmark for Beginners:** ACoS under 30% = likely profitable. CTR above 0.5% = strong ads. CVR above 10% = good listings. Focus on these three metrics first, the rest comes with experience. At the top of the page, **8 KPI cards** provide an at-a-glance summary for the selected period: | KPI | Description | What "Good" Looks Like | | --------------- | ------------------------------------------------ | ----------------------------------------------------- | | **Impressions** | Total number of times your ads were shown | Trending upward indicates growing visibility | | **Clicks** | Total clicks received across all campaigns | Steady growth with a healthy CTR | | **Spend** | Total advertising spend in your account currency | Controlled growth aligned with sales | | **Sales** | Total attributed sales from advertising | Should grow faster than spend | | **ACoS** | Advertising Cost of Sale (Spend / Sales x 100) | Below your break-even ACoS | | **CTR** | Click-Through Rate (Clicks / Impressions x 100) | 0.3% - 0.5% for SP is typical; above 0.5% is strong | | **CVR** | Conversion Rate (Orders / Clicks x 100) | 10% - 15% is solid for most categories | | **CPC** | Cost Per Click (Spend / Clicks) | Depends on niche; lower is better if CVR stays stable | ### How to Read KPI Cards Each card displays: 1. **The metric value** for the selected date range 2. **A trend arrow** (up/down) compared to the previous equivalent period 3. **A percentage change** showing growth or decline > **Pro Tip:** Focus on **ACoS and CVR first**. These two metrics together tell you whether your advertising is profitable (ACoS) and whether your listings are converting traffic into sales (CVR). Impressions and clicks are vanity metrics if they do not lead to conversions. {% hint style="warning" %} **Common Confusion:** A "red" ACoS arrow pointing down is actually *positive*, it means your advertising cost of sale decreased. Conversely, a "green" Sales arrow pointing up is good. Always check the direction in context of what each metric means. {% endhint %} ### Understanding Your Break-Even ACoS Before you can judge whether your ACoS is "good" or "bad," you need to know your **break-even ACoS**, the point at which your ad spend exactly equals your profit margin. **Formula:** ``` Break-Even ACoS = (Product Price - Product Cost - Amazon Fees) / Product Price x 100 ``` **Example:** You sell a yoga mat on Amazon DE for EUR 29.99. Your landed cost is EUR 8.00 and Amazon fees (referral + FBA) are EUR 11.00. ``` Break-Even ACoS = (29.99 - 8.00 - 11.00) / 29.99 x 100 = 36.6% ``` Any ACoS below 36.6% means your ads are profitable. Any ACoS above 36.6% means you are losing money on each ad-driven sale. > **Target ACoS vs. Break-Even ACoS:** Your target ACoS should be *below* your break-even ACoS. How far below depends on your goals. For maximum profit, set it 10-15 points below break-even. For aggressive growth (prioritizing market share), you might accept break-even or slightly above. *** ## Performance Trend Chart ![SellerMagnet PPC Analytics](/files/GZsmDoYjZAhP3aD3jwCH) A dynamic multi-metric chart that lets you switch between **6 views**: | View | Chart Type | Metrics Displayed | When to Use | | ------------------------ | ---------------- | ---------------------------------- | ---------------------------------------------------------- | | **Spend vs Sales** | Dual-line area | Spend (red) and Sales (green) | Daily profitability check, are sales outpacing spend? | | **ACoS Trend** | Single line | ACoS percentage over time (orange) | Track optimization progress over weeks/months | | **Impressions & Clicks** | Bar + line combo | Impressions (bar) + Clicks (line) | Monitor visibility and engagement trends | | **CTR & CVR** | Dual line | CTR and CVR percentages | Diagnose listing or targeting issues | | **CPC Trend** | Single line | Cost Per Click over time | Monitor bid competitiveness and market conditions | | **Orders Trend** | Bar chart | Daily/weekly order volume | Correlate with promotions, seasonality, or external events | Switch between views using the **toggle buttons** above the chart. The chart updates instantly without page reload. ### How to Read the Trend Chart Effectively > **Pro Tip:** Set the date range to **Last 30 days** and switch to the **ACoS Trend** view. A steadily declining ACoS line means your optimizations are working. If ACoS is flat or rising, it is time to review your keyword bids and search term quality. #### Example: Diagnosing a Sudden ACoS Spike You notice your ACoS jumped from 22% to 38% on a single day. Here is how to investigate: {% stepper %} {% step %} #### Switch to Spend vs Sales view **Switch to Spend vs Sales view:** Did spend spike or did sales drop? {% endstep %} {% step %} #### Switch to CPC Trend **Switch to CPC Trend:** Did your cost per click increase (more competition)? {% endstep %} {% step %} #### Switch to CTR & CVR **Switch to CTR & CVR:** Did conversion rate drop (listing issue or irrelevant traffic)? {% endstep %} {% step %} #### Check the Keyword Performance Table **Check the Keyword Performance Table** below the chart. Sort by ACoS descending to find the cause keywords {% endstep %} {% step %} #### Cross-reference with Search Terms **Cross-reference with Search Terms** page. Were there new, irrelevant search terms consuming budget? {% endstep %} {% endstepper %} *** ## Placement Performance Understand where your ads are performing best with a **placement breakdown**: * **Pie chart:** Visual distribution of spend/sales across placements * **Data table:** Detailed metrics per placement: * Placement name (Top of Search, Product Pages, Rest of Search) * Impressions, Clicks, Spend, Sales, ACoS > Use placement data to decide where to increase or decrease **placement bid adjustments** in your campaign settings. ### Placement Comparison Guide | Placement | Typical Behavior | Optimization Strategy | | ------------------ | ------------------------------------------------ | ---------------------------------------------------------------------------- | | **Top of Search** | Highest CTR, highest CPC, often best CVR | Increase bid adjustment if ACoS is below target, this is premium real estate | | **Product Pages** | Lower CPC, variable CVR depending on product fit | Good for brand defense and cross-selling; watch ACoS closely | | **Rest of Search** | Lowest CPC, lowest CTR, mixed CVR | Use as a volume play; reduce bids if ACoS is high | #### Example: Optimizing Placement Bids You sell premium stainless steel water bottles on Amazon DE. Your placement data shows: | Placement | Spend | Sales | ACoS | | -------------- | ------- | --------- | ----- | | Top of Search | EUR 450 | EUR 2,100 | 21.4% | | Product Pages | EUR 280 | EUR 620 | 45.2% | | Rest of Search | EUR 170 | EUR 410 | 41.5% | **Action:** Top of Search is performing well below your 30% ACoS target, consider increasing the Top of Search placement bid adjustment by 25-50% to capture more of this high-converting traffic. For Product Pages, investigate which competitor product pages are showing your ads and whether those placements are relevant. > **Pro Tip:** Top of Search placements typically convert 2-3x better than other placements for branded and high-intent keywords. If your Top of Search ACoS is strong, increasing the bid adjustment here is one of the fastest ways to scale profitable ad spend. *** ## Hourly Performance Heatmap (Dayparting) A **7x24 grid heatmap** visualizing performance by **day of week** and **hour of day**: * Switch between 6 metrics: **Sales**, **Clicks**, **Spend**, **Impressions**, **ACoS**, **CPC** * Color intensity indicates performance level (darker = higher value) * Identify your **best-performing hours** to optimize ad scheduling This is especially useful for **dayparting strategies**, shifting budget toward your highest-converting time slots. ### How to Use the Heatmap for Dayparting {% stepper %} {% step %} #### Select "Sales" as the metric **Select "Sales" as the metric** to see when customers are buying {% endstep %} {% step %} #### Select "ACoS" as the metric **Select "ACoS" as the metric** to see when your ads are most cost-efficient (look for lighter/lower areas) {% endstep %} {% step %} #### Compare the two **Compare the two:** the best time slots have high sales AND low ACoS {% endstep %} {% step %} #### Create Bid Rules **Create Bid Rules** based on your findings, for example, increase bids by 20% during your top-converting hours {% endstep %} {% endstepper %} #### Example: Dayparting for a German Marketplace Seller You sell kitchen accessories on Amazon DE. Your heatmap reveals: * **Peak Sales Hours:** Monday-Friday, 19:00-22:00 (after work) and Sunday 10:00-14:00 (weekend browsing) * **Lowest ACoS:** Tuesday and Wednesday evenings (19:00-21:00): ACoS of 18% vs. your average of 26% * **Highest ACoS:** Saturday 02:00-06:00: ACoS of 55% (low-intent late-night clicks) **Action:** Create a bid rule that increases bids by 15% during Tuesday-Wednesday evenings and decreases bids by 25% during Saturday early morning hours. This alone could lower your overall ACoS by 3-5 percentage points. {% hint style="warning" %} **Important:** Amazon does not natively support dayparting (time-based bidding). SellerMagnet's Bid Rules feature allows you to simulate dayparting by adjusting bids on a schedule. However, bid changes take effect with a slight delay, so use broad time windows (2-3 hour blocks) rather than trying to optimize by individual hour. {% endhint %} *** ## Keyword Performance Table Drill into individual keyword metrics with a **fully sortable and paginated table**: | Column | Description | | --------------- | --------------------------- | | **Keyword** | The keyword text | | **Match Type** | Broad, Phrase, or Exact | | **Impressions** | Number of ad impressions | | **Clicks** | Number of clicks received | | **Spend** | Total spend on this keyword | | **Sales** | Attributed sales | | **ACoS** | Advertising Cost of Sale | | **CTR** | Click-Through Rate | | **CVR** | Conversion Rate | | **CPC** | Cost Per Click | **Sorting options:** Sales, Clicks, ACoS, Spend (ascending/descending) Metrics are **color-coded** for quick scanning: * Green = Good performance (below target ACoS, strong CVR) * Yellow = Needs attention (approaching target ACoS threshold) * Red = Poor performance (above target ACoS, low CVR, high spend) ### Keyword Analysis Workflow Here is a structured approach to reviewing your keyword performance: **Step 1: Find Your Winners** Sort by **Sales descending** to see your highest-revenue keywords. These are the keywords driving your business. Ensure their bids are competitive and their ACoS is within target. **Step 2: Find Your Losers** Sort by **Spend descending**, then scan for keywords with high spend but zero or very low sales. These are burning your budget. Consider lowering bids or adding them as negatives if they are clearly irrelevant. **Step 3: Find Hidden Opportunities** Sort by **CVR descending** to find keywords with strong conversion rates but low impressions. These keywords convert well but may not be getting enough traffic. Consider increasing bids to win more auctions. **Step 4: Check Match Type Distribution** Filter by match type to compare Broad vs. Phrase vs. Exact performance. Typically, Exact match keywords have the lowest ACoS but also the lowest volume, while Broad match drives the most impressions but at a higher ACoS. > **Pro Tip:** Export the keyword table and sort by `Spend` descending. The top 20% of keywords by spend typically account for 80% of your total ad spend. Focus your optimization efforts on these high-impact keywords first, small ACoS improvements on high-spend keywords translate into significant savings. #### Example: Keyword Optimization Decision Matrix | Scenario | Clicks | Sales | ACoS | Action | | --------------------------------- | ------ | -------- | -------- | ------------------------------------------------------------------------ | | High clicks, high sales, low ACoS | 200+ | EUR 500+ | < 20% | Increase bid to capture more volume | | High clicks, low sales, high ACoS | 200+ | < EUR 50 | > 40% | Lower bid by 20-30% or check listing relevance | | Low clicks, high CVR, low ACoS | < 30 | EUR 100+ | < 15% | Increase bid significantly, this is a hidden gem | | High spend, zero sales | 50+ | EUR 0 | Infinite | Add as negative keyword or pause | | Low impressions, 0 clicks | < 100 | EUR 0 | N/A | Increase bid to test; if still no impressions, keyword may be irrelevant | *** ## Product Performance Table See how individual products perform in your ads: | Column | Description | | --------------- | --------------------------------------------------------------------- | | **Product** | Product image, name, and ASIN (Amazon Standard Identification Number) | | **Marketplace** | Country flag indicator | | **Impressions** | Ad impressions for this product | | **Clicks** | Clicks received | | **Spend** | Advertising spend | | **Sales** | Attributed sales | | **ACoS** | Advertising Cost of Sale | | **ROAS** | Return on Ad Spend (Sales / Spend) | | **CTR** | Click-Through Rate | | **CVR** | Conversion Rate | | **Orders** | Number of attributed orders | ### How to Use the Product Table {% hint style="info" icon="lightbulb" %} **Pro Tip:** Sort the product table by **ROAS descending** to find your most advertising-efficient products. These products earn the most revenue per euro spent on ads. Consider allocating more budget to campaigns promoting these high-ROAS products. {% endhint %} #### Example: Product-Level Budget Allocation You sell five products on Amazon UK. Here is your product performance: | Product | Spend | Sales | ACoS | ROAS | Action | | -------------------------- | ------- | ------- | ----- | ----- | ------------------------------------------- | | Premium Phone Case (Black) | GBP 120 | GBP 680 | 17.6% | 5.67x | Increase budget: top performer | | Premium Phone Case (Blue) | GBP 95 | GBP 310 | 30.6% | 3.26x | Maintain: acceptable ACoS | | Screen Protector 2-Pack | GBP 200 | GBP 220 | 90.9% | 1.10x | Reduce budget: nearly unprofitable | | Charging Cable (1m) | GBP 60 | GBP 0 | N/A | 0x | Pause ads: listing needs work first | | Phone Stand | GBP 45 | GBP 185 | 24.3% | 4.11x | Increase budget: strong ROAS with low spend | {% hint style="warning" %} **Do Not Just Pause Low-Performing Products.** Before cutting ad spend on a product, check if the listing itself is the problem. A product with high clicks but zero sales may need better images, pricing, or bullet points, not fewer ads. Fix the listing first, then re-evaluate ad performance. {% endhint %} *** ## ๐Ÿ” Filters | Filter | Options | Default | | ----------------- | --------------------------------------------------------------------------- | ------------ | | **Date Range** | Last 7, 14, 30, 60, or 90 days | Last 30 days | | **Campaign** | All Campaigns, or select a specific campaign | All | | **Marketplace** | All Marketplaces, or select a specific profile | All | | **Campaign Type** | All, SP (Sponsored Products), SB (Sponsored Brands), SD (Sponsored Display) | All | ### Filter Best Practices {% hint style="info" %} **When to use each date range:** * **Last 7 days:** Quick pulse check; useful after a bid change to see early results * **Last 14 days:** Good for A/B comparisons (this week vs. last week) * **Last 30 days:** Standard analysis window; most statistically reliable * **Last 60/90 days:** Trend analysis and seasonal pattern detection {% endhint %} {% hint style="warning" %} **Marketplace Filter Warning:** When viewing "All Marketplaces," currency values are displayed in each marketplace's native currency and aggregated. This means EUR (DE), GBP (UK), and USD (US) values are summed without conversion. For accurate financial analysis, always filter to a single marketplace. {% endhint %} *** ## ๐Ÿ“ค Export Click the **Export** button to download a CSV file containing all keyword and product performance data for the selected filters and date range. The exported file includes all columns visible in the data tables, plus additional metadata: * Campaign name and ID * Ad group name and ID * Targeting type * Bid amount at time of export > **Pro Tip:** Set up a monthly export routine. Download your keyword and product data on the first day of each month for the previous 30 days. Over time, this builds a historical dataset that is invaluable for year-over-year comparisons, seasonal planning, and tracking long-term optimization progress. *** ## ๐Ÿ”„ Before & After: Analytics-Driven Optimization Here is an example of what data-driven decision-making looks like in practice: ### Before: Managing PPC Without Analytics A seller running phone accessories on Amazon DE manages campaigns by checking Seller Central once a week. They adjust bids based on gut feeling and pause keywords that "feel" too expensive. | Metric | Value | | ------------------------------- | ---------------------- | | Monthly Ad Spend | EUR 1,200 | | Monthly Ad Sales | EUR 3,100 | | ACoS | 38.7% | | Wasted Spend (0-order keywords) | EUR 340 (28% of total) | | Top-Converting Hours Identified | None | | Keywords Actively Monitored | \~30 (top of mind) | ### After: 30 Days Using PPC Analytics The same seller now reviews the Analytics dashboard three times per week, uses the keyword performance table to cut wasteful spend, and applies dayparting insights from the heatmap. | Metric | Value | Change | | ------------------------------- | ---------------------- | ------------- | | Monthly Ad Spend | EUR 980 | -18% | | Monthly Ad Sales | EUR 3,450 | +11% | | ACoS | 28.4% | -10.3 points | | Wasted Spend (0-order keywords) | EUR 85 (8.7% of total) | -75% | | Top-Converting Hours Identified | 6 time slots | From zero | | Keywords Actively Monitored | All 280+ | Full coverage | {% hint style="success" %} **The Result:** By spending less money and earning more sales, this seller increased their advertising profit by over EUR 500/month, and reduced the time spent managing PPC from 4 hours/week to under 1 hour. {% endhint %} ***
โš ๏ธ Common Mistakes to Avoid {% hint style="danger" %} * **Mistake 1: Obsessing Over Daily ACoS Fluctuations** ACoS can swing wildly on any given day due to Amazon's attribution window, low sample sizes, or a single high-value order. Always evaluate ACoS over at least a 7-day window, and ideally 14-30 days, before making optimization decisions. * **Mistake 2: Ignoring Low-Impression Keywords** Keywords with very few impressions (under 100) are often overlooked, but they can be signals. If a keyword has 50 impressions, 3 clicks, and 2 orders, it has a 66% CVR, that is a keyword worth investing in. Sort by CVR to find these hidden gems. * **Mistake 3: Not Filtering by Marketplace** Aggregated data across marketplaces hides important differences. A keyword might have 15% ACoS on Amazon DE but 55% ACoS on Amazon FR. If you only look at the blended number (30%), you miss the fact that FR is dragging your profitability down. * **Mistake 4: Treating All Campaign Types the Same** Sponsored Products, Sponsored Brands, and Sponsored Display have fundamentally different purposes and benchmarks. SP is typically for direct-response sales, SB builds brand awareness, and SD targets audiences. Filter by campaign type when setting expectations and making comparisons. * **Mistake 5: Reacting to a Single Day of Data** If your CPC doubled on a Tuesday, do not panic and slash all bids on Wednesday. Check if it was an outlier (marketplace event, competitor spike, Amazon glitch). Wait 3-5 days to confirm a trend before making structural changes. {% endhint %}
\## ๐Ÿ”ง Troubleshooting ### "My Analytics page shows no data" {% stepper %} {% step %} #### Check connection status **Check connection status:** Go to PPC --> Settings and verify your Amazon Ads account is connected {% endstep %} {% step %} #### Check sync status **Check sync status:** Look for the sync indicator at the top of the page. If it shows "Syncing," wait for it to complete {% endstep %} {% step %} #### Check date range **Check date range:** Ensure the selected date range covers a period when you had active campaigns {% endstep %} {% step %} #### Check filters **Check filters:** Reset all filters to "All" to rule out overly restrictive filtering {% endstep %} {% endstepper %} ### "My KPI numbers don't match Seller Central" * Amazon Advertising reports data with a delay of up to 12-24 hours * Conversions are attributed based on a 7-day (for SP) or 14-day (for SB/SD) attribution window * SellerMagnet shows data based on the last successful sync: click **Sync Now** and compare again ### "The heatmap looks empty or has very light colors" * The heatmap requires at least 14 days of data to show meaningful patterns * If you have very low traffic (fewer than 10 clicks/day), the heatmap may not show clear patterns, increase your date range to 60 or 90 days ### "Keywords are missing from the table" * Keywords with zero impressions in the selected date range are hidden by default * Newly added keywords may not appear until the next sync cycle * Check that your campaign and marketplace filters are not excluding the campaigns containing those keywords *** ## Template: Weekly Analytics Review Checklist Use this checklist every week to stay on top of your PPC performance: ``` Weekly PPC Analytics Review: [Date] ===================================== 1. [ ] Review 8 KPI cards: any significant changes from last week? 2. [ ] Check Spend vs Sales trend: is the gap widening or narrowing? 3. [ ] Review ACoS trend: trending down (good) or up (investigate)? 4. [ ] Sort keywords by Spend descending: top 10 keywords still on target? 5. [ ] Sort keywords by ACoS descending: any keywords above 2x your target ACoS? 6. [ ] Check product performance: any product with ROAS below 1.5x? 7. [ ] Review placement data: Top of Search still outperforming? 8. [ ] Glance at heatmap: any new patterns emerging? 9. [ ] Export data for monthly archive (first week of month only) 10. [ ] Note 2-3 action items for next week: - Action 1: _______________ - Action 2: _______________ - Action 3: _______________ ``` > **Pro Tip:** This review should take 15-20 minutes once you are familiar with the dashboard. Consistency beats intensity, a brief weekly review is far more effective than an exhaustive monthly deep-dive. *** ## โ“ FAQ
What attribution model does Amazon use for ad sales? Amazon uses a last-click attribution model with a 7-day window for Sponsored Products and a 14-day window for Sponsored Brands and Sponsored Display. This means a sale is attributed to an ad click if the purchase happens within that window, regardless of whether the customer clicked other ads in between.
Why is my CVR showing 0% even though I have sales? CVR is calculated as Orders / Clicks. If you have very few clicks (e.g., 2 clicks and 1 order = 50% CVR), the number may appear as 0% due to rounding in some views. Increase the date range to accumulate more data.
Can I see data for campaigns that are currently paused? Yes. The Analytics page shows historical performance data for all campaigns, including paused and archived ones, as long as the selected date range includes a period when those campaigns were active.
How often is the data updated? Data freshness depends on your sync schedule (configurable in Settings). The default is daily. For near-real-time data, set the sync schedule to hourly.
What is the difference between ACoS and ROAS? ACoS (Advertising Cost of Sale) = Spend / Sales x 100. ROAS (Return on Ad Spend) = Sales / Spend. They are inverse measures of the same thing. An ACoS of 25% equals a ROAS of 4x. Lower ACoS is better; higher ROAS is better.
Why do my keyword-level sales not add up to my total campaign sales? Amazon does not attribute all sales at the keyword level. Some sales (especially for auto campaigns) may be attributed at the campaign or ad group level but not to a specific keyword. The "total" in the KPI cards reflects all attributed sales.
Can I compare two date ranges side by side? Not directly in the current version. However, you can export data for two different date ranges and compare them in a spreadsheet. We recommend keeping monthly exports for this purpose.
Does the heatmap account for time zones? Yes. The heatmap displays data in the **marketplace's local time zone** (e.g., CET for Amazon DE, GMT for Amazon UK, PST for Amazon US). This means the hours shown match when customers in that marketplace are actually active.
*** ## โžก๏ธ What's Next? {% content-ref url="/pages/EYVZo8o8rsyLvj6QVN1J" %} [PPC Search Terms](/ppc-management-beta/ppc-manager-overview/ppc-search-terms.md) {% endcontent-ref %} {% content-ref url="/pages/5gaYA3QhcKl8Rx0EmNCL" %} [PPC Keyword Research](/ppc-management-beta/ppc-manager-overview/ppc-keyword-research.md) {% endcontent-ref %} --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.sellermagnet.com/ppc-management-beta/ppc-manager-overview/ppc-analytics.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.