Performance Max: I Was A Skeptic & Now I’m Devout (Even In Bing) via @sejournal, @jonkagan

When Google first announced the existence of Performance Max back in 2020, to say I was skeptical of this ad unit would’ve been an understatement.

When it rolled out to everyone in 2021, I described my thoughts about it as “loud, angry, and distrusting”.

In my defense, look at it from a 2021 Jon perspective: Google gave you an ad unit that would opt you into areas you may not want to be in (Display, Partner Network, YouTube), which you couldn’t opt out of.

You also couldn’t target one network; if you didn’t add a YouTube video, it would make its own. There were no exclusions; there were no negatives. There was negligible reporting.

Additionally, it would show in all the ad placements you were already in, and potentially, cannibalize them. There was limited control over the budget.

All you knew was that you would give Google your money and hope it did right by you.

On top of it all, it was described as a supplementary function, but if you wanted to use Local Search Ads or Smart Shopping, you were forced to do this.

This was then followed by Google representatives recommending that we stop running Shopping campaigns because “PMax will handle it” (which contradicted the original descriptions).

Needless to say, I wasn’t thrilled about it. Then, when Bing (because I refuse to call them Microsoft Ads) announced it was going to be rolling out PMax back in 2024, I almost lost it.

My loyal, consistent, trustworthy little buddy, Bing, was going down the evil rabbit hole of non-transparent advertising, and I was angry. That was all then (I know that was just over a year ago, but give me credit).

Fast forward to June 2025 Jon, (maybe it is the early summer heat in New England), I am no longer that belligerently angry at PMax for existing (still angry about a lot of other things, though).

Now, for different reasons, I am afraid to say it: I am a Performance Max loyalist. Not just in Google, either, but also in Bing – I love the PMax function in both of them.

Why Was I Anti-PMax?

A little bit of background: I’ve been in the digital space for over 20 years. I’ve seen the evolution of search platforms many times over. Some changes were good. Several were terrible (a la “Enhanced Campaigns” or mandatory “MSAN”).

So, needless to say, I am a firm believer of: “If it ain’t broke, don’t fix it.” But, PMax was a fix for something that wasn’t broken (at least, at the time, I believed it).

More importantly, this ad unit went against a lot of Google’s claims of “trust and transparency.” This ad unit provided, at the time, almost no transparency whatsoever, so it sure didn’t give us a reason to trust it.

A little awkward (Screenshot from Google Transparency Center, July 2025)

This was essentially having the fox watch the hen house.

What if I didn’t want to trigger for a specific search? What if I didn’t have video assets and I couldn’t let Google create them? What do you mean I can’t get a full placement report of where my ad was showing?

Not to mention, initial data and results yielded little to no noticeable growth in a positive direction. But, there was a lot of burning cash somewhere.

But that was just Google. When Bing rolled out its PMax, the Audience Network had just become mandatory for search. The search syndication network was producing garbage, there was no video ad unit, and the documentation on the Bing PMax capability was negligible and hidden (shout out to Milton for helping me find it).

Why was this so hard to find?! (Screenshot from Microsoft Advertising, July 2025)

Why should anyone have been in a pro-PMax mindset at all?

And if you scroll through the old X (Twitter) hashtag of #PPCCHAT (which by the way is the best global paid search community there is), you will realize that few – if any – were, in fact, pro-PMax.

What Changed My Mind About Google?

I should first clarify that I now heavily use Performance Max. It is a necessity (think a necessary evil) in most direct response/performance-driven paid media initiatives.

I maintain several reservations about it. However, other reservations have eroded away over time.

When I first tested out Performance Max, it was a test effort for a consumer packaged goods (CPG) ecommerce company and a couple of quick service restaurant (QSR) brands.

For CPG, we were testing it as a supplement to shopping, and we were honestly ignorant of what it was doing.

For the QSR brands, we tested it out as an alternative to local search campaigns, as those were being “sunsetted” by Google.

If we wanted to continue our digital marketing push to hundreds of brick-and-mortar locations on maps, then our only option was to do PMax (net-net, we were forced to).

In both cases, the initial results were “dog water” (a phrase my 10-year-old son keeps using when describing the Jets’ season).

Why were they bad? There are multiple reasons, including but not limited to: lack of education, probably a poor setup on our part, multiple technical flaws on it via Google, and what seemed like a rush to market/incomplete system.

The CPG ecommerce brand abandoned the effort within a few months (at my recommendation, I should note). But the QSR brands – that was different. We started seeing the data.

For both brands, we had been using local search, YouTube, Search, Discovery (may it rest in peace), and every now and then, GDN – all for different needs.

So, getting them to work together for a single function made sense on paper, but was a novel concept to us.

The QSR brands were optimizing for conversions (we had six types), but one of the six types was more valuable than the others (Store Visits).

Once we moved to a conversion value strategy on PMax, we were off to the races. More so, we started seeing deliveries that exceeded prior deliveries in regular search or local search.

I miss local search (Screenshot from author, July 2025)

This shift in performance forced me to accept that I could compromise my lack of transparency for strong performance.

Something that was eating at me, though, was the impact on search.

For those who remember, briefly, PMax search was only on mobile. Then, it expanded to all devices. We did a study to prove it was cannibalizing regular search.

But ultimately, the study made me realize something: I may not be in control of the target and the function, but if the performance was there, my argument against it was going to have to diminish as quickly and quietly as Google Glass.

Ok, Then Why Did You Change Your Mind About Bing PMax?

My perception of Bing PMax changed for a different reason than Google’s.

If you’ve read my past articles, you know I am very much pro-Bing, but in very specific categories, such as healthcare. I am not huge on it in other categories.

So, entering into Bing PMax was going to have to be done either by force or because I heard a rumor.

Needless to say, I got backed into a corner that forced my hand on it (twice), and the first instance happened to coincide with a rumor.

First, note this: I am adamantly against the forced usage of the Bing audience network (MSAN) in search, and not being able to opt out of it, completely infuriates me.

Now, cue the rumor: I had been informed by a former Bing employee that if I wanted greater control of the audience network, I needed to go one of two routes:

1. Run audience network-specific ads, or
2. Run PMax ads.

I elected the PMax route (which, by the way, the rumor about that part was not, in fact, accurate).

I went this route because, at the same time, I had a health insurance brand that was crushing it in efficiency in Bing search, but we couldn’t really scale it anymore.

But, we had a test budget earmarked for direct response/performance tactics, and time was running out to use it (or I would lose it).

So, I threw out the idea of trying PMax in Bing. It had been negligibly attempted within the agency in various verticals with underwhelming performance.

We said, “Why not, let’s give it the old college try and prove that this was not going to work for us,” and we tested it against search.

Well … needless to say, I was wrong. It was beating out search. The only thing it couldn’t do – that Google could – was drive click-to-call leads.

Then What Happened?

A number of things:

• I somehow got selected to sit on a focus group panel for PMax with Google, and selfishly directed as much feedback as possible to bring on basics that should’ve been around since Day one (search query insight, demographic control, product distribution, keyword targets, negatives, etc.) Note: As of press time, some of this actually came to fruition, but I can almost guarantee I had little to no impact in making it happen.
• I worked with some brands that were Down For Testing (or “DTF”), and said, “This isn’t going away like Broad Match Modified did, so we need test it out, if you let me do it, I’ll buy you a sandwich, we’ll plan it out as zero return, and celebrate if it works out.”
• I tested out different scenarios: target return on ad spend (tROAS), target cost-per-acquisition (tCPA), max conversions, max value, with a Google Business Profile (GBP), without a product feed, etc. – all to see what the right approach would be.
• Ecommerce brands we went and tested as a supplement to shopping ads, and scenarios where it replaced shopping ads.
• I repeated scenarios where I could in Bing.
  • Bing for ecommerce quickly became a rising star for me in PMax.
  • If you’re willing to wait for the longer ramp-up period, it pays off.

• Most importantly, I stopped fighting PMax adoption. I decided that I could learn to work with less transparency if the returns came back as legitimate.

There Is, However, Some Stuff That Still Really Gets To Me

Don’t take this come around thought train as total acceptance. There are still several things that grind my gears, and tips I recommend for dealing with them:

• In Google, the moment you get access to the channel report, pore over it in detail. It cannibalizes Search and Shopping, which could mean you need to up your game on other entities, or even reallocate funds as needed.
• If you have the GBP connected, the distribution of spend on Maps is obscene. It makes me long for the days of local search ads, and when this happens, it comes at the expense of search distribution.
• Even with the Google Channel Distribution reports, the actual detailed reporting is pretty terrible. Bing doesn’t even have a channel report.
• If you thought you could use PMax as a way to get into Gmail ad units, think again. Less than 10% of the clients I work with who have PMax and channel reporting have actually shown in Gmail. If you want that placement, go to Demand Gen.

• Upload a video. Whatever you do (for the love of all that is sane), don’t let Google create a video for you. I’ve seen them; you definitely do not want them.

Not-So Pro-Tips For The World Of PMax

• Like my therapist wife says: You need to be comfortable with being uncomfortable, and PMax definitely makes you uncomfortable.
• Have a video ready to go. Don’t let Google make it. Shoot it with your cellphone if you need to.
• Do not launch without using search themes. You don’t have a lot of controls, but that is one to definitely use.
• Bing actually has a good search query report, and Google has recently started rolling out a comprehensive search query report. Both are helpful to understand where you’re mapping, and now with Google, you can use it to expand negative keywords.
• Brand exclusion is a go-to for avoiding competitor bidding.
• The audience signals are key for thriving. Build them a niche, but view it more as a look-alike audience than a pure target.
• Use every extension under the sun, because why not?
• In Bing, not all placements are pretty, and you can actually exclude certain placements by creative there. Utilize it.

The Takeaway

Performance Max, whether it is on Google or Bing, is an ad unit that makes you feel somewhat powerless, but honestly, that isn’t a bad thing.

There are a few verticals/scenarios where PMax isn’t usable (specifically, if it is “remarketing only” audiences or legal compliance restrictions).

You will likely be comfortable with the results, but uncomfortable with the method. You aren’t alone; this is a continuously evolving ad unit.

While you’re at it, especially in Google, don’t sleep on Demand Gen; it’s basically a PMax “lite.”

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Featured Image: Master1305/Shutterstock

Scaling PPC Campaigns Sustainably: Use The SCALE Framework To Move Beyond Actionism

Budget increase, performance drops, budget decrease. Almost every marketer knows that short-sighted game, where decisions are made on a daily basis and campaign performance fluctuates to extremes, without a clear goal.

I’ve seen this pattern destroy more campaigns than I can count. The problem isn’t bad ads or wrong keywords – it’s “actionism.”

That’s when you’re constantly changing things without a plan, reacting to yesterday’s numbers instead of building for tomorrow.

PPC scaling isn’t about doing more. It’s about doing the right things in the right order, which is why I highly recommend a sustainable growth framework to companies working on their long-term goals.

The following framework has consistently delivered three to five times growth while keeping campaigns profitable.

Why Most PPC Scaling Falls Apart

Here’s what I see marketers doing wrong every single day:

• Changing bids daily because yesterday’s numbers looked bad.
• Adding random keywords without thinking about why.
• Swapping ad copy constantly without proper tests.
• Throwing more money at broken campaigns.
• Jumping to new platforms before fixing the current one.
• Increasing or decreasing budgets without a goal.
• Triggering learning phases left and right, not letting the algorithm stabilize.

Sound familiar? These create a mess.

Bad results make you or your leadership panic and change more stuff. More changes mess up your data. Messy data means you can’t tell what’s actually working.

Your campaigns end up stuck between “meh” and “disaster,” never really growing.

The SCALE Framework: A 5-Step System For PPC Growth

Here’s the system I use to scale campaigns without the guesswork:

• S – Stabilize Performance.
• C – Capture Market Intelligence.
• A – Amplify What Works.
• L – Layer New Opportunities.
• E – Evolve And Optimize.

Step 1: Stabilize Performance

You can’t scale chaos. Before adding budget anywhere, fix what you have first.

Start with a reality check. Look at your campaigns and find what’s actually working. Which ad groups bring in customers? Which keywords convert? Which ads get clicked and actually lead to sales?

Write this stuff down – these are your money-makers.

Track your key numbers: How much it costs to get a customer, how much money you make per dollar spent, conversion rates, and average order size. These become your benchmarks for everything else.

Next, cut the dead weight. This sounds backwards, but scaling often starts with doing less. Pause campaigns that have been losing money for X+ days with no signs of life.

Remove ad groups that overlap and compete with each other. Stop throwing good money after bad.

Here’s the key: Take 80% of your budget and put it on your top 20% best performers. This gives you cleaner data and better results faster.

Make everything consistent. Create naming systems that make sense. Set up tracking that actually works. Build templates for ads and landing pages you can copy later.

Most importantly, set rules for when campaigns get more budget, like they need to hit your target cost per customer and keep it there before getting more money.

Analyze deeper. Don’t just look at surface numbers. Watch how your budget gets spent throughout the day.

Those Google Ads notifications about limited budgets? They’re garbage. They show up late, stick around for days after you’ve fixed things, and waste your time.

Instead, build a proper budget monitor. I use Google Ads scripts that loads data into Google Sheets so I can see exactly how fast money is burning in real time.

If you want something quicker to set up, Google has a budget depletion report in Looker Studio that works decently enough to start with.

Step 2: Capture Market Data

Once your campaigns are stable, it’s time to understand what’s happening in your market and where you stand against competitors.

Know your competition. Use auction insights to see who you’re really fighting against. Look at your products manually or use merchant center data to see how your pricing stacks up.

Find out what you’re good at and where you’re getting crushed. Maybe certain product categories just don’t work, or your margins are too thin.

Here’s the thing: Google wants you to dump everything into Performance Max and call it a day. That works for basic campaigns, but in my opinion, it won’t scale.

Real growth comes from understanding why some products sell and others don’t. Sometimes a small tweak fixes everything.

Other times, a product is just dead in the water. You need to know the difference if you want to grow consistently without wild swings in performance.

Track search trends and volume. Google Keyword Planner shows you search volume, plus three-month and year-over-year trends – perfect for spotting seasonal patterns.

Google Trends helps you see what’s hot and what’s dying.

Stay on top of market news by checking Google News regularly. Set up Google Alerts for your brand names and key industry terms so you don’t miss anything important.

If you’re in the EU and work with a CSS partner, ask for CSS Insights reports. They show you market data on clicks, impressions, and how deep other advertisers are bidding.

CSS Insights sample report (Image from author, June 2025)

These insights give you a clear picture of industry click volume, impression volume, and how tough your competition really is.

Always back your decisions with real data. Otherwise, you’re just guessing. But when you have solid data, you can make moves with confidence.

This analysis shows you how much room your current campaigns have to grow and where new opportunities are hiding.

Step 3: Amplify What Works

Now, you take your winners and make them bigger. This isn’t just throwing more money at campaigns. It’s a smart expansion based on what the data tells you.

Scale budgets the right way. For campaigns hitting your targets, increase budgets gradually. I mean gradually – max 20-30% every couple of days. Go faster and you’ll trigger Google’s learning phase or blow through cash before you know what hit you.

Watch your numbers like a hawk when scaling.

If your cost-per-customer jumps more than 20% or your return on ad spend (ROAS) drops below your limit, stop the increases immediately.

Fix what’s broken first. Also, remember that conversions take time. Don’t panic and make changes if performance wobbles for a day or two.

Segment everything by performance. Here’s where most people screw up scaling. They lump all their products together – bestsellers mixed with money burners. That’s a recipe for disaster.

Label your products by profit margins or performance, for example, with data-driven product segmentation.

Create scores or labels that make sense. Then, split your campaigns by these scores so similar products are grouped together. Your top performers get their own campaigns, your problem products get theirs.

Why? Because Google’s algorithm isn’t perfect. It might hit your average return target, but it’s doing it by letting your bestsellers carry the dead weight.

From the outside, everything looks fine, but you’re wasting tons of money on products that will never work while starving your winners of budget.

This is the biggest scaling blocker I see. Everything looks okay at the top level, but dig deeper and you’ll find massive waste.

Separate your winners from your losers, and suddenly you have way more budget to put where it actually makes money.

Step 4: Localize And Expand

Your home market is working. Now, it’s time to take those winning campaigns and spread them to new countries and platforms. But here’s the key: Don’t just copy and paste everything, hoping it works.

Go international the smart way. Start with countries that are similar to your home market. The same language is easiest, but similar buying behavior and economic conditions matter more.

If you’re crushing it in Germany, try Austria or Switzerland before jumping to Brazil.

Check your current data first. Look at your Google Analytics – you’re probably already getting some international traffic.

Start with countries that already convert for you organically. These are your low-hanging fruit.

Set up separate campaigns for each country. Don’t just translate your ads, localize them.

Different countries care about different things. Price might be everything in one market, while quality and service matter more in another.

Your checkout process, shipping costs, and customer service all need to work in the local language and culture.

Start small. Take your best-performing campaign and recreate it for one new country. Get that profitable first, then expand to more markets. Don’t spread yourself thin trying to launch everywhere at once.

Expand to new platforms carefully. Once you’ve maxed out Google Ads in your main markets, look at other platforms. But here’s what most people get wrong: They think Facebook works like Google, or TikTok works like Facebook. They don’t.

Each platform has its own game. Google captures people already looking to buy. Facebook interrupts people scrolling. TikTok is all about entertainment first.

Your ads, targeting, and strategy need to match how people actually use each platform.

Start with one new platform and master it before moving to the next. Take your winning products and test them, but expect to rebuild your ad creative from scratch. What works on Google Search probably won’t work on Facebook Feeds.

The mistake I see all the time? People launch on three platforms simultaneously, spread their budget too thin, and conclude none of them work.

Pick one, give it proper attention and budget, and make it profitable before adding more.

Step 5: Evolve And Optimize

Scaling isn’t a one-time thing. Markets change, competitors adapt, and platforms update their algorithms. You need systems that keep you ahead of the curve and focused on what actually matters, long-term growth.

Think long-term, not daily panic. Here’s where most marketers lose their minds. They check performance every day and freak out over weekly fluctuations. Stop it.

Focus on your North Star metrics, the big picture numbers that actually matter for your business over months and quarters, not days.

Set up proper attribution that shows the real customer journey. People no longer just click an ad and buy.

They see your Google ad, check you out on Facebook, read reviews, and then come back through organic search to purchase.

If you’re only looking at last-click attribution, you’re making decisions with half the story.

Marketing Mix Models (MMMs) help you understand how all your channels work together. They show you the true impact of each platform and how they influence each other. This is crucial when you’re running campaigns across multiple platforms and countries.

Let automation handle the boring stuff. Once you have enough conversion data, smart bidding strategies like Target CPA and Target ROAS can actually work well.

But they need proper setup and constant monitoring. Don’t just turn them on and hope for the best.

Build custom scripts or use third-party tools to automate the routine stuff, bid adjustments, budget pacing, and performance alerts. This frees you up to focus on strategy instead of daily maintenance.

Test everything, but do it right. Create a systematic approach to testing new ad copy, extensions, and landing pages. But only test one thing at a time, or you’ll never know what actually made the difference.

Watch for trouble before it hits. Set up early warning systems that alert you when performance starts shifting before it becomes a real problem.

Track things like impression share drops, quality score changes, and competitive pressure increases.

The goal isn’t to react to every small change, but to spot the big trends early so you can adapt your strategy before your competition does.

Common Pitfalls And How To Avoid Them

• The Patience Problem: Scaling takes time. Resist the urge to accelerate timelines or skip phases. Each phase builds on the previous one, and rushing leads to unstable growth.
• The Complexity Trap: As campaigns grow, complexity increases exponentially. Maintain documentation, standardized processes, and regular audits to prevent campaigns from becoming unmanageable.
• The Attribution Challenge: Multi-platform scaling makes attribution more complex. Invest in proper tracking and attribution modeling early to maintain visibility into performance drivers.

Building Sustainable Growth

Sustainable PPC scaling isn’t about revolutionary tactics or secret strategies. It’s about disciplined execution of proven principles, systematic testing, and patient optimization.

The SCALE framework provides the structure to move beyond actionism toward strategic growth.

By stabilizing performance first, capturing market intelligence, amplifying what works, layering new opportunities systematically, and continuously evolving your approach, you create a foundation for sustained success.

Remember: Scaling PPC campaigns is not about doing everything at once. It’s about doing the right things in the right order, with the discipline to stick to the process even when the temptation to “optimize” everything at once becomes overwhelming.

The companies that achieve sustainable PPC growth aren’t the ones with the most sophisticated tactics. They’re the ones with the most disciplined systems.

Build your system, trust your process, and let compound growth work in your favor.

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Featured Image: Roman Samborskyi/Shutterstock

Is Your Conversion Data Misleading You? 7 Common Google Ads Tracking Issues

Conversion tracking tends to be one of those things advertisers set up once and then forget about, until something fails – big time.

But in my 16 years of experience running Google Ads, I can confidently say it’s the single most important factor affecting PPC results. Way before campaign failure, when results first start lagging, faulty conversions are almost always to blame.

So, whether you want to improve performance, or save a campaign that’s heading towards collapse, the starting point should be the same. Check your conversion data.

Conversion data will only be useful for you if it’s accurate. Serious missteps can happen if you rely on Google Ads to optimize performance when it has misleading or incomplete conversion tracking.

If your numbers are wrong, you’ll end up scaling the wrong campaigns, pausing the ones generating a positive return, or having a wrong idea of return on ad spend (ROAS) altogether – and this happens more often than you think.

Here are seven of the most common causes of inaccurate or inconsistent conversion data in Google Ads, and what you can do to fix each one.

1. Conversion Tracking Isn’t Set Up Properly

Conversion tracking is often missing, duplicated, or firing in the wrong place. This is still one of the most common issues, and it can be the most damaging.

For example, you may track a thank-you page where users refresh the screen three times. Your backend will have one sale, but in Google Ads, you’ll see three.

Using reports like Repeat Rate is a great way to catch that error and ensure you fix it sooner rather than later.

When tracking is unreliable, it’s impossible to optimize performance accurately. Campaign decisions are made on incomplete signals, and smart bidding models won’t have the data they need to learn effectively.

Start by ensuring your conversion actions in Google Ads are appropriately defined.

Use Google Tag Manager to centralize tracking across pages and platforms, and confirm accurate tag firing using Google’s Tag Assistant or built-in diagnostics.

2. Tracking Low-Value Or Secondary Conversions

Not all user actions are created equal – at least not when it comes to Google Ads optimization.

Metrics like scroll depth, time on site, or video engagement can be helpful, but they shouldn’t be treated as primary conversion events in your ad account.

These types of interactions are better as supporting metrics (secondary conversions). They can offer insights into how users engage with your landing page or website.

This type of information is valuable, but it does not belong to the core set of conversion actions used to drive bidding decisions in Google Ads.

When Google optimizes towards actions that don’t directly tie to revenue or qualified leads, you risk directing your budget towards activities that look great on a dashboard but don’t move the needle in your business.

Instead, focus on tracking high-intent actions in your Google Ads account, like purchases, form submissions, or phone calls, and use the supporting metrics to help improve the user experience.

3. Data Doesn’t Match Between Google Ads And GA4

Discrepancies between platforms are expected, but that doesn’t mean they should be ignored. It’s common to see Google Ads report one number and Google Analytics 4 report another for the same conversion event.

The root cause typically comes down to attribution model differences, reporting windows, or inconsistent event definitions.

To reduce confusion, first ensure your Google Ads and GA4 accounts are correctly linked. Then, audit the attribution models in both platforms and understand how each system defines and credits conversions.

GA4 uses data-driven attribution by default, whereas Google Ads may still be using last-click or another model (but now defaults to data-driven models for most accounts). Align conversion settings as much as possible to maintain consistency in your reporting.

4. GCLID Is Missing Or Broken

Google Ads can’t attribute conversions to a specific click if the GCLID isn’t passed through correctly, which will cause in-platform results to be lower.

This issue tends to result from redirects, link shorteners, or forms that strip URL parameters.

Fixing it starts with enabling auto-tagging in your account. Then, confirm that the GCLID is retained throughout the user journey, especially when forms span multiple pages or involve third-party integrations.

Customer relationship management (CRM) systems and custom landing pages are often the culprits, so work with your developers to make sure GCLID values persist and aren’t overwritten.

5. Privacy Settings And Consent Mode Are Blocking Data

Unfortunately, privacy compliance has introduced new gaps in attribution. If a user declines consent, Google’s tags may not fire, leaving conversions untracked.

This is particularly relevant in regions governed by GDPR, like the EU, and similar regulations.

Consent Mode helps to bridge the gap. It adjusts how tags behave based on user permissions, allowing for some modeled data even without full cookie acceptance, making it a great solution.

Pair that with first-party data strategies and server-side tagging where appropriate.

Note, modeled conversions may take time to appear and don’t fully restore lost data, especially for smaller datasets or stricter consent regimes. But, it will help fill in the blanks responsibly.

6. Offline Conversions Are Delayed Or Missing

Offline conversions – like phone sales or in-store transactions – can be imported into Google Ads.

But if you’re inconsistent with your upload process or if it lacks the proper identifiers, those conversions won’t map to the original ad click.

Set up a schedule to upload offline conversions regularly, ideally on a daily or weekly basis. Include GCLID information and a timestamp with each entry to preserve click-level attribution.

Once the data is uploaded, monitor for errors inside the Google Ads interface. Minor mismatches in format or missing fields can stop conversions from registering entirely.

7. Tagging Conflicts Or Technical Errors

Even when tracking is conceptually correct, technical issues can block it from functioning.

Conflicting scripts, outdated plugins, or misplaced tags can all prevent conversion events from firing properly. These problems often go undetected until someone audits the data or sees a sudden drop in conversions.

Use Tag Assistant or Google Tag Manager’s Preview Mode to audit your implementation regularly.

Avoid conditional loading unless absolutely necessary, and coordinate with developers when other platforms – like Meta, HubSpot, or Salesforce – are active on the same pages.

Final Thoughts

Conversion tracking doesn’t exist in a vacuum, and it’s your job to make sure it plays well with the rest of your stack.

Incomplete conversion data is a strategic liability. Feeding Google Ads AI the right signals can mean the difference between PPC growth and stagnation.

By consistently auditing your setup and addressing these common issues, you’ll build cleaner data, glean better insights, and track your way to better performance.

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