Why Smart Bidding Pushes Every Advertiser to Their Maximum—And What You Can Do About It
November 2025
The moment you enter a Target CPA, you've already lost the negotiation.
When you set a tCPA or tROAS target in Google Ads, you reveal your economic maximum. Google's Smart Bidding then derives the effective CPC it can bid on your behalf—based on your target and your historical conversion rate. In competitive markets, auction dynamics push all advertisers toward their maximums, creating a Nash Equilibrium where everyone pays as much as they can afford.
Your impression share isn't determined by your skill as a media buyer. It's determined by a simple formula:
You don't set the CPC—Google derives it. Your conversion rate is a historical constant. The only levers you control are your target CPA (determined by business economics) and your conversion rate (improved through CRO). This paper explains the mechanism, the behavioral psychology that accelerates it, and the strategic options available to you.
The moment you enter a Target CPA, you've already lost the negotiation.
When you set a Target CPA (tCPA) or Target ROAS (tROAS), you aren't just giving Google a bidding instruction—you're revealing the maximum you can economically afford to pay for a customer. Google now knows your margin.
Google's Smart Bidding then optimizes toward that target—not below it. If the market could deliver leads at $17.50 CPA but you've told Google your target is $25, the algorithm will bid higher to capture more volume, pushing your actual CPA toward your stated ceiling. It costs Google a fraction of a penny to serve each ad impression. Every dollar between your minimum viable CPA and your maximum tolerable CPA represents value captured by the auction.
Information asymmetry is a well-documented source of market inefficiency in economics (Akerlof, 1970; Stiglitz, 2000). Google's position represents an extreme version: perfect information about all bidders, selling to bidders with no information about each other.
What Google knows: Every advertiser's target CPA/ROAS, conversion rates, quality scores, bid ceilings, historical performance, and exactly how each advertiser responds to competitive pressure.
What you know: Your own economics. That's it.
This isn't illegal or unethical—it's the nature of the platform. But it's worth naming as a structural feature that systematically advantages the auction operator.
The Bid Ceiling Model explains why your impression share is largely predetermined by your business economics—not your media buying skill.
Your effective CPC ceiling is determined by two factors:
Or equivalently, for tROAS bidding:
This formula determines what CPC Google can bid on your behalf. The weighted average of all competitors' implied max CPCs determines where the market clears. Your share is the gap between these two numbers.
The tCPA formula is unambiguous—your target is the answer. The tROAS formula is murkier because "AOV" can mean different things depending on your business economics and capital structure.
In practice, what belongs in the numerator is your Recoverable Value—the economic value you can actually capture from a conversion:
| Company Type | Recoverable Value | Rationale |
|---|---|---|
| Cash-constrained | Contribution Margin | Can only spend what the first order earns after all variable costs |
| Proven retention | CM × LTV multiplier | Knows lifetime value from data, can fund the payback gap |
| VC/PE-backed | CM × projected LTV | Can afford to lose money on the first order |
A bootstrapped e-commerce company with $30 AOV but only $15.60 contribution margin should set tROAS targets against $15.60—not $30. A venture-funded competitor might use $45 (3× contribution margin) because their capital structure supports a longer payback period. Same product, same AOV, radically different recoverable values—and therefore different implied max CPCs.
A critical clarification: you don't set a CPC. You set a tCPA or tROAS target. Google then derives the effective CPC it can bid based on your target and your historical conversion rate.
| What You Control | What's Fixed (Historical) | What Google Derives |
|---|---|---|
| Target CPA or Target ROAS | Conversion Rate | Implied Max CPC |
Conversion rate is an input, not an output of bidding strategy. Your CR is your historical performance—typically calculated over a lookback window like the last 30-90 days. It's a constant at any point in time. You cannot change your conversion rate by adjusting bid settings. You can only change it by improving your landing pages, offers, audience targeting, or ad creative—i.e., through CRO.
The "implied max CPC" is really an average ceiling. In practice, Google doesn't bid the same amount for every click. It varies bids based on predicted conversion probability for each individual auction:
High-intent signals (returning visitor, specific keyword, time of day patterns) → Google predicts higher CR → Bids above average
Low-intent signals (new visitor, broad match, unusual time) → Google predicts lower CR → Bids below average
Average across all auctions → Approaches your target CPA
Example with $25 tCPA and 17% average CR (implied max CPC = $4.25):
| Auction | Predicted CR | Google Bids | Logic |
|---|---|---|---|
| High-intent | 28% | $7.00 | $25 × 28% |
| Medium-intent | 17% | $4.25 | $25 × 17% |
| Low-intent | 8% | $2.00 | $25 × 8% |
| Blended Avg | 17% | ~$4.25 | → $25 CPA |
The algorithm's goal is to average toward your target across all auctions. It bids aggressively when it's confident in conversion, conservatively when it's not. But the ceiling—the average it won't exceed—is still determined by your target × your historical CR.
What happens if you set a target CPA that's mathematically impossible given your conversion rate and competitive CPCs?
Example: The market requires ~$3.75 CPC to be competitive. Your actual CR is 5%. At 5% CR and $3.75 CPC, the achievable CPA is $3.75 ÷ 5% = $75.
But you set tCPA = $25, hoping for better results.
Your implied max CPC: $25 × 5% = $1.25
Competitive CPC required: $3.75
Gap: $1.25 cannot compete against $3.75
Google's response: "Your target CPA is below your historical CPA. Ad serving will be limited." Google won't just burn your budget. It limits serving when your target is unreachable given your historical CR and the competitive landscape.
What would make $25 tCPA achievable? You'd need: $3.75 = $25 × CR, which means CR = 15%. A $25 tCPA only works if your conversion rate is 15%, not 5%. This is why CRO is the primary lever for competing at your business-economic CPA limit.
Google Search Ads uses a generalized second-price auction. You don't automatically pay your maximum bid—you pay just enough to beat the next competitor's Ad Rank.
In theory, this means you could pay significantly less than your maximum. In practice, in competitive markets with many advertisers bidding near their ceilings, prices converge toward those maximums.
When the second-highest bidder is at $8.50 and you're willing to pay $9.00, you pay $8.51—not much below your max.
A natural question: if everyone bidding their maximum is bad for advertisers collectively, why don't they coordinate to bid less?
The answer is mechanism design. Google's auction structure makes cooperation impossible:
Sealed bids. You can't see what competitors are bidding in real-time.
Continuous auctions. Millions of auctions per day make coordination logistically impossible.
Profitable defection. If others bid low and you bid your maximum, you capture all the volume.
Legal constraints. Explicit bid coordination would violate antitrust law.
Your CPA ceiling is a function of your business economics:
Average Order Value (AOV) or deal size
Customer Lifetime Value (LTV) and repeat purchase rates
Unit economics: COGS, fulfillment, overhead
Refund and chargeback rates
Growth vs. profit orientation
This last factor is critical. A PE-owned company focused on contribution margin will bid conservatively. A venture-funded company willing to spend 80% of LTV on acquisition might accept minimal returns. Same market, radically different maximum bids.
When a company says they can "afford to pay 3× the cart value," they're not being irrational—they're using a different number in the formula. If your first-order contribution margin is $15 but your proven LTV multiplier is 3×, your recoverable value is $45. You can fund a $35 CPA that looks insane to a competitor who only sees first-order economics.
This is why capital structure is a competitive weapon in paid acquisition. The company with:
Better retention data (proven LTV) can justify higher CPAs with confidence.
Lower cost of capital (can float the payback period) doesn't need immediate returns.
Higher risk tolerance (willing to bet on projected LTV) can outbid conservative competitors.
...can put a larger number in the numerator of the tROAS formula, resulting in a higher implied max CPC, resulting in more impression share. They're not better at media buying—they're playing a different game with different inputs.
| Scenario | First Order CM | LTV Multiplier | Recoverable Value | Sustainable CPA |
|---|---|---|---|---|
| Conservative (bootstrapped) | $15.60 | 1× | $15.60 | ~$10-12 |
| Moderate (proven retention) | $15.60 | 2× | $31.20 | ~$20-25 |
| Aggressive (VC-funded) | $15.60 | 3× | $46.80 | ~$30-35 |
Same product. Same first-order economics. But sustainable CPAs ranging from $10 to $35—a 3.5× spread—driven entirely by LTV assumptions and capital structure.
Consider the Medicare Supplement insurance vertical:
Policy commission: $350/year, paid over 6 years ($2,100 total LTV)
Cash flow reality: 9-month advance when you sell a policy (~$260 upfront)
The rest is paid over years
| Company Type | Max CPA | Payback Logic | Cash Constraint |
|---|---|---|---|
| Bootstrapped Startup | $260 | Immediate | 9-month advance only |
| Funded Company | $600 | ~2 years | Can float the gap |
| Multi-Billion Parent | $1,000 | ~3 years | Unlimited runway |
Same market. Same leads. Same product. Maximum CPAs ranging from $260 to $1,000—a 4x spread—driven entirely by capital structure and payback tolerance.
Here's the Medicare Supplement funnel for a funded company targeting $600 customer CPA:
| Funnel Stage | Rate | Max Cost at Stage |
|---|---|---|
| Target CPA (customer) | — | $600 |
| Close rate (contacted → customer) | 1 in 7 (14.3%) | $600 ÷ 7 = $85.71 |
| Contact rate (lead → answers phone) | 30% | $85.71 × 0.30 = $25.71 |
| → Target CPA for web lead (tCPA) | — | ~$25 |
| Click → Lead conversion rate | 17% | $25 × 0.17 = $4.25 |
| → Implied Maximum CPC | — | $4.25 |
A competitor with a $1,000 CPA tolerance can have an implied max CPC of $7.29 at the same 17% conversion rate. Google will systematically bid higher for them—not because they're smarter, but because their business economics allow it.
The market CPC isn't set by any single bidder—it's the weighted average of all bidders' implied max CPCs, weighted by their impression share. This weighted average represents the competitive floor you need to meet to maintain or grow your share.
| Advertiser | Share | tCPA | CR | Max CPC | Contrib. | Type |
|---|---|---|---|---|---|---|
| Giant A | 30% | $50 | 22% | $11.00 | $3.30 | VC-funded |
| Large B | 22% | $45 | 20% | $9.00 | $1.98 | PE-backed |
| Medium C | 18% | $40 | 18% | $7.20 | $1.30 | Scale-up |
| Medium D | 12% | $40 | 15% | $6.00 | $0.72 | Weak CR |
| Small E | 8% | $35 | 16% | $5.60 | $0.45 | Conservative |
| Small F | 6% | $30 | 15% | $4.50 | $0.27 | Cash-limited |
| You | 4% | $25 | 17% | $4.25 | $0.17 | Lower CPA |
| TOTAL | 100% | $8.19 | Wtd Avg |
Your implied max CPC is $4.25. The market's weighted average is $8.19. You are structurally locked out of growing beyond ~4% impression share at your current economics and conversion rate.
To reach 10% impression share, you'd need an implied max CPC around $8.19. At your 17% conversion rate, that requires a tCPA of $48.18—almost double your $25 target. Your business economics won't support it.
Understanding the formula explains the current state. But how did everyone end up at their maximum? Through a predictable cycle driven by well-documented psychological mechanisms.
The largest, best-funded competitors enter the auction with the highest CPAs, the best conversion rates, and the highest Quality Scores. In our example, Giant A (30%) and Large B (22%) control 52% of the market. Their high implied CPCs dominate the weighted average.
Now Google's Auction Insights report enters the picture. It shows every advertiser their impression share relative to competitors. This isn't just data—it's a set of psychological triggers:
Loss Aversion (Kahneman & Tversky, 1979). Humans experience losses roughly twice as intensely as equivalent gains. Watching impression share decline from 10% to 6% feels like losing—even if 6% at your target CPA is perfectly profitable.
Competitive Arousal (Malhotra, 2010; Ku et al., 2005). Laboratory and field research shows that auction participants systematically overbid when they perceive direct competition. The presence of identifiable competitors triggers emotional arousal that overrides rational calculation.
Social Comparison Theory (Festinger, 1954). Humans evaluate their standing by comparing to others, not by absolute measures. Auction Insights provides an explicit leaderboard.
Zero-Sum Framing. Impression share feels zero-sum: if they have 30%, that's 30% you don't have. In reality, profitability is not zero-sum—but the framing obscures this.
Organizational Incentive Misalignment. Marketing leaders are often evaluated on volume and market share—not marginal profitability. A CMO who "lost share to competitors" faces career risk, even if holding share would have required unprofitable bids.
Sunk Cost and Commitment Escalation (Staw, 1976). Once you've invested in a market—built the landing pages, trained the team—abandoning share feels like admitting failure.
As each advertiser adjusts their targets upward to recapture share, the weighted average rises. Eventually, every advertiser is paying their economic maximum. The auction has reached Nash Equilibrium—a state where no player can improve their outcome by unilaterally changing strategy.
If everyone had simply bid $3 CPC, the market-clearing CPA would be far lower. But no individual advertiser has an incentive to bid below their maximum if doing so means losing volume. This isn't manipulation—it's where rational self-interest leads.
Everything above assumes a stable pool of search impressions. But that pool is shrinking.
Large language models—ChatGPT, Claude, Perplexity, Google's AI Overviews—are intercepting queries that would have gone to traditional search. Informational queries ("what is X," "how do I Y") increasingly get answered directly by AI without a search results page.
The denominator shrinks. If total eligible impressions decline, the pool you're competing for gets smaller.
Supply decreases, demand stays constant. If advertiser budgets remain stable but available impressions decline, competition intensifies. CPCs rise mechanically.
Remaining queries may be higher intent. Informational queries go to AI; commercial queries ("buy X," "X pricing") still go to search. Competition concentrates on highest-value queries.
The escalation cycle accelerates. With a smaller pie, the same competitive dynamics play out in a more compressed space.
If you were structurally limited to 4% of a large market, you're now limited to 4% of a smaller market. Same constraints, fewer absolute impressions. The window for paid search as a scalable acquisition channel may be narrowing.
The right strategy depends on your position in the market.
Your position: You set the floor. Your high CPAs and strong conversion rates dominate the weighted average. Smaller competitors must either match your economics or accept smaller share.
Your position: You're in the squeeze. You can see the leaders' share, feel the pressure to catch up, but likely can't match their economics. This is the danger zone for unprofitable escalation.
Your position: You're structurally locked out of significant share in the main auction. Trying to scale through higher bids will likely destroy your economics.
Because conversion rate is a fixed input to the bidding formula, A/B testing and conversion rate optimization (CRO) are the most important levers for competing in tCPA strategies.
Return to the formula: Implied Max CPC = Target CPA × Conversion Rate
Your target CPA is fixed by your business economics—you can't afford more than $25 per lead. But your conversion rate is improvable through landing page optimization, offer testing, audience targeting, and ad creative.
| Scenario | tCPA | CR | Implied Max CPC |
|---|---|---|---|
| Before CRO | $25 | 17% | $4.25 |
| After CRO (+50% CR) | $25 | 25.5% | $6.38 |
A 50% improvement in conversion rate (17% → 25.5%) raises your implied max CPC by 50% ($4.25 → $6.38)—without changing your business economics or CPA target. You're now competitive against advertisers you couldn't touch before.
This is why CRO isn't just a "nice to have" in Smart Bidding strategies. It's the primary mechanism for gaining impression share at your economic limit.
When you improve conversion rate on tROAS bidding, you face a strategic choice:
Option A: Gain Impression Share
Keep your tROAS target constant. As CR increases, your implied max CPC increases. Google bids higher for you, you win more auctions, you gain share.
Option B: Improve Profitability
Raise your tROAS target proportionally to your CR improvement. Your implied max CPC stays the same—you maintain your position—but you're now converting more visitors on the same number of clicks.
| Scenario | CR | tROAS | Max CPC | Result |
|---|---|---|---|---|
| Before CRO | 3% | 200% | $3.00 | Baseline |
| Option A: Gain Share | 5% | 200% | $5.00 | ↑ CPC, ↑ Share |
| Option B: Profit | 5% | 333% | $3.00 | Same CPC, ↑ ROAS |
In Option B, you raise tROAS from 200% to 333%. Your max CPC stays at $3.00—you don't lose impression share. But now you're converting 5% instead of 3%: 67% more conversions from the same clicks with better unit economics.
This is why market leaders should consider raising their tROAS demands as their conversion rate improves. It defends their position while harvesting the profitability gains from CRO investment.
Beyond CRO, several other strategic options exist:
Raise prices (higher AOV), improve retention (higher LTV), reduce costs, raise capital to fund longer payback periods. These expand your maximum CPA, which expands your implied max CPC.
Smart Bidding is a machine learning system—it's only as good as the data you feed it. If you're counting low-quality leads as conversions, you're training Google to find more low-quality leads.
In the Medicare Supplement business, leads over 80 years old rarely qualified for policies—but they represented a significant portion of form fills. We dynamically redirected visitors over 80 to an alternative thank you page. Our conversion pixel only fired for qualified-age leads. Short-term, reported conversions dropped. Long-term, Google's algorithm learned what a "real" conversion looked like. Result: same lead volume, dramatically better contact rates and close rates, lower true cost per customer.
Import offline conversions. Feed actual sale data back to Google.
Use value-based bidding. Assign different values to different lead types.
Optimize for contacted/qualified leads rather than raw form submissions.
Long-tail keywords, niche geographic or demographic segments, emerging platforms where the giants haven't yet arrived.
SEO, content marketing, partnerships, referrals—acquisition channels where you're not in a real-time auction against well-capitalized competitors.
Operate profitably at a smaller scale rather than chase share at unsustainable economics. A 4% share at $25 CPA might build a better business than 10% share at $50 CPA.
Some practitioners use Marketing Efficiency Ratio (MER)—total revenue divided by total marketing spend—as a business-level target. MER captures blended performance across all channels, including attribution leakage (e.g., a Meta ad that generates a branded Google search that gets credit for the conversion).
MER is useful for portfolio-level planning and incrementality analysis. But it doesn't change auction dynamics. Google's Smart Bidding doesn't know your MER—it only knows the tROAS you give it and your conversion rate within its system.
The Bid Ceiling Model describes what happens inside a single auction. MER describes what happens across your entire marketing mix. They're complementary frameworks, not substitutes. You need both: MER to set your overall marketing budget and channel mix, and the Bid Ceiling Model to understand your competitive position within each auction.
When you enter a tCPA or tROAS target, you are not setting a CPC—you are revealing your margin. Google's Smart Bidding will derive the effective CPC it can bid based on your target and your historical conversion rate.
The auction is not rigged. It's a market reaching Nash Equilibrium. But it's a market where Google has perfect information about everyone's implied maximum, you have no visibility into competitors' economics, behavioral triggers push everyone toward their ceiling, and scale advantages compound across all dimensions.
Your conversion rate is a given—a historical constant. You cannot change it through bid settings. You can only change it through A/B testing, landing page optimization, and CRO. This is why CRO is the primary competitive lever in tCPA and tROAS strategies. It's how you compete at your business-economic CPA limit.
Understanding this changes how you compete. You stop trying to "win" the auction by setting aggressive targets—because if your CR doesn't support those targets, Google will simply limit your ad serving. Instead, you focus on the variables you control: your conversion rate, your conversion signal quality, your business economics, and where you choose to compete.
The game is designed this way. Once you understand that, you can make rational decisions about whether to play—and if so, how.
Andrew Zinman is the CEO of Convert72 Technologies LLC, a performance marketing company that selectively accepts Conversion Rate Optimization (CRO) consulting projects. Andrew leverages advanced consumer behavior insights to connect high-intent customers with brands at the optimal decision-making moment. With a team of experts in conversion optimization, search strategy, and data analytics, he has developed a CRO research system that delivers measurable results. His core expertise spans financial services, healthcare and telemedicine, senior (55+) markets, D2C e-commerce, and B2B lead generation.
Learn more at www.convert72.com
Inquiries: andrew@convert72.com