Dashboard & Analytics

Understanding Your TrackIQ Dashboard

The Dashboard is the first screen you land on, and the only one built to be read in half a minute. This is what each part is telling you, and the two numbers worth checking every morning. Watch the Dashboard walkthrough Prefer to watch? Ninety seconds on what each panel is telling you. The headline tiles The ten headline metric tiles Ten metrics across the top: Clicks, Impressions, Spend, Sales, ACoS, CPC, CTR, Conversion, CR and ROAS. Each tile carries three things — the figure for your selected period, a sparkline showing its shape, and the change against the previous period. Read the arrows as better or worse, not up or down. A falling ACoS shows as an improvement even though the number went down, because lower ACoS is better. The colour is doing the interpreting for you. The sparkline is more useful than it looks. A number that is flat overall but spiky underneath is a different business problem from one that declined steadily, and the tile tells you which without opening a report. Advertising: the budget pacing check The advertising panel with month-to-date spend against budget This panel is the fastest budget check in the product. It shows your active campaign count, then MTD Spend against your monthly budget as a progress bar, with ACoS, ROAS, Avg CPC and CTR beneath. How to use it: compare the bar against where you are in the month. Two-thirds through the month with the bar past three-quarters means you will overspend unless something changes. That is a decision you can make in one glance, and it is the single most valuable thing on this screen. Manage → takes you into the campaigns themselves. Optimization opportunities Optimization opportunities with potential savings A count of the improvements TrackIQ has found, with Potential savings and the Revenue at stake attached. These are not vague suggestions — each has a figure behind it. Expand the panel to work through them. Treat the savings number as an estimate of what is currently being wasted, not a guarantee, but a large one is always worth twenty minutes. Performance over time The performance chart with its three lenses One chart, three lenses: | Lens | Shows | |---|---| | Advertising Efficiency | how hard your ad spend is working | | Traffic to Sales | whether visits are turning into orders | | Sales vs Ad Spend | organic and ad-attributed sales against total spend | Sales vs Ad Spend is the one to look at most often. If ad spend climbs while total sales stay flat, you are buying sales you were already getting — and that shows up here before it shows up in ACoS. Expand opens it full width. Catalogue health Sales performance and stock health How many SKUs and categories you have, then a health bar splitting your catalogue into out of stock, critical, low and healthy, plus your top performer and any product-level alerts. The out-of-stock count is the second number to check daily. A stockout does not just cost the sales you would have made — it costs rank, and rank takes far longer to win back than a week of orders. Quick reports Recent and scheduled reports Your recently generated and scheduled reports, each marked Ready when it can be opened. All Reports → takes you to the full list. The thirty-second routine If that is all the time you have: 1. MTD spend against budget — will you overspend this month? 2. The out-of-stock count — are you about to lose rank on anything? Everything else can wait for a morning when you have longer. Those two have deadlines attached. The date range at the top right drives the whole screen. See Date Ranges, Granularity and Comparing Against the Previous Period for how the comparison works. Related - Reading the Optimization Opportunities Panel — TrackIQ's own shortlist of what to fix. - Advertising Efficiency, Traffic to Sales and Sales vs Ad Spend — Advertising Efficiency, Traffic to Sales, Sales vs Ad Spend. - Values vs % Change: The Comparison Toggle — the comparison toggle. - My Dashboard Is Empty — if nothing is showing.

Analyzing Your Data

Analytics is where you go with a question about the business rather than about a campaign. Five screens, each cutting the same underlying data a different way — so the only real skill is knowing which one answers which question. Watch the Analytics walkthrough Prefer to watch? A minute on which screen answers which question. Pick the screen by the question | Your question | Screen | |---|---| | Which products make the money? | Sales Performance | | What are people searching for, and am I winning it? | Search Query Performance | | Where do I rank for the keywords that matter? | Rank Tracker | | Which categories are actually profitable? | Category Insights | | Am I about to run out? | Inventory | Sales Performance: by product Sales performance headline tiles Per-ASIN performance, with Total Sales beside Ad Sales. The gap between those two columns is your organic business. A product whose ad sales are nearly all of its total sales is renting its position. One with high total sales and modest ad spend has genuine demand and is worth protecting. Category Insights: by category Category insights The same logic one level up, and the screen that carries TACoS alongside ACoS. The category table That pairing is the point. ACoS tells you how efficient the advertising was. TACoS tells you how dependent the category is on it. A category with a respectable ACoS and a climbing TACoS is quietly becoming more expensive to sell, and ACoS alone will never show you that. Category Insights is available on PRO and above. The other three Search Query Performance — what shoppers typed, how the whole market performed on it, and how much you captured. Weekly rather than daily. Its Recommended actions section is the fastest route to value in the product. Rank Tracker — where your products sit in search results for keywords you have chosen to track, day by day, and how that compares to competitors you add. Inventory — stock converted into days of cover, banded by urgency. The controls are the same everywhere Every Analytics screen shares the layout: headline tiles, a trend chart, a table with Search, Filters, Manage Columns and Export. Two habits pay off across all of them: Use the % change toggle. It answers “what moved?” rather than “what is biggest?” — and what moved is almost always the more useful question. Set the date range deliberately. Comparisons are always against the immediately preceding period of the same length, so an odd range produces an odd comparison. A worked example Suppose sales are down and you do not know why. 1. Sales Performance — sort by % change. Is it everywhere, or one or two products? 2. If it is concentrated: Inventory — did those products go out of stock? 3. If stock is fine: Rank Tracker — did they lose position? 4. If rank is fine: Search Query Performance — did demand for those searches fall, or did a competitor take your share? Each step rules out a cause, and by step four you have either found it or learned that the market moved rather than your account. Related - Filters, Manage Columns and Exporting a Table — the controls every table shares. - Date Ranges, Granularity and Comparing Against the Previous Period — ranges, granularity and comparison. - Values vs % Change: The Comparison Toggle — reading change correctly. - Exporting Data to CSV and Excel — getting it out.

How to Monitor Your Stock Levels

A stock level on its own tells you very little. Four hundred units is comfortable for one product and a crisis for another. The Inventory screen converts stock into time, and time is something you can act on. Watch the Inventory walkthrough Prefer to watch? A minute on days of cover and why stockouts cost rank. The two rows of figures The inventory summary tiles The top row counts units: | Tile | What it counts | |---|---| | Active Products | listings currently sellable | | On Hand | units in fulfilment centres now | | Inbound | units on their way to Amazon | | Reserved | units allocated to orders or transfers | | Unfulfillable | units Amazon cannot sell | | Out of Stock | listings with nothing available | The second row bands your catalogue by urgency, and this is the row to read first: | Band | Meaning | |---|---| | Critical | under 7 days of cover | | Low Stock | 7–20 days of cover | | Healthy | 21 days or more | | No Sales (30d) | not moving at all | Plus overall Days of Cover and Total units. Those thresholds are worth memorising. Critical means you have about a week — usually less than the lead time to get more stock in, which is exactly why it is flagged. Unfulfillable is the quietest problem here. Those units are sitting in Amazon's warehouses, counted in your total, and cannot be sold. A number that keeps climbing is worth investigating. No Sales (30d) is the opposite problem: stock you are paying to store that nobody wants. The product table The inventory table Every product with its ASIN, SKU, whether the listing is Active, its Status — In Stock or Out of Stock — and units On Hand. Sort by days of cover and you have your restocking order, most urgent first. That single sort is the main job of this screen. Use Filters to narrow to a status, and Manage Columns to bring in velocity and cover if they are not showing. Why this screen deserves a daily glance Every other problem in TrackIQ costs money. This one costs rank. When a product goes out of stock, Amazon stops showing it. When it comes back, it does not return to where it was — the sales history that earned that position has a hole in it, and competitors have taken the traffic. You lose the orders you would have taken and you pay to climb back. That asymmetry is why inventory alerts outrank advertising alerts even when there are fewer of them. Money you can win back. Rank you have to earn again. A routine that prevents most of it 1. Check the Critical count each morning. Anything in it needs a decision today. 2. Check Low Stock weekly. That is your reorder list, with time to act. 3. Check Unfulfillable and No Sales monthly. Both are money sitting still. To have this reach you rather than you going to look, Smart Alerts fire on low stock, critical stock and stockout forecast — see Alert Categories, Priorities and What Actually Triggers Them. You can also have a rule pause advertising on a product about to run out, so you stop paying for clicks you cannot fulfil. Related - Inventory Forecasting: Reordering Before You Have To — reordering before you have to. - Catch a Stockout Before It Costs You Rank — the playbook. - Monitoring Inventory Against Sales — what to look for, and what to do about it. - Inventory Forecasting and Purchase Orders — planning so the screen stays green.

Sales Performance: Which Products Carry the Business

Account-level numbers hide the thing you most need to know: which products are actually carrying the business, and which are only selling because you are paying for them. Analytics → Sales Performance answers that per product. Watch the Sales Performance walkthrough Prefer to watch? A minute on reading total sales against ad sales. The headline tiles The sales performance tiles The same six as the advertising screens — Total Spend, Ad Sales, ROAS, ACoS, Impressions, Clicks — for your whole catalogue over the selected period, each with its trend and its change. Performance trends The trend chart Ad sales against clicks, money on the left axis and counts on the right, with the usual Day / Week / Month and Values / % change controls. The table, and the comparison that matters The product table showing total sales beside ad sales Every product with its ASIN, SKU, and then the two columns to read together: Total Sales and Ad Sales. The gap between them is your organic business. | What you see | What it means | What to do | |---|---|---| | Ad sales are nearly all of total sales | the product is renting its position | test reducing spend and watch what survives | | Total sales well above ad sales | genuine organic demand | protect it — this is a product worth defending | | High spend, low total sales | you are buying sales that are not compounding | fix the listing or stop | That first row is the one worth acting on. A product whose sales collapse when you stop advertising never really had demand — it had a budget. Knowing which of your products those are changes how you allocate spend. TACoS, per product Spend divided by total sales is that product's TACoS — its true advertising cost, not just its cost against attributed sales. ACoS tells you how efficient a campaign was. TACoS tells you how dependent a product is. A product with a respectable ACoS and a rising TACoS is quietly becoming more expensive to sell, and ACoS alone will never show you that. How to use it in practice Find your gateway products. Sort by total sales. The top few are your business — make sure they are never out of stock and never under-advertised. Find the renters. Look for products where ad sales approach total sales. Test a spend reduction on one and watch for two weeks. Find the ignored. Products with real total sales and almost no ad spend are already working without help. Modest advertising on them often returns better than more spend on products you are already saturating. Where to go next For which products bring new customers rather than repeat ones, the AMC Cloud NTB ASINs dashboard answers that directly. For whether a product is winning the searches it should, see Search Query Performance. Related - Product Ads: ASIN-Level Ad Performance — the advertising view of the same ASIN. - Find Zero-Sales ASINs and Decide What to Do With Them — the playbook for the tail. - How to Monitor Your Stock Levels — the inventory side.

Inventory Forecasting: Reordering Before You Have To

Reading your current stock tells you where you are. Forecasting tells you when you have to act. TrackIQ does that with three numbers, and the useful one is the one most people never sort by. (For reading current stock levels, see How to Monitor Your Stock Levels. This article is about what happens next.) Watch the forecasting walkthrough Prefer to watch? Fifty-five seconds on turning stock into a reorder date. The three numbers The inventory summary tiles Daily Velocity (30d) — average units sold per day over the last thirty days. Days of Cover — On Hand ÷ Daily Velocity. How long your stock lasts at the current rate. Stockout Forecast — a projection that an ASIN will run out within 14 days at current velocity. It appears as an alert rather than a column. The important property of Days of Cover is that it is not a stock level — it is a countdown. It moves when either side of the division changes. A product with steady stock can drop from healthy to critical purely because demand picked up, and nothing about the stock number would have warned you. The bands, and why they may be wrong for you The product table | Band | Cover | |---|---| | Critical | under 7 days | | Low Stock | 7–20 days | | Healthy | 21 days or more | These are sensible defaults, but the only threshold that matters is your own lead time. If it takes three weeks from placing an order to units being sellable at Amazon, then “Low Stock” is already too late — a product at 15 days of cover will be out of stock for a week before your replenishment lands. Work out your real lead time, including the inbound receiving time at Amazon, add a buffer, and treat that as your reorder line. For many sellers it lands somewhere in the middle of the Healthy band. Velocity moves before you notice Daily velocity is a thirty-day average, which makes it stable — and slightly slow. Before a peak, real demand rises faster than the average. Your cover figure is therefore optimistic in exactly the period when running out is most expensive. In the run-up to a seasonal event, mentally discount days of cover. After a stockout, velocity is artificially low, because you sold nothing while unavailable. Cover on a freshly restocked product will look better than it is. A reorder routine 1. Sort by days of cover, ascending. That is your restocking order, most urgent first. 2. Apply your own threshold, not the Critical band. 3. Check velocity direction for anything close to the line — a product with rising velocity needs ordering sooner than its cover suggests. 4. Look at Inbound before ordering again. Units already on their way count. Let it come to you instead Three alerts do this monitoring for you, and fire on the same logic: | Alert | Fires when | |---|---| | Low Stock Alert | cover below 3 weeks | | Critical Stock Alert | cover below 1 week | | Stockout Forecast | projected to run out within 14 days | See Alert Categories, Priorities and What Actually Triggers Them. And for products that are going to run out regardless, a rule can pause their advertising automatically — so you stop paying for clicks on something you cannot ship. That is usually the highest-value automation in the whole product, because it saves money on a day when you are already losing sales. Related - Catch a Stockout Before It Costs You Rank — the playbook. - Find Zero-Sales ASINs and Decide What to Do With Them — the other end of the catalogue.

Date Ranges, Granularity and Comparing Against the Previous Period

Almost every reporting screen in TrackIQ carries the same set of controls in the same place. Learn them once and every screen becomes readable. Watch the date controls walkthrough Prefer to watch? Forty-eight seconds on the four controls and the two exceptions. The headline tiles and date range The date range Top right of the screen, showing something like Feb 01, 2026 - Feb 28, 2026. Everything below it — the summary cards, the charts, the table — is calculated for that range and nothing else. Two screens do not follow this rule, because their underlying data does not: - AMC Cloud reports by calendar month, so it has a month selector instead of a range. - Search Query Performance reports by week, and shows a span of weeks (for example Last 6 weeks) rather than arbitrary dates. The trend chart with its granularity and comparison controls Day, Week, Month Sitting with the chart, this toggle changes how the trend line is bucketed. It does not change the totals above it — the same period is being summed either way, just drawn at a different resolution. Use Day to find the exact date something changed. Use Week to see a trend without weekend noise. Use Month for anything seasonal. vs previous Every summary card carries a second line like ▼16.8% vs prev. That compares your selected range against the immediately preceding range of the same length. Choose 28 days and it compares against the 28 days before; choose a single week and it compares against the week before. This is worth being deliberate about. If you pick an arbitrary 17-day window, the comparison is against the previous 17 days, which may straddle a weekend differently and move the figure for reasons that have nothing to do with your advertising. Arrow colour follows the metric, not the direction. A falling ACoS is shown as an improvement even though the number went down, because lower ACoS is better. Do not read red as “down” and green as “up” — read them as worse and better. Values vs % change Beside the comparison control, this switches the table between showing raw figures and showing the change against the previous period. It is the fastest way to answer “what moved?” across a long table: switch to % change and sort. A note on very recent data Amazon delivers data on its own schedule, and different data sets arrive at different speeds. The last day or two of any range can look artificially low simply because not everything has landed yet. If yesterday looks like a collapse, check it again tomorrow before acting on it. Related - Values vs % Change: The Comparison Toggle — the toggle that sits beside it. - Search Query Performance Is Weekly: Reading Week Cohorts Correctly — the one report that ignores your range. - Time to Conversion: Checking Your Attribution Window — why recent days under-report.

Filters, Manage Columns and Exporting a Table

Every data table in TrackIQ — campaigns, keywords, products, inventory, DSP, AMC — carries the same four controls. They behave identically everywhere. Watch the table controls walkthrough Prefer to watch? Fifty-two seconds on the four controls every table shares. Search A plain text box above the table. It matches against the table's main identifying column: campaign name on the campaign screens, product title or code on the product screens, keyword on the keyword screens. Use it for a known item. Use Filters for a set. Active filters shown as removable chips Filters Opens the filter panel for that screen. The available filters follow the table's own columns, so the campaign screen filters on things like status and type, and the inventory screen filters on stock condition. Filters combine, and they apply to the export as well as to the screen. That last part matters: if you export while a filter is active, you export the filtered set, not the whole table. Manage Columns Most tables carry more columns than fit on screen. Manage Columns shows the full list and lets you choose which appear. This is worth doing properly rather than scrolling sideways. On the campaigns table, for example, hiding the columns you never look at makes the ones you do look at fit in a single view, and the table becomes something you can scan instead of navigate. Export Sends the current table — with your filters and column choices applied — to a file. Exports are prepared in the background rather than downloaded instantly, because a wide table over a long date range can be large. You can carry on working while one is prepared, and every export you have requested is listed under Exports in the sidebar, with its type, account, marketplace, status and the time it was requested. A table with many columns, where Manage Columns earns its place Paging Below the table: an entries per page selector and a count reading something like Showing 1 to 22 of 22 entries. That count is the honest total after filtering. If it says 22 and you expected 200, a filter is on — or your date range is narrower than you think. Related - Exporting Data to CSV and Excel — the export itself. - Analyzing Your Data — the wider screen these controls sit on.

Reading the Optimization Opportunities Panel

Most of the dashboard tells you what happened. This panel tells you what to do about it, ranked by how much money is at stake. It sits inside the Advertising card, collapsed behind a heading that looks like a label rather than a list — which is why plenty of people never open it. Watch the walkthrough Prefer to watch? Seventy seconds on reading a row, and what Potential savings does and does not mean. Finding it The Optimization Opportunities panel, expanded On the main dashboard, in the Advertising card, look for a heading like “27 Optimization Opportunities” with a chevron beside it. Click the heading to expand. The number is the count of things the product currently thinks are worth changing. It moves on its own as your data does. Reading one row Every row carries four pieces of information, and together they are a complete instruction. | Part | Example | What it tells you | |---|---|---| | Campaign name | Northwind Goods — MGO 525 — SP — Generic — Multi — Must Win | exactly where to go | | Ad type badge | SP | which console and which attribution window | | The reason | ACoS 39.3% exceeds 30% target | the rule that flagged it, with your actual figure | | The amount | −$9.5K | what it is costing you | That third column is the part worth valuing. The panel names the threshold it used and your number against it, so you are never guessing why something appeared. An alert that cannot explain itself gets ignored; one that shows its working gets acted on. Reading the two totals Potential savings and Revenue sit below the list. Potential savings aggregates what the listed opportunities are costing. Hover the info icon beside it for the precise definition — it is worth reading once so you know exactly what is being counted before you quote the figure to anyone. Two cautions about it, both important: It is potential, not banked. It is what you would stop wasting if you acted on everything listed — not money that appears if you do nothing, and not a forecast of profit. Cutting spend is not free. A campaign at 39% ACoS against a 30% target is inefficient, not worthless. Pausing it removes the spend and the sales. See When a high ACoS is the right answer below. How to work it The list is already in the order that matters — money at stake, descending. So work top-down and stop when the amounts stop being worth your time. 1. Read the reason before the name. “ACoS 39.3% exceeds 30% target” tells you this is a bid problem, not a listing problem. 2. Check the ad type. An SP row is judged on a 7-day window; SB and SD get 14 days, so a recent Brands campaign will look worse than it is. See Why SP, SB and SD Numbers Don't Add Up. 3. Decide the intent. Is this campaign supposed to be efficient, or is it defending a position? 4. Act, or dismiss it deliberately. Either is fine. What is not fine is leaving 27 items unread every week. When a high ACoS is the right answer The target that flags these rows is a single number applied across campaigns that are doing different jobs. - Defending a keyword you own — a higher ACoS can be entirely rational; you are paying to hold ground a competitor wants. - Launching — ACoS is expected to be poor. You are buying sales history and rank. - Harvesting — here the target genuinely applies, and an overshoot is real waste. So the useful question is not “is 39% too high?” but “is this campaign doing the job I set it?” The panel cannot know your intent. You can. From reading to not having to read If the same rows keep reappearing, you are doing manually what the product will do unprompted. Rule-Based Optimization has a Hit my Target ACoS recipe that scales each bid by how far it sits from target — which is the same judgement this panel is making, applied automatically and continuously rather than whenever you remember to look. The panel is the diagnosis. A rule is the treatment. See Rule-Based Optimization. Related - Understanding ROAS and Key Amazon Advertising Metrics — what ACoS is and is not telling you. - Understanding Your TrackIQ Dashboard — the rest of the screen. - Advertising Efficiency, Traffic to Sales and Sales vs Ad Spend — the chart beside this panel.

Advertising Efficiency, Traffic to Sales and Sales vs Ad Spend

One card on the dashboard holds three different charts, switched by the tabs across its top. They are not three views of the same thing — each answers a different question, and knowing which is which saves you from reading the wrong one. Watch the chart walkthrough Prefer to watch? Seventy-four seconds on which tab answers which question. Advertising Efficiency — is the advertising working? Advertising Efficiency: spend and sales as bars, ACoS and TACoS as lines Four series on two axes. Bars are money on the left; lines are percentages on the right. | Series | Shape | Read it for | |---|---|---| | Total Ad Spend | bar | what you put in | | Ad-Attributed Sales | bar | what came back | | ACOS | line | efficiency of the advertising | | TACOS | line | dependence of the business on advertising | Read the two lines against each other. That pairing is the whole point of this tab: - ACoS steady, TACoS rising — advertising is working fine, but a larger share of your revenue now requires paying for it. Organic demand is eroding underneath a perfectly healthy campaign. - ACoS rising, TACoS steady — an advertising problem, not a business problem. - Both falling — the good case: efficient advertising on top of growing organic sales. That first row is the one worth catching, and ACoS alone will never show it to you. See Understanding ROAS and Key Amazon Advertising Metrics. Traffic to Sales — is the listing working? Traffic to Sales: sessions as bars, Unit Session % as a line Two series. Sessions as bars, Unit Session % — your conversion rate — as a line. This tab has nothing to do with advertising. It separates the two halves of a sales change: | What moved | Where the problem is | |---|---| | Sessions fell, conversion flat | fewer people arriving — rank, visibility, or ad delivery | | Sessions flat, conversion fell | the detail page — images, price, reviews, availability | | Both fell | usually availability. Check stock first | That last row is worth knowing: going out of stock takes conversion and traffic down together, because Amazon stops showing an unavailable product. See Inventory Forecasting. Sessions rising while conversion falls is the classic sign of buying the wrong traffic — more visitors, less relevant. Worth checking your search terms. Sales vs Ad Spend — how much of the business is paid? Sales vs Ad Spend: organic and ad-attributed sales stacked, with ad spend as a line Three series: Organic Sales and Ad-Attributed Sales stacked as bars, with Total Ad Spend as a line across them. Stacking is the point. The bar height is your total sales, and the split inside it is the mix. So this tab answers one question the other two cannot: how much of the business would still be there if you stopped advertising? Watch the proportion rather than the heights. A stack that grows while the paid portion grows faster is a business becoming more dependent on advertising — the same story TACoS tells on the first tab, shown as volume rather than a ratio. The spend line is there for shape, not scale. If it climbs while the bars do not, you are buying less with more. Which tab for which question | The question you actually have | Tab | |---|---| | Is my advertising efficient? | Advertising Efficiency | | Am I getting more dependent on ads? | Advertising Efficiency (TACoS) | | Why did sales drop? | Traffic to Sales | | Is it traffic or the listing? | Traffic to Sales | | How much of my revenue is organic? | Sales vs Ad Spend | | Is spend keeping up with sales? | Sales vs Ad Spend | Two things that apply to all three Expand in the top-right of the card opens the chart larger. On a daily series across a month, that is usually the difference between seeing a trend and guessing at one. The right-hand edge is always unreliable. Every one of these is a daily series, and the last day or two is still accruing — attribution windows have not closed and advertising data lands later than sales. A cliff at the right edge is reporting, not trading. Look again tomorrow before acting. See My Ad Data Is Missing or Looks Wrong. Related - Values vs % Change: The Comparison Toggle — reading the change correctly. - Why Sponsored Products, Brands and Display Numbers Do Not Simply Add Up — before you total the series.

Values vs % Change: The Comparison Toggle

Beside every Performance Trends chart sit two small toggles: −− vs previous, and Values / % change. They are easy to ignore and they change what the chart is telling you. Watch the walkthrough Prefer to watch? Sixty-five seconds on when each toggle is the honest one. What each one does The controls sit at the top right of every Performance Trends chart vs previous overlays the preceding period as a dashed line. Same length, immediately before — so a 28-day view compares against the 28 days before it. Values plots the actual numbers. % change plots movement instead. They combine, and the combination is the point. Values, with vs previous The default, and right most of the time. You see this period solid and last period dashed, in the same units. Scale is preserved, so you can tell whether a change is large or merely visible — a spike that looks dramatic in isolation often turns out to be a normal Tuesday once last month is drawn beside it. Use it for: “are we up or down, and by how much?” % change Plots the movement rather than the level, which does two useful things. It makes small series comparable to large ones. A campaign spending $200 and one spending $20,000 cannot share a y-axis in Values — the small one is a flat line at the bottom. In % change they are directly comparable. It surfaces the thing you actually care about, which is usually the direction rather than the amount. Use it for: “what moved most?” The trade is that % change hides scale. A 300% rise on $40 and a 3% rise on $400,000 look nothing alike in reality and can look similar here. Check the tile above before acting. A rule of thumb | Question | Setting | |---|---| | Are we up or down? | Values + vs previous | | Which of these moved most? | % change | | Is this spike real? | Values + vs previous | | Comparing very different sizes | % change | | About to quote a number | Values | The tiles use it too The vs prev figure on each headline tile is the same comparison in one number — “▲23.9% vs prev” means this period against the one immediately before. Two cautions there: Percentage points versus percent. When the metric is itself a percentage — ACoS, CTR, conversion — a change from 40% to 44% is 4 percentage points, not a 4% rise. It is a 10% rise. Getting this backwards over-reports or under-reports every efficiency change. Direction is not quality. ACoS falling is good; impressions falling usually is not. The arrow colour tells you the direction, not whether to be pleased. Granularity changes the comparison too Day / Week / Month sets the grain, and the comparison period follows it. Daily advertising data is noisy. Weekday patterns make every daily chart look volatile, and a single quiet Sunday can read as a collapse. For anything longer than a fortnight, Week is usually the honest view. The caveat that applies to all of it Whatever you set these to, the last day or two of any period is still filling in — Sponsored Products is credited over 7 days, Brands and Display over 14. So a vs previous comparison ending today compares a settled period against an unsettled one, and will always flatter the past. If the comparison needs to be fair, end it a fortnight ago. See My Ad Data Is Missing or Looks Wrong and Where Your Data Comes From and How Fresh It Is. Related - Date Ranges, Granularity and Comparing Against the Previous Period — the comparison period itself. - Analyzing Your Data — the screens this toggle sits on.

Category Insights: Benchmarking Your Categories

Analytics → Category Insights groups your products into categories you define, and reports each one as its own line of business. One column makes it different from every advertising screen: Total Sales sits beside Ad Sales, so you see the whole category rather than just the advertised part. Watch the walkthrough Prefer to watch? Sixty-seven seconds on why Total Sales beside Ad Sales changes what you can see. The screen Category Insights, with Total Sales alongside Ad Sales The standard Analytics layout — six headline tiles, Performance Trends with Day/Week/Month and the Values / % change toggles — plus + Add Category. The table gives you, per category: Total Sales · Ad Sales · Spend · Impressions · Clicks · Total Units · ACoS Total Sales is the column that matters Every Amazon Ads screen reports ad sales — what advertising was credited with. This screen reports total sales as well, which lets you compute the thing advertising reporting cannot show you: how much of a category is paid. That is TACoS at category level, and it answers a question ACoS never does: | Pattern | Reading | |---|---| | Ad sales rising, total sales flat | advertising is replacing organic, not adding to it | | Both rising together | advertising is genuinely growing the category | | Total sales strong, ad sales small | a healthy organic category — do not over-invest | | Total sales falling, ad sales holding | organic erosion hidden behind steady ad performance | The first and last rows are the ones worth catching, and neither is visible on any advertising screen. See Understanding ROAS and Key Amazon Advertising Metrics. Categories are yours to define + Add Category creates one. These are your groupings, not Amazon's browse nodes — which means they are only as useful as the thinking behind them. Group by something you would make a budget decision about: - A product line you fund as a unit. - A price tier, where the margin maths is similar. - A use case, if that is how your customers shop. Grouping by something you would never act on separately produces numbers you will never use. And a category that mixes a hero product with a long tail averages the hero away. Reading it Compare categories against each other, not against a single target. A launch category should look worse than a mature one. Watch Total Units beside Total Sales. Units rising while sales fall is a pricing or mix change, not a demand change. Use vs previous. A category whose ACoS moved while spend did not is the one to open. Read categories before products. Six category rows tell you where to look faster than two hundred product rows — the same argument as Optimization Groups, applied to what you sell rather than how you buy it. How this differs from Optimization Groups Both group things and report per group. They group different things: | | Category Insights | Optimization Groups | |---|---|---| | Groups | products | campaigns | | Lives under | Analytics | Amazon Ads | | Shows | total and ad sales | ad performance | | Answers | how is this part of the business? | how is this part of the advertising? | Most accounts want both, and they will not line up perfectly — one campaign often advertises products from several categories. That mismatch is normal, and it is why the two screens answer different questions. Availability Category Insights starts at PRO. On Starter the section is not in the sidebar at all. See What's Included in Each Plan. Related - Sales Performance: Product-Level Reporting — the level below this one. - Optimization Groups — the advertising-side equivalent. - Benchmark yourself against your own category — the playbook. - Before You Add a Product — reading category traction as a product-research signal.