Why a Google Ads “Growth Manager” Should Matter to Anyone Selling Across Borders
Let me start with a confession that will annoy my fellow agency owners: most cross-border sellers I meet are terrible at Google Ads. Not because they’re dumb, but because they’re trying to run a global business on a platform that punishes neglect. You’re juggling Amazon PPC, TikTok Shop campaigns, and Shopify email flows, and Google Ads sits there like a leaky faucet—dripping margin every day while you focus on the fires that are actually burning. The problem isn’t creative or budget; it’s that Google’s own recommendations are self-serving, and most third-party tools just repackage the same obvious advice. So when I saw GoodLads launch on Product Hunt, I didn’t care about the AI hype. I cared about one specific claim buried in the thread: that a human with 15+ years of Google Ads experience built a system to run experiments against Google’s recommendations, not with them. For any seller spending serious money on search—whether you’re selling on Shopify or driving traffic to an Amazon listing—that’s the most interesting sentence I’ve read this quarter.
The Real Problem: Google’s Recommendations Are a Conflict of Interest
Let’s be honest about what Google Ads has become. The interface is designed to extract maximum spend, not maximize your return. The makers of GoodLads—Pavel Kucherbaev and Yannick Veys—make this point bluntly in their launch thread. Veys, who has 15+ years optimizing Google Ads, calls out a specific example: when your campaign is “limited by budget,” Google recommends increasing the budget. That sounds helpful. But Veys argues the opposite: “Limited by budget actually means: you pay too much per click.” His counter-intuitive fix is to reduce your target cost per acquisition, which can improve performance with the same budget.
Think about what that means for a cross-border seller. You’re already paying currency conversion fees, dealing with longer shipping times, and competing against local sellers who understand the cultural nuance of each market. The last thing you need is a platform nudging you to spend more when the real issue is that your bids are too aggressive for the conversion rate you’re actually getting. The GoodLads thesis is that Google’s suggestions are designed to increase your spend, not your profitability. Whether you agree or not, the fact that a tool exists to systematically challenge those suggestions is valuable in itself.
The deeper issue here is experimentation fatigue. Pavel, who launched TimeTuna (which hit #1 of the day in December), describes the pain point perfectly: launching the first campaign from scratch was “more complicated than filing a tax return in the Netherlands,” and after launch, it was hard to “keep experimenting consistently” to attract new paid clients with a good cost of acquisition. That’s the exact problem I see with mid-sized sellers. They have the budget to compete, but they don’t have a dedicated PPC manager. So they set up a few campaigns, let Google’s automated bidding run, and check in once a month to see if they’re losing money faster than last month.
Why Amazon sellers should care more than Shopify ones
Here’s where I’ll be contrarian: if you’re a pure Amazon FBA seller, you might think Google Ads is irrelevant because you’re spending on Amazon PPC. But the smartest operators I know are using Google Ads to drive traffic to their Amazon listings or their Shopify storefronts as a hedge against Amazon’s algorithm changes. The problem is that Amazon PPC and Google Ads require completely different skill sets. Amazon’s platform is more straightforward—you’re bidding on intent signals within a marketplace. Google Ads is a complex beast with Quality Score, ad relevance, and a labyrinth of campaign types. The GoodLads approach—structured experimentation with statistical testing—is exactly what you need if you’re trying to build a sustainable traffic source outside of Amazon’s walled garden.
What GoodLads Actually Does: An AI That Proposes, You Dispose
The core product is an “AI growth manager” that connects to your Google Ads account via the API and runs a continuous experimentation loop. But here’s the critical design choice that sets it apart from every other “AI marketer” I’ve seen: human approval is required before any change goes live. In the Product Hunt thread, Dylan Friddle praises this, saying he “wouldn’t want anything touching an ad account on its own.” Pavel confirms this was intentional: “AI helps with the feedback, summary, and coming up with new experiment ideas, but the actual changes in Google Ads only happen with a user approval.”
This is the right call, and it’s why I’m taking this product seriously. The market is flooded with tools that promise fully autonomous ad management. They fail because Google Ads is too context-dependent—what works for a $10k/month pet supply store in Germany won’t work for a $250k/month electronics brand in the US. The GoodLads team scoped their product to accounts spending between $10k and $250k per month, which tells me they understand their ICP. Below $10k, you don’t have enough data for meaningful experiments. Above $250k, you probably have an in-house team that’s already doing this work.
The workflow is built around a Kanban board, which caught the eye of Evan Taft in the comments: “Keeping track of what was tested and what happened sounds genuinely useful.” That’s the thing—most sellers don’t have a system for tracking their ad experiments. They might test a new headline, see a good day, and assume it worked. They don’t account for day-of-week effects, seasonality, or the fact that the control group would have performed better anyway. GoodLads applies statistical testing to determine whether a hypothesis actually moved the needle.
Where the math breaks
The makers are refreshingly honest about the limitations of their statistical approach. When asked how long a hypothesis sits on the Kanban before getting a verdict, Pavel explains that it depends on “the number of clicks, and the size of the impact.” A huge impact (25% improvement) might be visible within a week. A modest impact (5%) might take four weeks. And very small impacts might not be detectable at all. Their recommendation is to run experiments for at least two weeks.
Here’s where the math gets uncomfortable for cross-border sellers: if you’re running ads in multiple countries with different languages and currencies, your data gets fragmented. A $10k/month account spread across five markets means only $2k per market—probably not enough for statistically significant results in any single one. The tool might be better suited for someone running a consolidated campaign structure across similar markets (US, UK, Canada, Australia) rather than someone trying to manage wildly different regions like Japan, Brazil, and Germany simultaneously.
The Incumbent Landscape: What Are You Actually Comparing This To?
To understand whether GoodLads is worth your attention, you need to see it against the alternatives. The first comparison is Google’s own Recommendations engine. It’s free, but it’s designed to increase spend. The second is an actual human PPC agency. They’re effective but expensive—typically charging 15-20% of ad spend or a monthly retainer that doesn’t make sense for accounts under $50k/month. The third category is semi-automated tools like Optmyzr or AdEspresso, which offer automation but still require you to know what you’re doing.
GoodLads sits in a middle ground: it’s cheaper than an agency, more intelligent than Google’s native suggestions, and more structured than DIY tools. The key differentiator is the Kanban-based experimentation workflow combined with the AI’s ability to generate hypotheses based on Veys’ 15+ years of know-how. The makers claim some of these insights “often are different from the recommendations given by Google,” which is either a huge value proposition or a red flag, depending on your perspective.
The comparison that matters most for cross-border sellers is against Helium 10 or Jungle Scout if you’re an Amazon seller. Those tools are fantastic for product research and keyword optimization within Amazon, but they don’t touch Google Ads. If you’re trying to build a brand that survives outside Amazon’s ecosystem, you need a Google Ads strategy, and GoodLads might be the missing piece in your tooling stack.
The “one-click apply” temptation
There’s a revealing exchange in the comments where Yannick admits they’ve had mixed reactions to the human-approval requirement: “Some people actually prefer to just have a one click apply button.” This is where I’ll push back on the makers. I understand the appeal of autonomy—it saves time. But for a cross-border seller, the last thing you want is an AI making unilateral changes to your ad account while you’re asleep in a different time zone. The approval requirement isn’t a bug; it’s the feature that makes this tool safe to use.
What Cross-Border Sellers Can Borrow (Even If You Never Buy the Tool)
Here’s the part I want you to take seriously even if you never sign up for GoodLads. The underlying philosophy—structured, continuous experimentation with statistical rigor—is something you can apply to every part of your cross-border operation. Not just Google Ads, but Amazon PPC, TikTok Shop campaigns, and even your Shopify email flows.
First, institutionalize your experimentation. Most sellers I talk to have a “test everything” attitude but no actual system for tracking what they tested, what the hypothesis was, and what the outcome was. They remember that “we tried lowering price once and sales went up” without remembering the season, the competitive landscape, or the ad spend behind that test. A simple Kanban board—even in Trello or Notion—would be a massive improvement over the status quo.
Second, challenge platform recommendations. Google isn’t the only platform with a conflict of interest. Amazon recommends you use FBA for everything because it makes them more money. Shopify recommends Shop Pay because it increases their transaction volume. Meta recommends broad targeting because it simplifies their auction. None of these recommendations are designed to maximize your profitability. They’re designed to maximize platform revenue. The GoodLads example—reducing target CPA instead of increasing budget when limited by budget—is a masterclass in thinking independently.
Third, don’t let perfection be the enemy of progress. The statistical testing approach means some experiments will be inconclusive. That’s fine. The goal isn’t to win every test; it’s to have a high rate of consistent experimentation. Pavel says it well: “a consistent high rate of experimentation is a very good proxy for success.” For cross-border sellers, this is especially important because you’re dealing with multiple markets, multiple currencies, and multiple customer behaviors. What works in the US might fail in the UK, not because your product is bad, but because the search intent differs.
Where My Judgment Says It Falls Short
I’m not going to pretend this is a perfect product. The first issue is the pricing. The Product Hunt launch includes a 50% promo code “MAKEITEASY,” but the actual pricing isn’t disclosed in the thread. That’s a red flag for me. If you’re targeting accounts spending $10k-$250k/month, the tool needs to be priced at a level where it’s obviously cheaper than hiring a PPC manager but expensive enough that the company can survive. If it’s $99/month, it’s probably not sustainable. If it’s $2,000/month, it’s only worth it for accounts at the higher end of their target range.
The second issue is the single-platform dependency. This tool only works for Google Ads. If you’re a cross-border seller running ads on Amazon, TikTok, and Meta, you need a tool that gives you a unified view. GoodLads is solving one slice of your advertising problem. That’s fine if you’re already using specialized tools for each platform, but it adds another subscription to an already bloated SaaS stack.
Third, the “know-how” is concentrated in one person’s experience. Veys has 15+ years of experience, which is valuable. But AI models trained on one person’s playbook are inherently limited. Google’s algorithms are constantly changing, and what worked in 2019 might not work in 2026. The tool needs to learn from its users’ experiments, not just from Veys’ historical knowledge. I’d want to see how the AI incorporates new learnings from the broader user base over time.
Finally, there’s the question of whether this solves the right problem for cross-border sellers. The biggest pain point for most of my readers isn’t experimentation—it’s finding products that can actually compete internationally. Google Ads optimization is a second-order problem. If your product doesn’t have international demand, no amount of ad optimization will save you. The makers might argue that they’re not trying to solve that problem, and they’d be right. But it means this tool is for sellers who’ve already validated their product-market fit and are now trying to scale efficiently.
What I’d Watch / Test Next
If you’re intrigued by the GoodLads approach but not ready to hand over your Google Ads account, here’s what I’d do this week:
Audit your current Google Ads experiments. Open your account and look at the last 30 days. How many actual experiments did you run? Not changes—experiments with a hypothesis and a success metric. If the answer is fewer than three, you have a process problem, not a tool problem. Start a simple spreadsheet or Trello board to track your next three experiments, including what you expect to happen and how you’ll measure success.
Try the GoodLads product with the promo code. The 50% discount code “MAKEITEASY” is available for the Product Hunt launch. Even if you only use it for a month, you’ll get access to the Kanban workflow and the AI-generated hypotheses. The most valuable part might not be the automation—it might be seeing what a 15-year veteran would test in your account. You can learn from those suggestions even if you don’t apply them.
Apply the counter-intuitive logic to other platforms. The “limited by budget actually means you pay too much per click” insight applies to Amazon PPC too. If your Amazon campaigns are hitting their daily budget, don’t just increase the budget. Look at your target ACoS and see if you can lower it to force more efficient bidding. The same logic applies to TikTok and Meta—platforms always want more budget, but sometimes the fix is tighter targeting or lower bids, not more money.
Build your own experimentation cadence. Whether you use GoodLads or not, commit to a weekly experiment review. Pick one variable to test—headline, bid strategy, landing page, audience—and run it for two weeks. Document the hypothesis, the data, and the verdict. After a month, you’ll have a portfolio of learnings that most of your competitors don’t have.
The bottom line: GoodLads is worth watching because it represents a philosophy more than a product. It’s a bet that platform recommendations are self-serving, that experimentation should be structured, and that human oversight is non-negotiable. Those are three beliefs I share. The question is whether the execution matches the philosophy—and whether you’re ready to hand over your ad account to an AI that learned its tricks from a Dutch tax return hater.
