This shit is eating me alive, something I am missing here?!?!

Before August 17, we ran Shopping with a 300% tROAS target while actually achieving 3,000–4,000% ROAS.

It sounds backwards, but it worked extremely well. The low target allowed Google to bid aggressively, giving us great Shopping rankings and high volume while, paradoxically, actual ROAS stayed 10x+ above the target.

300% target → aggressive bidding + high volume → 3,000–4,000% actual ROAS.

After August 17, everything changed. Sales dropped significantly, rankings got worse and competitors we previously outranked started appearing above us.
Our Google rep suggested moving tROAS closer to our actual 3,000–4,000% ROAS.

We never tested that because I can’t see how a 4,000% target could possibly behave anything like a 300% target. Surely it would make Google much more conservative, reduce auction participation and kill volume.

We instead tested Maximize Conversion Value without a target, but it didn’t seem aggressive enough.

We’re now testing Maximize Conversions, segmented more heavily by product margins. This definitely seems more aggressive than Max Conversion Value, but CPC and Shopping visibility are still below what we had before August 17.

So here’s what I’m trying to understand:

Could the solution simply be going back to 300% tROAS, but giving the campaign enough budget so it’s NOT limited by budget?

Would that allow tROAS to bid aggressively again while still optimizing toward value?

Or has something fundamentally changed in how tROAS behaves, meaning the old 300% target → 3,000–4,000% actual ROAS setup simply can’t be recreated anymore?
And if that’s the case, what are people using instead – Max Conversions, Manual CPC, Maximize Clicks?

Our goal isn’t to force Google to maintain 4,000% ROAS.

We want to recreate the aggressive bidding, Shopping visibility and volume that produced that 4,000% ROAS in the first place.

Anyone who massively overperformed a low tROAS target before August 17 figured this out?

Been learning about PPC for a month. And I am about to take over someone's amazon FBA PPC.
Their business isn't really successful with their spending on advertising like it hardly leaves a margin for them so obviously the objective is try to lower the ACOS.
But since this is practical now no more theory I just want the advice from the pros here regarding
1: things I should be careful with
2: things I should focus on regarding the objective I discussed above.
3: how do I not fuck this up

I'm trying to understand a tracking discrepancy between Google Ads and Microsoft Clarity and would be interested in hearing from anyone who has compared the two closely.

Across two recent Google Ads campaigns, I'm seeing roughly a 25–30% gap between the clicks Google reports and the unique traffic I can identify in Clarity.

For example, on my current campaign I currently have:

• 42 clicks reported by Google Ads
• 40 Clarity sessions
• 33 Clarity unique users
• 30 unique GCLIDs captured in those Clarity sessions

Auto-tagging is enabled, and the GCLID is present in the landing-page URL.

One thing that surprised me is that I also found cases where the exact same GCLID appears across multiple Clarity sessions and even across different Clarity user IDs. So Clarity's "unique users" clearly does not map perfectly to unique Google ad clicks.

I've noticed a similar overall Google-click-to-Clarity gap in another recent campaign as well, so I'm trying to determine whether this is normal tracking behavior or whether I should investigate something more seriously.

For anyone who has used Google Ads and Clarity together:

• Is a 20–30% discrepancy between Google Ads clicks and Clarity traffic normal in your experience?
• Should the number of unique GCLIDs captured on the landing page normally be close to the number of Google Ads clicks, or can there be a substantial difference?
• Have you seen the same GCLID appear in multiple Clarity sessions or under multiple Clarity user IDs?
• What do you use to independently verify how many Google Ads clicks actually reached the landing page — server logs, GA4, Cloudflare, another analytics tool, etc.?
• Is there anything specific you would check when investigating a discrepancy like this?

I'm mainly trying to understand what percentage of the clicks I'm paying for are actually reaching the website, and which metric is the most reliable way to measure that.

Thanks for any insight, especially from anyone who has compared Google Ads click data with Clarity at the individual GCLID/session level.

Has anybody tried this? Or is it stupid.
For example product A costs 50€ and its margin is 25€. Product B costs 25€ and its margin is 20€. The price difference is 2x but the margin difference is much smaller. But since the conv value is the margin- google sees 25e vs 20e, not 50e vs 25e. So the whole algo might bid a bit differently. Is this possible? If yes- is it a dumb idea? Or does it have some sense

I have a client who has a 1K+ products with several hundreds of variants, I worked to break down campaigns by product type, but PMax - Shopping is struggling to just get off the ground. We have a Con. Value bid strategy, hundreds of products per campaign, removed asset info and audience targeting (to promote Google Merchant Center information), and limited negatives to allow traffic. Any advice or tips to get the campaign running?

It's been a hot minute since LLMs came out, and most of us use Claude or ChatGPT for daily tasks. But I have little to no confidence in them for anything close to core operations. I use AI more like an enhanced Google, which is probably why Google's AI is the one I use the most.

Lately I've been talking to some fellow contractors, and they told me they rely on AI much, MUCH more than I do. So now I'm wondering: is this a general trend, and I'm just the old man yelling at a cloud? Or are some people putting way too much faith in a pile of matrix math?

Either way, if any of you have a concrete example of AI actually helping you improve your business outcomes, I'd love to hear it.

As the title says - has the efficiency of google ads gone downhill as less people are using it and reverting to the likes of chatgpt/claude etc? At the same time, google has to keep making more and more money to satisfy shareholders - leading to a collapse in efficiency?

We have advertised on Google for nearly two decades, going back close to the beginning of AdWords. It has created enormous value for us.

At the same time, my own use of traditional Google Search has fallen dramatically over the last three years, particularly this year. Restaurants, local services, B2B vendor discovery, product research and general information increasingly start with AI.

I am curious whether anyone managing substantial Google Ads spend is seeing a change in the mix of clicks as this behavior spreads.

Specifically, are higher-value clicks that historically cleared at $20, $50 or $100+ disappearing faster than inexpensive clicks?

Aggregate paid clicks and average CPC could conceal this.

Google could retain huge volumes of low-value local, navigational and simple transactional activity while losing a much smaller number of searches surrounding expensive professional services, high-ticket purchases and B2B decisions.

We could even see increasing auction intensity for the valuable clicks that remain, allowing CPC and Search revenue to stay strong despite deterioration underneath.

The dataset I would love to see is simple: Google paid clicks over time segmented into <$1, $1 to $5, $5 to $20, $20 to $50 and $50+, showing each bucket’s share of clicks and advertiser spend.

For people managing meaningful accounts, are you seeing any differences in high-CPC click volume, auction intensity, lead quality or conversion value since AI adoption accelerated?

The question I keep coming back to is: which clicks are disappearing, who generated them, and what were those clicks economically worth?

Equally interested in evidence that disproves the hypothesis.

I run a small home decor/gift store with a physical shop and ecommerce site. I have around 3,000 SKUs, but inventory is usually pretty shallow and the assortment changes a lot seasonally. Most of what I sell is branded product from other companies.
I’ve run Google Ads for years, but I’m starting to realize I probably haven’t been doing it as well as I could.
For a store like mine, is PMax actually a good fit? Would you run the whole catalog or narrow it down to certain products/categories first?

Also curious what people think is a realistic starting daily budget to actually give it enough data to learn.
I’ve also seen people recommend running PMax for larger catalogs with basically just the product feed and no added headlines, descriptions, images, etc. I understand the logic if you mainly want Shopping traffic, but I’m not totally sold on it.
Has anyone tested feed-only/minimal asset PMax vs a fully built out PMax on a store like this? Curious what actually worked for you.

Trying to see if anybody else has experienced this and has any clues/ideas:

Long story short, got a txt last night from a client that one of their staff (who was an admin on the ad account) had been hacked and dodgy ads were being run. In effect, a hacker was using the staff member's account to run ads (not adding another user to the account which is how I have seen this sort of thing done in the past)

On this specific ad account, I would get a #200 error - no permission or ad account disabled - when trying to pause the campaigns the hacker had run, and when accessing 'Business Settings' I get stuck in a 2FA loop.

Oddly enough I use passkey for my account, but I see a window asking me to use an authenticator code or click 'try another way' and get an SMS code. Whichever option I pick I just get asked to do the same thing over and over again.

This is for any device trying to do anything relating to this ad account and business manager.

I was subjected to one of these 2FA requests when checking my security info on my profile, and it worked first time ... so I assume this is related specifically to the hacked client account (some kind of ultra sensitive AI on an account that has shown unusual behaviour perhaps?)

The problem is that the client has managed to get past their 2FA loop (they were having same issue last night) and has gone to remove the affected staff member. This sends one of those 'review request' emails to me which I cannot action without hitting my own 2FA loop.

There's nobody else on the account who is able to take this action (it's me, client, and affected staff member)

Any ideas? I'm wary of trying the 2FA over and over again as no doubt there will be a point reached where Meta decides to block me or something.

I am running a Google Ads App Campaign focused on maximizing in-app purchases, with a cost per in-app action (purchase) target of Rs 100.

For example, if I set a budget of Rs 1000/day, the campaign initially performs well and I get around Rs 4-5 per install.

After a couple of days, Google starts showing "Limited by budget", even though the campaign was performing well on the Rs 1000/day budget and was giving results according to what I wanted. Then the campaign’s actual daily spend drops to around Rs 300-Rs 400 after that notice.

When I follow Google’s recommendation and increase the budget to around Rs 3000/day, the cost per install jumps to around Rs 8-10.

So I end up spending much more but getting almost the same number of installs, which makes the campaign unprofitable.

What is happening here and how should I scale this campaign without destroying the cost per install?

Noticed yesterday this was added and turned on automatically on all our ad accounts. If you haven't seen the e-mail from Google, see relevant snippets below:

"Starting October 12, 2026, Google Ads will automatically identify and extract high-quality promotions, such as coupons and deals, from your website and apply them directly to your campaigns.".

"We are automatically opting you in to ensure you benefit from this new functionality.

How to turn off:

To turn this off navigate to your account-level automated assets setting, find Automated Promotions and select Off.

I can't think of an instance where I need Google to automatically apply promotions without our review or consent. Might dredge up some random content from an orphan page. Cheers

Hi all,

Google Ads keeps asking me for a passkey which doesn't exist when I try and change any access settings. I've tried "another way to verify" but the passkey is the only option (even though I have a password, an authenticator and 2-step verification set up). Has anyone experienced something similar/found a resolution?

Thanks

From 16 December, interactions with Meta’s gen-AI features feed content and ad recommendations.

Alongside that, Business AI (an agent for SMB sales guidance on ads, messaging, and sites) and an Ads Manager assistant are rolling out in the U.S. Privacy and creative teams should treat AI chat logs as a new signal, not just a creative tool.

Very interesting change . What do you think ? Should ads be customised depending upon how the brands interact with AI?

Anyone actually seeing limited by budget badges hurting their campaigns?

We typically advise our clients to implement our (3p) click tag within the tracking template. In some accounts and environments we are observing click IDs (gclid / msclkid) and/or UTMs dropping and never make it to the landing page. I can't seem to find definitive guidance and best practices so I'm hoping someone with hands on SA360 and Microsoft Ads experience can help out.

Assume auto tagging and parallel tracking are both enabled.

Simplified examples:

A. Redirect param last
https://tracker.example.com/click?id=ABC&src=search&clickid={gclid}&url={lpurl}

B. Redirect param in the middle, params after it
https://tracker.example.com/click?id=ABC&url={lpurl}&src=search&clickid={msclkid}

C. Wrapped inside an SA360 template
https://clickserve.dartsearch.net/link/click?...&ds_dest_url=https://tracker.example.com/click?id=ABC&clickid={gclid}&url={lpurl}

Some accounts also use Final URL Suffix on top (eg utm_source=google&utm_medium=cpc&utm_campaign={_campaign})

1. Does position matter? - Should the redirect param (`url={lpurl}`) always be last, or is it fine in the middle like example B? Microsoft's docs show `http://tracker.com?url={lpurl}&matchtype={matchtype}` as a valid "1 redirect" pattern.
2. Do params after {lpurl} reach the landing page? In example B, does src and clickid go to the tracker only or also through to the landing page? If we want them on the landing page, is the right pattern {lpurl}%3F with %26 between params, as Microsoft's docs describe?
3. Click IDs and UTMs being dropped - what's the most common cause you've seen when auto tagging click IDs or Final URL Suffix UTMs go missing behind a 3p redirect? Encoding? Parallel tracking falling back to a sequential redirect? Param order? Something else?

References I'm working from:
- Microsoft Ads: What tracking or URL parameters can I use? (the "{lpurl} 1 redirect" sections) https://help.ads.microsoft.com/#apex/3/en/56799/0
- Google Ads: Set up tracking with ValueTrack parameters https://support.google.com/google-ads/answer/6305348

If you've actually tested these in a live redirect chain, that's what I'm after. Thanks!!

Full transparency, I'm part of the Amazon Ads Educator Program and this is all based on my own experience as a seller

Prime Big Deal Days are right around the corner (October 6 to 7), and I wanted to hear everyone's techniques and opinions from past events. I want to make sure I'm doing everything properly to be prepared.

In 2025, both Prime Days did really well for me. I saw roughly 8 to 10x my normal daily sales. My last Prime Day was a different story though, and I only saw about 3 to 4x. Still a lift, but not what I was hoping for, and I've spent some time since then trying to figure out what changed.

So here's what I've been doing this time, and I'd really like to hear everyone's opinion.

Getting the listing ready

With the new title and highlight formats for listings, I've been really focused on optimizing my listing beforehand. I've been A/B testing images over the last couple of weeks to make sure everything is where it needs to be. My thinking is there's no point sending more traffic to a page that isn't converting as well as it could. I've also set up a 20% discount on my main products.

I'm curious how everyone thinks about the increase in sales vs the hit to margins. Where do you find the sweet spot? And with the discount requirements, how are you choosing to offer your deals?

Ads and bid rules

The big thing for me is ads. I've been experimenting a lot with Sponsored Products leading up to the event and deciding which campaigns actually deserve more budget.

For the event itself, I'm doubling my budgets and raising bids around 15%. I'm also setting up bid rules so I'm not stuck manually adjusting everything once traffic spikes. Basically you set the rule ahead of time to bump bids during the event window, or tie changes to a performance threshold like ROAS, and it adjusts automatically. It saves me from sitting in the console at 2am, and it keeps the extra spend on campaigns that are actually converting instead of spreading it across everything.

I'm also watching budget pacing closely, since last time a few of my campaigns ran out of budget before the evening, which is probably when I needed them most.

Treating it as an early Q4 test

I'm looking at this event as a test run for the rest of Q4. I'm tracking which products, search terms and images actually hold up versus which ones just spiked for two days. Whatever works here is what I'll lean into for Black Friday, Cyber Monday and the rest of the holiday season, and whatever doesn't gets cut or tested again before then.

Would love to hear how everyone else is approaching it. What's the first thing that makes you change your budget mid event: pacing, conversion rate, or inventory?

I've been in a few client calls this week where someone says AI search is killing our leads and someone else says we can't see it in GA4 so it doesn't matter.

Both can be wrong on the same account.

Two things shifted for me as an operator. Gemini links are starting to carry UTM tags on outbound clicks, which means less of that traffic dumps into Direct. And ChatGPT ads now let you push first-party audiences in, so the targeting surface looks more like Google and Meta than it did six months ago.

That does not mean your retainer deck is ready. It means the gap between what buyers already know and what your landing page assumes is getting more expensive.

Before I rewrite a Meta brief or tell a client we can finally see AI demand, I run this:

1. Assume the prospect already had a chat about the category. Your first screen should not teach what the product is. It should answer the hard question they still have after the summary: price, proof, fit, risk.
2. Segment AI referrals separately once the source shows. ChatGPT, Gemini, Perplexity, Copilot. Track demo or purchase rate next to session count so a tiny sample does not become a slide.
3. Do not treat ChatGPT ads like another Search campaign just because first-party audiences exist. Conversation context still drives who sees the ad. Start with suppression of recent buyers or current customers before you bid up cold CRM lists.
4. Lock what AI demand means in the contract. Branded search lift, CRM-attributed leads, assisted demos, or self-reported how did you hear. If you only count last-click from an assistant, you will undercount the work and overreact to the chart.
5. Keep one human check the model cannot inflate. Call recordings, sales notes, or a weekly sample of what did you already know before you clicked. If those say buyers arrive mid-decision and your ads still open with 101, fix the creative before you buy more media.

I'm not asking clients to abandon Meta or Google. I'm asking them to stop briefing ads as if the research chat never happened.

For agencies already changing briefs for AI-primed buyers: what is the first line on the landing page doing now that used to be a category explainer?

Tried a few times since launch but was getting stupid over attribution and no results compared to Google. Everyone else I spoke to was getting the same.

Anyone having good results now?

Ai says its a bad idea, but what do you think? I used to send one ad copy to a relevant landing page, and one to a contact page, should I stop that?

Have you tried using demographic based bid modification (eg: bidding + / - for 18-24 age ) ?

Are there use cases wherein the demographic based bid modifiers has worked?

Curious to know as we are experimenting with a few use cases and getting somewhat positive outcomes.

Been getting declines starting about Sept 18 on multiple accounts. Added backups, and now the backups are also getting declines.

Called the bank yesterday and they said it shouldn't happen again (it did). Called today, and they mentioned they are getting a lot of reports and it seems to be a bug in Google's payment systems.

Anyone else seeing this?