What you'll find in this article
- Why an inherited Google Ads account needs a structured audit before any optimization, and what happens when you skip it
- What to gather before touching the account: access, business context, and the historical baseline
- The complete Google Ads audit checklist in priority order, from conversion tracking to assets
- The red flags that signal a fundamentally broken account vs. one that just needs tuning
- What to do, and crucially what not to do, in the first 30 days after taking over
- How to turn the audit into a documented baseline that makes every later decision measurable
Taking over an existing Google Ads account is a fundamentally different task from building one from scratch. When you build, you control every decision and you know the reasoning behind each setting. When you inherit, you walk into a system of decisions you didn't make, made for reasons you don't know, on data you can't fully reconstruct. The temptation is to start "fixing" things immediately. That temptation is the single most expensive mistake in account handovers.
This article documents the Google Ads account audit process I've refined since 2021 across dozens of inherited accounts. It's not a generic best-practices list, it's the concrete operational sequence I follow, in the order I follow it, with the logic behind each step and the things experience has taught me to look for that no checklist template ever mentions. The same sequence holds whether you are handed two simple search campaigns or a sprawling mix of google ads campaigns spanning Search, Shopping, and Performance Max.
The structure of a proper audit has three phases: gathering context (before you open the account in any analytical sense), the diagnostic checklist (systematic verification, in priority order), and the baseline documentation (recording the account's state so that everything you change later is measurable against a known starting point). The order matters. An audit that jumps straight to "are the campaigns structured well?" without first verifying that conversions are tracked correctly is an audit built on numbers you can't trust.
Before you start: access, context, and the historical baseline
The first mistake in auditing an inherited account happens before you analyze anything: opening the account, seeing something that "looks wrong", and forming an opinion before you understand the context that produced it. A campaign structure that looks chaotic might be the residue of a deliberate test. A high CPA might reflect a deliberate brand-awareness phase. Context first, judgment second.
Before the analytical work, I make sure I have three things in place.
1. The right level of access, and your own access
Confirm you have admin (or at least standard) access to the Google Ads account itself, and critically, visibility into the surrounding ecosystem: the linked Google Analytics 4 property, Google Merchant Center if it's e-commerce, Google Tag Manager, and Search Console. An audit limited to the Google Ads interface alone misses half the picture, because conversion tracking, the foundation of everything, usually lives partly outside Google Ads. Google's own guidance on account access levels is documented at About access levels in your Google Ads account.
I now insist on my own access being granted through my own manager (MCC) account, never logging into a shared login the previous manager used. Twice early in my career I audited an account through credentials that were revoked mid-audit when the previous agency was offboarded, losing access to the work in progress and, worse, to the change history I was reconstructing. Linking the account to my MCC also gives me the change history under my own identity going forward, so every edit to the campaigns and ads is attributable, which is the first brick of the documented baseline.
2. Business context that the interface can't tell you
Before reading a single metric, I get answers to a short set of questions from the client: What is the actual business goal of this account, leads, sales, revenue, ROAS target? What is the true margin and customer value, so I can judge whether the current CPA is healthy or catastrophic? Were there recent events, a website migration, a rebrand, a seasonal peak, a budget freeze, that explain anomalies in the data? Has the conversion setup changed in the period I'm about to analyze? An account that looks like it "collapsed" three months ago might simply have switched its conversion action at that point, making the before/after incomparable.
3. The historical baseline, captured before you change anything
The most important pre-audit action is exporting and saving the account's performance over the last 12 months at campaign level, before you touch anything. This is your immutable record of "the account as inherited." Once you start making changes, this baseline is the only thing that lets you prove, to the client and to yourself, what the account looked like at handover and what your work changed. I export 12 months of monthly data (spend, conversions, CPA, ROAS, conversion value, impression share) per campaign and store it outside the account.
Across the inherited accounts I've audited, the ones where I captured a clean 12-month baseline before any change were dramatically easier to defend in the first client review. When performance dipped in week three (often for reasons unrelated to me, learning-phase noise, seasonality), I could point to the documented starting point and the documented changes, and separate signal from coincidence. In the accounts where I skipped this step early on, I had no way to counter the "performance got worse since you took over" conversation with anything but assertion. This isn't something Google documents, it's a pattern that became obvious only after getting burned by its absence.
The operational audit checklist, in priority order
The Google Ads audit checklist below is ordered by diagnostic dependency, not by where the items appear in the interface. Each step produces information needed to interpret the next one correctly. Auditing campaign performance before verifying conversion tracking is like evaluating a patient's blood pressure with a broken cuff: every number after that is suspect.
1. Conversion tracking, the foundation of everything
This is where every audit must begin, and where I spend the largest share of the total time. In Tools > Conversions, I inventory every conversion action and check, for each: its status (is it recording conversions, or showing "No recent conversions"?), its source (website tag, GA4 import, Google Analytics, offline import), its count setting (One vs. Every, which should be "One" for lead-gen and "Every" for e-commerce, getting this wrong inflates or deflates the entire account), its category, and whether it's included in the main "Conversions" column or only in "All conversions." Google's reference on counting is at About conversion counting options, and the broader setup guidance at About conversion tracking.
Then the single most important check of the entire audit: reconcile Google Ads reported conversions against an independent source of truth. For e-commerce, that's the backend order count or GA4 purchases; for lead-gen, the CRM. Compare the same date range. A gap of roughly 10–15% is normal and expected, attribution models, time lags, and cross-device differences all contribute. A gap of 40%, or a number that swings wildly month to month, is a tracking problem that invalidates every performance metric in the account.
The most common, and most damaging, problem I find in inherited accounts is double-counted conversions. The classic pattern: a website purchase is tracked both by a Google Ads tag and by an imported GA4 conversion, both feeding the Conversions column. The account looks like it's running at a 6x ROAS; the business is actually at 3x and wondering why the "great" Google Ads numbers don't show up in the bank account. I've inherited at least five accounts where the previous manager had been optimizing toward a target ROAS that was structurally double the real one. Until that's fixed, no other optimization matters, the bidding algorithm is being fed a fictional reward signal.
2. Account structure and the "what is actually running" map
With tracking understood, I map what's actually live. Not the theoretical structure, what is genuinely spending. I sort all campaigns by cost over the last 90 days and immediately see where the money goes. Frequently 80% of spend sits in two or three campaigns, and a long tail of paused, near-zero, or zombie campaigns clutters the account. I note campaign types (Search, Performance Max, Shopping, Display, Demand Gen), how they overlap, and whether multiple campaigns are competing for the same queries, a common inherited-account problem where Search and Performance Max cannibalize each other.
3. Budget and bidding strategy review
For each significant campaign I check the bidding strategy and whether it's appropriate for the campaign's conversion volume. A Target ROAS or Target CPA strategy on a campaign with very few weekly conversions is a frequent inherited problem, the algorithm doesn't have enough signal to optimize, producing volatile results the previous manager may have been fighting blindly. I also check for budgets that are constantly capped (impression share lost to budget) versus budgets that never spend in full, both signal misallocation. The goal is to concentrate spend on the structurally high converting campaigns and starve the ones that only look active. Google's overview of Smart Bidding is at About Smart Bidding.
In inherited accounts, I've repeatedly found that the bidding strategy listed in the campaign settings doesn't match the strategy the account is effectively pursuing, because the conversion goals feeding it were changed at some point without resetting expectations. A campaign nominally on "Maximize conversion value with a target ROAS" but with the target set unrealistically high behaves, in practice, like a coverage-throttled campaign that never spends. Google's documentation describes how each strategy is supposed to work; what the documentation can't tell you is that an inherited strategy is only as good as the conversion data it was historically fed, and that history is often the real problem, not the strategy label.
4. Search terms, match types, and negative keyword hygiene
For accounts with Search or Shopping campaigns, the search terms report over the last 90 days, sorted by cost, reveals how clean the account really is. I look for high-spend terms with zero conversions, terms that are clearly off-target (informational queries in a transactional account, competitor or brand terms you don't want to pay for, irrelevant variants), and whether a coherent negative keyword strategy exists at all. I also check how the account chooses to match keywords to queries, because a legacy broad match setup running without Smart Bidding or solid negatives is one of the fastest ways an inherited account leaks budget. Negatives must be applied at the correct level too, deciding for each one whether it belongs to a single campaign or ad group rather than being scattered inconsistently. An inherited account with no negative keyword lists, or with lists that haven't been touched in a year, is almost always leaking budget on irrelevant traffic.
5. Quality Score, audiences, signals, and remarketing setup
For Search campaigns I review your quality score at the keyword level, because consistently low scores often point to a mismatch between keyword, ad, and destination that has been quietly inflating CPCs for months. Then I check what audience data the account is collecting and whether it's being used. Are remarketing lists populated and large enough to be usable? Is Customer Match set up, and is the list fresh? For Performance Max campaigns, what audience signals are attached to each asset group? An account that has been running for a year but has no usable first-party audience data has been leaving one of its most valuable assets uncollected, and that's both a finding and an opportunity for the audit to surface.
6. Ads, assets, and creative health
Finally, the creative layer. For Responsive Search Ads I check ad strength, the number of active ads per ad group, whether headlines and descriptions are actually differentiated or just padded to fill slots, and whether the calls to action are clear and varied rather than repeated across every asset. I also confirm that each ad sends traffic to a relevant landing page that matches the promise of the ad, since a strong creative pointed at a weak or off-topic page wastes the click. For Performance Max and Demand Gen, I review asset group ratings (Low/Good/Best) and whether image, video, and text assets are present and varied. Missing video assets in Performance Max, for instance, mean Google auto-generates them, often poorly, which is a quick, visible finding for the audit report.
7. Settings, locations, schedules, and the "set and forgotten" layer
The last sweep covers the settings that quietly distort accounts: location targeting set to "presence or interest" when it should be "presence" (a frequent source of irrelevant international traffic), ad schedules and bid adjustments left over from an old strategy, device adjustments that no longer make sense, and network settings (Search Partners, Display Network expansion) silently enabled. Google's note on location options is at About location targeting. These settings rarely cause dramatic failures, but in aggregate they erode efficiency, and they're the kind of thing that accumulates in an account passed between managers.
Red flags: telling a broken account from one that just needs tuning
Not every problem found in an audit carries the same weight. Part of the audit's value is classifying findings by severity, so the client understands the difference between "this needs fixing eventually" and "this is actively destroying money right now." I sort findings into three tiers.
The most dangerous inherited account isn't the obviously broken one, it's the one that looks like it's performing brilliantly. When I take over an account showing suspiciously good numbers, a 9x ROAS in a category where 3–4x is normal, my first assumption is a tracking problem, not a genius predecessor. Nine times out of ten in my experience, "too good to be true" performance in an inherited account traces back to conversion double-counting or a soft conversion (newsletter signup, add-to-cart) being counted as a primary conversion. Auditing the suspiciously good account with the same suspicion as the obviously bad one has saved me from inheriting someone else's measurement fiction and being blamed when it "broke" on my watch.
The first 30 days: what to do, and what not to do
The audit produces a prioritized list of findings. The instinct, and often the client's expectation, is to act on all of them immediately. This is exactly where discipline matters most, because an inherited account that has been running on automated bidding has accumulated a learning history, and aggressive changes throw it into instability precisely when you most need clean data to understand what you've taken on.
Fix immediately: the money-losing critical findings
The only changes I make in the first days are the critical-tier findings, the ones costing money or corrupting data every day they persist. Broken or double-counted tracking gets fixed first (and the baseline annotated with the date, so the before/after discontinuity is documented). Obvious budget hemorrhages, a campaign serving on a clearly irrelevant high-cost term, a duplicate campaign double-spending, get stopped. These are not optimizations, they're stopping active damage.
Wait and observe: everything else
For the significant and improvement tiers, I deliberately wait. The first two to four weeks are for watching the account behave with correct measurement in place, now that tracking is trustworthy. Many "problems" identified in the audit look different once you can see them measured correctly. A campaign that looked like a poor performer under double-counted tracking may turn out fine once the measurement is honest, or vice versa.
The pattern I've seen repeatedly: the accounts where I changed many things in the first week consistently took longer to stabilize and produced murkier results than the accounts where I fixed only the critical issues and then waited. When you change tracking, bids, budgets, and structure all at once, you lose the ability to attribute any subsequent change in performance to any specific action, and the automated bidding strategies re-enter learning simultaneously, compounding the noise. Google's documentation confirms that significant changes trigger a learning period; what it doesn't quantify is how badly several simultaneous changes interact in a single account. From repeated observation, sequencing changes one variable at a time, after the audit, produces both better results and a clearer story to tell the client.
Turn the audit into a living baseline document
The final deliverable of the audit isn't a one-time PDF, it's the foundation of the account's ongoing decision log. I record the inherited state (the 12-month baseline), the audit findings classified by severity, the critical fixes made and their dates, and the planned sequence for addressing the rest. Every change from that point forward gets logged against this document. Six months later, this is the single most valuable artifact in the account, it's the difference between "I think things got better" and "here is exactly what was wrong at handover, what I changed, when, and what each change produced."