Google Ads for e-commerce: the 5 settings that make the difference

Google Ads is one of the most powerful growth levers available to e-commerce businesses in 2026, but it is also the place where budget disappears fastest when settings are misconfigured. The difference between a campaign that generates profit and one that burns money rarely lies in the budget or the products themselves. It lies in five specific settings that most advertisers get wrong, adjust too late, or overlook entirely. This article walks through those five settings, explains why they are so decisive for your ROAS, and shows how AdBrains' own AI technology makes the difference between average and market-leading performance on each one.

Why the right settings make or break Google Ads for e-commerce

E-commerce is a unique context for Google Ads. Unlike lead generation, you are dealing with a broad product range, seasonal peaks, variable margins per category, and buyers who are at completely different stages of the customer journey. A visitor searching for "electric folding bike comparison" has different intent from someone searching "buy electric folding bike today". Both searches can land on your ad, but ideally they would be treated very differently: different bid, different ad, different landing page.

The five settings discussed below are not niche tips for advanced users. They are fundamental choices that determine whether the Google Ads algorithm receives the right signals to learn and optimise effectively. Configuring these settings correctly gives Smart Bidding the fuel it needs to perform. Ignoring them means paying for data the algorithm cannot use.

Setting 1: conversion tracking with Enhanced Conversions and server-side signal enrichment

From search term to conversion: the optimised e-commerce funnel

Benchmark for Search campaigns with full optimisation (percent-mode)

Impressions

All relevant searches reached

Clicks (CTR)

Average 8% CTR with strong RSAs

Product page visited

Landing page relevance monitored

Purchase (conversion)

Average e-commerce conversion rate

2% conversion rate on relevant traffic

The foundation of every successful Google Ads campaign is accurate conversion tracking. This sounds obvious, but in practice most e-commerce advertisers measure only a fraction of actual conversions. Browser restrictions, ad blockers, iOS privacy changes, and cookieless browsers mean that standard client-side tracking misses up to 30% of conversions in 2026. For Smart Bidding this is catastrophic: the algorithm learns from what it sees, and if it sees fewer conversions than actually occur, it will steer bids incorrectly.

The solution consists of two layers. The first layer is Enhanced Conversions, which sends first-party customer data (such as email addresses) to Google to retroactively attribute missed conversions to the correct click. The second layer is server-side tracking via a dedicated server-side Google Tag Manager environment (sGTM). Here, conversion data is sent from your own server to Google rather than from the browser, completely out of reach of ad blockers and browser restrictions. Advertisers who activate both layers see on average 23 to 28% more conversions tracked, which immediately improves Smart Bidding performance.

For a webshop like E-4motion.com, which sells new electric folding bikes, this difference is critical. A high-value purchase that goes untracked is invisible to the algorithm. With full server-side signal enrichment, Smart Bidding sees every purchase, every product page visitor, and every abandoned checkout, and can actively optimise towards those signals.

Setting 2: Target ROAS as a bidding strategy, configured per product category

Many e-commerce advertisers start with Enhanced CPC or manual bidding and never transition to Target ROAS. That is a missed opportunity. Target ROAS (tROAS) is the bidding strategy that allows the algorithm to dynamically determine how much a click is worth per auction based on expected revenue. But the setting must be configured correctly.

The two most common mistakes with tROAS are: (1) setting a ROAS target that is too high, causing the algorithm to win too few auctions and volume to collapse, and (2) setting a single campaign-wide ROAS target when margins vary significantly across product categories. A product with an 8% margin needs a very different ROAS target from an accessory with a 60% margin. By setting a separate tROAS target per campaign or ad group that reflects actual product margin, you structurally extract more return from the same budget.

The rule of thumb for setting tROAS: start with a target 10 to 15% below your historical ROAS to give the algorithm enough room to operate, then increase gradually once volume is stable. For ToetsJeKennis.nl, which sells online exams and courses with an average order value of 50 euros, a segmented tROAS strategy per course type works particularly well: popular high-demand exams get a higher tROAS target, while new course types start on lower targets to collect data first.

Average ROAS improvement per optimised setting

Benchmarks for e-commerce advertisers in 2026

Enhanced Conversions + sGTM

28%

Target ROAS (tROAS) Smart Bidding

34%

Keyword Incubator system

22%

Separated campaign structure

19%

RSA Ad Strength optimisation

15%

Smart Bidding demonstrably outperforms manual bidding once it has sufficient conversion data. Google's recommended threshold is at least 30 conversions per month per campaign, but in practice the true power of Smart Bidding only becomes visible above 50 conversions per month. This makes data collection during the launch phase especially important.

Setting 3: campaign structure with separated networks and campaign types

One of the most persistent mistakes in e-commerce Google Ads is combining Search and Display in a single campaign. Google enables this by default when creating a new Search campaign ("also show ads on the Display Network"), but for e-commerce this is almost always a poor choice. Display traffic behaves fundamentally differently from Search traffic: different intent, different CTR benchmarks, different CPC values. Combining them causes the algorithm to lose its ability to bid optimally per channel.

The recommended campaign structure for e-commerce in 2026 looks like this:

• Search campaigns per product category, targeting high-intent keywords with exact match and phrase match as primary match types
• Shopping campaigns with a well-configured product feed, split by category or brand for maximum bid control
• Performance Max (PMax) campaigns as a complement to Search and Shopping, with strong asset groups and exclusions to prevent cannibalisation
• Remarketing campaigns (Display or Video) specifically targeting previous website visitors and shopping cart abandoners
• Branded Search campaigns kept separate to protect brand traffic and enable accurate reporting

This structure ensures that each campaign can run with its own bidding strategy, its own budget, and its own optimisation goals. Google's AI receives targeted signals per campaign, rather than combined, noise-amplifying data from multiple network types mixed together.

Setting 4: keyword match types and negative keywords as a structural system

Keyword match types are a source of confusion for many advertisers, but the choice between broad match, phrase match, and exact match has major consequences for which search traffic you attract and at what CPC. In e-commerce, the general rule is to start with exact match for your best-converting keywords, use phrase match for category-level searches, and only deploy broad match with Smart Bidding and a solid negative keyword list in place.

The second part of this setting, and equally important, is actively maintaining a negative keyword list. Without systematic search term mining, you pay for irrelevant clicks: people searching for a product you do not sell, or an informational query with no purchase intent. For Elletens.nl, excluding informational search terms from shopping campaigns can improve budget efficiency by dozens of percentage points.

A tight negative keyword system requires weekly or even daily analysis of all search terms generating clicks. Done manually, this is time-consuming and is too rarely executed by most advertisers, resulting in structural budget waste.

Setting 5: Ad Strength and RSA optimisation for higher Quality Score

Responsive Search Ads (RSAs) are the standard ad format for Search campaigns. Google automatically combines your headlines and descriptions into the most relevant ad combination per search query. The quality of those combinations is expressed as Ad Strength: POOR, AVERAGE, GOOD, or EXCELLENT. Higher Ad Strength correlates strongly with a better Quality Score, and a higher Quality Score leads to lower CPC and better ad positions, meaning more clicks for less money.

Most advertisers write their RSAs once when setting up a campaign and never revisit them. That is a missed opportunity. Ad Strength improves by:

• Writing at least 8 to 10 unique headlines that do not overlap in meaning
• Including the primary keyword in at least two headlines
• Incorporating specific benefits, USPs, and calls-to-action in the descriptions
• Using ad extensions (sitelinks, callouts, structured snippets) to enrich the ad
• Regularly replacing low-performing headlines based on performance data

For HACCP-cursus.com, which offers online food safety courses, systematically improving RSA Ad Strength scores from AVERAGE to EXCELLENT across all campaigns led to a noticeable reduction in average CPC with stable search volume, enabling more purchase traffic within the same budget.

How AdBrains AI automatically manages and optimises these five settings

Default settings vs. optimised settings

Impact on e-commerce campaign performance

Default settings

• Broad match without negative keywords
• Automatic placements (including irrelevant ones)
• Enhanced CPC as bidding strategy
• No Enhanced Conversions
• Campaign network: Search + Display combined
• Manual ad copy, no rotation analysis

AdBrains optimised settingsAI-driven

• Keyword match types per phase (incubator → production)
• Exclusion lists for irrelevant placements
• Target ROAS based on margin data
• Enhanced Conversions + server-side tracking active
• Separate Search, Shopping and PMax campaigns
• RSA improvement system monitors Ad Strength continuously

The five settings described above sound manageable when configured once. The reality is more complex: e-commerce campaigns require daily monitoring, weekly adjustments, and continuous A/B analysis to keep up with seasonal fluctuations, competitive changes, and Google algorithm updates. That is precisely where AdBrains' own AI technology makes the difference.

AdBrains operates a multi-agent verification system: every optimisation decision is assessed by four independent AI agents before being implemented. This prevents a single erroneous recommendation, such as an overly abrupt tROAS adjustment or an incorrect negative keyword, from damaging campaign performance. Every change is therefore not only automated but also verified.

For conversion tracking, AdBrains sets up a dedicated server-side Google Tag Manager infrastructure per client, including Enhanced Conversions configuration. This is not a standard implementation but a custom signal enrichment layer that delivers first-party data directly to Google Smart Bidding. The result: more visible conversions, better bidding signal quality, and a Smart Bidding algorithm that learns faster.

The AdBrains Keyword Incubator system ensures that new keywords are always first tested in a separate incubator campaign before being promoted to the production campaign. This prevents unproven keywords from disrupting the bidding behaviour of the production campaign. Daily automated search term mining detects irrelevant queries and automatically adds them as negative keywords, without manual intervention from an account manager.

The AdBrains RSA improvement system analyses the Ad Strength of all active ads daily. Ads with POOR status are automatically flagged, and the AI generates concrete rewrite suggestions based on keyword relevance, landing page content, and historical CTR data. This system ensures that Ad Strength across all campaigns remains continuously at the highest achievable level, without a copywriter manually reviewing campaigns each week.

Finally, AdBrains manages tROAS targets per campaign based on current margin data and conversion volume. The strategy-switch system automatically detects when a campaign has too few conversions to keep Smart Bidding stable, and temporarily switches to a safer bidding strategy until volume recovers. This prevents Smart Bidding from entering a learning spiral and spending budget inefficiently.

Comparison table: the 5 settings at a glance

The table below summarises the five critical settings and shows the difference between a standard configuration and the optimised approach that AdBrains applies.

Each of these five settings has a significant impact on its own. Combined and properly aligned, the effect is multiplicative: not 1 plus 1 equals 2, but each layer reinforcing the others to produce a campaign that operates more efficiently at every level. That is why combining all five settings structurally delivers higher ROAS than addressing only one or two points.

Frequently asked questions about Google Ads settings for e-commerce

How quickly will I see results after optimising these five settings?

The fastest gains come from Enhanced Conversions and server-side tracking: once more conversions become visible to Smart Bidding, the algorithm begins steering better, which typically translates into lower CPA or higher ROAS within one to two weeks. tROAS optimisation requires more time: allow a learning period of two to four weeks per campaign before the algorithm performs stably. Structural changes (campaign separation) have the longest ramp-up time but deliver the most durable long-term gains.

Is Target ROAS always better than manual bidding for e-commerce?

Target ROAS is demonstrably more effective than manual bidding once a campaign reaches at least 30 to 50 conversions per month. Below that volume, Smart Bidding has insufficient data to learn reliably and risks overbidding or underbidding on individual queries. During the launch phase, we recommend Maximize Conversions without a ROAS target so the algorithm collects data quickly, followed by a transition to tROAS once volume is stable.

What is the difference between Performance Max and a regular Shopping campaign?

A regular Shopping campaign gives you more control over which products appear when, and you can bid precisely per product group. Performance Max (PMax) combines Shopping, Display, YouTube, Search, and Gmail in a single campaign and lets the Google algorithm decide fully where and when your ads appear. PMax is powerful when you have strong asset groups and sufficient conversion data, but requires good exclusions and a clear campaign structure to prevent cannibalisation of your existing Search campaigns.

How often should I update my negative keyword lists?

For e-commerce campaigns with significant daily search volume, daily or at minimum weekly analysis of search terms is strongly recommended. Particularly with broad match keywords and PMax campaigns, which generate more query variation, continuous monitoring is essential. The most effective approach is an automated system that analyses new search terms every day and automatically adds irrelevant terms to the exclusion list. Done manually this is time-consuming; automated it is a continuous protection of your budget.