The biggest Google Ads mistake ecommerce brands make

The biggest Google Ads mistake ecommerce brands make has nothing to do with your feed, your creative, your campaign structure, or your bidding strategy. It's not a technical error. It's not a missing setting.

It's emotional decision-making. And it's probably happening in your account right now.

That means pausing ads after 24 to 48 hours because results look off. Rebuilding your campaign structure every few weeks with no real reason. Switching agencies for the fourth or fifth time because a bad month felt unbearable. Making tweaks that feel like progress but are really just a response to anxiety. This affects everyone. Beginners and experienced operators alike. The difference between someone who wins and someone who keeps spinning is not knowledge of a secret tactic. It's discipline over their own reactions.

What it actually looks like

You launch a campaign. Two days in, it's not where you hoped. So you pause it. Or you change the target. Or you rebuild the whole thing.

Or you've had a great run. Revenue is up, budgets are scaling. Then one Wednesday afternoon performance looks soft and you message your agency asking what to do - after spending 25% of the daily budget by midday.

That second scenario is a real story. Chris had a client in the UK who had been crushing it in mid-October. They were doubling budgets almost every day. Then one Wednesday at 12pm the client sent a WhatsApp message asking whether they should scale back or set a higher target. At that point, they'd spent around 25% of the day's budget. Performance mid-morning hadn't looked great.

We were crushing it for like almost two weeks straight with high profit margin. And he writes me a message at 12pm in the middle of the week, middle of the day, after spending 25% of the budget.

Chris held firm. Don't touch anything. Wait until at least end of day. That afternoon, the numbers started to climb. From around 9pm to midnight, orders kept rolling in. That day - the one that looked mediocre at noon - turned out to be a record day. Close to 10k in revenue. If they'd cut the budget or adjusted the target at lunchtime, they would have disrupted the algorithm right before it hit its stride.

That's one story. There are many more like it. The pattern is the same every time: a short-term reaction nearly kills a long-term result.

Why it happens

Nobody likes losing money. That's the core of it. When performance dips, the instinct is to do something. And doing something feels better than sitting still.

There's also a small dopamine kick in making a change. You're not just watching things fail - you're taking control. You close your laptop feeling like you acted. The problem is that the action had no rational basis. You changed something without knowing if it was the thing to change. And now you have less data than you started with, because you interrupted the process.

Chris calls it misreading short-term noise as truth. You think you have data. But you don't. And deep down you probably know it. You just can't sit still.

This happens at every level. Brands spending a few hundred a day do it. Brands with seven and eight figure monthly revenue have people on their team who do it. The ones who consistently win are the ones who've trained themselves not to react - to look at a bad day the way a scientist looks at a result they don't understand yet. Not with panic. With curiosity.

The three rules that fix it

These aren't hacks. They're operating principles. Simple to understand, hard to stick to.

Rule one: zoom out before you touch anything.

If yesterday was bad, look at the week. If the week looks off, look at the month. One bad day might be weather. It might be a holiday. It might be a Wednesday. Chris has said he won't act on a single bad day no matter what. Even two or three bad days still need context before they justify any change. Zoom out, breathe, then decide if there's actually something to address.

Rule two: set a minimum data threshold.

No big moves until you have enough conversions and clicks to spot a real pattern. This is especially true in the learning phase. If you're in learning and performance doesn't look right, the answer is almost always to wait. The algorithm can't optimize without data. If you cut it off early, you're not saving money - you're just resetting the clock.

You need to be able to point to real data before making a real decision. Not a feeling. Not a gut read at 11am. Real numbers over a meaningful time window.

Rule three: one change at a time.

This is where a lot of operators go wrong even when they've got rules one and two right. They identify a problem, then change five things at once. New agency. New ads. New campaign structure. New target. All in the same week.

If your ROAS then goes up, you don't know which of those changes caused it. You learned nothing. You're back to guessing. If it goes down, same problem.

Make one adjustment. The right one, based on the data you have. Then wait. See what moves. Then decide the next step. Like a scientist, not like someone who needs to feel busy.

This is not a casino

Google Ads isn't random. If you remove the things that aren't working and double down on the things that are, results will follow. Chris puts it plainly in the video - this is not a casino. If you stick to your process, act on real data, and don't panic, there's no mystery about where this goes.

He uses a gym analogy that lands well. If you train consistently and cut the foods that are working against you, you will get in shape. There's no world where you do both correctly and fail. The same logic applies to ads. Remove what's not working, double down on what is, and keep going. If it's still not working after a proper test window, then you dig into why - the offer, the creative, the hook. You break it into puzzle pieces and find which one needs fixing.

What doesn't work is changing everything at once in a panic and hoping something sticks.

There are brands that have run ads at a loss for a month or two and still came out winning, because they didn't overreact. They kept reading the data, removing what wasn't working, scaling what was. That patience is not easy. But it's what separates the operators who actually scale from the ones who stay stuck in a loop of restarts.

If you want to go deeper on how this shows up in real accounts, read why ecom brands overcomplicate Google Ads - the pattern is the same.

What to do this week

Three things. Pick the one that applies most right now.

If you have campaigns in the learning phase: don't touch them. Set a reminder to check back in five days. Not tomorrow.

If you've been making changes every few days with no clear reason: write down the actual data point that justifies the next change before you make it. If you can't write it down, it's not a real reason.

If you've been through multiple agencies and the results keep being disappointing: ask whether the briefing, the data access, and the time given to each agency was actually enough to work with. The pattern might not be the agencies.

The fix for emotional decision-making is not a new tool or a smarter campaign structure. It's a simple operating rule: don't act until the data says act.

If you want to see how we apply this in practice across real client accounts, read through our process or see the results we've built with brands who gave it time to work.

Frequently asked questions

What is the biggest Google Ads mistake ecommerce brands make?

Emotional decision-making. That means pausing ads after one or two days, rebuilding campaigns without a real reason, or switching agencies too often. These moves feel productive but they're based on fear, not data. The account needs time and patience to give you anything useful to act on.

How long should I wait before making changes to a Google Ads campaign?

It depends on your spend and conversion volume. A few bad hours mid-day is not a signal. A few bad days might not be either. The goal is to collect enough conversions and clicks to see a real pattern. In the learning phase especially, the most important move is to wait and not touch anything.

Why do ecommerce brands keep switching Google Ads agencies?

Usually because they're reacting emotionally to short-term results. If you've had four or five agencies and nothing has worked, the issue probably isn't the agency. Ask yourself whether each switch had a clear, rational reason behind it or whether it was driven by a rough week of performance.

What is the one-change-at-a-time rule in Google Ads?

If you change your campaign structure, your agency, and your ads all at the same time and your ROAS changes, you have no idea which change caused it. You're back to guessing. Make one adjustment, wait for enough data, evaluate, then decide what to do next.

Is it ever okay to make changes during the learning phase?

Almost never. The learning phase exists because the algorithm is gathering data. If you change something in that window, you reset the process and throw away whatever data was collected. The most productive thing you can do in the learning phase is let it run.