Maximize Conversion Value: bidding on revenue not clicks

Clicks are easy to measure, but revenue pays the bills. Yet many Google Ads campaigns in 2026 still optimise for clicks or sessions, while the underlying business goal is revenue growth. Maximize Conversion Value is the Smart Bidding strategy that fundamentally changes this: instead of chasing the maximum number of conversions or clicks per budget, Google's algorithm targets the highest possible total conversion value within the available budget. For e-commerce advertisers and sophisticated lead generation accounts, this is often the most direct route to a higher ROAS and better return on ad spend. This article explains what Maximize Conversion Value is, when to use it, how to combine it with Target ROAS, and how AdBrains AI technology pushes this strategy significantly further than manual management ever could.

What is Maximize Conversion Value?

Maximize Conversion Value is an automated bidding strategy within Google Ads that falls under the broader Smart Bidding umbrella. The algorithm uses machine learning to determine the optimal CPC in every auction with one single objective: maximising the total conversion value generated within the campaign budget. The strategy is available for Search campaigns, Shopping campaigns, and Performance Max (PMax).

The critical difference versus Maximize Conversions is that the strategy does not count how many conversions occur, but rather how much revenue those conversions are worth. If an advertiser can buy two clicks where click A leads to a €30 purchase and click B to a €150 purchase, Maximize Conversion Value will systematically allocate more budget towards the search behaviour associated with click B. This makes it exceptionally well-suited for webshops with diverse product price ranges or order values.

Maximize Clicks vs. Maximize Conversion Value

What does each bidding strategy actually optimise for?

Maximize Clicks

• Optimises for highest click volume
• Ignores conversion value per click
• Attracts cheap, broad traffic
• No distinction in customer value
• Suitable for brand awareness
• Risk of low ROAS at high budgets

Maximize Conversion ValueRecommended

• Optimises for highest revenue per budget
• Weighs each conversion by actual value
• Attracts buyers with higher order values
• Differentiates per product and audience
• Suitable for e-commerce and value-based leadgen
• Pairs with Target ROAS for cost control

A key technical requirement is that conversion values must actually be tracked in Google Ads. This can be done via static values (every conversion carries a fixed value, as is the case for online courses) or via dynamic values (the real transaction value is passed per purchase through the dataLayer and conversion tracking). Without tracked conversion values, the algorithm has nothing to optimise on and Maximize Conversion Value effectively behaves like Maximize Conversions.

Maximize Conversion Value vs. other bidding strategies

The table below offers a structured overview of the most common bidding strategies alongside their optimisation objectives, data requirements, and best use cases.

For a webshop like E-4motion.com, which sells new electric folding bikes across multiple configurations and price points, the difference between optimising for conversion volume and optimising for conversion value is substantial. Cheaper accessories may convert more frequently, but the algorithm running on Maximize Conversion Value will correctly prioritise the higher-value bike purchases that truly drive revenue growth.

When does Maximize Conversion Value work best?

Average ROAS improvement after switching to Maximize Conversion Value

Benchmarks by campaign type (Google Ads, 2026)

Shopping campaigns

34%

Search campaigns

27%

Performance Max

41%

Display remarketing

19%

Not every campaign is ready for Maximize Conversion Value from day one. The strategy performs best when specific conditions are met. Below are the key prerequisites before making the switch.

• Dynamic conversion values are implemented: the real transaction value must be passed per purchase through conversion tracking, enabling the algorithm to distinguish between a €25 sale and a €250 sale.
• Sufficient conversion history: Google recommends at least 30 to 50 conversions within the past 30 days to give the algorithm enough learning data. Below this threshold the learning phase is longer and more volatile.
• Variable order values in the product range: the strategy is most impactful when there is a meaningful spread between lower-priced and higher-priced items in the campaign.
• Complete and reliable conversion measurement: Enhanced Conversions or server-side tracking via a sGTM setup ensures that delayed or cross-device conversions are correctly attributed and counted.
• Budget is not set too restrictively: if the daily budget is very tight, the algorithm cannot express its preference for higher-value traffic because it runs out of budget before reaching the most valuable auctions.

For campaigns that do not yet track dynamic conversion values, or that have just launched, it makes sense to start with Maximize Conversions and implement dynamic values alongside. Once tracking is validated and volume is sufficient, moving to Maximize Conversion Value is a natural progression.

Combining with Target ROAS for cost-controlled value bidding

Pure Maximize Conversion Value has one inherent limitation: the algorithm maximises revenue without factoring in costs. In theory it could spend the entire budget on a single expensive auction if that offers the highest expected conversion value. The solution is adding a Target ROAS (tROAS) goal on top of Maximize Conversion Value. A tROAS of 500% instructs Google to generate at least five euros of revenue for every euro of ad spend.

Google itself considers the combination of Maximize Conversion Value with a tROAS goal one of the most powerful Smart Bidding configurations for mature e-commerce campaigns. In the Google Ads interface the two are effectively merged: once you set a tROAS goal within Maximize Conversion Value, Google activates the combined Smart Bidding model. For an online course platform like ToetsJeKennis.nl with a consistent average order value of approximately €50, this configuration delivers exactly the right balance: the algorithm knows the maximum it can bid per auction to achieve the desired ROAS while still maximising total revenue.

How AdBrains AI automatically optimises Maximize Conversion Value

Maximize Conversion Value is powerful in theory, but in practice it requires continuous attention: conversion values must be accurate, tROAS goals need regular calibration, and the quality of the signal feeding Google's Smart Bidding is the single most important driver of outcomes. This is precisely where AdBrains' proprietary AI technology creates a structural advantage.

The foundation is our server-side signal enrichment via a dedicated sGTM infrastructure. Every conversion flowing through our clients' campaigns is enriched with first-party data: the real transaction value, product category, customer type, and device. This enriched signal feeds directly into Google's Smart Bidding, ensuring the algorithm knows not only that a conversion occurred but also exactly what it was worth and what type of user generated it. Advertisers using Enhanced Conversions or server-side tracking typically track an average of 23% more conversions compared to standard client-side setups, giving the algorithm substantially more learning data to work with.

On top of signal enrichment, our automatic tROAS optimisation module adjusts bidding strategy goals daily based on conversion trends, seasonal patterns, and margin targets per client. When average order values increase due to a promotional period or seasonal spike, our AI automatically raises the tROAS target, allowing the algorithm to bid more aggressively on the most valuable auctions. When volume dips, the AI temporarily lowers the target to avoid disrupting the learning phase.

Our multi-agent verification system ensures every adjustment to bidding strategy targets is reviewed by four independent AI agents before the change goes live. This prevents errors such as an accidentally over-aggressive tROAS goal that causes the campaign to underspend. This is a fundamental difference from manual management, where such mistakes are often only noticed after weeks of declining performance.

For clients with a varied product assortment, such as E-4motion.com with new electric folding bikes across multiple price tiers, our Keyword Incubator safely tests new keywords in a separate incubator campaign before promoting them to the production campaign where Maximize Conversion Value is active. This prevents the algorithm from consuming budget on generic traffic that converts at low order values. Only keywords proven to drive above-average conversion value are promoted, keeping the Smart Bidding signal clean and high-quality.

How Maximize Conversion Value distributes bids

From impressions to revenue, percent mode

100% Impressions

All auctions Google enters

38% Clicks with high revenue potential

Smart Bidding filters on expected conversion value

11% Conversions

Purchases and leads with tracked value

7% Revenue above target ROAS

Transactions that exceed the goal

Maximum revenue per euro of budget spent

Practical examples: e-commerce and lead generation

For an e-commerce store like Elletens.nl, switching from Maximize Conversions to Maximize Conversion Value with dynamic transaction values shifts the algorithm's focus from volume to value. Rather than optimising for the highest number of transactions (which often means cheaper, easier-to-sell products dominate), the algorithm redirects budget towards the product categories and audience segments that demonstrably generate higher order values.

In a lead generation context, such as Clima-Active.nl generating quote requests for air conditioning and heat pump installations, Maximize Conversion Value works equally well when conversion values are assigned based on expected project revenue. A heat pump installation lead carries a higher expected value than a small split-unit air conditioning lead. By embedding this logic into conversion tracking, the algorithm steers towards the most commercially valuable quote requests rather than simply the highest volume of form submissions.

Implementation checklist for Maximize Conversion Value

1. Validate your conversion tracking: confirm that dynamic transaction values are correctly passed through the dataLayer and visible in Google Ads conversion columns.
2. Implement Enhanced Conversions or server-side tracking: maximise coverage of all conversions, including cross-device and delayed purchases, via Enhanced Conversions or a sGTM setup.
3. Assess conversion history: ensure the campaign has achieved at least 30 conversions with tracked values in the past 30 days before switching.
4. Set Maximize Conversion Value as the bidding strategy: in campaign settings, choose Maximize Conversion Value and optionally set a tROAS goal slightly below your historical ROAS.
5. Actively monitor the learning phase: avoid major budget or structural changes for the first two to four weeks to allow the algorithm to stabilise.
6. Evaluate and gradually adjust tROAS: after the learning phase, assess whether the campaign is hitting its tROAS target and spending its full budget. Adjust the goal in increments of 10-15% as performance allows.

Frequently asked questions about Maximize Conversion Value

What is the difference between Maximize Conversion Value and Target ROAS?

Maximize Conversion Value is a bidding strategy that targets the maximum total revenue within the available budget, with no cost constraint. Target ROAS is an optional goal you can add within Maximize Conversion Value to instruct the algorithm to generate a minimum amount of revenue per euro of ad spend. In the Google Ads interface, the two are effectively combined once a tROAS goal is set. For most mature campaigns, using Maximize Conversion Value with a tROAS goal is the recommended configuration, as it balances revenue maximisation with cost efficiency.

How long is the learning phase after activating Maximize Conversion Value?

The learning phase typically lasts two to four weeks after activating or significantly adjusting the bidding strategy. During this period, the algorithm collects data on which auctions, keywords, and audiences generate the highest conversion values. Campaign performance may fluctuate temporarily. Avoid making major structural changes, such as adjusting the budget by more than 20% or adding new ad groups, as each significant change restarts the learning phase.

Is Maximize Conversion Value suitable for lead generation campaigns?

Yes, but only when leads are assigned tracked conversion values. In the simplest approach, an advertiser manually assigns a fixed value to different lead types based on historical close rates and average project values. A more advanced approach involves connecting CRM data to conversion tracking so that leads are valued based on actual revenue generated. For clients like Clima-Active.nl, assigning higher values to heat pump leads than to air conditioning leads enables the algorithm to prioritise the most commercially valuable quote requests automatically.

What happens if my conversion tracking is incorrect?

Inaccurate or incomplete conversion tracking is the leading cause of underperformance with Maximize Conversion Value. If the algorithm receives unreliable conversion values, it cannot distinguish between valuable and less valuable auctions. In the worst case it optimises for incorrect values, leading to budget allocation on the wrong products or audiences. Always validate your tracking setup fully, ideally reinforced with Enhanced Conversions or server-side tracking via sGTM, before activating Maximize Conversion Value. The investment in accurate tracking always pays off: every additional conversion tracked improves algorithm guidance and ultimately raises ROAS.