Most brands don’t know they’re wasting money on branded ads. Are you one of them?
What if your Google Ads strategy is quietly draining your budget? Many advertisers are paying high CPCs even when there’s no real competition. It’s often because they’re unknowingly bidding against themselves.
Join BrandPilot AI on July 17, 2025 for a live session with Jenn Paterson and John Beresford, as they explain The Uncontested Paid Search Problem and how to stop it before it eats into your performance.
In this data-backed session, you’ll learn:
Why CPCs rise even without competitor bidding
How to detect branded ad waste in your own account
What this hidden flaw is costing your brand
Tactical strategies to reclaim lost budget and improve your results
Why this matters:
Brands are overspending on Google Ads without knowing the real reason. If you’re running branded search campaigns, this session will show you how to identify and fix what’s costing you the most.
Register today to protect your spend and improve performance. If you can’t attend live, sign up anyway and we’ll send you the full recording after the event.
The good news: Google Ads isn’t broken in B2B; it’s just being used wrong.
The platform works brilliantly for consumer brands because their strategies align with consumer behavior, but B2B operates in an entirely different universe with complex buying journeys involving multiple stakeholders.
This guide will help you modify Google Ads to perform better for B2B paid marketing campaigns.
Issue 1: AI Automation Optimizes For The Wrong B2B Objectives
Google’s AI-powered automation creates the biggest challenge for you at this time.
Why? The actions that signal customer engagement for Google Ads do not align with how B2B shoppers behave, leading to incorrect AI analysis of and actions taken on B2B ad success.
For example:
Performance Max campaigns optimize for volume conversions rather than quality opportunities, resulting in a doubling of lead volume while halving lead quality.
Google Smart Bidding tends to attract users who are likely to take lightweight actions, such as downloads or sign-ups; these actions are unlikely to result in qualified B2B buyers, leading to low-value conversions and wasted spend.
How To Fix Google Ad AI’s Misalignment For B2B PPC
Phase 1: Implement Strategic AI Controls
Disable automatic audience expansion in Search campaigns to maintain targeting precision.
Use Target ROAS instead of Target CPA, setting values based on actual customer lifetime value.
Insights are available from day one, and campaigns can be optimized manually or with AI. Plus, with seamless Google Ads integration and automated multilingual message diversification at scale, Vehnta lets you go to market faster and more effectively.
What You Get
Faster launch cycles.
More qualified leads.
Better performance.
Scalable impact. without the usual manual overhead.
Campaigns are built on intelligent targeting and high-quality inputs, so optimization starts smart and improves from there.
The Result
Reduced wasted budget on low-value conversions like downloads or sign-ups.
Issue 2: Generic Targeting Wastes Budget On Wrong Audiences
Most B2B campaigns tend to target broad demographics rather than specific firmographics, resulting in wasted spend on prospects that are a poor fit.
Traditional metrics create a “metrics mirage” where campaigns focused on clicks draw unqualified leads instead of high-intent decision-makers.
Additionally, broad messaging often fails to resonate across diverse markets, whereas precise targeting is effective at scale.
One multinational retailer with 500+ locations across four countries cut costs by60% and tripled engagement by implementing hyper-local, multilingual campaigns tailored to specific regions.
How To Fix PPC Ad Targeting Waste
Phase 1: Implement Firmographic Precision
Phase 2: Configure Account-Level Monitoring
Set up cross-domain tracking to monitor multiple touchpoints from the same organization.
Use UTM parameters with company identifiers to track organizational buying patterns.
Create audiences based on account-level engagement patterns.
The Easy Way
Vehnta’s Similarity engine leverages a 500M+ company database to identify prospects that match your best customers with surgical precision.
Simply:
Insert one or more existing customers or your Ideal Customer Profile (ICP) into the Similarity Engine.
The Similarty Engine analyzes economic data, industry sectors, and semantic relevance to find similar companies.
This approach makes targeting 10x faster than manual audience research.
Additionally, it provides precision that extends far beyond basic lookalike audiences.
Then, the Search Terms feature provides full visibility into searches performed by your target audience, organized by company and location for actionable insights.
What You Get
A radically faster, more precise way to build high-value target lists.
Prospect lists that closely mirror your best customers, aligned to your ICP from day one.
Full visibility into the actual search behavior of those companies.
The Result
Smarter segmentation.
Faster activation.
Better-performing campaigns fueled by insight, not assumptions.
Issue 3: Marketing/Sales Alignment Problems
B2C metrics fail to capture the complexity of B2B interactions, resulting in a fundamental disconnect between marketing activities and sales outcomes.
Most B2B marketing teams operate under the myth that success requires high lead volumes, but this creates qualification bottlenecks since most B2B sales teams can effectively pursue only a few qualified opportunities simultaneously.
This quality-over-quantity approach delivers results: an enterprise SaaS provider targeting only $1B+ companies achieved 70% cost reduction and 3x engagement by focusing on ultra-precise targeting aligned with sales capacity.
Steps to Fix Marketing/Sales Misalignment
Align Campaigns with Sales Capacity
Calculate your sales team’s true capacity for working on qualified opportunities.
Set monthly lead generation goals that align with sales capacity, rather than arbitrary growth targets.
Develop lead scoring systems that qualify prospects before they reach the sales team.
Implement progressive profiling to gather firmographic information during conversion.
Optimize for Opportunity Quality
The Easy Way
Vehnta’s Insight Collection provides real-time business intelligence that automatically qualifies prospects, focusing on high-quality opportunities from pre-qualified target companies instead of generating hundreds of unqualified leads monthly.
The VisionSphere function provides a ranked list of companies most interested in your business, calculated by proprietary algorithms reflecting genuine buying interest.
What You Get
Consistently higher-quality pipeline, driven by real-time insight into which companies actually show buying intent.
Focused efforts on prospects that are already aligned with your offering.
A ranked view of interested accounts.
Clarity on where to prioritize and when to engage.
More efficient sales motions.
Stronger conversion rates.
Faster deal velocity.
All the intelligence you need, without the noise.
Issue 4: Scalability Of ABM Approaches
The challenge of scaling Account-Based Marketing through Google Ads lies in managing hundreds of target accounts while maintaining surgical precision.
Traditional ABM approaches require significant manual effort and dedicated specialists, making it difficult to achieve scale without compromising quality.
However, this complexity can be overcome: a global manufacturer targeting 4,000+ plant locations reduced spend from $160K to $40K while generating 2.5x more qualified leads through automated ABM systems.
How To Fix Account-Based Marketing (ABM) Scalability
Phase 1: Implement Automated Account Intelligence
Use advanced similarity algorithms to identify high-value prospects matching your best customers.
Automate audience research and list-building processes that typically consume weeks of specialist time.
Deploy AI-powered campaign creation that generates optimized targeting in minutes.
Set up automated monitoring across hundreds of target accounts without additional team members.
Phase 2 Create Scalable Precision Systems
Build campaigns that automatically diversify messaging across multiple languages.
Implement systems providing full visibility into search behavior across target companies.
Use proprietary algorithms to rank companies by genuine buying interest.
Deploy real-time optimization eliminating manual analysis while maintaining quality.
The Easy Way
Vehnta accelerates campaign execution through a truly scalable ABM approach, enabling accurate targeting and real-time performance tracking across your entire B2B account list.
Integrated AI Campaign Generation allows marketers to generate highly relevant, B2B-tailored campaigns in minutes, not days, while minimizing budget waste on low-intent traffic. From day one, teams gain access to actionable insights and can fine-tune performance manually or through automated optimization.
Thanks to seamless Google Ads integration and automated multilingual message diversification at scale, Vehnta eliminates the operational friction that often stalls ABM at the execution phase.
What you get: ABM that finally matches the speed and scale of your growth ambitions, without the typical overhead. Campaigns go live faster, reach the right accounts with precision, and continuously improve through data-driven optimization. Marketing teams save time, reduce costs, and drive more qualified pipeline, while maintaining control and strategic clarity. The complexity is gone; the impact remains.
The Strategic Transformation: From Volume to Value
The transformation from failing to succeeding with B2B Google Ads requires fundamentally rethinking how paid search fits into complex, multi-stakeholder B2B sales processes. Companies achieving breakthrough results abandon volume-based B2C tactics for precision-focused, account-based strategies that create budget efficiency and market dominance within targeted segments.
The competitive opportunity is significant: while competitors chase high-volume keywords and vanity metrics, strategic B2B marketers focus on qualified accounts and pipeline impact using advanced targeting intelligence and automated optimization systems.
Ready to transform your B2B Google Ads approach?
Discover how Vehnta works and achieve precision at scale—cut costs, improve targeting, and align every campaign with how your customers actually buy.
There’s no one-size-fits-all answer when it comes to deciding how much of your marketing budget should go toward SEO versus PPC.
But that doesn’t mean the decision should be based on gut instinct or what your competitors are doing.
Marketing leaders are under more pressure than ever to show a return on every dollar spent.
So, it’s not about choosing one over the other. It’s about finding the right balance based on your goals, your timelines, and what kind of results the business expects to see.
This article walks through how to think about budget allocation between SEO and PPC with a focus on what kind of output you can reasonably expect for your spend.
Whether it’s Google Ads, Microsoft Ads, or paid social, you’re paying for clicks, impressions, and leads right now.
That cost is largely predictable and better to forecast. For example, if your cost-per-click (CPC) is $3 and your budget is $10,000, you can expect about 3,300 clicks.
PPC spend can be directly tied to pipeline, which is why it’s often favored by performance-driven teams.
With SEO, you’re investing in long-term growth. You’re paying for content, technical fixes, site structure improvements, and link acquisition.
But you don’t pay for clicks or impressions. Once rankings improve, those clicks come organically.
The upside is compounding growth and reduced cost per lead over time.
The downside? It can take months to see meaningful impact, and the cost-to-output ratio is harder to predict.
It’s also worth noting that PPC costs often increase with competition, while SEO costs tend to remain relatively stable over time. That can make SEO more scalable in the long term, especially for brands in high-CPC industries.
How Urgency And Goals Influence Budget Splits
If you need leads or traffic now, PPC should probably get the bulk of your short-term budget.
Launching a new product? Trying to meet quarterly goals? Paid search and social can give you the volume you need pretty quickly.
But if you’re trying to reduce customer acquisition cost (CAC) in the long run or improve visibility in organic search to support brand awareness, SEO deserves more attention. It builds value over time and often pays dividends past the life of your campaign.
Many brands start with a 70/30 or 60/40 split favoring PPC, then shift the mix as organic efforts gain traction.
Just make sure you set clear expectations: SEO is not a quick fix, and over-promising short-term gains can backfire when the board wants results next quarter.
If you’re rebranding, expanding into new markets, or supporting a product launch, a heavier upfront PPC investment makes sense. But brands that already rank well organically or have strong content foundations can afford to rebalance the mix in favor of SEO.
Why Organic Traffic Is Getting Harder To Defend
One emerging challenge for organic marketing is the rise of AI Overviews in Google Search. More brands are seeing a dip in organic traffic even when they maintain strong rankings.
Why?
Because the search experience is shifting. AI-generated summaries are now answering questions directly on the results page, often pushing traditional organic listings further down.
That means your SEO strategy can’t just be about rankings anymore. You need to invest in content that earns visibility in AI Overviews, featured snippets, and other enhanced search features.
This may involve rethinking how content is structured, focusing more on schema markup, FAQs, and direct-answer formats that AI models tend to surface.
In practical terms, your SEO budget should now include:
Structured content planning built around entity-based search.
Technical SEO improvements like schema and page speed.
Multimedia content like images and videos, which AI often pulls into results.
Continual refresh of older content to maintain relevance in evolving search formats.
This shift doesn’t mean SEO is no longer worth it. It means you need to be more strategic in how you spend.
Ask your SEO partner or in-house team how they’re adapting to AI search changes, and make sure your budget reflects that evolution.
Budget Planning Based On Realistic Outputs
Let’s put this into numbers. Say you have a $100,000 annual digital marketing budget.
Putting $80,000 toward PPC might get you 25,000 paid clicks and 500 conversions (based on a fictional $3.20 CPC and 2% conversion rate).
The remaining $20,000 on SEO might buy you four high-quality articles a month, technical clean-up work, and backlink outreach.
If done well, this might start showing traction in three to six months and bring in sustained traffic over time.
The key is to model your budget around what’s actually possible for each channel, not just what you hope will happen. SEO efforts often have a longer lag time, but PPC campaigns can run out of gas as soon as you turn off the spend.
You should also budget for maintenance and reinvestment. Even strong SEO performance requires fresh content and updates to keep rankings.
Similarly, PPC campaigns need regular optimization, creative testing, and bid adjustments to stay efficient.
You should also plan for budget allocation across different campaign types: brand vs. non-brand, search vs. display, and prospecting vs. retargeting.
Each serves a different purpose, and over-investing on one without supporting the others can limit growth.
For example, allocating part of your PPC budget to retargeting warm audiences can drastically improve efficiency compared to cold prospecting alone.
While branded search often delivers low-cost conversions, it shouldn’t be your only area of investment if you’re trying to scale.
What To Communicate To Leadership
Leadership wants to know two things: how much are we spending, and what are we getting in return?
A mixed SEO and PPC strategy gives you the ability to answer both.
PPC provides short-term wins you can report on monthly.
SEO builds long-term momentum that pays off in quarters and years.
Explain that PPC is more like a faucet you control. SEO is more like building your own well. Both are valuable.
But if you only have one or the other, you’re either stuck renting traffic or waiting too long to see the impact.
Board members and non-marketing executives often prefer hard numbers. So, when proposing a budget mix, include projected costs per acquisition, estimated traffic volumes, and timelines for ramp-up.
Make it clear where each dollar is going and what kind of return is expected.
If possible, create a model that shows various scenarios. For example, what a 50/50 vs. 70/30 SEO/PPC split might look like in terms of conversions, traffic, and cost per lead over time.
Visuals help ground the conversation in data rather than preference.
Choosing The Right Metrics For Each Channel
One challenge with mixed-channel budget planning is deciding which key performance indicator (KPI) to prioritize.
PPC is easier to measure in terms of direct return on investment (ROI), but SEO plays a broader role in business success.
For PPC metrics, you may want to focus on KPIs like:
For example, paid search might drive immediate clicks, but your top-converting landing page could rank organically and reduce spend over time.
When To Adjust Your Budget Mix
Your initial budget allocation isn’t set in stone. It should evolve based on performance data, market shifts, and internal needs.
If PPC costs rise but conversion rates drop, that could be a cue to pull back and invest more in organic.
If you’re seeing strong rankings but low engagement, it may be time to shift some SEO funds into conversion rate optimization (CRO) or paid retargeting.
Seasonality and campaign cycles also matter. Retailers may lean heavily on PPC during Q4, while B2B companies might invest more in SEO during longer sales cycles.
Set quarterly review points where you re-evaluate performance and make adjustments. That level of agility shows leadership you’re making informed decisions, not just sticking to arbitrary ratios.
Avoiding Common Budget Mistakes
Some companies go all-in on SEO, expecting miracles. Others burn through paid budgets with nothing left to sustain organic efforts. Both approaches are risky.
A healthy mix means budgeting for:
Immediate lead gen (PPC).
Long-term traffic growth (SEO).
Regular testing and performance analysis.
Don’t forget to budget for what happens after the click: landing page development, CRO, and reporting tools that tie it all together.
Another mistake is treating SEO as a one-time project instead of an ongoing investment. If you only fund it during a site migration or a content sprint, you’ll lose momentum.
Same goes for PPC: Without a proper landing page experience or conversion tracking, even high-performing ads won’t deliver meaningful results.
Balancing Short-Term Wins With Long-Term Growth
There is no universal perfect split between SEO and PPC. But there is a perfect mix for your goals, stage of growth, and available resources.
Take the time to assess what you actually need from each channel and what you can realistically afford. Make sure your projections align with internal timelines and expectations.
And most importantly, keep reviewing your mix as performance data rolls in. The right budget allocation today might look very different six months from now.
Smart marketing leaders don’t choose sides. They choose what makes sense for the business today, and build flexibility into their strategy for tomorrow.
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.
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.
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.
To my fellow marketers, I first wrote this title in the summer of 2020, back when I thought, “Wow, surely things couldn’t get worse.” Needless to say, I was wrong.
Here’s the actual quote I started with last time:
“If you’re reading this, then it is early July, you’ve made it this far in the game of ‘Let’s See What Else Can Happen in 2020’.”
We have largely left the world of all-day Netflix and sourdough, and moved on to more pressing things like understanding the impact of tariffs on a brand’s willingness to run digital, and wondering how, five years later, my NY Jets are still so terrible.
With those changes has come a shifting dynamic in search, once called “PPC” (I have always disliked that term), more recently referred to as search engine marketing (SEM) and paid search, which is now simply “paid media.”
With this shift in ad types, ad placements, and management comes a shift in how we target audiences for our ads.
Why? Ad technologies change, ad units change, and thus, targeting changes. Not to mention, a shift in “what is demand?” affects more people than those who are actually qualified to see your ads.
I didn’t see economy-driven searches overtaking COVID-19 in my future (Screenshot from Google Trends, June 2025)
And once again, there are caveats:
Consumer sentiment is in flux as the economy rocks back and forth from concerning to good.
Google’s look-alike audiences (similar audiences) sunsetted (except for Demand Generation).
Audience targeting can easily be mixed up with various forms of AI targeting (i.e., Meta Advantage+).
Cookie deprecation started and then stopped, but first-party and modeled audience data became worth as much as gold.
The concept of the keyword match type (or even the keyword itself) is continuing to erode away.
Who Is Worthy To See Your Ads?
Not everyone who views your ad is truly qualified. Whether it is in-market, demographic, geographic, behavioral, etc., not everyone should see your ad.
To put it bluntly (and I am trying my best not to sound rude), some individuals are not worth spending ad dollars on for a specific ad.
For high price point items:
Income often correlates with CVR based on category (Image from author, June 2025)
For more age-specific items:
Age is often a deciding factor as well (Image from author, June 2025)
With times being as uncertain as they are, brands must tighten their purse strings and become more selective in their prospecting efforts to help the bottom line.
One would think that this concept, focusing ads on a particular audience, would always be the case, but the reality is, mid to larger brands will still often do the “spray and pray” approach, with just small audience adjustments.
Why?
Tighter audiences help with return on investment and efficiency, but they can wreak havoc on volume and total revenue when done too excessively.
This leaves the advertiser with a decision to make: What is the best approach?
Improve ROI but at a lower return volume, and then open up the floodgates later with a looser audience target.
Keep a looser audience and focus on return volume to build a better audience profile, and then tighten during your peak season to improve profitability.
A hybrid, where you lean toward return volume, cast a wider net – the ROI won’t be amazing, but you won’t go bankrupt, all by controlling somewhat focused audiences, and scaling bid strategy controls.
The most important (and first) step: Identify who your ideal customer is.
Important disclaimer: Identify who your ideal customer is/has been, not who you think it is going to be/should be.
Be sure to pore over your analytics and conversion data to decipher this. Otherwise, any future steps are pointless.
Learn exactly who your converter is (Image from author, June 2025)
Previously, to weed out the less qualified and still feed the top of the funnel and prospect, you would need to lean heavily into audience exclusion and audience targeting. That is still true, to a degree, and more specifically in the case of paid search.
However, for more modern concepts, such as Performance Max, Demand Generation, LinkedIn, or Meta, we are leaning more toward the target, as the exclusion may not be as readily or easily available for use.
Audience targeting vs. exclusion: Yes, they are similar, but different. Here’s a quick refresher:
For example: “I am selling a luxury car with a high price point, so I am only showing the ad to those whose household income is in the top 10%.”
Note: This is still valid in most scenarios. However, certain platforms and verticals do have limitations or restrictions.
Excluding: Indirectly targeting an audience by minimizing the ad units’ reach, based on consumers’ characteristics, by intentionally preventing ads from showing to those individuals.
For example: “I am excluding homeowners, so they are not served my apartment rental ads.”
Not doing one or both is as good for you as trusting a truthful outcome from Theranos.
How does one use these targets and exclusions to tighten one’s belt?
Audience Targeting
This is not rocket science, and more importantly, it doesn’t need to be applied account-wide, just high (sometimes mid) funnel initiatives.
Particularly in search, the more specific the query (often mid- to long-tail searches), the higher the qualification, the higher the likelihood of conversion.
But those are often few and far between (terrible for prospecting in terms of feeding the top of the funnel).
So, audience targeting becomes a necessity for high-volume search keywords. Otherwise, you’re spending your already limited budget on everyone (not ideal).
We break audience targeting into two types: actualized behavior and user traits.
The most common form (and easiest to use) of actualized behavior is retargeting.
Cart abandoners are the lowest-hanging fruit. It is a simple setup and deployment (I am a huge advocate of it via Google Analytics 4):
As much as I dislike GA4 UI vs. GA UA, they make audience creation fairly simple. (Image from author, June 2025)
But keep in mind: If you’re still getting those queries off a top-of-funnel query (generic, short-tail), then the qualification is already lower to start off with.
Frequently, we separate out retargeting past shoppers, retargeting site/cart abandoners, and prospecting (brand new visitors) from one another. Thus, controlling spend, creative, and user experience for each category.
At the same time, these lists can be used as exclusionary, ensuring there is no overlap, and a consumer receives an experience they were not intended for, which works well for prospecting audiences.
When thinking about user traits, these can be tied to platform-predicted behavior (i.e., affinity or in-market), or even self-identified characteristics (i.e., age, gender, income, etc.).
User traits are great at isolating targeting to your most qualified/relevant audience.
For example, anyone can eat at one of my fast-casual restaurant locations across the major cities of Connecticut.
But suppose I want to maximize the cost-per-customer efficiency for the “kids eat free” special. In that case, I will target parents of children under 12, not in the top 25% of the Herfindahl-Hirschman Index (HHI), but who have some disposable income, who enjoy eating, and are within a five-mile radius of one of our locations.
Make the audience that meets your typical customer (Image from author, June 2025)
But a nice little function these days is that Google and Meta are learning from current activity to help build out in-market audiences on a rolling basis.
It is great for all of Meta, PMax, YouTube, Demand Gen, etc.
Google is finally being helpful without a sales rep (Image from author, June 2025)
Using these tools, we have taken a step to prequalify the audience we’re prospecting. If they don’t convert at first (but do engage with the page), at least they’re pulled into our remarketing lists as a higher degree of qualification for later.
Net-net: These consumers are deemed worthy of seeing our ads.
Audience Exclusion
To put it bluntly, exclusion is a vastly underrated, yet wildly glorified version of a search negative keyword list.
But rather than saying we don’t want to show if someone searches for XYZ, we say, we don’t want to show for you.
When we apply exclusions in any channel, we are saying, “I am open to anyone seeing my ads, provided they aren’t [fill in the blank].”
I know it sounds harsh, but it is highly effective and important.
Remember, not everyone is right for your brand, but they may still try and find a way to see the ads.
Exclusions can be simple, such as geography or time of day, or they can be much more specific.
One of the key times I see this needed is for YouTube and Google Display Network (GDN).
You want to capture a wide audience, but you know not everyone is right.
I should note, though, that certain verticals (those falling under Housing, Employment, and Credit or HEC policies in Google and anti-discriminatory policies in Meta) limit what can be excluded.
In addition, the rapidly growing share of wallet ad unit, Performance Max, in both Google and Bing (I still refuse to call it Microsoft), you cannot exclude audiences (yet), but you can exclude keywords (Google only beta) and brands.
Some day… (Image from author, June 2025)
It is a glorified negative keyword (Image from author, June 2025)
Takeaway
You’ll get fewer visitors, but a more qualified audience. You also maintain control of who you’re spending ad dollars on.
We are in the early stages of exiting the world of keywords and focusing on the audience. At the same time, platforms continue to reduce control and transparency of who/what/when/why/how your ad is served. That hurts your wallet and your bottom line.
When you can’t use first-party audiences, learn your typical customer’s profile, and build audiences for it.
By ensuring you target the right audience and exclude the wrong ones, you can make sure your operation continues to thrive another day.
Keeping up-to-date on industry Google Ads benchmarks is crucial to help answer questions you might get from clients or exec such as:
“Is this a good CTR?”
“Why is our CPA so high?”
“What’s a good conversion rate, anyway?”
Questions like these come up all the time, especially when budgets are tight and performance dips even slightly.
But unless you’ve got fresh benchmark data on hand, these conversations are usually filled with guesswork, vague assurances, or worse, outdated reports that no longer reflect how competitive today’s ad landscape really is.
Wordstream by LocaliQ recently updated its Search Advertising benchmarks for 2025, compiling real data from thousands of Google and Microsoft Ads campaigns across 20 verticals.
The data consists of data points from thousands of campaigns in both Google and Microsoft Ads for some of the top industries. Some of the top industries include:
Arts & Entertainment.
Automotive.
Education.
Finance & Insurance.
Health & Fitness.
Home Improvement.
Shopping & Retail.
Travel.
While these benchmarks are a starting point, it’s important to note that many factors go into setting benchmarks that are attainable for your business.
We hope this data is useful for you to help level-set expectations and goals for your business, and get a sense of how you stack up to the competition.
In this report, you’ll find benchmarks for Search campaigns in Google & Microsoft Ads for:
Click-through rate (CTR).
Average cost-per-click (CPC).
Conversion rate (CVR).
Cost per lead (CPL).
Let’s dig into the data.
Average Click-Through Rate In Google & Microsoft Ads By Industry
Data from LocaliQ benchmark report, June 2025
The average click-through rate for Google & Microsoft Ads across all industries averaged out to 6.66% over the last 12 months.
Compared to when the company first started gathering data in 2015, the average CTR for search ads was minimal at 1.35%.
The business category that boasted the highest CTR was Arts & Entertainment, with an astounding 13.10% CTR.
At the other end of the spectrum was Dentists and Dental Services at a 5.44% CTR.
The CTR metric should be analyzed as only one indicator of performance, not the end-all-be-all when trying to determine if your ads are doing well.
The widespread in CTR performance is influenced by:
Your competition (Is the SERP saturated?).
Your bidding strategy.
Your position on the results page.
Your ad copy relevancy.
Your audience targeting.
High CTR doesn’t always mean high performance, though. Sometimes it just means your ad is click-worthy, not necessarily that it’s converting. That’s why CTR should be viewed as one piece of the puzzle, not the whole picture.
If your CTR is low compared to your industry average, tools like Google’s Quality Score can help pinpoint the problem areas, from poor ad relevance to weak expected click-through rate.
Average Cost-Per-Click In Google & Microsoft Ads By Industry
Data from LocaliQ benchmark report, June 2025
The average cost-per-click for Google and Microsoft Ads across all industries over the past 12 months averaged $5.26.
While the Attorneys and Legal Services showcased one of the lowest CTR categories, it also boasted the highest average CPC. In 2025, the average CPC for this industry came in at $8.58.
This average is unsurprising, given the higher-than-average cost of acquiring a customer.
On the lower end of the spectrum, the Arts & Entertainment industry had the lowest average CPC at $1.60.
Similar to analyzing the CTR metric, average CPC is just one performance indicator.
For example, your ads may show a low average CPC and a low CTR. This could mean your bids aren’t high enough to be competitive in the market, and you may want to consider raising bids.
On the other hand, if you have a higher-than-average CPC, you’ll want to monitor these more closely to ensure you can prove your return on ad spend/investment.
Average Conversion Rates In Google & Microsoft Ads By Industry
Data from LocaliQ benchmark report, June 2025
The average conversion rate across all industries for Google and Microsoft Ads in the last twelve months was 7.52%.
The average conversion rate is calculated from the number of leads/sales you get divided by the number of clicks from your ad.
When looking at the data from 2025, the average conversion rate varied highly across industries.
On the high end of performance, Automotive had the highest conversion rate at 14.67%, followed by Animals and Pets at 13.07%.
The industries that had the lowest conversion rate included:
Finance & Insurance: 2.55%
Furniture: 2.73%
Real Estate: 3.28%
When looking at these industries and the products they sell, these conversion rates make sense.
Furniture is a high-ticket item for many customers. Users do a lot of research online before making a purchase. Not only that, but because of the price tag, many customers end up purchasing in stores instead of online.
While the conversion rate may be low in this particular industry, it’s more important than ever to be able to measure offline conversions, such as in-store visits or purchases.
In the apparel industry, new brands seem to pop up every day.
If you do a simple search for Nike sneakers, the number of sellers and resellers for these types of products has skyrocketed in recent years.
The amount of competition can directly contribute to a low (or high) conversion rate.
Average Cost Per Lead In Google & Microsoft Ads By Industry
Data from LocaliQ benchmark report, June 2025
The average cost per lead across all industries for Google and Microsoft Ads in the last twelve months was $70.11.
The average cost per lead is a core KPI that advertisers should keep a pulse on when analyzing performance.
It remains one of the most scrutinized metrics by marketing and finance teams alike.
It’s no surprise that certain industries have a much higher CPL compared to other industries. Some of the factors that can influence CPL include:
Average CPC.
Average CTR (this influences your CPC).
Audience targeting.
Conversion rate.
The type of product/service you’re selling.
On average, the CPL across all industries reported was $70.11.
The Attorneys and Legal Services industry had the highest CPL out of all industries at a whopping $131.63.
However, while the CPL may be high, many businesses in that industry find that well worth the investment, considering their return on each individual they represent.
Those industries with lower-priced products and services likely have a lower CPL goal.
The industries that showed the lowest CPL in 2025 were Automotive Repair, Services & Parts at $28.50, followed by Arts & Entertainment and Restaurants & Food at $30.27.
Compared to last year’s data, 13 out of the 23 industries reported an increase in CPL.
Data from LocaliQ benchmark report, June 2025
While the last few years have seen such a large fluctuation in CPL due to the record inflation and economic instability, the year-over-year changes in CPL have mellowed out a bit.
Summary
Benchmark reports are exactly that: benchmarks. They’re not scorecards, and they don’t account for your specific brand, audience, goals, or tech stack.
So, if your numbers don’t perfectly align with the averages, it doesn’t mean you’re underperforming.
If you’re looking to make progress in the second half of the year, try following the tips below:
Make sure your goals are aligned with your industry’s actual buying journey.
Explore alternative platforms like Microsoft Ads to diversify CPC risk.
Prioritize ad relevance and landing page experience.
Google Marketing Live 2025 was a whirlwind of announcements, with over 30 new product updates and features unveiled, most of them powered by AI.
The event highlighted Google’s commitment to transforming advertising through AI across four key pillars: Search, Creativity, Measurement, and Agentic Capabilities.
Here’s a breakdown of the major announcements and how marketers can take advantage of these updates in 2025.
Search Updates
Most of the Search updates were centered around numerous AI capabilities, which isn’t surprising.
Updates to Search included:
Ads in AI Overviews now on Desktop. Ads are now live in AI Overviews for desktop users in the U.S. These ads show in the scrollable AI-generated summary box and aim to match high-intent queries with tailored results.
AI Mode in Google Search. This is a separate conversational search experience, powered by Gemini. Ads will soon appear contextually within longer conversations, such as when a user is narrowing down a decision. This is still in testing, but advertisers should expect rollout later this year.
AI Max for Search Campaigns. While technically announced a few weeks before GML, there were more updates shared. It’s a suite of features including creative and targeting enhancements to optimize your existing Search campaigns.
Clearer Ad Labeling in AI Surfaces. As ads become more integrated into exploratory formats, Google is refining how they’re labeled to maintain transparency.
Smart Bidding Exploration. A new toggle setting in Google Ads for Search campaigns that allow you to capture additional conversions that you may not have been eligible for due to existing bidding restrictions. It provides a more flexible ROAS target.
These updates signal that traditional keyword-first search strategies won’t cut it anymore.
If you’re not feeding the right creative and conversion signals into your campaigns, you’ll be left out of this AI-first discovery layer.
Performance Max Updates
There were some very welcome updates announced for the Performance Max campaign type that are worth noting for advertisers.
Channel-level performance. This is one of the most requested features for Performance Max, and now it’s here. Advertisers will have access to what channels their ads are serving on, as well as better search term and ad asset reporting.
Search terms reporting. Another top-requested feature, advertisers will have the same level of search term reporting for Search and Shopping placements in their Performance Max campaigns.
Exclusion of interacted users. In order to better reach net new users, advertisers will be able to exclude people who are searching for your brand, or have interacted with a YouTube video, website, or app – all with one click. It’s important to note that this feature isn’t available yet, and will be rolling out later this year.
Creative Updates
To meet the growing demand for dynamic and engaging content, Google introduced tools that simplify and scale creative asset production.
Updates were announced across Display, Video, and Demand Gen inventory.
Demand Gen Maps inventory. While technically not a creative update, this falls within visual updates. Advertisers using Demand Gen campaigns will be able to reach users who are searching for businesses and locations using Promoted Pins. The goal is to drive in-store traffic and sales.
New Creator Partnerships central hub. In a huge move towards social influence, Google announced a new hub to work with creators directly in the Google Ads interface. Advertisers can use this to integrate creator-influencer content into their ad strategy.
Insights Finder. Advertisers can find the top trending creators for a specific topic, category, or industry to help narrow down their potential partnerships in the YouTube Creator community.
YouTube Shoppable Masthead. Available on the mobile Masthead placement, you can now make your ad placement shoppable to drive website traffic and conversions.
Shoppable CTV. This feature will be available for Demand Gen and Performance Max campaigns, where users can engage with products directly on their TV screen.
New video ads across Google surfaces. Video ads are coming to Search, Image Search, and Google Shopping placements within Performance Max campaigns.
Reformat and extend video assets. This will use generative AI to take your existing assets and extend them to all available asset ratios.
New Peak Points ad format. This new ad format is powered by Gemini, and will integrate your ads within YouTube videos at precisely timed moments.
Accelerated checkout for Demand Gen campaigns. You will now be able to redirect YouTube shoppers directly to your checkout or cart from your ad.
Asset Studio in Google Ads. This is a one-stop studio for advertisers to create high-quality assets and variations. You can even generate images and videos using your products to create lifestyle imagery. This will be available in Google Ads and Merchant Center.
Brand profile updates. What used to only be managed through Google Business Profile can also be managed through Merchant Center.
A/B Testing in Merchant Center. You’ll be able to review content suggestions, A/B test opportunities, promotion recommendations, and more.
Content hub in Merchant Center. It takes video from your social channels and website to provide AI-powered video recommendations for product campaigns.
AI tools in Product Studio. This will help create brand images and videos, allowing you to save and/or publish assets across Google in one click.
The bulk of the updates from Google Marketing Live were surrounded by creative updates, which indicates where Google is putting its best foot forward in terms of differentiating its ad platform from others.
Measurement Updates
Google’s new measurement tools offer more granular insights and facilitate data-driven decision-making.
Incrementality test thresholds lowered. Available to test within the Google Ads UI starting at $5,000 per test instead of the previous $100,000 threshold.
Attributed brand searches. This feature will help quantify the number of users who searched for your brand after seeing a video ad.
Meridian Scenario Planner. Helps model future campaign budgets and forecasts to better allocate spend.
Manage cross-channel budgets in Google Analytics. You’ll now be able to analyze performance, adjust spend, and optimize cross-channel budgets directly in Google Analytics.
Data Manager updates. This uses your first-party data sources to understand your data strength and how to better optimize campaigns as a result. Includes sources like BigQuery, HubSpot, Oracle, Salesforce, Shopify, and more.
Web and App integrations in Google Ads. Unified web and app conversion tracking can help optimize customer journeys.
tROAS bidding for iOS App campaigns. A new bidding type available to iOS instead of just bidding on Installs, helping make your campaigns more profitable in the long run. It will now include event-level data to improve iOS optimization and reporting.
Agentic Capabilities
Google is introducing agentic tools that act on behalf of advertisers, automating routine tasks and providing strategic recommendations.
Marketing Advisor. This is an agent built within Chrome to help solve problems, including voice interaction. Its main goal is to help with instant task completion and business advice.
Google Ads Expert. This is aimed to help streamline campaign creation, along with speedy performance improvements, providing and applying specific recommendations based on your existing campaign and business data. Google mentioned it would also proactively identify and fix problems before they impact your ads.
Google Analytics Expert. Get strategic advice and recommendations based on your Google Analytics data. Currently, this is in limited beta.
These updates are aimed at providing more streamlined support to Google advertisers, as they’ve gotten feedback about a lack of Google-supplied support over the past few years.
How Marketers Can Start Testing These Updates
With so many updates announced, jumping in without a plan is a good way to burn budget. Here’s how you can strategically get ahead of the rollout:
1. Phase Your Adoption
Not every tool will be immediately available, or available in all markets.
Start with what you can control: Asset Studio, Merchant Center profile updates, Google Analytics 4 attribution enhancements, etc.
2. Set Up Controlled Tests
If you’re not ready to go all-in on new features, set up campaign experiments or geo splits when testing new Smart Bidding Exploration or incrementality tools.
Watch how performance shifts before scaling further or adding new features to test.
3. Audit Your Current Creative
Make sure your images, headlines, and videos meet Google’s quality guidelines. That foundation matters before layering AI enhancements.
Remember, your AI-powered creative will only be as good as the inputs you’re giving the system!
4. Document What You Change
This is a must for all advertisers. Whether testing creative variations or letting the agentic assistant make tweaks, log what was modified. It’s the only way to evaluate impact.
5. Involve Your Team(s) Early
Help your designers, analysts, and media managers understand what’s changing. Many of these updates will shift how each department works.
Which Features Stand Out The Most?
While Google Marketing Live introduced a huge set of new features, certain updates stand out for their potential to significantly benefit smaller advertisers.
In my opinion, these updates are the ones worth paying attention to, especially for SMBs.
Smart Bidding Exploration
Smart Bidding Exploration is a significant enhancement to Google’s automated bidding strategies.
This feature allows campaigns to tap into a broader range of search queries by using machine learning to analyze various signals and predict conversion likelihoods.
It adjusts bids in real-time, enabling advertisers to reach users during their research and consideration phases, even before they enter the traditional sales funnel.
For smaller advertisers with limited budgets, Smart Bidding Exploration offers a way to discover untapped traffic sources without overhauling existing keyword strategies.
By leveraging AI to identify high-performing queries, businesses can expand their reach and drive more conversions efficiently.
Incrementality Testing
Google has reduced the minimum spend requirement for incrementality testing from $100,000 to just $5,000.
This change democratizes access to advanced measurement tools, allowing smaller advertisers to assess the true impact of their campaigns on brand perception and customer behavior.
Previously, only large advertisers could afford to run incrementality tests. Now, smaller businesses can gain valuable insights into how their advertising efforts influence customer actions, enabling more informed decision-making and optimized marketing strategies.
Enhanced Video Asset Tools
Google’s new video asset tools, including the Asset Studio and AI-powered features like image-to-video transformation and outpainting, simplify the creation of engaging video content.
These tools allow advertisers to generate high-quality videos from existing images and expand visuals beyond their original frames, making it easier to produce content suitable for various platforms.
Video content is increasingly important in digital marketing, but producing it can be resource-intensive. These new tools lower the barrier to entry, enabling smaller advertisers to create compelling videos without the need for extensive resources or expertise.
A/B Testing In Merchant Center
Google has introduced A/B testing capabilities within Merchant Center, allowing advertisers to test different product titles, images, and descriptions directly in the platform.
This feature enables businesses to identify the most effective content variations to enhance engagement and conversion rates.
For ecommerce businesses, especially smaller ones, optimizing product listings can significantly impact performance.
This new testing feature provides a straightforward way to experiment and refine listings based on real user data, leading to better outcomes with minimal effort.
What Comes Next For Marketers
Google Marketing Live 2025 wasn’t just about showcasing new features. It was a signal that the way we plan, build, and measure campaigns is shifting yet again.
Marketers who test early, stay curious, and apply these tools with intention will be in the best position to benefit.
That doesn’t mean blindly adopting every new update. It means understanding where automation can help, where oversight is still critical, and where your strategy needs to evolve.
The biggest gains won’t come from the tools themselves, but from how you choose to use them.
More Resources:
Featured Image: Brooke Osmundson/Search Engine Journal
As paid media marketers, we often default to the “big” platforms: Google, Meta, and increasingly, TikTok.
However, there’s a quiet powerhouse in the app marketing world that too many advertisers overlook: Apple Search Ads (ASA).
If you work with apps or even if your business uses an app as a secondary conversion point, ASA is one of the most intent-driven ad platforms you can leverage.
Unlike other platforms where discovery can feel like throwing spaghetti at the wall, ASA puts you directly in front of users already searching for what you offer.
That’s not just high intent. That’s purchase-ready behavior.
So, why aren’t more marketers fully embracing Apple Search Ads? Usually, it’s because they either assume it’s only for app developers or they’re intimidated by yet another ad platform to learn.
With a bit of strategic setup and a clear understanding of how ASA differs from other platforms, you can unlock a high-performing new channel.
This guide will walk you through everything you need to know.
What Is Apple Search Ads And Why Should You Care?
Apple Search Ads is Apple’s proprietary platform that lets advertisers promote apps directly inside the Apple App Store.
It operates similarly to paid search platforms: Advertisers bid on keywords and pay when users tap their ads.
Instead of driving traffic to websites or landing pages, ASA drives users directly to your App Store product page. From there, users can immediately download or purchase the app.
So, why should that matter to marketers?
App discovery still happens in the App Store. Despite the rise of social and influencer-driven app marketing, the App Store remains the No. 1 source of app discovery.
Intent is extremely high. Unlike display or social placements, users are actively searching for solutions when they encounter Apple Search Ads.
ASA can help boost organic rankings. High ad-driven downloads can influence your organic App Store ranking, creating a halo effect for long-term growth.
If you’re investing in user acquisition or app engagement, Apple Search Ads deserves to be part of the conversation.
Where Do Apple Search Ads Show Up?
If you think that ASA placements are strictly within the App Store search results, think again.
Currently, your ads can appear in four key placements.
1. Search Results
This is the most coveted placement. Ads appear at the very top when a user searches for a keyword. This is where intent is at its peak.
Image credit: ads.apple.com, May 2025
2. Search Tab (Suggested Apps)
Ads appear before a user types in a search term. This is a great placement for brand awareness and introducing your app to broader audiences.
Image credit: ads.apple.com, May 2025
3. Today Tab
These ads show up on the App Store’s homepage, which is the first thing users see when they open the App Store. It’s ideal for major launches or branding campaigns.
Image credit: ads.apple.com, May 2025
4. Product Pages (While Browsing)
Ads appear when users scroll through other app product pages. These placements capture users who are in browsing mode, often comparing similar apps.
Image credit: ads.apple.com, May 2025
Each placement serves a different purpose, from brand awareness to high-intent acquisition.
Apple Search Ads Basic Vs. Advanced: Which One To Choose?
At first glance, Apple’s two solutions, “Basic” and “Advanced,” might seem like they serve similar purposes. They don’t.
Apple Search Ads Basic
This solution is designed for small app developers or businesses without dedicated marketing teams.
It’s entirely automated: You enter a monthly budget (up to $10,000), and Apple does the rest. It handles targeting, bidding, and ad delivery.
You get very limited reporting and zero visibility into which keywords or placements are driving installs. There’s no ability to control cost-per-tap, and optimization is virtually non-existent.
Apple Search Ads Advanced
This solution, on the other hand, is a fully-featured platform that gives you control over every element of the campaign: keywords, audience targeting, bidding, scheduling, and performance measurement. It’s what any performance marketer should be using.
If you care about scalability, performance optimization, or insight into where your spend is going, the decision is easy.
Advanced is the only real option. Basic may work for small developers, but if you’re reading this guide, it’s probably not for you.
Navigating The Apple Search Ads Platform
If you’re coming from a Google Ads or Meta Ads background, ASA will feel both familiar and refreshingly simple, but it wouldn’t be a proper ad platform without its own quirks.
Here’s a quick walkthrough of what to expect when navigating the platform:
Dashboard Simplicity: ASA’s dashboard prioritizes campaign overviews with fewer tabs and less complexity than Google Ads or Meta.
Campaign Setup: You’ll name your campaign, set your daily budget, choose your app, and select the countries or regions where you want to advertise.
Ad Groups: Within each campaign, you create ad groups where you set targeting, keywords, audience refinements, and bids.
Reporting: Apple provides performance metrics such as impressions, taps (clicks), cost per tap (CPT), conversions, and cost per acquisition (CPA). For deeper insights, you’ll need to integrate with Apple’s SKAdNetwork or third-party Mobile Measurement Partners (MMPs) like Adjust or AppsFlyer.
There is one key difference between this platform and the Google Ads platform, and that comes in the form of ad creatives.
You won’t create ads in the traditional sense like other platforms. Apple Search Ads automatically pulls your app’s name, icon, screenshots, and description from your App Store listing.
While this limits creative flexibility, it ensures that ads align perfectly within the app’s branding.
For more custom creatives, there is the option to create custom product pages within Apple App Store Connect, but we’ll cover that later in this guide.
Understanding Keyword Targeting And Match Types
Keyword targeting is at the heart of Apple Search Ads, and while it borrows concepts from Google Ads, there are some critical differences.
Exact match is exactly what it sounds like. Your ad will only appear when the user’s search matches your keyword or a very close variation.
Broad match is more flexible, allowing your ad to appear for related terms, synonyms, and phrases. Broad match is helpful for keyword discovery, but can sometimes cast too wide a net if not monitored closely.
You can also opt into Search Match, which lets Apple automatically match your app to relevant search terms.
It uses metadata from your app listing (like your title, keywords, and category) to decide where your ad should show.
While it can be helpful in discovery campaigns, you’ll want to keep a close eye on what it’s actually matching to, as it often surfaces low-quality or irrelevant terms. Now, here’s the kicker: Apple does allow negative keywords, but managing them is far more frustrating than it should be.
Unlike Google Ads, you can’t easily apply negatives across multiple campaigns in bulk or through a shared library.
There’s also no built-in keyword suggestion tool to help you filter or negate irrelevant terms based on live data. If you want to block poor-performing keywords, you have to manually upload them one by one into the ad group or campaign.
There is another option to copy/paste them into the interface, but I’ve found that you have to build them out in Excel by match type, then use a Notepad (or something similar) to format it the way Apple can ingest it.
You can’t paste a linear list like most platforms can. You’ll need to format negative keywords something like this:
This makes proactive negative keyword management a bit of a time suck.
Keyword management is doable, but it’s not frictionless. You’ll need a spreadsheet handy and some patience, especially if you’re working across multiple campaigns.
The structure of your Apple Search Ads campaigns is one of the biggest levers you can pull for performance and efficiency.
It helps you control budgets, isolate performance by keyword type, and make smarter bid decisions.
In my experience, the most successful campaign structure includes four campaign types/categories:
Brand campaign.
Competitor campaign.
Category campaign.
Discovery campaign.
Brand Campaign
Your brand campaign captures people already searching for your app by name.
It usually delivers the cheapest installs and highest conversion rates, making it a reliable foundation.
Competitor Campaign
This campaign targets searches for other apps in your space.
For example, you’re marketing a personal budgeting app. If someone searches for “Mint” or “YNAB” (which stands for You Need A Budget), you can show up as an alternative.
These campaigns are competitive, so expect higher CPTs.
Category Campaign
This campaign focuses on generic terms like “budget app” or “meal tracker.”
These users are high intent but still evaluating their options. It’s a great area for differentiation.
Discovery Campaign
Lastly, your discovery campaign should use broad match and search match to find new terms.
Keep bids lower here and treat it as a research engine.
Once you build out this structure, you’ll be able to track which intent tiers are performing, allocate budget accordingly, and avoid muddy data from mixed-match types.
It’s the first step toward scale and clarity.
Lastly, once you’ve mastered the basics of Search campaigns in Apple, I’d recommend branching out to the broader campaign types (Search Tab, Product Page, Today Tab).
Additional Targeting Options In Apple Search Ads
While Apple Search Ads is primarily keyword-driven, there are a few targeting levers you can pull to refine who sees your ads.
They’re not as deep as what you’d get on Meta or TikTok, but they’re still useful.
You can refine your audience by:
Device type, choosing to target users on iPhone or iPad. This is especially useful if your app performs better on one format.
Customer type, allowing you to target new users, returning users, or users of your other apps. This comes in handy for re-engagement or cross-promotion strategies.
Demographics, including age ranges and gender, although these are more directional than precise.
Location, which supports geographic segmentation down to the region or country level.
While these refinements are helpful, they don’t work like standard audience building in Google Ads or Meta Ads. You won’t be building layered lookalike audiences or behavior-based segments.
ASA targeting leans more on keyword intent, with these settings helping you narrow the lens.
Used thoughtfully, these refinements help stretch your budget further and ensure you’re reaching the right slice of users without completely overhauling your campaign structure.
Make The Most Of Your Apple Search Ads Bids
Apple Search Ads operates on a cost-per-tap bidding model. You set the maximum amount you’re willing to pay for a tap (essentially a click), and Apple runs an auction to determine whether your ad gets shown.
What makes ASA different is that the auction isn’t just about who bids the most.
Apple weighs relevance, meaning that apps with higher conversion rates and better alignment to the search query can win placements with lower bids.
That means throwing money at ASA doesn’t guarantee success. Smart bidding is about segmenting intent and adjusting bids based on performance.
Here’s how to frame your approach to bidding:
For brand keywords, your relevance score is naturally high. These campaigns usually perform well with low bids.
Competitor keywords are more competitive and less relevant, so you’ll need moderate-to-high bids to be visible.
Category terms tend to be broad and competitive. They’ll require higher bids and careful tracking of CPA to avoid wasted spend.
In discovery campaigns, you’re exploring unknowns. Start with low bids until you identify what works, then break the winners into new ad groups.
You’ll also want to make frequent bid adjustments. Unlike Google Ads, ASA doesn’t offer much in the way of automated bidding or budget pacing.
This means manual optimization matters a lot more, and performance can shift quickly based on ranking changes or user behavior.
The takeaway? Stay active. Set up a regular cadence to adjust bids and keep your spend aligned with what’s driving installs.
Custom Product Pages In Apple Search Ads
If you’ve worked with Apple Search Ads in the past, you might remember Creative Sets. That’s the old name of this feature.
Today, you create ad variations using Apple’s Custom Product Pages. These are alternate versions of your App Store product page with different screenshots, app previews, and promotional text. When paired with specific ad groups or keywords in ASA, they allow you to show different visuals depending on the search intent.
Creating custom product pages requires a few things:
You must design and upload a new set of screenshots and app previews through App Store Connect.
Each custom product page needs unique metadata, which could be different calls to action, seasonal themes, or value props.
You can create up to 35 custom product pages per app, but you’ll want to be intentional about what each one highlights.
Once approved by Apple, these pages can be assigned to specific ad groups or keywords inside your ASA campaign.
For example, if you’re running a meditation app, you might build one page emphasizing sleep content and another emphasizing stress relief.
Then, when a user searches [meditation for sleep], your ASA campaign can direct them to the custom page showing your sleep-focused content.
These variations not only improve relevance, but they can meaningfully lift conversion rates when executed properly.
Since ASA doesn’t allow you to change much else about your ad creative, this is one of the few levers you can pull to align creative with user intent.
Common Mistakes That Can Derail Performance
Even seasoned marketers trip over Apple Search Ads’ simplicity. It’s not a complicated platform, but it is easy to get wrong if you treat it like something it’s not.
1. Too Much Search Match
One of the most common missteps is relying too heavily on search match. It sounds like a time-saver, but it often matches your app to irrelevant or low-converting keywords.
If you do use it, pair it with a discovery campaign and monitor the search terms closely.
2. Not Using Custom Product Pages
Another pitfall is ignoring custom product pages. Most advertisers just run with the default App Store listing, missing an easy opportunity to align visuals with user intent.
It’s a mistake that can silently eat away at your conversion rate.
3. Bid Stagnation
Then, there’s bid stagnation. ASA doesn’t come with automated bid rules, which means if you’re not manually adjusting CPTs, your performance will erode over time.
4. Forgetting Negative Keywords
Finally, many marketers forget to actively review negative keyword opportunities. If you’re not trimming irrelevant traffic, you’re probably paying for taps that will never convert.
The good news? Most of these mistakes are fixable once you know what to look for and take the time to make deliberate optimizations.
The Bottom Line: Is Apple Search Ads Worth It?
If you market an app, or even plan to in the future, Apple Search Ads is absolutely worth testing.
It puts your brand in front of users with the highest purchase intent available in the app ecosystem.
While it lacks some of the advanced audience targeting of other ad platforms, it compensates with simplicity, clear keyword intent, and an ecosystem designed for conversions, not just clicks.
Like any paid media channel, success comes from thoughtful campaign structure, active management, and the willingness to iterate.
If you’ve been putting Apple Search Ads on the back burner, now’s the time to give it the attention it deserves.
Google claims that search results with AI Overviews generate the same amount of advertising revenue as traditional search results.
This claim was made during Google Marketing Live when the company revealed plans to expand AI Overview ads to desktop users and more English-speaking markets.
If true, this could reshape how marketers perceive Google’s AI-powered future. However, the claim raises questions about how Google measures success and what it means for your campaigns.
Marketers need to understand what lies behind these claims and what they indicate for the future of search advertising.
AI Overviews Reaches Massive Scale
Google launched AI Overviews on mobile in the US last year. Since then, the company has quickly expanded the feature worldwide. It now processes AI-generated responses for users in more than 200 countries.
Shashi Thakur, Google’s VP/GM of Advertising, stated during the press session:
“We started rolling out AI overviews in search on US mobile last year. At this point, we are reaching a billion and a half users using it every month.”
Thakur oversees advertising across Google’s search products. This includes Google.com, Discover, Image Search, Lens, and Maps. He noted that users are happy with the feature.
The expansion shows Google’s confidence in both user adoption and commercial success. The company announced the desktop expansion that morning at the event, representing the latest phase of their rapid global rollout.
Thakur explained the growth impact:
“The consequence of us building AI overviews is that people are seeing growth. People are asking more of those questions… So we are seeing growth. So people are asking more questions. Many of those questions are even commercial. So we are seeing a growth even in commercial.”
Google’s Broader Vision For Search Evolution
Google’s approach to AI Overviews reflects a fundamental shift in how the company thinks about search capabilities. Thakur outlined this vision:
“At its core, we think about search as expanding the kinds of curiosities you can express. Humans have innumerable number of curiosities. There’s only a fraction of those that gets expressed to search. The more we advance the technology, the more we advance the product, users can bring more of their curiosities to search.”
This philosophy drives Google’s push toward AI-powered responses that can handle more complex and nuanced queries than traditional keyword-based searches.
How Google Measures AI Overview Monetization
Google’s revenue claims are based on controlled experiments. The company compares identical search queries with and without AI Overviews. They use standard A/B testing methods.
This means showing the AI feature to some users while holding it back from others. Then they measure the revenue difference.
Thakur explained to reporters:
“When we say AI overviews monetizes at the same rate, if you had taken the exact same set of queries and not shown AI overviews, it would have monetized at some rate. This continues to monetize at the same rate.”
The testing focuses on overall business value and revenue. It doesn’t examine individual metrics, such as click-through rates. Google emphasized this represents performance across many queries, not individual searches.
For advertisers, this suggests AI Overviews don’t hurt existing search advertising effectiveness. However, the long-term effects of changing user behavior patterns remain unclear.
Shashi Thakur speaks to press at Google Marketing Live. Photo: Matt G. Southern/Search Engine Journal.
Strategic Approach To AI Overview Advertising
Google states that ads within AI Overviews adhere to the same quality guidelines as traditional search ads. The company requires that ads be of high quality and fit well with the user experience. All ads must be marked as sponsored content.
Advertisers have three placement options for AI Overview ads: above the AI response, below the response, or integrated within the AI answer itself. This gives marketers flexibility in how they appear alongside AI-generated content.
The complexity of modern user behavior drives Google’s advertising strategy. Thakur noted:
“I think the main thing to take away from those conversations is user journeys are complicated. And users get inspiration to get into their commercial journeys at innumerable points in their journeys.”
The integration focuses on identifying commercial intent within complex queries through what Google refers to as “faceted” searches. These are complex questions that contain multiple sub-questions, some of which have commercial intent.
Thakur gave an example of a user asking about airline rules for traveling with pets. That person might then need pet carriers or travel accessories, creating natural opportunities for advertising. The AI system can identify these layered commercial needs within a single complex query.
Google uses various classifiers to identify commercial intent, including shopping queries, travel queries, and insurance queries. This automated classification system helps match ads to relevant user needs.
Thakur stated:
“Ads need to be high quality, and they need to be cohesive with the experience. Ads of this nature extend how good the answer is for certain users.”
Google reports positive user feedback about ads shown with AI Overviews. This suggests the integration doesn’t significantly hurt user satisfaction.
This user acceptance seems crucial to Google’s strategy. The company plans to expand AI Overview advertising to more platforms and markets.
Shashi Thakur speaks to press at Google Marketing Live. Photo: Matt G. Southern/Search Engine Journal.
Implications For Digital Marketers
The revenue parity claim addresses advertiser concerns about AI’s impact on search advertising effectiveness.
Thakur acknowledged the fundamental question marketers are asking:
“So now, the question we often get from our advertisers, and it’s a natural question, which is, this is great. Search is evolving in lots of exciting directions. How do we participate? And how do we connect with our customers in the context of this evolving experience?”
Thakur noted that over 80% of Google advertisers already use some form of AI-driven advertising technology. This suggests the industry is ready for more AI integration.
However, the shift toward AI-powered search responses may require advertisers to adapt their strategies. Users are asking increasingly complex, longer queries. Traditional keyword targeting may not be effective in addressing these.
Google’s solution involves increased automation through tools like the newly announced “AI Max for search” feature. Early beta testing of AI Max has shown promising results, with advertisers experiencing an average 27% increase in conversions while maintaining similar return on investment (ROI) targets.
Thakur explained the motivation behind AI Max:
“So the motivation for this, essentially, was this changing user behavior. That’s number one. As we heard from our advertisers, we got the feedback very clearly that transparency and control of the form, they were already used on search campaigns. That continues to be super important in addition to the automation.”
The tool maintains the transparency and control features that advertisers expect from traditional search campaigns, including keyword performance reporting and campaign controls. This addresses concerns about losing visibility when embracing automation.
The company’s emphasis on automation reflects a challenge. It’s hard to match ads to sophisticated, conversational queries that can contain multiple commercial intents.
Manual keyword strategies may become less effective over time. This is especially true as search behavior evolves toward natural language interactions.
AI Mode Expansion Creates New Opportunities
Beyond AI Overviews, Google is testing ads within its new AI Mode, which enables fully conversational search experiences. Early data indicates that users in AI mode ask questions that are up to twice as long as regular search queries.
These longer, more conversational queries create additional opportunities for identifying commercial intent within complex questions. The extended query length often means users are providing more context about their needs, potentially making ad targeting more precise.
Google is applying lessons learned from AI Overviews to ensure ads in AI mode maintain the same quality and user experience standards.
Looking Ahead
Thakur emphasized that Google’s approach remains focused on delivering a high-quality user experience while providing business value to advertisers.
The actual test of Google’s revenue claims will come as AI Overviews mature. User behavior patterns need time to solidify.
As Google continues expanding AI Overview advertising globally, digital marketers face a balancing act. They must embrace new automated tools while maintaining the control and transparency that drive successful campaign performance.
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