Which metrics should I monitor to catch poor ad performance?

The Monday written summary

Every account I run gets a Monday morning written summary. Four numbers, one paragraph, sent before anything else opens. The point isn’t the document. It’s reading the same numbers the same way every seven days, so a drift registers as a drift instead of a month-end surprise. Each number below names its report.

The four weekly numbers

CPA trend

Cost per acquisition at the account level, then for the top three campaigns by spend, on a rolling seven-day window against the prior seven days and the trailing twenty-eight. One week in isolation is noise; the trend across three windows is signal. First move: that campaign’s search terms report, before bids.

Spend pacing

Month-to-date spend divided by days elapsed, multiplied by days in the month, against budget. Pacing well over budget in the first ten days means a bid strategy off its leash. Pacing well under means starving the auction. First move: change history for the prior fourteen days.

Zero-conversion spend share

The report: campaigns or ad groups view, cost descending, conversions filtered to zero, last thirty days. Total every ad group that spent over a hundred dollars and produced nothing, divided by total account spend, and watch the trend week to week. For a reference point, a median 30.7% of visible search-term spend went to terms with 2 or more clicks and zero conversions across the accounts in my Q3 2026 Google Ads benchmarks (N = 25). The cause is usually three or four ad groups the bid strategy won’t defund because its conversion signal arrives too rarely to retrain the model.

Impression share, split by budget and rank

The report: campaigns view with Search Lost IS (budget) and Search Lost IS (rank) added, week over week. Lost-to-budget means the campaign hits daily cap and Google would spend more. Lost-to-rank means it can’t win the auction at the bid and Quality Score it has. The two dictate completely different fixes: impressions lost to budget on a healthy conversion rate leave revenue on the table, while a large loss to rank means you’re paying up for the impressions you do win. Budget is the more common ceiling in my book. In 23 of 31 Search accounts in my Q3 2026 benchmarks, impression share lost to budget was larger than impression share lost to rank, and the median account lost 37.9% to budget against 26.2% to rank (N = 31). Read both columns before you raise a bid.

Read a sudden drop in impression share as an instruction to look rather than an instruction to bid, and read it alongside the budget column, because the three impression-share figures sum to 100% and a campaign losing most of its impressions to budget has a hard ceiling on what its rank column can report. Fixing the budget loss makes the rank number climb on its own. Lost-to-rank climbing while lost-to-budget falls toward zero can also be the correct resting state on an account whose bids were capped on purpose, and clearing the first-page floor is worth doing only when the implied cost per lead, divided by your close rate, still clears what a sale earns. Should I raise bids when the budget isn’t spending works that comparison through on an account where the answer was no.

Search campaigns: seven numbers behind three reports

The default view rewards more match types and more spend. These seven sit further in.

Search-term irrelevance rate

The report: search terms, last ninety days, cost descending. Tag the top two hundred queries relevant or irrelevant, divide irrelevant cost by total cost. Know what the report leaves out before you trust the ratio. Across the 11 accounts where I pulled every search-term row in Q3 2026, the terms Google showed covered a median 52% of account spend, with a range of 20% to 71% (N = 11). The irrelevance rate you calculate describes the visible half. Tight match types keep it low, and broad match needs closer reading. The fix is rarely a longer negative list. It’s tighter match types, audience signals on Performance Max, and a decision about where broad match operates.

Top-spend keyword performance

On most Search campaigns a handful of keywords carry most of the cost. Read them weekly: spend, clicks, conversions, conversion rate, CPA. One going off the rails masks a healthy account average for two or three weeks, so reading the ten weekly catches it on day seven instead of day twenty-one. First move: the search terms it triggered, and its match type.

Quality Score on top-spend keywords

The report: keywords view with Quality Score, Landing Page Experience, Ad Relevance, and Expected CTR added, cost descending. A score below 5 on a keyword taking more than a few percent of campaign spend is a warning sign. The score itself isn’t an auction input, but it summarizes the same three quality signals Ad Rank reads in real time. Don’t read it as a CPC verdict. Across 30 Google Ads accounts I manage, 30 days to October 21, 2026, the 7 accounts with enough clicks in both Quality Score bands (1 to 5 and 7 to 10) paid a median 0.98x as much per click on the low-score keywords, and low-score clicks cost more in only 3 of the 7 (N = 7, range 0.89x to 3.86x). Under Smart Bidding the bid moves too, so judge a weak score by cost per conversion. Three below 5 in the top ten by spend calls for a landing-page and ad-copy rebuild. Two is a warning. One is noise.

Monthly, widen to the top fifty and bucket them seven-or-higher, four-to-six, three-or-lower, plus a fourth bucket for keywords with no score. That last bucket is often the biggest. In my Q3 2026 benchmarks, a median 38% of keyword spend ran on keywords with no Quality Score reported, and a median 4% ran on keywords scored 7 to 10 (N = 31). A growing share slipping into the bottom bucket means the account’s ads and landing pages are drifting away from the queries it pays for.

Click-through rate on exact-match keywords

The report: keywords view filtered to match type equals exact, impressions descending. Read each keyword against its own history. A CTR that collapses with real impression volume means the keyword is matching queries it no longer represents, or the ad misses the intent.

Conversion rate by match type

The report: dimensions or segment view, segmented by match type at ad group level. Exact should convert highest, phrase lower, broad meaningfully lower than phrase. When the order inverts the data is lying, usually from a tracking de-duplication failure or searches for your own brand name slipping into broad. A broad-match rate that doubles the exact rate on the same keyword root often means broad is picking up people who were already looking for you. My default is that no campaign bids on the client’s own brand: the brand name and its misspellings sit as phrase-match negatives at the account level, and the one exception is a competitor’s ad holding the brand search above the organic result. The Tracking Stack reference covers the de-duplication contract.

Impression share by audience segment

The report: audiences view inside a campaign, impression share segmented by audience. Customer Match lists fed from email and SMS should clock the highest impression share and conversion rate, because logged-in past purchasers searching category terms are the cheapest conversions in the account. If they sit low while cold audiences absorb the spend, layer the audience as a bid modifier and raise the floor.

Top impression rate against rising CPC

The report: search campaigns view with Top Impression Rate, Absolute Top Impression Rate, and Average CPC added, last thirty days against the previous thirty. When top impression rate falls while CPC rises, you’re paying more per click for worse placement. You’re outbid on rank, not on budget, and more bid won’t recover the position.

Display and Performance Max: six numbers Google buries

Search has the search-terms report, where a bad query carries a name and a cost. Display has no equivalent. Google files placements under Insights, and Performance Max scrubs most of it into a “Placements where your ads appeared” download with no spend column. These placements can absorb a large share of the budget, and they rarely get audited.

Placement category share

The report: Insights or Where ads showed, sorted by cost, mobile-app placements broken out. Most meaningful engagement should come from a short list of placements. A thousand placements taking ten dollars each is the canonical Performance Max display leak. First move: export placements, sort by cost, exclude the long tail below a minimum click threshold. Thirty minutes in the account-level exclusion list at the MCC.

Viewability rate

The report: campaigns view with Active View Viewable Impressions divided by total impressions, or the Insights tab on Performance Max. Google’s Active View documentation defines a viewable display impression as fifty percent of the ad on screen for one second, and a viewable video impression as fifty percent on screen while playing for two seconds. Track it against its own history, and exclude the placements that drag it down.

Mobile-app placement spend

The report: placement type filter set to mobile-app in the Where ads showed view. The highest-friction inventory in the system: children’s games and lock-screen tap traps. Click-through rates look exceptional, conversion rates collapse, session duration sits under three seconds because most clicks were accidental. Exclude mobileappcategory::69500 (Games), then the Display Network mobile-app exclusion at account level. Performance Max takes the same exclusions through account-level placement exclusions, which most accounts never open.

View-through to click ratio

The report: conversions segmented by attribution type, view-through against click-through. A view-through conversion fires when someone saw the ad and converted later without clicking. Useful as a directional signal, dangerous as a KPI. When view-through conversions dwarf click conversions, the platform is claiming conversions off impressions that may never have been seen. Keep the view-through window short and keep those conversions out of any ROAS used to set bids. Four-times return on clicks and twelve-times on view-through is a campaign that needs the click number.

Audience overlap

The report: audience insights at campaign level with overlap percentage against Customer Match and remarketing lists. On Meta, the audience overlap tool. A prospecting campaign that overlaps the remarketing list is buying impressions on people who already converted, and retargeting would have reached them at a lower CPM. Performance Max does this constantly, firing at warm audiences because they convert faster and make the asset group look efficient. Meta fails differently: two prospecting ad sets on overlapping audiences bid against each other while both report as functional. First move: consolidate or rebuild into distinct buckets.

Engagement and session duration on paid traffic

The report: GA4 traffic-acquisition view, source filtered to paid, engaged sessions and average session duration against total sessions. GA4 counts a session as engaged if it lasts ten seconds or longer, fires a conversion event, or includes two or more pageviews. Read paid engagement against organic engagement on those same URLs. A paid segment far below organic means broad-match queries on irrelevant pages, app placements, or a page that renders slowly on mobile. Segment to display and read session duration: a cluster of sessions lasting a few seconds means accidental clicks dominate.

The monthly revenue check

Five numbers on the first Monday, all asking whether the spend turned into money.

Blended ROAS against Shopify

Compare platform-reported results against what the store recorded for the same range: Shopify Analytics, Reports, Sales by traffic source, and the Shopify orders GA4 attributes to paid search on a last-non-direct basis. The gap is the metric. Google Ads conversions within ten percent of those paid-search orders says the tracking stack is honest. On a multi-channel account, GA4 paid-channel conversions should land within fifteen percent of the sum of Google Ads and Meta reported conversions. Wider than either band says the platform is claiming results the store can’t see, and no bid change fixes a tracking problem. The Google Ads versus Shopify reconciliation lists the causes in the order I rule them out. Sales by referrer adds the second layer, showing referring URLs, and catches a click parameter stripped at checkout. First move: server-side conversions, a GA4 enhanced measurement audit, and a recheck of whether the consent banner is blocking the pixel.

New-customer ROAS

Total ROAS hides repeat purchases. A returning-customer order through a paid click is a margin loss most months, because that customer would have bought through email or direct. New-customer ROAS, isolated through Shopify customer reports or the platform’s new-customer acquisition column, says whether paid pays for itself. A blended ROAS of three-point-five against a new-customer ROAS of one-point-two means paid is subsidizing the existing-customer base rather than building one.

Primary conversions against all conversions

The report: conversions view with the Conversions and All conv. columns side by side, last thirty days, then the conversion actions list with every action’s category and primary or secondary status. The gap shows how much the account records that it doesn’t bid on, and it’s where non-lead actions hide. Across 22 lead-gen accounts in my Q3 2026 benchmarks, all conversions ran a median 2.3x primary conversions, and 5 of the 22 ran above 10x (N = 22). 6 of 29 lead-gen accounts counted a non-lead action or a click proxy as a primary conversion (N = 29). Read the category of every primary action, not its name. Broken conversion tracking is the most common finding in the audits I ran in 2026, and this screen is where it shows first.

Cost per conversion against target CPA

The report: campaigns view with Cost per Conversion and Target CPA visible, segmented by week for the last ninety days. A single week over target is noise. Several consecutive weeks well above target is structural. Both platforms let actual CPA roam above target on the belief a future conversion is likely, and three weeks of being wrong calls for a manual reset, not more learning time. The fix is a tighter conversion definition, a lower target, or a pause on the worst ad group.

Conversion volume against rising spend

The report: campaigns view with Cost and Conversions plotted as a time series, last six months, weekly. In a healthy account the lines move together; in a decaying one spend climbs while conversions flatten. The cause is audience saturation, creative fatigue past recovery, or a tracking change that broke attribution. Check whether the new cost per conversion still clears margin before you add budget.

The four reports that explain the numbers

Metrics say something moved. These four say why, in this order.

Auction insights, campaign and ad group level, top three spenders. Watch for impression share lost to budget rising on campaigns that used to clear inventory, and a new competitor in the top three with a high overlap rate. Fix: bid cap review, ad rank diagnosis, and a check on a competitor’s new price promotion.

Change history, the most under-used report in Google Ads. Filter the break period by change type: budget, bid strategy, Performance Max assets, conversion goals. Often one change explains the entire drop, usually a bid strategy switched to maximize conversions on thin conversion data. Fix: revert it and run the original strategy for a full conversion cycle.

The Performance Max asset report, next to the placement report. The asset report often shows the algorithm fixated on one headline or image that produces clicks and no orders. Fix: placement exclusions and asset group splits by intent.

GA4 landing pages: Pages and Screens, Session source / medium secondary, filtered to google / cpc, read against engagement rate. A page taking a big share of paid traffic at weak engagement and a low conversion rate is the leak, not the keyword that sent the click. Fix: rebuild it or reroute the traffic.

The cadence is the product

On a home-services client I monitor weekly, the Meta dashboard showed a large click count at a very low cost per click across the trailing ninety days. It looked excellent by every surface metric. The cadence caught what the dashboard didn’t: the campaigns were lead-form objectives where every form open registered as a click, and only a small fraction of those opens became completed forms. The founder would have kept scaling spend against the leak. A related gap is common: 9 of the 18 accounts in my Q3 2026 Meta benchmarks, carrying 42% of spend, optimized for no conversion event at all (N = 18). The metric that matters is rarely the metric the platform highlights.

If I open one number first it’s the zero-conversion spend share, the fastest read on whether the problem is tuning or structure. On Search that job belongs to search-term irrelevance, which distorts every metric downstream. On Display it’s placement category share: the long tail explains the collapsed viewability, the mobile-app spend, and the three-second sessions. The numbers matter less than reading them on the same day, in the same order, every week.

Run the free 25-page Setup Checklist for the diagnostic written out, use the Wasted Spend Calculator for a directional dollar figure from your spend and red-flag count, or read the wasted-ad-spend library. The services overview walks the structural fix. Founders who want me running this cadence can start with my free written audit, sent with read-only access.

When to bring me in

Bring me in when cost per lead keeps rising and the fixes above haven’t moved it, when you can’t tell which campaigns produce booked work, or when the search terms report shows money going to searches you’d never pick.

I'm Conner Crowe, and I write every audit myself. Send the free audit request and add me as a read-only user, and within 24 hours of access you'll have a written read on where the spend leaks and what to fix first. No call needed, and nothing in your account or store changes.

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