Robin Tesselaar shares practical Google Ads guidance for ecommerce businesses, including beginner tutorials on Google Merchant Center and campaign setup, plus advice on Performance Max, testing, and measuring profitability.
Most useful for practical Google Ads guidance on ecommerce setup, Performance Max, testing, and profitability.
Best for
B2B ecommerce SaaS or brands needing Google Ads advisory or content collaboration.
Not for
Consumer brand seeking creator-led paid sponsorship for broad awareness and direct sales.
Key takeaways
High ROAS can still lose money because margin matters more than headline return.
Performance Max needs boundaries, margin splits, branded traffic protection, and customer-value signals.
Merchant Center setup requires verification and correct account connections before Shopping ads launch.
Check first: Confirm audience data, sponsorship terms, rates, and inquiry route before contacting them.
Main ideas
ROAS is not return: accounts can look profitable while losing money · Performance Max needs boundaries and business signals to work · Testing is a budget-structure question, not a budget threshold
Robin Tesselaar shares practical Google Ads guidance for ecommerce businesses, from beginner setup tutorials to advice on Performance Max, campaign testing and profitability. Their work connects the mechanics of launching campaigns with the business question of whether they are bringing in profitable growth.
Tesselaar’s advice links campaign decisions to commercial outcomes.
In why a high ROAS can still lose money, the key distinction is margin: a 4x return on ad spend can be less profitable than a 2x return, and blended averages can hide the value of the next dollar spent.
The Performance Max guidance turns that principle into account structure—separating products by margin, protecting branded traffic and giving the system customer-value signals.
For readers earlier in the process, the Merchant Center setup tutorial explains why verification and correct account connections matter before launching Shopping ads.
Together, these examples make their work useful to ecommerce readers seeking clear setup guidance and a more profit-focused way to assess campaign results.
Robin Tesselaar's ideas centre on one recurring argument: ecommerce Google Ads accounts are often judged by the wrong number, and the fix is account structure built around profit rather than the platform's most visible metric.
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Robin teaches beginners the setup work that prevents later policy problems and treats testing and Performance Max as engineering problems shaped by margin, customer value and budget—not by a single best-practice template.
ROAS is not return: accounts can look profitable while losing money
Robin's central argument is that revenue divided by ad spend ignores the costs that determine whether a campaign made money: cost of goods, shipping, returns and fulfilment.
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Three consequences follow.
Platforms gravitate toward high-volume, low-margin products because they sell easily, so gross profit falls while ROAS looks strong.
They also reward warm audiences, allowing a brand-heavy account to attribute conversions that would have happened without the ad.
And blended averages hide diminishing returns: a channel with a better headline ROAS can produce less profit on the next increment of spend than one with a lower headline number.
Robin recommends profit-on-ad-spend, a break-even ROAS derived from margin, separate branded and non-branded ROAS, new customer acquisition reporting in Performance Max, and nCAC from the CRM.
The post works through the arithmetic: at a 35% gross margin, break-even ROAS is 2.86x.
Below that, a campaign loses money; a 4x ROAS campaign can lose money while a 2x campaign can be the most profitable.
It contrasts two channels as spend rises: the channel with a 5x headline ROAS returns only 1.5x on the next increment, while one with a 4x headline ROAS returns 3x.
In a reported case, using Google's new customer acquisition goal moved new customer share from 39% to 51% and cut cost of new customer acquisition by 30%, even though ROAS had looked strong throughout.
Performance Max needs boundaries and business signals to work
Robin argues that Performance Max rewards accounts with structure and penalises those that hand it a blank cheque.
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The recommendations are specific: run a dedicated exact-match branded search campaign so Performance Max competes for cold, non-branded traffic and its contribution becomes visible; split asset groups by margin, giving high-margin products a high target ROAS and low-margin clearance a low one or excluding it, rather than blending margins into a single average; feed CRM lists, high-value purchaser segments and lifetime-value-weighted audiences instead of generic interest targeting; and use conversion value rules so a small sale and a large sale do not send the same signal. Robin also treats search themes as a diagnostic, not a targeting wish list: if Google marks a theme low usefulness, Performance Max already owns those queries, so themes should cover discovery terms not yet captured.
The post is a five-part checklist, with each setting tied to the problem it solves.
Margin-split asset groups matter because, without them, Performance Max optimises for whatever converts most easily, not what is most profitable.
Brand protection follows the same logic: isolating branded traffic makes non-brand ROAS a more realistic measure.
Testing is a budget-structure question, not a budget threshold
Robin rejects the assumption that Google Ads requires thousands a month before testing is worthwhile.
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There is no minimum budget; what changes with spend is how testing is organised.
The framework adapts to what a brand can spend, with campaign structure and budget strategy shifting accordingly.
Ask Robin for the specific budget bands and test designs.
Robin frames the question they get asked most often as whether a minimum budget exists. Their answer shifts the discussion from whether a brand can test to how it should structure a test at whatever level it can afford.
Skipped setup work leads to disapprovals and wasted budget
Robin's beginner material prioritises unglamorous configuration: it determines whether campaigns run cleanly.
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Merchant Center is presented as the starting point for every Google Shopping campaign, not an administrative detour.
Details people rush through often return as disapprovals and suspensions.
On Google Ads, Robin describes a common failure pattern: a new advertiser opens an account, is pushed into an unfamiliar campaign type, spends a few hundred euros and concludes Google does not work.
Robin's counterpoint is that setup, not Google, was usually the problem.
The Shopify-to-Merchant-Center post walks through account setup for Shopify, store verification, inviting a team member, feed labels and connecting Merchant Center to Google Ads.
It warns that mistakes at the start can mean months of avoidable disapprovals.
The Merchant Center post covers the same ground, including shipping and return policies, while the Google Ads tutorial covers account setup, launching a first campaign and beginner mistakes that quietly waste budget.
Robin's advice puts Performance Max in two roles: a starting point and a campaign that must prove itself
Robin calls Performance Max a strong starting point for many new ecommerce brands, while still A/B testing campaign types to find the highest ROAS.
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For every account they manage, Robin checks where spend is going, which placements generate conversions and whether the focus is profitability rather than cheap cost per click.
Then they make one change and watch the data.
The goal is to move spend toward results, not make the account look complicated.
Read alongside Robin's structure-first argument, the advice is clear: Performance Max is a reasonable place to begin only when brand traffic is protected, margins are separated and results are tested rather than assumed.
Robin's shorter Performance Max post states the default position clearly: profitability, not cheap CPCs, should decide.
The five-part structure post spells out when that starting point is defensible.
Together, the posts help readers assess whether Robin sees Performance Max as a solution or a hypothesis to test.
Start here to understand what Robin Tesselaar says most ecommerce Google Ads reporting gets wrong: how can an account look successful while losing money, and what should replace ROAS?
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Robin Tesselaar argues that ROAS is not return: it measures revenue divided by ad spend before accounting for cost of goods, shipping, returns and fulfillment.
The post gives concrete counterexamples: a 4x ROAS campaign can lose money, while a 2x ROAS campaign can be the most profitable if its margin is better.
It names three ways ROAS misleads: it ignores margins, rewards warm audiences and hides diminishing returns through blended averages.
The margin math is specific: at a 35% gross margin, break-even ROAS is 2.86x.
The post also contrasts average and marginal ROAS across two channels, and recommends POAS, break-even ROAS, branded versus non-branded ROAS, NCA reporting in PMax and nCAC.
It cites a new-customer case in which new-customer share moved from 39% to 51%, volume rose 54% and cost of new-customer acquisition fell 30%, while ROAS had looked strong.
For brands planning a campaign
Use this to screen whether a Google Ads expert manages profit rather than dashboard ROAS. Ask candidates to report POAS, break-even ROAS, new-customer share and nCAC, and explain what they would change if brand-heavy conversions were flattering the account.
This explains how to structure Performance Max so it does not simply spend on whatever converts most easily.
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Newcomers can see Robin Tesselaar's operating model for PMax before evaluating campaign results.
This post lays out a five-part Performance Max structure.
First, protect branded traffic with a dedicated exact-match branded search campaign, so PMax competes only for cold, non-branded traffic.
Second, split asset groups by margin: put high-margin products in one group with a high target ROAS, and low-margin clearance in another with a low target ROAS or exclude it entirely.
Third, feed CRM lists, high-value purchaser segments and LTV-weighted audiences rather than generic interest audiences.
Fourth, use conversion value rules so a $20 sale and a $200 sale are not treated as the same signal.
Fifth, use search themes as a diagnostic: if Google marks themes as low usefulness, PMax already owns those queries, so focus on discovery terms not yet captured.
Robin Tesselaar says accounts losing on PMax hand Google a blank check, while winning accounts give it structure first.
For brands planning a campaign
Useful for assessing hands-on PMax operating skill. A paid advisory or content collaboration could focus on branded-traffic protection, margin-split asset groups, value rules and CRM audience inputs rather than generic PMax optimisation claims.
Read this to understand the first technical step before Google Shopping ads can run: what must be set up correctly in Merchant Center to keep campaigns from failing later?
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This post introduces a Merchant Center setup tutorial covering what Merchant Center is and how it works, filling in business details, verifying the online store, inviting a team member, setting up shipping and return policies, and connecting it to Google Ads and Shopify.
The practical reason to get the details right is that skipped setup steps can later lead to disapprovals and suspensions.
Merchant Center is presented as the starting point for every Google Shopping campaign, not an administrative detour.
For brands planning a campaign
A clear onboarding asset for ecommerce merchants. It shows how Robin Tesselaar teaches the feed and account setup needed to prevent later policy problems, relevant to SaaS companies serving merchants with Shopping campaigns.
This explains how to get a Shopify store into Merchant Center correctly.
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It is a practical starting point for merchants preparing to run their first Shopping campaign.
This post describes a Shopify-to-Merchant-Center tutorial covering what Merchant Center is and why it is needed, setting up the account for Shopify, verifying the store, inviting a team member, setting up feed labels, and connecting Merchant Center to Google Ads.
Robin Tesselaar warns that mistakes at the outset can lead to months of fighting avoidable disapprovals.
The post presents this connection as the foundation for running Google Shopping ads.
For brands planning a campaign
Useful for merchant onboarding and support content. A collaboration could pair this Shopify-specific walkthrough with a SaaS platform's own onboarding flow to reduce feed and approval errors.
Read this to see how Robin Tesselaar introduces ecommerce Google Ads to people who have never run a campaign: what does a sensible first setup look like, and which early mistakes waste money?
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The post describes a beginner's tutorial on Google Ads for ecommerce.
It covers how Google Ads works for ecommerce, setting up an account correctly, launching a first campaign and avoiding beginner mistakes that quietly waste budget.
Robin Tesselaar describes a common failure pattern: people open an account, get pushed into a campaign type they do not understand, spend a few hundred euros and conclude Google does not work.
The counterpoint is that the problem is usually the setup, not Google.
For brands planning a campaign
Useful for assessing beginner-facing teaching and content fit. It shows whether Robin Tesselaar can turn account setup into clear, practical guidance that helps a SaaS company reduce early budget waste.
This explains whether meaningful Google Ads testing is possible without a large budget.
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Newcomers can start here to see how campaign structure changes with spend.
This post tackles the assumption that Google Ads requires thousands a month before testing is worthwhile.
Robin Tesselaar says there is no minimum budget; the testing structure changes at different budget levels.
The tutorial covers the testing framework used for ecommerce brands, campaign structure and how budget strategy changes with spend.
The emphasis is on adapting the test design rather than waiting for a large budget.
For brands planning a campaign
Useful for budget-sensitive merchants and for assessing whether an expert can work with smaller accounts. It supports advisory or content angles on testing systems that scale from limited spend to larger budgets.
Read this to understand Robin Tesselaar’s default position on PMax and account testing: when is PMax a sensible starting point, and what checks should follow?
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Robin Tesselaar describes Performance Max as a strong starting point for many new ecommerce brands, but says they should still A/B test campaign types to optimise for the highest ROAS.
The post recommends checking every managed Google Ads account: review where spend goes, analyse which placements generate conversions, and prioritise profitability over cheap CPCs.
Make one change, then watch the data.
The goal is to shift spend toward the sources of results, not to make the account look complicated.
For brands planning a campaign
A concise statement of Robin Tesselaar's operating style: use PMax as a practical starting point, alongside testing, placement review and a focus on profit. Useful for a paid advisory brief where the client wants disciplined, test-led account changes rather than complexity.
Robin argues that return on ad spend can make an ecommerce account look healthier than it is.
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Revenue divided by ad spend leaves out costs such as goods, shipping, returns, and fulfillment; it can also hide repeat-customer conversions and the weaker returns on added spend. The post contrasts ROAS with profit measures, including POAS and the cost of acquiring new customers.
Uses a numerical comparison of two channels’ results as spend rises to show why marginal performance can matter more than headline ROAS.
For brands planning a campaign
Brands considering Robin for measurement or account advice can discuss margin-based targets, new-customer reporting, and how to assess the next increment of spend—not just the dashboard’s average ROAS.
Robin’s Performance Max advice is to give the campaign more useful boundaries and signals: separate products by margin, provide customer data, assign different conversion values where appropriate, and protect branded search traffic so non-brand performance is easier to assess.
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They also present search themes as a diagnostic for discovery opportunities.
Organizes recommendations as a practical account checklist, tying each setting to the behavior or measurement problem it addresses.
A separate post calls PMax a strong starting point for many ecommerce brands, while recommending a review of spend and placements, tests of other campaign types, and changes based on results.
For brands planning a campaign
This gives a SaaS company a concrete basis for an advisory discussion about PMax account structure, feed and margin segmentation, customer-data signals, and whether reported results reflect incremental non-brand acquisition.
Two beginner tutorials focus on foundational Google Merchant Center and Google Ads setup.
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The Merchant Center material covers account setup, business details, store verification, team access, feed labels or shipping and return policies, and connecting the account to Google Ads and Shopify. The Google Ads tutorial covers account setup, launching a first campaign, and common budget-wasting mistakes.
Frames setup as a sequence of steps for beginners and connects skipped configuration work with problems that may surface later.
For brands planning a campaign
These topics could suit onboarding content or client education for a B2B ecommerce SaaS company, especially where setup errors lead to disapprovals or campaign problems.
Robin challenges the idea that testing Google Ads requires a large minimum budget.
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The stated approach is to change the testing structure according to spend level rather than assume a single budget threshold works for everyone.
Presents budget as a constraint on how to structure tests, rather than as a simple yes-or-no barrier to testing.
For brands planning a campaign
A brand could explore Robin’s ability to tailor a testing plan to clients with different spend levels. Before commissioning guidance, ask for the framework and examples of how decisions change at each budget level.
The available posts cover Google Ads, Performance Max, Shopify-to-Merchant-Center setup, budget testing, and profitable measurement.
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They do not name an employer, agency, client, sponsor, affiliate program, investment, or owned business; Google’s ad products and Shopify appear as tutorial subjects, not disclosed commercial relationships.
References to accounts “we manage” and a testing system “I use to test and scale ecommerce brands” suggest team or agency work, but do not identify the business.
Ask Robin to clarify who they work with and whether any brand relationships are paid.
Start with the profitability argument: revenue divided by ad spend leaves out cost of goods, shipping, returns and fulfillment, so a strong-looking ROAS can still lose money, while a lower headline number can point to a more profitable account.
Then read the Performance Max structure pieces, which set out the conditions Robin says make the campaign type usable: protect branded search first, split asset groups by margin, feed real customer data and track value rather than volume.
The beginner Merchant Center and Google Ads tutorials cover setup work that Robin identifies as a source of later disapprovals and wasted budget.
Testing at different budget levels is framed as a structural question, not a minimum-spend threshold.
Like Robin, they approach Google Ads performance from the audit side, writing about ecommerce accounts and how panic-driven changes can compound poor results.
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Both use account data to guide the next move, and discuss brand traffic and Performance Max measurement rather than accepting reported ROAS at face value.
Davies focuses on diagnosing a specific problem: separating a genuine fall in market demand from competitor pressure.
They use an impression share report by day and share a third-party script for judging brand share inside Performance Max.
Robin focuses more on structural fixes and setup steps, building the profitability case from margin arithmetic rather than demand-versus-competition tests.
The closest match to Robin's central argument: both use the gap between ROAS and contribution margin to show why an account can look fine and still fail to grow.
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Both organise their advice as short, numbered lists of changes for a specific account and contrast retargeting and warm-audience spend with reaching new customers.
Paxton's examples span Meta and Google and follow client turnarounds, with revenue and margin figures before and after changes that include post-purchase email and free-shipping thresholds.
Robin stays within Google Ads, covering campaign mechanics such as asset group structure and conversion value rules.
They teach beginners Merchant Center and account setup rather than narrating a full client engagement.
Both urge readers to question what a strong ROAS number proves, using brand search as the clearest example of a metric that flatters an account.
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They also work through break-even ROAS from margin and cover recent Google product behaviour for ecommerce advertisers.
Fry focuses on Google's own testing and bidding changes, including Conversion Lift becoming self-serve on Search and Performance Max, and a beta Target ROAS calculator built from margin.
They examine what those tools do and do not prove.
Robin's comparable material covers making Performance Max work through boundaries and business signals, alongside step-by-step setup tutorials for beginners.
This section answers one placement question: do Robin Tesselaar’s posts show they reach the people a B2B ecommerce SaaS company wants — client-side ecommerce operators and in-house Google Ads buyers — rather than only fellow Google Ads practitioners?
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The strong signal is topical relevance.
Their posts (14 April to 30 September 2026) cover practical Google Ads work for ecommerce stores: connecting Shopify to Merchant Center, setting up Merchant Center and a first Google Ads campaign, testing at any budget, structuring Performance Max around margin and branded-traffic protection, and reading ROAS against gross profit and new-customer cost.
They address store owners and marketers running their own accounts, making the content relevant to the target campaign.
The posts do not establish measured audience composition: the only published audience figure is a LinkedIn follower count, with no information about followers’ job function, seniority, employer, company size, or geography, and no platform audience data (for example, YouTube demographics).
Before committing to a paid advisory or content collaboration, ask for recent results on comparable Merchant Center and PMax setup and testing topics, covering reach and, if available, follower or audience analytics such as job titles, seniority, company size, and country for the last 90 days, plus any audience survey.
LinkedIn follower counts and platform analytics can speak to function, seniority, and location; ask for a documented source, such as an audience survey, for employer or occupation claims.
LinkedIn followers
5,347
Recorded on the LinkedIn profile that published the reviewed posts · 2026-10-09
The posts disclose no brand partnerships, sponsorship formats, rates or media kit.
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Robin Tesselaar shares educational Google Ads tutorials and commentary for ecommerce businesses, with no sponsored placements, affiliate disclosures or labelled collaborations.
They write from the perspective of someone managing Google Ads accounts for ecommerce brands, suggesting client-service work rather than creator sponsorship inventory, but publish no service offering, pricing or terms.
There is no official partnership or sponsorship inquiry page, form or contact route.
For a paid advisory or content collaboration, brands would need to make direct contact and agree terms privately.
Confirm scope, deliverables and disclosure expectations with Tesselaar before planning a campaign.
For a B2B ecommerce SaaS company seeking a Google Ads expert to improve client Performance Max and Merchant Center setups, Robin Tesselaar is a strong subject-matter fit, with two conditions.
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Their posts show direct work in the areas the company needs: a five-part PMax structure that protects branded traffic with a dedicated exact-match campaign, splits asset groups by margin, feeds CRM and LTV-weighted audiences, uses conversion value rules, and treats search themes as a discovery diagnostic; Merchant Center and Shopify setup tutorials covering account creation, store verification, team access, feed labels, shipping and returns, and the Google Ads connection; first-campaign setup and budget-tiered testing; and profitability measurement that replaces headline ROAS with POAS, break-even ROAS, branded versus non-branded ROAS, new-customer share, and nCAC.
A separate PMax post adds a disciplined, test-led operating style: start with PMax for many new ecommerce brands, but review spend and placements, test other campaign types, and move budget toward profit.
The conditions are commercial and audience-related.
Their posts disclose no sponsorship formats, rates, media kit, or inquiry route, so this is not a ready-made sponsorship buy; it would need to be negotiated as a paid advisory or content collaboration.
The only published audience figure is a LinkedIn follower count, with no job-function, seniority, employer, company-size, or geography data.
Before proceeding, request recent audience analytics for comparable posts and confirm terms.
Decision: proceed to a scoped paid advisory or co-created content pilot, not a broad sponsorship.
When to choose a specialist
For a consumer brand such as a skincare or fashion label seeking a creator-led paid sponsorship to drive broad awareness and direct sales through a discount code on Instagram or TikTok, Robin Tesselaar is a poor fit based on their posts.
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The posts focus on technical Google Ads work for ecommerce operators: Merchant Center setup, PMax structure, budget testing, and profitability measurement.
The only published audience figure is a LinkedIn follower count, with no engagement metrics, demographics, or platform analytics, so there is no documented consumer reach to buy.
Their posts disclose no sponsorship formats, rates, affiliate terms, media kit, or inquiry route.
Before proceeding, request audience data for the consumer platform you intend to use and confirm that Tesselaar offers sponsorship inventory there.
A worked campaign example
For the B2B ecommerce SaaS company's needs, sell an advisory-led content pilot, not a sponsorship.
The company wants to help its merchant clients fix PMax and Merchant Center setups.
Angle: 'Before you scale PMax, stop it from buying branded traffic and low-margin SKUs.' Pilot structure: (1) a 60-minute diagnostic session for the SaaS company's client-facing team, built on the five PMax controls in Tesselaar's posts: a dedicated exact-match branded search campaign, margin-split asset groups, CRM and LTV-weighted audience signals, conversion value rules, and search themes used only for discovery gaps; (2) a Merchant Center readiness walkthrough for Shopify merchants, covering account setup, store verification, team access, feed labels, shipping and return policies, and the Google Ads connection, with a disapproval-prevention checklist; (3) a measurement session that replaces average ROAS with POAS, break-even ROAS from gross margin, branded versus non-branded ROAS, new-customer share, and nCAC.
Repurpose each session into one co-branded LinkedIn post or short tutorial from Tesselaar, linking to the SaaS company's downloadable checklist.
Measure pilot sign-ups, checklist downloads, session attendance, and a short post-pilot survey asking client teams which single account setting they changed.
Before booking, ask Tesselaar for audience analytics on comparable posts, agree rates and deliverables, confirm disclosure, and decide whether direct product promotion is included.
If audience data or terms are unavailable, run the pilot as paid advisory only and do not buy reach.
Choose Martin Davies when the client's first problem is diagnosing why a Performance Max account underperforms or whether branded search is inflating results.
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The posts cover two specific decisions.
One is splitting brand out of Performance Max: run a dedicated branded search campaign with exact-match keywords and negatively exclude brand from Performance Max, then use a brand-versus-non-brand report to see how much brand traffic the campaign already owns.
The other is using an impression-share-by-day report to distinguish a market-wide demand drop from a competitor taking share.
For a SaaS client whose Performance Max account looks strong mainly because it is buying branded traffic, the brand-exclusion method is a direct starting point.
The posts cover diagnosis and one Performance Max brand tactic, not the broader build a SaaS client's Merchant Center and Performance Max setup requires.
They do not cover Merchant Center account creation, store verification, feed labels, shipping and return policies, or asset-group-by-margin structure.
The brand-exclusion post is from May 2024; confirm the approach against the live account, as Google's current Performance Max brand-treatment defaults may have changed the mechanics.
Davies is the stronger choice for a focused brand-cannibalization or demand-versus-competition audit, and a weaker one for a full Merchant Center and Performance Max setup overhaul.
Choose Jack Paxton when the client's issue is an unexplained sales drop or when catalog and retention economics are the real constraint.
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The posts give a triage order for a sudden revenue drop: check whether tracking agrees across Shopify, GA4, and Meta; check the store conversion rate; check what changed in the ad account; then check seasonality and external context.
They also describe a home goods client case that cut retargeting from 65% of spend to 25%, added LTV-weighted audience inputs from Klaviyo, built a post-purchase sequence, raised the free-shipping threshold, and removed weak SKUs from the catalog feed.
That feed cleanup is the closest work in the comparator set to Merchant Center and Shopping feed decisions, but it appears as part of a growth case rather than a feed setup tutorial.
The posts report one client's outcome: revenue of $197K in month 4 and $280K in month 9, with contribution margin at 23%.
This is a single case, not evidence of a repeatable Performance Max structure, asset-group margin split, branded search protection, or Merchant Center setup process.
Use Paxton to diagnose a drop or for catalog and retention thinking.
Don't treat the case numbers as a forecast; ask for evidence of repeatable results and a separate owner for the Merchant Center and Performance Max setup the SaaS client needs.
Choose Jordan Fry when the client's decision needs measurement proof rather than another campaign setup.
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The posts cover self-serve Conversion Lift for Search and Performance Max to test how many sales the ads actually caused, a warning that brand search ROAS is the easiest number in the account to make look good, and a margin-based Target ROAS method that treats Google's profit-margin calculator as a breakeven floor rather than a target.
The method recalculates breakeven when real margin differs after returns, payment fees, and shipping: a 15% margin gives 6.67x breakeven, but a 12% real margin moves it to 8.33x.
For a SaaS client that needs to know whether a Performance Max account is genuinely profitable, this is more useful than setup guidance.
The Conversion Lift test has eligibility floors: at least 1,000 observed conversions and at least $5,000 in campaign budget; it is not available to every account.
Many small and mid-size clients cannot run it.
The posts do not cover Merchant Center setup, feed labels, or Performance Max structure and asset-group work, so the build-and-fix work still needs a setup owner.
The margin method also depends on the client providing a true post-returns, post-fees margin that Google Ads does not contain.
Robin Tesselaar's seven LinkedIn posts cover two beginner tutorials on connecting Shopify and Google Merchant Center and setting up a first Google Ads account, a framework for testing at different budget levels, a five-part structure for making Performance Max work, a shorter post on using Performance Max as a starting point, and an argument that return on ad spend is not the same as return once cost of goods, shipping, returns, and fulfilment are counted.
The posts do not show publication dates, so they cannot be ordered chronologically or used to claim that Robin's views have shifted over time.
Several posts describe video tutorials, but no transcripts accompany them; the descriptions here reflect the accompanying post text, not the videos.
The LinkedIn account was observed on 9 October 2026, and the only audience figure shown is a follower count.
The posts here do not include engagement data, audience demographics, employer or client names, sponsorship terms, rates, or a media kit, so brand relationships and commercial offers are undocumented rather than absent.
The similar-creators section compares Robin with Martin Davies, Jack Paxton, and Jordan Fry using two posts each from those creators.
