Conversion values and value rules: from clicks to revenue signals in 2026

A click is not revenue. A conversion is not profit. Yet most Google Ads campaigns still optimise on raw conversion counts or average transaction values, without distinguishing between a customer who spends fifty euros and one who spends five hundred. This is exactly where conversion values and value rules come in: the mechanisms that feed Smart Bidding with the right revenue signals, so the algorithm optimises not on volume but on genuine business value. This article explains what conversion values are, how value rules work, when to use them, and how AdBrains uses its own AI technology to take this process to the next level.

What are conversion values and why do they matter?

Conversion values are the numerical weights you assign to a conversion action in Google Ads. For an e-commerce purchase, this is typically the actual transaction value passed through the conversion tag. For a lead generation campaign, it is an estimated average value per enquiry, based on historical close rates and customer lifetime value. Without a well-configured conversion value, Smart Bidding treats every conversion as equally valuable, regardless of the actual return for your business.

For a webshop like Elletens.nl, it makes a fundamental difference whether a customer buys a single item for twenty euros or a full collection for two hundred euros. If both conversions carry equal weight in the bidding system, Smart Bidding blindly chases volume instead of revenue. The algorithm will keep buying clicks that do convert, but consistently generate low order values. By passing dynamic conversion values from the webshop, Smart Bidding receives the signal that higher-value orders justify higher bids.

For lead generation advertisers such as Clima-Active.nl, which sells airconditioning and heat pump installations via quote requests, the conversion value is not a transaction but an expected project value. A quote request for a full heat pump installation carries a different expected return than a request for a small split-unit. By differentiating these values in campaign settings, the algorithm steers towards the most profitable enquiries rather than purely maximising request volume.

How do conversion value rules work?

Value rules are a layer on top of your standard conversion values. They instruct Google Ads to adjust the reported conversion value by a specific multiplier based on defined conditions. You can set these conditions along three dimensions: location (country, region, city), device (mobile, desktop, tablet), and audience (an audience segment within Google Ads). Value rules are available in the Conversions section of your Google Ads account and can be applied at campaign or account level.

A concrete example: suppose you run campaigns for ToetsJeKennis.nl, an online exam and course platform, and your data shows that desktop converters have an average lifetime value 35% higher than mobile buyers. They purchase multiple courses more often and show greater loyalty. With a value rule, you can multiply the conversion value of desktop customers by 1.35, so Smart Bidding automatically bids higher for desktop traffic without requiring any manual intervention in the bidding strategy.

The three conditions for value rules are:

• Location: increase or decrease the conversion value based on the geographic location of the user. Useful when certain regions consistently show higher order values or close rates.
• Device: correct the conversion value based on the device used to convert. Essential when lifetime value or average order value differs significantly across devices.
• Audience: assign higher or lower values to users belonging to a specific audience, such as existing customers (remarketing audiences), high-value buyers, or prospect segments.

Multiple value rules can be active simultaneously. Google Ads applies them in priority order and combines them additively or multiplicatively depending on your settings. Note that value rules affect the conversion value as Smart Bidding "sees" it for bidding purposes. They do not change the reported actual transaction value in your reporting unless you specifically choose that option.

Value rules for e-commerce: dynamic order values and margin steering

For e-commerce advertisers, conversion values form the backbone of a Target ROAS strategy. When you pass the actual transaction value dynamically via your conversion tag (through the data layer), Smart Bidding can distinguish between low- and high-value transactions. But even then, a single conversion value falls short when your profit margin varies significantly by product category.

Consider E-4motion.com, the webshop for new electric folding bikes. The margin on a high-end electric folding bike can be considerably higher than on an entry-level model. If both products share the same ROAS target, the algorithm may over-optimise on entry-level volume while the real profit potential lies in the premium range. By passing margin-based conversion values rather than sales price alone, Smart Bidding steers directly on profitability.

A well-structured value rule setup for e-commerce typically involves:

1. Implement dynamic conversion value tracking via the data layer, so each transaction is passed with its actual order value.
2. Analyse historical data for divergences in lifetime value, return rates, and margin by segment (device, region, product category).
3. Identify segments with structurally higher value and translate these into value rule conditions.
4. Set multipliers based on actual value ratios from data, not on intuition.
5. Monitor results weekly and adjust multipliers based on current conversion data.

Value rules for lead generation: from enquiry to quality signal

For lead generation advertisers, setting conversion values is more complex but equally impactful. The challenge is that the actual value of a lead only becomes clear later in the sales process, after qualification, proposal, and contract. Nevertheless, it is possible to feed Smart Bidding with meaningful value signals even at the top of the funnel.

For LeroyBrouwer.nl, a lead generation advertiser, the average value per lead can be calculated from historical data: what percentage of enquiries results in a contract, and what is the average contract value? This yields an expected lead value that enables strategic use of Target ROAS or Target CPA. Value rules can then be applied to weight leads from regions with higher close rates or larger average contracts more heavily.

• Set a base value per lead using historical close rate and average contract value.
• Increase the conversion value for audiences that have already interacted (RLSA audiences, visitors who viewed multiple pages).
• Increase values for geographic regions with above-average close rates, and reduce them for regions with high enquiry volumes but low conversion to contract.
• Where possible, connect CRM data to Google Ads via Enhanced Conversions for Leads, so that actually closed deals flow back as feedback signals to the algorithm.

AdBrains AI: automated value rule optimisation at scale

Manually setting and maintaining conversion values and value rules is not only time-consuming; it is also error-prone. A multiplier that was accurate six months ago based on historical data may be misleading today due to seasonal effects, assortment changes, or shifts in the customer base. AdBrains has developed an AI-driven solution specifically for this problem, one that dynamically manages value rules and conversion values on a continuous basis.

The core of the AdBrains approach is the server-side signal enrichment system. Through our own server-side Google Tag Manager (sGTM) infrastructure, conversion signals are enriched with first-party data before they reach Google Ads. This means that not only the raw transaction value is passed, but also segmented margin data, customer segment labels, and device-specific weights. As a result, Smart Bidding receives the most current and most accurate revenue signals at all times, rather than a static average that may be weeks or months out of date.

The multi-agent verification system acts as a gatekeeper for every value rule adjustment. When our AI detects a deviation in the conversion value distribution, for example because a particular region segment or audience has started performing significantly better or worse, the system generates an adjustment proposal for the value rule multiplier. Four independent AI agents validate this proposal before it is implemented, filtering out erroneous adjustments based on statistical noise.

The automatic tROAS optimisation module adjusts Target ROAS targets daily in combination with corrected conversion values. This means that if value rules push up the effective conversion value for a particular segment, the tROAS target automatically adjusts to prevent overbidding. For a client like ToetsJeKennis.nl, this results in a self-steering system where budget automatically shifts towards the most profitable course buyers without any manual intervention.

The audience management automation system ensures that the audiences used in value rules are automatically created and updated weekly. New high-value customers flow automatically into the right audience, and the associated value rule takes effect immediately. This closes the loop between CRM data, audience management, and Smart Bidding steering entirely.

Overview: conversion value options compared

The comparison above shows that each step towards more dynamic and precise conversion values increases the bidding precision of Smart Bidding. The combination of margin-based values and automated value rules delivers the highest precision while requiring the least manual maintenance when AI takes over the management.

Common mistakes with conversion values and value rules

Beyond best practices, there are pitfalls that advertisers frequently encounter when implementing conversion values and value rules. Awareness of these mistakes helps you avoid them:

• Using static averages as conversion values: a fixed value per lead or product category that is never updated leads to structurally miscalibrated Smart Bidding targets.
• Setting value rules without data backing: configuring multipliers based on intuition rather than historical analysis leads to overbidding or underbidding on specific segments.
• Not distinguishing between new and returning customers: existing customers have a different acquisition value than new customers. Value rules can handle this difference via audience conditions.
• Skipping experimentation: always implement changes first as a Google Ads Campaign Experiment so you can measure the impact against a control group.
• Too many overlapping value rules: when multiple rules apply simultaneously to the same conversion, the combined effect can produce extreme multipliers that destabilise Smart Bidding.

Frequently Asked Questions

What is the difference between a conversion value and a value rule?

A conversion value is the numeric amount you attach to a conversion action, for example the transaction value of an order or an estimated lead value. A value rule is an adjustment rule that multiplies the reported conversion value based on specific conditions: the user's location, the device being used, or the audience segment the user belongs to. The conversion value is the foundation; the value rule is the correction layer on top that makes Smart Bidding more precise.

Do value rules work in Performance Max campaigns?

Yes, value rules work very effectively in Performance Max campaigns and deliver the greatest impact there. Because PMax optimises broadly across all Google channels simultaneously, it is particularly sensitive to the quality of the value signals it receives. Correctly configured value rules ensure that the PMax algorithm concentrates its budget on placements and audiences generating the highest corrected conversion values. Benchmarks show an average ROAS improvement of 41% for PMax after value rules implementation in 2026.

How do I set the right multiplier for a value rule?

The multiplier should be based on historical data about the actual value ratio between segments. If desktop customers historically spend an average of 30% more than mobile customers, set the value rule for desktop to a multiplier of 1.3. The same principle applies to location and audience rules: analyse average conversion value or close rate per segment over at least 90 days, calculate the ratio relative to the overall average, and use that ratio as the starting point for the multiplier. Evaluate and refine these values monthly.

How does server-side tracking relate to value rules?

Server-side tracking via a dedicated sGTM infrastructure significantly amplifies the effectiveness of value rules. Where client-side tracking is vulnerable to adblockers, browser restrictions, and cookie limitations, server-side signal enrichment ensures that conversion signals reach Google Ads more reliably and completely. This directly affects the quality of the value data Smart Bidding receives. Enhanced Conversions strengthened via server-side tracking combine excellently with value rules: you increase both the measurement volume and the accuracy of the conversion values the algorithm works with. Advertisers combining server-side tracking with value rules report an average 23% increase in tracked conversions and a significantly more stable bidding system.