How do I optimize my bidding strategy?

Start by matching your bid strategy to what “winning” actually means for your business

Before you touch targets or budgets, get brutally clear on your primary outcome. In Google Ads today, most bidding “optimization” mistakes happen because advertisers choose a strategy that optimizes the wrong thing (or optimizes the right thing using the wrong data).

If your goal is to generate as many actions as possible (leads, purchases, sign-ups) within your budget, you’ll typically be best served by Maximize conversions, optionally paired with a target CPA to put guardrails around efficiency. If your goal is to generate the most valuable outcomes (revenue, profit, qualified pipeline) you’ll usually outperform conversion-volume bidding by moving to Maximize conversion value, optionally paired with a target ROAS to control return.

In competitive markets, the “secret” is rarely a clever bid tweak—it’s switching from optimizing for count to optimizing for value, then feeding the system clean value signals so it can bid more aggressively only when the auction is likely to produce better customers.

Quick reality check: what you can (and can’t) control with Smart Bidding

Smart Bidding sets bids at auction-time using a wide range of signals (such as device, location, time, query intent, and audience signals). That’s exactly why it can beat manual bidding in volatile, competitive auctions. The tradeoff is that you should stop thinking in terms of “keyword bids” and start thinking in terms of inputs (conversion measurement, values, targets, budgets) and feedback loops (learning periods, conversion delay, reports).

Also note that for Search and Display, Enhanced CPC was deprecated effective the week of March 31, 2025. If you were relying on ECPC as a “light automation” option, many accounts effectively ended up back on manual-style behavior unless proactively migrated. Practically speaking, that makes Smart Bidding (tCPA/tROAS or the Maximize strategies) the main performance path for most advertisers who want algorithmic bidding.

Build the measurement foundation first (because bidding can only optimize what you measure)

Optimizing bidding without fixing measurement is like tuning a race car using a broken speedometer. You can make changes, but you won’t know what’s real—and automated bidding will learn the wrong patterns.

At a minimum, ensure conversion tracking is enabled and stable, and that the conversion actions you want the bidder to use are actually included in the account’s “Conversions” reporting (that inclusion setting governs what most conversion-based bidding strategies optimize toward). If you remove or break conversion tracking for the actions used by bidding, conversion-based strategies can stop serving or collapse performance because the system loses its feedback signal.

Shift from “any conversion” to “the right conversion” (especially for leads)

If you generate leads, don’t let the bidder optimize on the easiest-to-get form fills if those leads don’t turn into revenue. Pick one clear stage of your funnel to optimize toward—ideally a stage with a relatively short conversion delay and enough monthly volume to train the system reliably (a common minimum threshold is around 15 conversions per month for many value-based setups). Then feed quality back into the platform via offline imports and/or enhanced conversions so bidding learns which clicks create the best downstream outcomes.

For value-based bidding to work, you need meaningful values. If you can’t pass true revenue or profit, start with proxy values (lead scoring, product-tier values, qualified vs. unqualified lead values) and improve them over time.

Use conversion value rules to steer value-based bidding without fragmenting campaigns

Conversion value rules let you adjust the value recorded for a conversion based on conditions like audience, device, and location. That’s a powerful lever in competitive markets because it helps you tell the bidder, “A conversion from this type of user is worth more than a conversion from that type of user,” which is often closer to real business economics.

Use these rules to reflect reality (higher LTV audiences, stronger geographies, higher-intent device segments), but keep them consistent and defensible. Overly aggressive multipliers can “poison” learning by making the system chase inflated value signals.

Optimize the system the right way: targets, budgets, learning time, and the feedback loop

Once measurement is solid, bidding optimization becomes a disciplined process. The highest-leverage work is usually: set the right target, give the system enough budget room to find conversions, and evaluate performance on time windows that respect conversion delay.

Set initial targets based on history, then adjust deliberately (not emotionally)

Targets are not just “preferences”—they directly change how aggressively the system bids. As a rule, if you want more volume, you typically raise your target CPA or lower your target ROAS. If you want more efficiency, you typically lower your target CPA or raise your target ROAS. Expect spend and volume to move meaningfully when you make major target changes.

When you’re unsure where to set targets, use simulator tooling and bid strategy reporting to estimate the tradeoff between volume and efficiency. This is especially important in competitive markets where “slightly too strict” targets can choke traffic, while “slightly too loose” targets can spike spend with weak returns.

• If you want to scale spend: increase target CPA or reduce target ROAS gradually, then reassess after enough time has passed for conversions to report.
• If you need profitability fast: decrease target CPA or increase target ROAS, but expect conversion volume to drop as the system becomes more selective.
• If you’re using target ROAS: don’t constrain budgets too tightly—overly constrained budgets can prevent the strategy from reaching the auctions needed to hit your value goal.

Respect the learning period and conversion delay (this is where most “optimizations” go wrong)

After meaningful changes—new bid strategy, target changes, structural changes, or adding/removing campaigns/keywords from a portfolio—the bid strategy may enter a Learning state. During this calibration time, fluctuations are normal. Depending on volume and conversion cycle length, calibration can take up to roughly 50 conversion events or about 3 conversion cycles to settle toward the new objective.

Separately, always account for conversion delay (the time between click and conversion). If you evaluate performance including very recent days, CPA can look artificially high and ROAS artificially low because conversions haven’t fully reported yet. A disciplined approach is to evaluate in windows that include at least two full conversion cycles, and for many advertisers, longer windows (like a month or at least ~50 conversions) produce more reliable conclusions.

A critical best practice: avoid making multiple target changes inside a single conversion cycle unless there’s a true business emergency. When targets change faster than conversions report, you end up training the system against shifting goals with incomplete feedback, which commonly creates volatility and underperformance.

Advanced controls for competitive markets: fix constraints, then use the right “override” tools

When you’re in a crowded auction, performance problems are often caused by constraints that quietly block the bidder from doing its job. The fastest wins usually come from diagnosing those constraints and removing them before you touch creative, keywords, or landing pages.

Use bid strategy status as your diagnostic starting point

Bid strategy statuses are designed to tell you what’s limiting performance “under the hood.” For example, a strategy can be limited by inventory (not enough eligible volume), by bid limits (max/min constraints preventing optimal bids), or by being budget constrained (can’t bid enough to achieve the goal). You want to resolve these first, because no amount of target tweaking will fix a strategy that’s fundamentally handcuffed.

• If you’re limited by inventory: expand relevant targeting (for Search, that may mean adding coverage, using broader match where appropriate, or expanding to additional intent themes) so the system has enough auctions to learn and compete.
• If you’re limited by bid limits: remove or relax max/min bid limits. In competitive markets, strict limits frequently suppress volume and prevent the bidder from entering the auctions that actually convert.
• If you’re budget constrained: either raise budget or tighten targets (depending on whether your priority is volume or efficiency). Don’t expect stable ROAS/CPA if budget is constantly choking the strategy’s ability to participate.

Know how bid adjustments behave under Smart Bidding

With Smart Bidding strategies like target ROAS and Maximize conversions, most traditional bid adjustments are not used the way advertisers expect. In many cases, the cleanest way to “steer” performance is to segment campaigns by intent, geography, or product economics and set different targets, rather than trying to force granular bid modifiers on top of automation. One notable exception that remains useful is the ability to exclude a device by setting a device adjustment to -100%.

Use seasonality adjustments for short, exceptional events—not normal seasonal swings

Seasonality adjustments are an advanced tool meant for predictable, short-lived conversion rate shocks—think a 72-hour flash sale where you genuinely expect conversion rate to jump meaningfully beyond normal patterns. They’re best used for short events (often 1–7 days) and generally don’t perform as well when stretched beyond about two weeks. Importantly, you shouldn’t use them for typical seasonal periods where user mix shifts gradually; Smart Bidding is already designed to account for that.

Use data exclusions when conversion tracking breaks (and do it fast)

When tracking fails—tag removed, site outage, import outage—Smart Bidding can “learn” that conversion rate collapsed and start bidding down aggressively. Data exclusions help reduce the impact by preventing the strategy from using the bad conversion data for optimization (while still keeping the reporting visible in your account).

The key operational detail is that exclusions apply to clicks, so you must exclude the click dates that would have produced the missing conversions, factoring in your typical conversion delay. Apply exclusions as soon as you identify the issue, then watch performance as the exclusion takes effect and be prepared to adjust targets and budgets temporarily to keep spend within comfort while the system stabilizes.

If you’re optimizing your bidding strategy in Google Ads, it helps to start by matching the bid strategy to your real business goal (volume vs. value), then make sure your measurement is solid (only the right primary conversions, reliable values, and no tracking gaps), and finally tune targets like tCPA or tROAS patiently enough to get through learning and conversion delay before judging results; when something breaks (like tracking outages), using data exclusions can also prevent Smart Bidding from “learning” the wrong signals. If you want a practical way to stay on top of these checks without living in bid reports, Blobr connects to your Google Ads and runs specialized AI agents that continuously review bids, budgets, conversion signals, and landing-page alignment, then turns best practices into clear, prioritized actions you can apply when you’re ready.