Tag: Campaign Performance

How I Cut Google Ads Invalid Clicks by 50% With Audiences

Advertisers are projected to lose $172 billion a year to ad fraud by 2028. I have seen how quickly that problem can move from an abstract industry statistic to a very real performance issue inside a Google Ads account.

The risk is especially high in competitive industries where CPCs are expensive and every wasted click hurts. One client I worked with was in exactly that situation, and invalid click activity was dragging campaign performance below any profitable level.

After testing the usual defenses, I adjusted Google Ads audience targeting in a way that reduced invalid-click activity by 50% and brought the campaigns back to profitable performance.

Case study: How I cut invalid clicks by 50%

The client sold book editing and ghostwriting services. The search terms triggering the ads were relevant and high intent, but the traffic was not converting anywhere close to the level needed for profitability.

The warning signs appeared quickly. Google was reporting a 60% to 80% invalid click rate. Microsoft Clarity recordings showed bot-like behavior from Google Ads traffic. Many search terms had click-through rates above 80%, and some were even above 100%. GA4 and other analytics tools also showed far fewer sessions than the number of clicks reported in Google Ads.

I tested third-party click fraud tools first, but they did not produce any measurable improvement in performance.

Next, I filed an investigation with Google. Google agreed that suspicious activity existed, but said it had already caught all of it and had not charged the account for those clicks.

I was still confident that Google was not filtering out all of the invalid activity, so I decided to use the targeting controls inside the account more aggressively.

I added 540 Google-defined audiences to the Google Search campaigns and set them to Targeting.

The result was immediate. The invalid click rate dropped by 50%, and the conversion rate rose back to profitable levels.

Here is why I tested this approach, why I believe it worked, and what advertisers should understand before trying it in their own accounts.

What click fraud and invalid clicks actually are

Google defines invalid clicks as clicks on ads that do not come from genuine user interest. That includes intentionally fraudulent activity, accidental clicks, and duplicate clicks.

In practice, this can include actual fraud, such as competitors clicking ads, as well as less malicious behavior like accidental double-taps.

Google does not charge advertisers for clicks it determines are invalid. If Google initially charges for a click and later classifies it as invalid, it credits the advertiser back for that activity.

Why the usual defenses can fall short

Google catches a lot of invalid click activity, but this account showed me that the system is not perfect.

That gap is why so many third-party click fraud tools exist. Most of them try to identify suspicious IP addresses and block them before they can keep costing advertisers money.

The challenge is that fraudsters understand how these tools work. They can cycle through IP addresses with VPNs and avoid being stopped by a system that only blocks previously identified addresses.

If a tool blocks an IP address after suspicious activity occurs, that may help only if the same IP address is used again. When the source keeps changing, old IP exclusions lose much of their value.

There is also a platform limit to consider: Google allows a maximum of 500 IP address exclusions per campaign.

The tactic: Add audiences set to Targeting

I started thinking about what might separate fraudulent traffic from legitimate traffic. Google’s predefined audiences stood out because Google builds hundreds of audience segments from demographics, search behavior, and browsing behavior.

For example, someone researching private jet companies and Rolex watches might be classified by Google as a luxury shopper and added to that audience.

My hypothesis was simple: fraudsters who constantly rotate IP addresses may not also be building normal-looking online behavior profiles that fit neatly into Google’s predefined audiences.

So I added most of the available audiences to the Search campaigns. I was not trying to target only audiences that matched the ideal customer. I was using the audiences as a filter for users who carried enough Google audience signals to look more like real people.

The key detail is that I chose Targeting, not Observation.

When I use Targeting, Google limits ads to people who trigger the keywords and also belong to the selected audiences.

When I use Observation, Google simply reports how people in those audiences engage with the ads compared with everyone else. The ads can still show to anyone who triggers the keywords.

I would only test this tactic in accounts with unusually high invalid click rates. It can create real downside, including the risk of blocking legitimate searchers who do not fit inside Google’s predefined audience segments.

How to test this in your own account

In a Search campaign, go to Audiences > Edit audience segments > Targeting > Browse. Then select the audiences you want to add and click Save.

Common questions about fighting click fraud

Will Google refund clicks it identifies as invalid?

If Google identifies a click as invalid when it happens, I am not charged for that click. If Google identifies the click as invalid later, the account receives a credit toward future advertising.

How do I see how many invalid clicks I am getting?

The Invalid activity credit report in Report Editor inside the Google Ads UI provides the most detailed reporting.

I look at two key metrics there: Invalid clicks, which are clicks I was not charged for, and Credited clicks, which are clicks I was originally charged for but later credited back.

I can also add the Invalid clicks and Invalid click rate columns at the campaign level, though not at the ad group or keyword level.

What is a normal invalid click rate?

A February study found an 11.4% invalid click rate across 43,700 accounts.

Industry makes a major difference. While the average invalid click rate for StubGroup clients is very close to that study’s finding, I have seen advertisers in competitive industries with invalid click rates above 40%.

Should I file an investigation with Google?

If I have reason to believe Google is charging for invalid clicks, I consider filing an investigation here.

Why this approach worked best

Using Google’s predefined audiences as a filter cut this account’s reported invalid click rate in half. More importantly, it blocked activity that Google had said it was already catching, which turned failing campaigns into profitable ones.

Inspired by this post on Search Engine Land.

July 3, 2026
Google Performance Max Diagnostics Reveal Asset Gaps

I’m seeing Google add a new Channel Diagnostics feature to Performance Max, and it gives advertisers a more centralized way to understand asset issues that may be holding back campaign delivery across Google’s channels.

The new Channel Diagnostics section is available inside Insights & Reports > Channel Performance for Performance Max campaigns. For me, the value is that advertisers no longer have to dig as deeply to figure out whether missing or disapproved assets are limiting where a campaign can serve.

With this update, I can review diagnostics across all Performance Max channels or drill into a specific channel when I need more detail. I can also identify missing or disapproved assets that affect campaign eligibility and see which asset types, such as headlines, descriptions, or images, need attention.

This matters because Performance Max has often been criticized for limited visibility into campaign issues. I see Channel Diagnostics as a useful step toward making those issues easier to spot, especially when missing creative assets may prevent campaigns from serving across Search, Display, YouTube, Discover, Gmail, and Maps.

By surfacing channel-specific asset gaps in one place, Google is giving advertisers more actionable insight without forcing them to manually audit every asset group. That can make troubleshooting faster and help teams prioritize the fixes most likely to restore eligibility or improve delivery.

The bottom line is that Channel Diagnostics gives Performance Max advertisers a quicker way to identify and fix missing assets. I see it as a practical improvement for keeping campaigns eligible across Google’s full range of inventory.

This update was spotted by a Google Ads Specialist who shared it on LinkedIn.

Inspired by this post on Search Engine Land.

July 3, 2026
How One Broken PPC Form Cost Months of Valuable Leads
I think every PPC professional has at least one mistake they wish they could erase. For Danny Gavin, founder of Optidge, it was not a failed bidding strategy, a blown budget, or a campaign that never found its footing. It was something much simpler, and in many ways, much more painful.

When Danny joined me on PPC Live The Podcast, he shared the story of a technical issue that kept landing page leads from reaching the client. For one to two months, the campaigns were still generating qualified prospects, but the client believed nothing was working because those enquiries never appeared in their inbox.

The mistake that no one spotted

At the time, Danny’s agency was still small, with only a handful of people managing client accounts. One client, an autism therapy provider, appeared to be getting strong results inside Google Ads.

Clicks were rising. Cost per lead looked healthy. From inside the ad platform, everything pointed to success.

But the client was growing more frustrated because no enquiries were coming through.

The problem was not Google Ads.

It was not the landing page.

It was the email notification system.

Every form submission was being stored correctly in the database, but a technical failure stopped the notification emails from reaching the client. Because neither side realized those emails had failed, the issue went unnoticed for weeks.

By the time the problem was found, dozens of leads had already gone cold.

Why the emotional impact was worse than the technical problem

What stood out to me was that the financial loss was not the part Danny remembered most. The harder part was the feeling that his agency had let the client down. Because he knew the client personally, the mistake felt even more personal.

His team had spent weeks reporting positive campaign performance while the client saw no return from their investment. That disconnect created guilt, regret, and a real sense of helplessness.

As Danny explained it, the agency felt as if it had taken the client’s money without delivering value, even though the campaigns themselves were actually working.

Honesty became the first step

Once the problem became clear, Danny did not try to hide it. His view is straightforward: when mistakes happen, honesty is the only response that gives you any chance of repairing trust.

Instead of making excuses, the agency investigated immediately, exported every lead stored in the database, and gave the client everything they could recover. Many of those opportunities had already gone cold, but at least the client had access to the data that still existed.

From there, the focus had to move from blame to prevention.

Building systems that stop the same mistake happening twice

That experience changed the agency’s processes in a lasting way.

Instead of relying on one notification email, Danny’s team introduced multiple safeguards:
- CC’ing the agency on every lead notification.
- Automatically logging every lead into a shared Google Sheet.
- Testing forms regularly to confirm submissions and notifications both work.
- Checking with clients routinely to confirm leads are actually being received.
Those checks are now part of the agency’s standard operating procedures. They are no longer assumptions about technology working in the background.

Why communication matters as much as optimisation

Looking back, Danny sees the technical failure as only part of the issue. Communication failed too. No one had asked the simple question: “Are you actually receiving the leads?”

Today, communication is one of Optidge’s core values.

Rather than expecting PPC specialists to manage constant client communication while also running campaigns, the agency brought in dedicated account managers whose primary role is to keep clients informed.

The lesson I took from this is simple: campaign metrics alone do not define success.

Success only happens when the client experiences the results you are reporting.

Sometimes clients remember how you responded

At first, the relationship with the client ended. Danny assumed the mistake had permanently damaged the trust they had built.

Years later, though, that same client reached out again about potentially working together. In her email, she described Optidge as the most professional agency she had worked with. For Danny, it was a reminder that clients do not forget mistakes, but they also remember how agencies respond to them.

Transparency, professionalism, and a genuine effort to improve can leave a stronger impression than perfection.

Common PPC mistakes Danny still sees today

Although this happened years ago, Danny still sees agencies making similar mistakes today.

One of the biggest is focusing only on traffic instead of business outcomes. Sending visitors to a page is no longer enough.

Strong lead generation requires understanding what happens after someone clicks.

When Danny audits accounts, he often finds agencies failing to:
- Feed qualified lead data back into advertising platforms.
- Review search terms thoroughly and maintain negative keywords.
- Build landing pages that match campaign intent.
- Measure lead quality instead of simply counting conversions.
Without those fundamentals, campaign optimisation is based on incomplete information.

Where AI is genuinely helping lead generation

Danny believes AI has real potential in lead generation, but not always in the way marketers expect.

One of the most useful opportunities is phone call analysis.

Instead of manually listening to every conversation, AI can now help agencies:
- Generate call transcripts.
- Categorise calls by quality.
- Identify whether a call became a genuine sales opportunity.
- Feed qualified conversion data back into Google Ads.
That makes it possible to optimise around real business outcomes instead of surface-level metrics.

Why AI still needs human oversight

Even though Danny is using AI, he does not treat it as an infallible system.

Like automation inside advertising platforms, AI can make mistakes, miss context, and confidently reach the wrong conclusion.

For industries with strict privacy requirements, such as healthcare, AI may not be appropriate for handling sensitive customer information at all.

His advice is to trust AI enough to improve efficiency, but always verify the work.

Human expertise still matters.

The biggest lesson

I do not think any PPC professional can avoid mistakes completely.

What defines a strong agency is how it responds when something goes wrong.

That means being honest, fixing the immediate problem, building safeguards, and making sure the same issue does not happen again.

As Danny puts it, a mistake only becomes valuable when you have genuinely learned from it.

Inspired by this post on Search Engine Land.
July 3, 2026
Google Demand Gen Gets Gemini Creative and Reporting Boost

I’m seeing Google roll out a new set of Demand Gen updates designed to help advertisers improve creative performance, reach more potential customers across YouTube, and measure campaign results with more clarity.

For me, the bigger story is that Demand Gen is becoming less about manually adapting assets and more about using AI-assisted tools to make creative work harder across Google’s most visual surfaces.

Demand Gen campaigns are built to drive discovery and conversions across Google’s visual placements. With these latest updates, I see Google trying to reduce creative friction while giving advertisers better visibility into what is actually moving performance.

Google says the enhancements arrive as YouTube continues to show value for customer acquisition. The company cited research from Measured showing that 72% of incremental conversions on YouTube come from new customers.

What’s new. I’m watching Demand Gen add expanded video resizing capabilities, giving advertisers the ability to automatically transform creative into more aspect ratios, including vertical-to-square, vertical-to-landscape, and square-to-landscape formats.

That matters because it should make it easier to adapt existing creative for different YouTube placements without having to produce every version manually from scratch.

Why I care. Expanded video resizing can help existing assets fit more YouTube inventory, Gemini can provide AI-powered recommendations before launch, and new web-to-app measurement can give marketers a clearer view of how Demand Gen campaigns influence app installs and return on ad spend.

Gemini joins the creative workflow. Google is also bringing Gemini-powered recommendations directly into the Demand Gen campaign creation process, which makes AI guidance part of the asset selection workflow instead of a separate optimization step.

When advertisers choose image and video assets, Gemini will offer automated suggestions for optimizing creative for YouTube. I see this as a way for marketers to improve asset choices before campaigns go live, rather than waiting for performance data after launch.

Better app measurement. Demand Gen now includes Web to App Acquisition Measurement, allowing advertisers to measure when web campaigns lead users to install an app.

The new reporting gives me a more complete way to evaluate campaign performance because it attributes app installs generated through Demand Gen campaigns. That should help advertisers better understand the full impact of their media spend.

The bottom line. I see Google’s latest Demand Gen updates as a practical combination of AI-powered creative guidance, more flexible video optimization, and broader measurement tools that can help advertisers improve performance while gaining clearer insight into customer acquisition.

Inspired by this post on Search Engine Land.

July 3, 2026
Discover Google’s New Tool for Tracking Invalid Click Credits
Recently, I stumbled upon Google’s new documentation that sheds light on a handy tool called the Invalid Activity Credit Report. It’s designed to give us advertisers a clearer picture of refunds issued for those pesky invalid clicks and interactions.

The big picture. Although it’s not entirely clear if the report itself is brand new, it’s definitely showcasing some metrics we’ve seen before, like the invalid click rate. What’s exciting is that the documentation provides a detailed view of credits issued for invalid traffic in both Search and Performance Max campaigns.

How it works. Google mentions that they use automated systems to detect and filter out invalid traffic before it costs us anything. However, if any invalid activity slips through, these credits come to the rescue post-billing.

In such cases, Google might issue credits to cover the associated spend.

While I’ve seen these credits in billing and transaction histories before, this new report breaks down:
- Credited clicks
- Credited interactions
- Credited spend
- Campaign-level impact
- Adjusted performance metrics after credits are applied
Why we care. Having a transparent view of how much of our campaign budget is being refunded due to invalid activity helps me understand my true performance and costs much better. Plus, this new documentation is a gem for raising awareness about a tool many of us might not have known about.

Google’s goal with this report seems to be providing a better understanding of campaign performance after these adjustments.

They say that it helps us:
- See costs, clicks, and interactions post-credits.
- Reduce the hassle of manually reconciling billing credits with campaign performance.
- Gain insights into how Google’s invalid traffic protections affect each campaign.
How to access it. Finding this report is straightforward through the Report Editor in Google Ads.

Just go to the Template Gallery, and select “Invalid Activity Credit Report: Search & PMax” to generate a report with standard campaign metrics, alongside new columns for credited clicks, interactions, and amounts.

You can even add performance metrics to see how campaigns fare after credits adjustment.

What to watch. The report could soon become invaluable for those of us running large budgets, especially if we’re meticulously examining traffic quality and discrepancies in reported performance versus billing.

As AI-driven campaign automation grows, insights into invalid traffic and refunded spend will likely become critical in our campaign strategies.

Inspired by this post on Search Engine Land.
June 2, 2026
Boost Your App Campaigns with Google’s New Consent Insights

I’ve got some exciting news about Google Ads: They’ve introduced something called App Consent Insights! This new feature aims to give us, the advertisers, a much clearer picture of how consent affects our app campaign performance.

What’s new? There’s this cool diagnostics view that breaks down consent data across various apps, platforms, regions, and traffic sources. It’s a game changer for understanding where we might have gaps in our setup.

Zoom in. I can now see an overall consent rating described as “Excellent,” “Good,” or “Poor.” Plus, there’s a live count of apps actively sending consented data and a detailed table that shows consent rates for conversions, including the differences between EEA and non-EEA users.

Why it matters to us. With privacy regulations getting stricter, consent isn’t just a compliance issue—it’s a critical factor for measurement and optimization. This update gives us more visibility into how consent setups could be holding back our performance.

Between the lines. Google is making it easier for us to measure and act on consent data at a time when signal loss significantly impacts campaign performance.

What to watch. We should start looking at optimizing not just for conversions, but also for improving consent rates as another lever of performance.

Bottom line. With better visibility into consent, we can achieve better data quality and ultimately, better campaign outcomes.

First seen. Google Ads expert Thomas Eccel first noticed this update on LinkedIn.

Inspired by this post on Search Engine Land.

April 22, 2026
Unexpected Google Ads Disapprovals Disrupt Campaigns
I’ve noticed a growing concern among advertisers, as many of us are experiencing unexpected disapprovals from Google Ads. These disapprovals are often linked to DNS and 500 server errors, even when our websites seem to be functioning perfectly fine. This issue is raising serious questions about the platform’s reliability and our campaign’s performance stability.

Earlier this week, as a passionate participant in PPC advertising myself, I started hearing about these widespread issues from fellow advertisers. Multiple agencies and their clients were unexpectedly affected.

For instance, Ryan Berry, the Managing Director at Cornerhouse Media, reported that over 1,500 ads were disapproved in a single account at 1:30 p.m. UTC. Others have been receiving overnight emails informing them of disapproved ads.

Why this matters to us. When our ads are suddenly disapproved, it can abruptly halt traffic, leads, and revenue, even if our websites are working just fine. If Google’s systems are mistakenly flagging issues, like DNS or server errors, we are forced to waste precious time troubleshooting problems we didn’t create. This highlights the urgent need for quicker responses and escalations when such platform glitches occur.

Here’s what fellow advertisers and I have observed:
- DNS errors flagged, even when our IT teams find no issues.
- HTTP 500 errors noted, despite landing pages loading normally.
- Repeated disapprovals across numerous accounts.
Charlotte Osborne, a Google Ads trainer, mentioned encountering two separate cases involving erroneous DNS and 500 errors with no discovered client-side issues. Similarly, Google Advertising specialist Joshua Barr has been dealing with a surge of disapproval emails at night for weeks.

What’s probably occurring. Google’s ad review process employs automated crawlers to evaluate landing pages. If these crawlers experience temporary server issues, DNS lookup failures, redirects, or timeouts, it could lead to ad disapprovals under the “destination not working” policy.

This means that even if:
- our sites are live for users,
- the issue is only temporary,
- or the problem lies with Google’s crawlers,
we could still face ad disapprovals.

What actions we should take now:
- Verify Google Ads policy manager for precise reasons behind disapprovals.
- Test landing pages from different locations and devices.
- Review DNS uptime, redirects, and CDN/firewall settings.
- Submit appeals for disapprovals that are clearly incorrect.
- Document impacts on an account level for potential platform-wide issues.
Bottom line. This situation serves as a stark reminder that our hard work on strategy can be undermined by such technical glitches. When Google’s systems fail, it risks both our advertising spend and our potential leads.

Initial reports. Ryan Berry in the UK initially spotted these issues, alongside Anthony Higman, who detected similar problems in the US.

Inspired by this post on Search Engine Land.
April 14, 2026
10 Years of PPC Insights: When Breaking Rules Pays Off

I’ve spent a decade delving into PPC strategies and what I’ve learned is that chasing ‘best practices’ often limits true performance potential. Real growth stems from daring to deviate and experiment with new methods.

PPC conversations frequently revolve around sticking to best practices. These mandates include maintaining clean account structures, controlling match types, scaling budgets incrementally, ensuring campaigns don’t overlap, and keeping everything logical and easy to explain.

While these fundamentals do promote consistency and prevent inefficiencies, they are not the secret to achieving significant gains.

Looking back, many of the most impactful improvements came from testing unorthodox ideas that didn’t neatly fit into the established frameworks, but instead aligned with how platforms like Google Ads and Meta actually operate. These platforms don’t optimize for best practices, but rather for signals, prompting a rethink in approach to performance.

Control Still Matters: Revisiting SKAGs

In several accounts, reintroducing Single Keyword Ad Groups (SKAGs) for high-intent, high-revenue keywords led to improved performance. Ad relevance shot up, conversions grew, and query matching became more precise. It’s not about reverting to old structures, but recognizing where control adds value.

The narrative that machine learning abolishes the need for such control is overly simplistic. My experience shows that precision matters, but only in contexts where the intent justifies it.

Harnessing Broad Match with Control

Historically, broad match has been met with skepticism due to its expansive nature. However, combining broad match with aggressive negative keyword management allows Google to explore broadly while you shape the output through strategic query mining.

By continuously refining query inputs, broad match can expand reach without compromising relevance, redefining how control is applied.

When Visibility Trumps Efficiency: Target Impression Share

Target Impression Share often supports defensive strategies, but applying it to high-value, non-branded terms can boost SERP dominance even at the cost of efficiency. In such cases, ensuring visibility can outweigh concerns over cost efficiency, especially when aiming for market dominance rather than mere competition.

Focusing on Conversion Quality: Weighting Over Tracking

Most lead generation accounts capture multiple conversion actions, but treating them equally can lead to suboptimal interpretations. In one instance, assigning different values based on conversion likelihood—like prioritizing phone calls—shifted optimization to improve conversion quality rather than volume.

This approach emphasizes what’s truly valuable, ensuring platforms optimize effectively based on input.

Competitor Bidding: Leveraging Existing Intent

Despite their reputation for inefficiency, competitor campaigns succeed by capturing existing intent. Users searching for competitor brands often convert thanks to their advanced position in the decision process, proving crucial when strategically managed with clear positioning and relevant landing pages.

Rethinking Top-of-Funnel Keywords

Although often removed for low conversion rates, top-of-funnel keywords can indirectly enhance account performance by strengthening remarketing pools and audience signals, thus supporting high-intent campaign efficiency.

These queries play an unseen but vital role in driving conversions across the account.

Trusting the Data Over Assumptions

Initial audience hypotheses frequently miss the mark, whereas data often pinpoints the most efficient converters. By trusting data and adjusting strategies accordingly, accounts can improve performance by aligning with audience realities.

Revisiting Account Structure’s Role

While clean setups simplify management, they’re not always the most effective. Controlled overlaps between campaigns can leverage shared signals for better auction outcomes, challenging the notion that rigid structures lead to optimal performance.

Treating Product Feeds as Dynamic

In Shopping campaigns, product feeds are often overlooked. Yet, revisiting and adjusting feed details—like product titles and attributes—can significantly enhance product visibility and click-through rates, underscoring their strategic importance.

Retargeting: A Hub for Testing Strategy

Retargeting is not just about conversions; it’s ideal for testing variations in messaging and creative content due to its high-intent audience. Successful test results can then be confidently scaled, reframing retargeting as a strategic testing ground.

The Real Secret Behind Top Account Success

Over the years, I’ve realized that outperformance doesn’t stem from strictly adhering to playbooks, but from understanding and influencing platform signals and stepping beyond conventional boundaries to outperform beyond expectations.

Inspired by this post on Search Engine Land.

April 9, 2026
Unveiling Google’s PMax Timeline: Boost Your Ad Strategy

Recently, I discovered that Google has launched an exciting new feature for Performance Max campaigns. As an advertiser, I’m always on the lookout for tools that provide clearer insights, and this new channel performance timeline view does just that. It offers a comprehensive breakdown of how different channels like Search, YouTube, and Display contribute to my campaign results over time.

What’s New

The latest update introduces a timeline graph that showcases channel-level contributions over a selected period, complete with investment and performance filters. This means I can quickly identify which channels are excelling and which ones might need a bit more attention.

The chart features helpful visual cues—like a yellow box highlighting channel performance evolution over time, and a pink box indicating different ad types, such as All Ads, Ads Using Product Lists, and Ads Using Video.

Why I Care

Managing Performance Max campaigns across multiple channels often left me guessing about where my budget was working best. This new view provides valuable insights into channel-level trends, allowing me to adjust strategies or budgets more efficiently. If I notice YouTube underperforming while Search is thriving, I can now make informed decisions without relying purely on guesswork or exported data.

The Big Picture

This new view empowers me to evaluate PMAX performance more effectively, without relying solely on Google’s automated decisions. Now, I can see consistent underperformance or excellence across channels, which guides my budget and asset strategies moving forward.

The Bottom Line

Though it’s not full transparency, this update is a significant move in the right direction. I now have a more structured way to detect trend anomalies in PMax campaigns early and make necessary adjustments to optimize performance.

First Spotted

This feature was first noticed by Axel Falck, Head of Search at Le Mage du SEA, who shared his insights on LinkedIn.

Inspired by this post on Search Engine Land.

April 2, 2026
Master Media Optimization in Long Sales Cycles
In my experience, navigating long sales cycles is like orchestrating a complex symphony, with people, timing, and operations all playing vital roles. I’ve learned that when I value leads appropriately, I can give paid media platforms the clarity they need to perform better.

In these extended sales journeys, much of the action post-lead submission revolves around the human element. If I focus my campaign optimization efforts solely on sales outcomes, I’m essentially allowing ad platforms to react based on the sales team’s monthly performance, which often overlooks lead quality—a dilemma no amount of tweaking can resolve.

The advice to “optimize the full funnel” suggests monitoring media expenditure through to revenue generation. However, beyond capturing leads, the factors that drive sales often exist outside the realm of paid media—it’s tied to the sales team composition, their workload, and other myriad factors beyond your control with targeting or creative updates.

When My Sales Team Becomes the Signal

With over 15 years in financial services marketing under my belt, I’ve seen this phenomenon extend beyond industries like mortgages or insurance. If human interactions are a key part of your sales process, this will resonate with you.

Picture someone like Dave in your organization. For example, in my case, Dave is a talented mortgage advisor, but in your world, he might be your leading enterprise sales rep, an outstanding business development manager, or the star project estimator.

Dave isn’t just successful because he gets better leads. His natural gift for establishing connections, asking insightful questions, and reassuring clients enables him to close deals at a rate far exceeding his peers.

But Dave isn’t omnipresent. He deserves vacations, he might pursue new career opportunities, or your company may recruit more like him. Consequently, the composition of your sales team is in constant flux. A surge of seasoned closers one month might juxtapose a shortfall the next, influenced by recruitment drives or personnel departures like Dave moving on with two coworkers.

This variability can lead to targeting conundrums. When conversion rates plummet as a junior rep fills in during Dave’s absence, algorithms may misinterpret it as a targeting issue rather than a staffing concern.

If my campaigns are programmed to optimize towards sales, the algorithm might surmise, “Targeting malfunctioning—these clicks now yield lower quality conversions; time to redirect spending.”

Such assumptions can lead to previously effective keywords being disabled, active audience engagement dwindling, and overall account performance declining, despite leads remaining unchanged.

Dig deeper: Diagnose and Overcome the Largest PPC Growth Barriers

Operational Influences on Conversion Data

There’s more at play than merely the sales team’s structure. Imagine this scenario:

During Q4, workloads often intensify as everyone races to finalize deals by year-end. Response times may surge from two days to over a week, prompting impatient clients to look elsewhere.

Market dynamics could shift abruptly, leading to the withdrawal of your most competitive product. Or, summer vacations reduce staffing, resulting in some leads growing cold long before follow-up. Then, in September, everything stabilizes again.

These are just typical examples of everyday operational hiccups. Be it budget sanctions being stalled, fluctuating product ranges, or project delays, each can uniformly distort your conversion metrics.

The algorithm may misinterpret targeting effectiveness when, in reality, your team is simply juggling leads from other originations.

When Dave Becomes Unstoppable: The Santa Claus Rally

The Santa Claus Rally, often referred to as the December Effect, is a fascinating instance I’ve witnessed where human actions can throw algorithmic targeting for a loop.

Every December around the third week, something peculiar unfolds in the financial services arena: lead-to-sale conversion rates soar, with uplifts skyrocketing up to 150% compared to usual weeks.

Optimizing for sales might lead the algorithm to deduce, “This week’s strategy is phenomenal!” Yet, reality hits during the holiday week, plummeting conversion rates to fractions of their regular levels.

None of this is attributable to paid media strategies. By week three, individuals like Dave enter ‘goal-accomplishment’ overdrive. They’re motivated by year-end bonuses, pushing through one last campaign before the break—swiftly reaching out to leads, following up assertively, and converting deals they might usually spend longer nurturing. Dave’s productivity hits a new high.

With the advent of the holiday week, everyone checks out mentally. Customers stop answering calls, and Dave finally uses his PTO. Meanwhile, those still working spend more time planning family events than business goals.

The lead attributes, targeting, and ad placements remain consistent. The program simply adjusts bids and valuations based on the seasons, reflecting when Dave and team take their much-deserved vacations.

Investigate further: Streamline Your Marketing Funnel and Eliminate Costly Gaps

Knowing When to Cease Optimization

So, if I find that sales-focused optimization skews due to uncontrollable factors, I wonder where this optimization boundary should be drawn. How can I curb this distortion while ensuring the right leads?

The answer lies in finalizing control at lead submission—but evaluating leads isn’t about counting them. It requires ascertaining their probability of conversion and the financial worth of the final sale.

An issue with high-value industries is their frequently low sales numbers, making it nearly impossible for automated systems to gather meaningful insights. Lead valuation counters this by providing a greater volume of conversion events as opposed to sparse sales data.

Consequently, automated bidding performs efficiently, facilitating campaign testing and audience analysis, while maintaining data accuracy. Optimizations draw from lead quality before Dave—or the sales crew—steer the wheel.

Importantly, while downstream conversions or revenue may be imported into platforms powerfully, it only succeeds if volume is ample, conversion delays are short, and sales processes are stable.

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Creating Lead Valuation Systems

I begin with a robust analysis of historical data, preferably spanning a year, although six months can suffice. My goal is to discern which leads converted and assess their value, identifying any shared characteristics evident at inquiry.

For financial endeavors, relevant metrics might include loan value or terms. In a B2B context, relevant dimensions might involve business size or industry. Construction projects often boil down to scope and immediacy.

Afterward, I categorize leads by their conversion probability and typical deal size, then assign an estimated revenue value.

The checkpoint for accuracy is straightforward: ensure that your leads’ cumulative projected value closely mirrors actual generated revenue over a timeline. If discrepancies exist, the model needs adjusting. It’s prudent to revisit these models routinely, ideally quarterly, in response to dynamic campaign and operational changes.

For instance, I might qualify a high-probability lead at $850, a median lead at $420, and lesser-chance leads at $120.

Upon formulating this, conversion tracking is configured to relay anticipated values back to platform conversion actions, thereby deploying value-based bidding (like Google Ads’ target return on ad spend) to guide the algorithm towards valuable leads.

Dive deeper: Harness Automation for Lead Gen Success in PPC

Focusing on Controllable Aspects

The advice to “optimize the full funnel” resonates as common sense till we grasp how much we can’t control. For instance, I can shape targeting, craft compelling creatives, enhance landing pages, and streamline initial form engagements. Thereafter, it’s primarily on Dave or the sales team and extraneous factors far removed from my campaigns.

Expecting an algorithm to optimize for invisibles misleads it into chasing erroneous audiences from flawed assumptions.

Instead of ceasing post-lead tracking, I recommend sustained monitoring, as it sheds light on areas of triumph and those needing rectification. Consider these pointers:
- With steady lead quality and declining sales, it’s an operational challenge, not a paid media dilemma.
- Simultaneous drops in both lead quality and sales might prompt campaign evaluations.
- Sudden sales surges with stagnant lead quality often indicate Dave excelling, not improved targeting.
Such detailed insights are invaluable but shouldn’t dictate optimization strategy.

Develop robust lead value assessments, convey expected valuations back to your systems, and allow algorithms to excel at identifying optimal leads. Leave other aspects to Dave’s capable hands.

It’s essential to delineate where your control ceases, marking where optimization should logically end.

Inspired by this post on Search Engine Land.
March 30, 2026