By The AdLabs Team
Why Reporting Is the #1 Skill
If you asked us to name the single most impactful skill for Amazon PPC success, the answer would probably be bidding strategy, but there is a close second. Reporting & analytics.
Not just reading numbers — anyone can open the ad console and recite that ACOS went up 5%. The skill is understanding the context behind those numbers, telling a story based on the trends, and turning that story into action items that actually move the business forward.
Reporting is a foundational and extremely important aspect to becoming a highly proficient Amazon advertiser. You have to be able to combine, manipulate, and interpret your performance data to answer key strategic questions and properly navigate your business strategically.
This guide covers everything: the reports Amazon gives you, the tools to manipulate them, the frameworks to interpret them, and the systems to present them. We're drawing from years of managing hundreds of Amazon advertising accounts and building the reporting infrastructure that makes that possible.
Whether you're a solo seller, a freelance manager, or an agency team — this guide will transform how you work with Amazon PPC data.
The Reporting Mindset
The Three-Step Analytics Framework
Every great reporting workflow follows three steps. Miss any one of them, and your reporting falls apart.
- Pull the right metrics together. Know which reports exist, how the data is formatted, and how to combine sources to answer the question at hand.
- Craft a story that explains what's happening and why. Context is everything. Sales being flat could be catastrophic (middle of Prime Day) or phenomenal (week after Prime Day in a declining market).
- Turn that story into action items. This is where most people fail. They can see that ACOS rose, they can even explain why — but they don't deliver a clear recommendation for what to do next.
If you have an advertiser who can figure out what's happening AND figure out what to do about it — that's what makes a rockstar. Most people can do one or the other. The combination is rare and extremely valuable.
The Five Golden Metrics
Regardless of which report you're in, there are five core metrics you should always pull first. Everything else is calculated from these:
From these, you can derive: CTR, CPC, CVR, ACOS, ROAS
Always start with the raw ingredients. Don't jump to calculated metrics first — start with the five golden metrics, then derive the rest. This prevents you from misinterpreting aggregated, calculated metrics.
The Growth Decomposition Formula
When someone asks "why are sales up?" or "why are sales down?" — decompose:
In Amazon terms: Sessions × Unit Session % × Average Selling Price
There are only three levers that move sales. Everything else rolls up into one of these. If sales are down, it's always one (or a combination) of these three things. Your job as an analyst is to figure out which one changed and why.
Critically Thinking Through Metrics
CTR tells you how good of a first impression your product makes when it appears in search results or on product pages. A high CTR means your main image, price, reviews, and title are winning attention. A low one means they're not.
Why CTR changes:
- Placement shifts — If more impressions come from product detail pages (lower CTR naturally) vs. top of search (higher CTR), overall CTR changes even if nothing about your product changed.
- Main image quality — The single biggest controllable factor. A/B test your images relentlessly.
- Price competitiveness — If competitors run lightning deals, your CTR may temporarily drop.
- Competition — A new entrant with a more eye-catching listing can steal clicks without you doing anything wrong.
- Keyword relevance — Broader keywords = lower CTR because the search intent is less specific.
Before blaming your creative, check your placement data. CTR dropping might just mean more of your impressions shifted to product pages (which always have lower CTR) — not that your main image got worse.
Conversion rate is how good your product is at closing the deal after someone clicks through. It's the metric that determines whether traffic turns into revenue.
Why CVR changes:
- Funnel stage of traffic — Bottom-of-funnel keywords (specific, purchase-intent) convert at 15-30%. Top-of-funnel (browsing, research) might convert at 2-5%. If your traffic mix changes, CVR changes.
- Brand vs. non-brand mix — Branded search converts dramatically higher. If branded traffic dips, overall CVR drops even though nothing on your listing changed.
- Product strength — Price, reviews, image quality, A+ content, bullet points. These form the core conversion rate for your product.
- Competitor actions — Deals, coupons, new entrants undercutting on price.
- Macro trends — Seasonal shifts, economic conditions, post-Prime Day hangover.
Your actual CPC is determined by three overlapping factors:
Amazon uses second-price auction: you pay $0.01 more than the next highest bidder
- Your max bid — including placement modifiers and dynamic bidding settings
- Market price — what competitors are willing to pay (the second-price auction)
- Quality score — how relevant Amazon deems your product for that keyword. Less relevant = Amazon charges a premium.
ACOS and ROAS are outputs, not inputs. They are the result of your CPC and your conversion rate (or Revenue per Click). There are only two ways to improve ACOS:
- Lower your CPC — through better bids, improved quality score, or less competitive keywords
- Improve your conversion rate/RPC — through better listings, pricing, reviews, or adjusting your targeting mix to focus on higher CVR terms.
Treating ACOS as the problem rather than the symptom. High ACOS is never the root cause — it's always either a CPC problem or a conversion rate problem. Diagnose which one before you try to fix it.
The Sponsored Product Reports
Amazon gives you several reports in the ad console. Each one slices the same underlying spend data differently. Here's our breakdown of the most important ones — what they show, their quirks, and how to actually use them.
The search term report shows you which actual customer search queries triggered your ads, compared to the keywords you're targeting. This is the foundation of keyword harvesting and negative keyword optimization.
| Feature | Details |
|---|---|
| Date range | ~65 days back (not 60 — we've verified) |
| Time units | Summary or Daily |
| Key columns | Target keyword, Customer search term, Match type, Impressions, Clicks, Spend, Sales, Orders, Same/Other SKU splits |
| Attribution | Labeled as "7-day" for Sponsored Products |
Top Use Cases
- Keyword harvesting — Find converting search terms from broad/phrase campaigns to target as exact match
- Negative keyword identification — Pivot table all search terms, sum spend, filter for $0 sales with significant spend
- Tactical breakouts — Tag search terms as brand/non-brand/competitor using VLOOKUP, then pivot to see tactical performance splits
- Same SKU vs. Other SKU analysis — Critical for ranking campaigns. If 80% of attributed sales are "other SKU," you're cross-selling, not ranking the advertised product.
One search term can appear across dozens of ad groups. Always create a pivot table to aggregate search term performance before drawing conclusions. A term spending $1 across 100 ad groups looks harmless at the row level but could be $100 of waste when summed.
Essentially the search term report with two bonus columns: Impression Rank and Impression Share. These are game-changing for understanding your competitive position.
- Impression Share — The percentage of total impressions your brand captured on that search term (not campaign, not ASIN — brand)
- Impression Rank — Where your brand stacks up against all competing brands on that term
Example: 58,000 impressions at 0.5% share = ~11.6 million total possible impressions
How to Read the Report
Sort by total possible impressions to see where the biggest volume opportunities live. Then cross-reference with your ACOS and conversion rate:
- High volume + low ACOS + low rank → Push harder here. Room to grow profitably.
- High volume + high ACOS + low rank → Fix conversion rate first, then push.
- You're Rank #1 with high share → Not much room to grow on this term. Look elsewhere.
If your impression share increased but total possible impressions decreased, you're capturing a larger share of a shrinking market. This is a powerful data point for client conversations: "We're performing better than ever — the market itself is contracting." You can cross reference this with the SQP reports to show true search volume on terms over time.
Breaks performance down by individual ASIN. Goes back 90 days — 30 days longer than search term reports.
Top Use Cases
- Per-product P&L — VLOOKUP total sales from Seller Central business reports alongside ad spend from this report. Now you have per-ASIN TACOS and total profitability.
- Percentage of total analysis — Calculate each ASIN's share of total ad spend vs. share of total sales. Mismatches reveal over- and under-invested products.
- Same SKU ratio — Divide same-SKU sales by total (same + other). Products below 50% are primarily driving cross-sell, not same-product velocity.
- Conversion rate troubleshooting — Sort by CVR, lowest to highest. The bottom products deserve investigation — check for listing issues, negative reviews, or pricing problems.
The most flexible report in the suite. This is one of our favorites because of its unmatched date range: up to 5.5 years of data with daily, weekly, monthly, and quarterly time units. Hourly data goes back 30 days.
| Time Unit | Date Range | Best For |
|---|---|---|
| Summary | 5.5 years | Period totals, quick snapshots |
| Daily | 5.5 years | Trend charts, performance monitoring |
| Weekly | 5.5 years | Weekly reporting cadence |
| Monthly | 5.5 years | Month-over-month analysis, client reporting |
| Hourly | 30 days | Dayparting analysis |
The Power of Campaign Naming
This report becomes exponentially more powerful with good campaign naming conventions and structure. If your campaigns contain ASINs, categories, tactics (brand/non-brand), and target ACOS in the name, you can use text functions (TEXT BEFORE, TEXT AFTER, LEFT, RIGHT) to extract those variables and pivot the data in unlimited ways.
For example: with single-product campaigns and structured naming, you can build per-product monthly trend reports going back years — something the advertised product report simply can't do because of its 90-day limit.
Search Query Performance — The Best Data on Amazon
If there's one data source that changed how we analyze Amazon businesses, it's the Search Query Performance report (SQP). It's the only place Amazon gives you organic-level, keyword-level data about your brand versus the total market.
What Makes SQP Special
- Actual search volume — Amazon reveals how many times each query was searched. Before SQP, this data didn't exist.
- Full-funnel metrics — Impressions → Clicks → Add to Carts → Purchases (the "ICAP funnel")
- Your share at every stage — Impression share, click share, add-to-cart share, and purchase share per keyword
- Brand view and ASIN view — Roll up to your entire brand or drill into one specific product
Where to Find It
Seller Central → Brands → Brand Analytics → Search Query Performance. Available only to brand-registered sellers. Monthly breakdowns are the sweet spot — weekly creates too much data for too little incremental insight.
Use the free Seller Central Utilities Chrome extension to bulk-export SQP data across multiple months at once. Without it, you're downloading one month at a time — manually. The extension does all months in a single click and outputs one unified spreadsheet.
Building Your SQP Dashboard
The raw SQP export needs work before it's useful. Here's the process we use:
- Download 12-18 months of monthly brand-view data using Seller Central Utilities
- Add classification columns — Manually tag or use AI to tag each search query as brand, non-brand, or competitor. Assign product categories. This is a one-time effort; subsequent months mostly reuse the same terms.
- VLOOKUP classifications onto new data exports so future months auto-tag
- Build pivot tables and charts for search volume trends, impression share trends, click share, and purchase share — all filterable by tactic and category
One under-appreciated feature of SQP: Amazon breaks out purchase rate by shipping speed (Same Day, 1-Day, 2-Day). We've consistently seen that same-day shipping converts nearly 50% higher than 2-day. This means if your inventory gets spread thin and more customers see 2-day delivery instead of same-day, your conversion rate will silently drop — and you'll wonder why sales fell when nothing about your ads changed.
People often wonder how SQP impression share compares to the ad console's impression share report. They will not match — and that's expected. The SQP likely includes organic impressions limited to page one of search results, while the ad console includes all ad placements (including product detail pages). Sometimes the ad-side estimate of total possible impressions will be higher (more product page impressions), sometimes lower (no organic data).
SQP Data Made Actionable — Not Just a Dashboard You Check Once a Month
AdLabs surfaces your Search Query Performance data at the keyword level back 2 years — impression share, click share, purchase share, weekly, for all your key products — so you can act on competitive gaps immediately instead of exporting CSVs and building pivot tables from scratch.
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Excel Mastery for PPC Reporting
At the core of Amazon PPC reporting is Excel (or Google Sheets). You don't need macros or VBA. But you absolutely need to master these seven functions that we use every single day.
If you learn one thing from this guide, learn pivot tables. They allow you to group, sum, and segment data in seconds. Every report we create starts with a pivot table.
Use cases:
- Aggregate search term performance across all campaigns
- Sum ASIN-level data from the advertised product report
- Break out match type allocation and performance
- Create tactic-level views (brand / non-brand / competitor)
When pulling impression share into a pivot table, use AVERAGE or MAX/MIN — not SUM. If a search term appears 5 times at rank #1 and you sum it, you'll get rank 5. AVERAGE or MAX/MIN gives you the correct rank of 1.
2. VLOOKUP — Cross-Reference Everything
VLOOKUP lets you pull data from one sheet into another based on a shared identifier — usually an ASIN, SKU, or campaign name. We use it constantly to merge data sources: pulling product titles into ASIN-level reports, pulling category names from inventory sheets, comparing duplicate bid files across uploads.
3. CONCATENATE — Build Campaign Names at Scale
Concatenate combines multiple cells into one. It's the only way to create campaign names at scale. If you're launching 2,400 campaigns across 800 ASINs with three tactics each, you build your naming variables in separate columns and concatenate them together. Trying to type 2,400 campaign names manually is a recipe for errors and wasted hours. Get the free campaign naming generator template →
4. TEXT BEFORE / TEXT AFTER (or LEFT / RIGHT)
The inverse of concatenate — extract variables from campaign names. If your campaign naming puts the ASIN at the beginning and target ACOS at the end, these functions strip those values out so you can pivot and analyze by any variable embedded in your naming convention.
TEXT BEFORE and TEXT AFTER are more flexible than LEFT/RIGHT because they work with variable-length values. LEFT(10) always grabs 10 characters — fine for ASINs which are always 10 characters, but TEXT AFTER is better for values like target ACOS where "5%" and "30%" have different lengths.
5. IF / AND / OR Statements — Layered Logic
If statements let you apply conditional logic: "If ACOS > target and tactic = non-brand, flag as 'Over Target'." Layer AND and OR for multi-condition logic. AdLabs uses sophisticated layered logic for bid optimization calculations, placement modifier formulas, and automated flagging of keywords that need attention.
6. Conditional Formatting — Visual Pattern Recognition
Color-code your data using conditional formatting to create heat maps across multiple KPIs. This is especially powerful for creative analysis — when evaluating dozens of DSP creatives, color-coding ROAS, CTR, conversion rate, and cost-per-click across all creatives lets you spot "green clusters" where performance is strong across the board, not just on one cherry-picked metric.
7. Charts — Tell the Story Visually
Line charts for trends over time. Bar charts for comparisons. Pie charts for allocations. Combined with pivot tables and a filter dropdown for individual ASINs, you can build interactive dashboards entirely within Excel that show spend and sales trended by day for any product in your catalog.
Data Storytelling & Advanced Reporting
The What → Why → So What Framework
Every insight you communicate — whether in an email, a reporting call, or a Slack message — should follow this structure:
- What happened? — State the significant metric change. Only mention metrics that are actually meaningful. Don't recite scorecards.
- Why did it happen? — This is where your analytical skill shows. Drill into the root cause. Never say "due to optimizations" — that's not a reason.
- What happens next? — Give a concrete recommendation. This is what separates an email people read from one they unsubscribe from.
"ACOS decreased due to optimizations. We're going to continue optimizing." — This is the #1 example of lazy reporting. It says nothing. The client learns nothing. It doesn't build trust or demonstrate expertise. Always name the specific cause and the specific next step.
The "Ask Why Seven Times" Approach
The classic business principle says ask "why" five times to get to a root cause. In Amazon PPC, we joke that you need seven. Here's an example:
- What? Sales dropped 30% this month.
- Why? Conversion rate fell 60%.
- Why? Price went from $15 to $22.
- Why? Brand increased MSRP due to supply costs.
- So what? At this CPC, we can't afford the current conversion rate. We recommend finding a middle ground — $18.99 — and testing if we can recover enough conversion rate to maintain ranking while preserving margin.
The client doesn't need seven layers of "why" — they need you to have done that work, to clearly articulate the logic, and present the conclusion and next steps.
Percentage of Total — Understand the Concentration of Your Numbers
Whenever you're analyzing product-level performance, always calculate percentage of total — both for sales and for spend. This instantly reveals allocation mismatches.
When a product drives 10% of sales but consumes 23% of spend, that's an immediate flag for reallocation — especially if other products with better efficiency are starving for budget. Be sure to roll up/pivot data into the parent ASIN or a broader tag to get an accurate gauge of performance.
Year-Over-Year Context Is Non-Negotiable
Never report month-over-month without also showing year-over-year. December to January will always look like a disaster month-over-month. But if you're up 40% year-over-year and your January dip is smaller than last year's, you're actually outperforming.
Similarly, always check if search volume for your category has changed. SQP data makes this possible. If the total market contracted by 20% but your brand maintained share, that's a success story — not a failure.
Campaign Tagging Built In — Filter Any View in Seconds
AdLabs tags campaigns by tactic, product, and initiative automatically — so you can filter by brand vs. non-brand, ranking campaigns, or individual product lines without manually tagging hundreds of campaigns in a spreadsheet.
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Building Your Reporting Dashboard
The Three Essential Dashboard Layers
Every good Amazon reporting dashboard needs at least these three layers:
- High-level performance overview — Total sales, ad spend, TACOS, ACOS trended over time with multiple date ranges (month-to-date, year-to-date, year-over-year with both % and # comparisons)
- Product-level drill-downs — Individual ASIN, parent ASIN or category tag-levet performance with trend lines, ACOS targets, and strategic notes
- Strategy-level breakouts — Brand vs. non-brand vs. competitor spend splits, ranking campaign tracking, single keyword performance, initiative-specific views (Black Friday, new launches)
Why the Amazon Ad Console Isn't Enough
The ad console can't combine ad data with organic data. It can't show TACOS. It can't let you build trend views by individual ASIN over custom date ranges. And it can't show year-over-year comparisons for any period you want, instantly. You always end up exporting to Excel, spending hours building manual reports, and delivering something that's already stale by the time it reaches your client.
Campaign Tagging Is Everything
The most important reporting practice isn't building the dashboard — it's tagging your account entities properly. Without tags, you can't filter or segment. With them, any view becomes possible:
- Product tags — Category, ASIN, product line, sizing
- Tactic tags — Brand, non-brand, competitor, auto, single-keyword
- Initiative tags — Product launch, seasonal push, ranking campaign, BFCM
These are just a few ideas, each account will need its own custom setup and unique tag values. With proper tagging, you can duplicate any custom dashboard page in AdLabs, apply a new tag filter, and instantly have a product-specific or initiative-specific report without rebuilding anything.
The goal of your dashboard is to answer client questions before they ask them. When the client says "I don't even log into Amazon anymore — I just look at this dashboard," you've won. You become unfireable because losing you means losing their entire visibility into their business.
Client Reporting That Retains
Know Your Audience
The CMO and the CEO need completely different reports. The CMO wants product-level keyword data and campaign details. The CEO wants three bullet points: are we growing, are we profitable, and what should we do differently.
If you say things that the CEO doesn't understand, it doesn't make you look smart. It makes you fireable. They will always value someone who can communicate effectively over someone who's just smart or can merge numbers.
The rule: The higher the executive level, the more summarized and visual your reporting needs to be. Bullet points, not spreadsheets. Simple charts, not 50-column tables. Action recommendations, not raw data dumps.
Always Have a Visual Ready
Never walk into a reporting call with just the ad console open. Prepare at least one visual — a chart, a table, a screenshot — that answers the most important question the client is likely to ask. Three approaches to fast visuals:
- Excel / Google Sheets — Quick bar charts, line charts, pivot tables
- Pre-built dashboard — With API-connected data that refreshes automatically
- Screenshots with annotations — From any tool, annotated with arrows and notes
Reporting Calls Are Sales Calls
Every reporting call is a retention event. You're not just updating the client on numbers — you're demonstrating your value and selling them on continuing to work with you.
- Show the work you've done, not just the results
- Preemptively address concerns before they raise them
- Always end with clear next steps and action items
- Follow up with an email summary using bullet points
- Make your dashboard the client's "home base" they return to daily
Handling Performance Issues
When things go wrong — and they will — the quality of your analysis determines whether you keep or lose the client.
What happened: A top-selling SKU dropped from 100 units/day to 5 units/day. BSR tanked.
Why: Price was increased from $15 to $22 in one week. Conversion rate plummeted 60%. At the new price point, CPCs couldn't deliver profitable visibility.
The recommendation: "We can't profitably increase bids at this conversion rate. We recommend testing $18.99 — a middle ground that still maintains the product's positioning relative to competitors, and may recover enough conversion rate to regain ranking while preserving improved margins."
The visual: A screenshot from Helium 10 showing price trending up and BSR trending down in perfect inverse correlation.
Result: Client approved the price adjustment. Conversion rate partially recovered. Rankings stabilized within two weeks.
What happened: Year-over-year product sales declined despite consistent ad investment.
Why: SQP showed non-brand search volume for the product's core keywords was down 25% YoY. Total ad traffic hadn't dropped — the market itself contracted.
The recommendation: Shift from growth-mode investment to efficiency-mode. Cut least incremental tactics (starting with brand defense), preserve margins while the market recovers, and monitor SQP monthly for volume recovery signals.
Result: Total margins improved even as sales stayed flat. Client understood the context and didn't blame the ad strategy for the decreasing sales.
Email Communication Best Practices
- Always use bullet points — Never bury three action items in a paragraph. Colon, bullet, bullet, bullet.
- Write your first draft, then cut 25% — Shorter emails get read. Long emails get filed.
- Include one visual per email — A screenshot, a chart, something scannable.
- End every email with "Next Steps" — A clearly labeled section with what you're doing and what you need from them.
Dashboards That Make You Unfireable — Always-On, Client-Ready
AdLabs dashboards combine ad data with total data, showing TACOS, organic %, and total sales on a product-by-product level — white-label shareable live links your clients can check daily.
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The Reporting-First Manager
The difference between a good PPC manager and a great one isn't the number of bid changes they make or the complexity of their campaign structure. It's their ability to look at data and see what it means.
Anyone can read scorecards. That's not your job. Your job is to be an interpreter — translating raw data into strategy, context, and action.
The Reporting Stack We Recommend
- Search Term Impression Share Report — For competitive positioning and keyword-level insights
- Advertised Product Report — For per-ASIN analysis combined with Seller Central data
- Campaign Performance Report — For historical trend analysis and tactical breakouts
- Search Query Performance (SQP) — For organic-level market intelligence, search volume trends, and share-of-voice tracking
- Excel / Sheets — For pivot tables, charts, and one-off analysis
- Dashboard tool — For always-on, client-facing reporting that makes you unfireable
Your Reporting Checklist
- Save search term data regularly — Amazon only keeps ~65 days
- Always pivot table before drawing conclusions from any report
- Calculate percentage of total for every product-level analysis
- Use the What → Why → So What framework for every insight
- Build SQP exports into a monthly dashboard with classifications
- Tag campaigns by tactic, product, and initiative for effortless filtering
- Show year-over-year context alongside month-over-month
- Make your dashboard the client's home base
- Present visuals, not spreadsheets, in every client interaction
- Always end with next steps — never leave the client guessing
The AdLabs Philosophy on Reporting
We believe reporting is not overhead — it's the product. The campaigns you run are only as good as your ability to measure, interpret, and communicate their impact. A beautiful campaign structure with no reporting discipline is flying blind. A simple structure with excellent analytics will outperform it every time.
Invest in your reporting. Build systems that scale. Create visuals that tell stories. Deliver insights that drive decisions.
Data without a story is just noise. A story without data is just opinion. Together, they're strategy.
This guide is based on research from 11 episodes of That Amazon Ads Podcast (Episodes 13, 16, 18, 19, 21, 22, 52, 73, 77, 93, 120), masterclass lessons on advertising reports and critically thinking through metrics, and insights from managing hundreds of Amazon advertising accounts.