Paid Media Archives Paid Media

Aug 22 2025

Tips For Running Competitor Campaigns In Paid Search via @sejournal, @timothyjjensen

Paid search professionals constantly debate the merits of running paid search campaigns bidding on competitor brand names. Questions such as the following may arise:

Is bidding on your competitors ethical?
Are the high costs-per-click (CPCs) worth spending the budget on?
Are you actually reaching people with buying intent?

In this article, I’ll talk through answers to these questions and more to help you understand if a competitor search campaign might be right for your brand.

Competitor Bidding Ethics

Google and Microsoft allow you to bid on your competitor’s name within keywords (and this right has even been tested in the courts here and here.), but you cannot directly mention a trademarked brand name (that you don’t have the rights to use) in ad copy.

In addition, even if you don’t include their name, you should not write your ad copy in a way that a user thinks they may be going to your competitor’s site instead of yours.

For instance, you might use the headline “Official Site” (without mentioning whose official site you’re pointing to). When a user sees that in conjunction with having searched for the competitor’s name, they may naturally think they’re going to that company’s site.

Finally, the landing page should also clearly feature your brand’s name and logo in order to avoid deception.

Cost-Benefit Analysis Of Competitor Bidding

Let’s face it: competitor keywords can have expensive CPCs. High competition around these keywords in many industries drives up cost.

You’ll also generally struggle to achieve a decent quality score due to other companies’ brand keywords naturally being deemed less relevant to your ads and landing pages, which can also impact cost.

Because of the high potential cost, competitor bidding does not make sense for all industries or brands.

For instance, if you’re selling products with a low profit margin, bidding on these pricy keywords may not work. Generally, this tactic works best for higher cost, higher margin products and services, as it’s easier to still yield a return on investment (ROI) after higher costs-per-acquisition (CPAs) and lower conversion rates.

Be careful also about entering competitor bidding “wars” for the sole reason that other brands are bidding on your name. This action can quickly lead to rising CPCs for all with little payoff.

One scenario where I’ve seen competitor bidding work best is when a company offers a very specific, complex service that’s difficult to sum up in a search query but has established brands that the right prospects would be familiar with.

For instance, if you’re promoting software for a particular type of industrial machine, niche buyers may be aware of companies that already provide that software.

Once you’ve established a use case for competitor bidding, you should establish a list of brands to use.

Determining Competitors To Bid On

When figuring out which competitor brands to bid on, you should rely on a combination of both internal company data as well as ad platform data.

First of all, talk with key stakeholders in marketing and sales to determine who the brand considers to be top competitors.

Who has similar products and services? Which brands target similar prospects (whether by location, demographic, or company traits)?

Note that this list may not and likely will not contain all potential competitors.

If you have established paid search campaigns already, use auction insights to see the top brands showing up for the same queries as yours. Of course, these may not all be completely relevant and will require some vetting through.

Once you’ve compiled a list, it’s time to think through the keywords you’ll bid on.

Who Is (And Isn’t) Your Audience

Be careful about going unnecessarily broad in the keywords you’re using in competitor campaigns.

Generally, if you’re just bidding on the brand name alone, you’re likely reaching a lot of existing customers looking to log in, place online orders, or find a nearby location without giving a second thought to anything else.

For instance, Apple isn’t going to sell many MacBooks by bidding on the word “Microsoft.”

Ideally, you want to reach people who are in a research phase, indicated by wording in their search query:

[Brand name] + cost/pricing
[Brand name] + compare/vs
[Brand name] + reviews
[Brand name] + pros/cons
[Brand name] + alternatives
[Brand name] + features

While a potentially riskier strategy, as people may be in a heated moment, you could also test targeting people experiencing issues and potentially in the market to switch:

[Brand name] + support
[Brand name] + troubleshoot
[Brand name] + cancel

Create Your Ads

Now, think through the ad copy you’ll put in front of prospects searching for competitors. Take some time to review competitor ads and offers, considering how your calls-to-action (CTAs) will stack up.

Think through areas where you “win” against certain competitors and highlight those. Remember that these may vary based on the brand you’re bidding against.

For instance, you may have lower costs than a certain competitor and highlight pricing for those searches, while you may have higher costs than another competitor but have unique features to highlight.

Also, look at how your offers compare. If one competitor offers a seven-day demo and you offer a 30-day demo, feature that in your ad.

This also should be an area you regularly monitor and adjust CTAs based on how competitors tweak their ads and offers.

What Happens After The Ad?

One maxim applicable to any paid search campaign is that what happens on the search engine results page up to the ad click is only one portion of the user experience.

A significant portion of the decision process happens after reaching the landing page, beyond what you can control in keywords and ad copy.

Think through what your prospect is seeing based on the context that they were researching a competitor. Your homepage probably isn’t the best place to land them, and the same sales landing page you use for more general keywords may not be ideal either.

Assuming a user is comparison shopping, placing some content on your landing page positioning your brand against others will likely help.

For instance, you could create a table showing how your features and pricing stack up vs. competitors (either mentioning specific names or providing industry averages).

You could also hone in on trust signals that set your brand apart. Highlight industry awards you’ve won. Mention the number of accounts serviced. Talk about how many integrations you have with commonly used products.

If you need to establish a baseline for comparing against other companies, prompt a large language model (LLM) to put together a list of features for your brand and a list of top competitors.

Provide the URLs for pages that would contain products/services to flesh this out.

Launch And Monitor Results

Once you have your competitor campaigns fleshed out, it’s time to get them off the ground and see what performance looks like.

In addition to ensuring proper conversion tracking and watching for lead/sale quality, you’ll also want to keep an eye out for both how current competitors change up their offers and new competitors entering the space that may be worth targeting.

With a carefully thought-out setup and proper monitoring, you may find that competitor search campaigns allow you to capture leads or sales from queries you were not previously reaching.

On the other hand, you may discover that for your industry, the CPAs and conversion rates aren’t worthwhile, but as with anything in PPC, you ran a test and learned the results.

At the very least, take stock of potential competitors in your field and consider testing if you are looking to expand your reach in paid search.

More Resources:

Featured Image: SvetaZi/Shutterstock

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Aug 7 2025

6 AI Marketing Myths That Are Costing You Money [Webinar] via @sejournal, @duchessjenm

Stop letting AI drain your budget. Learn how to make it work for you.

Think AI can fully run your marketing strategy on autopilot?

Or that AI-generated content should deliver instant results?

It is time to bust the AI myths that are slowing you down and costing you money.

Join Bailey Beckham, Senior Partner Marketing Manager at CallRail, and Jennifer McDonald, Senior Marketing Manager at Search Engine Journal, on August 21, 2025, for an exclusive webinar. Get the insights you need to stop wasting time and money and start leveraging AI the right way.

In this session, you will learn:

Why this session is essential:

AI tools can’t run your strategy on autopilot. You need to make smarter decisions, ask the right questions, and guide your AI tools to work for you, not against you.

This webinar will help you unlock AI’s full potential and optimize your content to improve your marketing performance.

Register now to learn how to get your content loved by AI, LLMs, and most importantly, your audience. Can’t attend live? Don’t worry, sign up anyway, and we will send you the on-demand recording.

Ecommerce MGMT 0 Comments

Aug 6 2025

The Great Reversal: Why Agencies Are Replacing PPC With Predictable SEO via @sejournal, @mktbrew

This post was sponsored by Market Brew. The opinions expressed in this article are the sponsor’s own.

What if your client’s PPC budget could fund long-term organic growth instead?

Why do organic results dominate user clicks, but get sidelined in budget discussions?

Organic Drives 5x More Traffic Than PPC. Can We Prove It?

The Short Answer: Yes!

Over the past decade, digital marketers have witnessed a dramatic shift in how search budgets are allocated.

In the past decade, companies were funding SEO teams alongside PPC teams. However, a shift towards PPC-first has dominated the inbound marketing space.

Where Have SEO Budgets Gone?

Today, more than $150 billion is spent annually on paid search in the United States alone, while only $50 billion is invested in SEO.

That’s a 3-to-1 ratio, even though 90% of search clicks go to organic results, and only 10% to ads.

It’s not because paid search is more effective. Paid search is just easier to measure.

But that’s changing with the return of attribution within predictive SEO.

What Is Attribution?

Attribution in marketing is the process of identifying which touchpoints or channels contributed to a conversion or sale.

It helps us understand the customer journey so we can allocate budget more effectively and optimize campaigns for higher ROI.

As Google’s algorithms evolved, the cause-and-effect between SEO efforts and business outcomes became harder to prove.

Ranking fluctuations seemed random. Timelines stretched.

Clients became impatient.

Trackable Digital Marketing Has Destroyed SEO

With Google Ads, every dollar has a direct, reportable outcome:

Impressions.
Clicks.
Conversions.

SEO, by contrast, has long been:

A black box.

As a result, agencies and the clients that hire them followed the money, even when SEO’s results were higher.

PPC’s Direct Attribution Makes PPC Look More Important, But SEO Still Dominates

Hard facts:

SEO drives 5x more traffic than PPC.
Companies pay 3x more on PPC than SEO.

Image created by MarketBrew, August 2025

You Can Now Trace ROI Back To SEO

As a result, many SEO professionals and agencies want a way back to organic. Now, there is one, and it’s powered by attribution.

Attribution Is the Key to Measurable SEO Performance

Instead of sitting on the edge of the search engine’s black box, guessing what might happen, we can now go inside the SEO black box, to simulate how the algorithms behave, factor by factor, and observe exactly how rankings react to each change.

This is SEO with attribution.

Image created by MarketBrew, August 2025

With this model in place, you are no longer stuck saying “trust us.”

You can say, “Here’s what we changed. Here’s how rankings moved. Here’s the value of that movement.” Whether the change was a new internal link structure or a content improvement, it’s now visible, measurable, and attributable.

For the first time, SEO teams have a way to communicate performance in terms executives understand: cause, effect, and value.

This transparency is changing the way agencies operate. It turns SEO into a predictable system, not a gamble. And it arms client-facing teams with the evidence they need to justify the budget, or win it back.

How Agencies Are Replacing PPC With Measurable Organic SEO

For agencies, attribution opens the door to something much bigger than better reporting; it enables a completely new kind of offering: performance-based SEO.

Traditionally, SEO services have been sold as retainers or hourly engagements. Clients pay for effort, not outcomes. With attribution, agencies can now flip that model and say: You only pay when results happen.

Enter Market Brew’s AdShifted feature to model this value and success as shown here:

: Screenshot from a video by MarketBrew, August 2025

The AdShift tool starts by entering a keyword to discover up to 4* competitive URLs for the Keyword’s Top Clustered Similarities. (*including your own website plus 4 top-ranking competitors)

: Screenshot of PPC vs. MarketBrew comparison dashboard by Marketbrew, August 2025

AdShift averages CPC and search volume across all keywords and URLs, giving you a reliable market-wide estimate and details for your brand towards a monthly PPC investment to rank #1.

: Screenshot of a dashboard by Marketbrew, August 2025

AdShift then calculates YOUR percentage of replacement for PPC to fund SEO.

This allows you to model your own Performance Plan with variable discounts available to the Market Brew license fees with an always less than 50% of PPC Fee for clicks replaced by new SEO traffic.

: Screenshot of a dashboard by Marketbrew, August 2025

AdShift simulates a PPC replacement plan option selected based on its keywords footprint to instantly see savings from the associated Performance Plans.

That’s the heart of the PPC replacement plan: a strategy you can use to gradually shift a clients’ paid search budgets into measurable performance-based SEO.

What Is A PPC Replacement Plan? Trackable SEO.

A PPC replacement plan is a strategy in which agencies gradually shift their clients’ paid search budgets into organic investments, with measurable outcomes and shared performance incentives.

Here’s how it works:

Benchmark Paid Spend: Identify the current Google Ads budget, i.e., $10,000 per month or $120,000 per year.
Forecast Organic Value: Use search engine modeling to predict the lift in organic traffic from specific SEO tasks.
Execute & Attribute: Complete tasks and monitor real-time changes in rankings and traffic.
Charge on Impact: Instead of billing for time, bill for results, often at a fraction of the client’s former ad spend.

This is not about replacing all paid spend.

Branded queries and some high-value targets may remain in PPC. But for the large, expensive middle of the keyword funnel, agencies can now offer a smarter path: predictable, attributable organic results, at a lower cost-per-click, with better margins.

And most importantly, instead of lining Google’s pockets with PPC revenue, your investments begin to fuel both organic and LLM searches!

Real-World Proof That SEO Attribution Works

Agencies exploring this new attribution-powered model aren’t just intrigued … they’re energized. For many, it’s the first time in years that SEO feels like a strategic growth engine, not just a checklist of deliverables.

“We’ve pitched performance SEO to three clients this month alone,” said one digital strategy lead. “The ability to tie ranking improvements to specific tasks changed the entire conversation.”

– Sean Myers, CEO, ThreeTech

Another partner shared,

“Instead of walking into meetings looking to justify an SEO retainer, we enter with a blueprint representing a SEO/GEO/AEO Search Engine’s ‘digital twin’ with the AI-driven tasks that show exactly what needs to be changed and the rankings it produces. Clients don’t question the value … they ask what’s next.”

– Stephen Heitz, Chief Innovation Officer, LAVIDGE

Several agencies report that new business wins are increasing simply because they offer something different. While competitors stick to vague SEO promises or expensive PPC management, partners leveraging attribution offer clarity, accountability, and control.

And when the client sees that they’re paying less and getting more, it’s not a hard sell, it’s a long-term relationship.

A Smarter, More Profitable Model for Agencies and SEOs

The traditional agency model in search has become a maze of expectations.

Managing paid search may deliver short-term wins, but it comes to a bidding war with only those with the biggest budgets winning. SEO, meanwhile, has often felt like a thankless task … necessary but underappreciated, valuable but difficult to prove.

Attribution changes that.

For agencies, this is a path back to profitability and positioning. With attribution, you’re not just selling effort … you’re selling outcomes. And because the work is modeled and measured in advance, you can confidently offer performance plans that are both client-friendly and agency-profitable.

For SEOs, this is about getting the credit they deserve. Attribution allows practitioners to demonstrate their impact in concrete terms. Rankings don’t just move, … they move because of you. Traffic increases aren’t vague, … they’re connected to your specific strategies.

Now, you can show this.

Most importantly, this approach rebuilds trust.

Clients no longer have to guess what’s working. They see it. In dashboards, in forecasts, in side-by-side comparisons of where they were and where they are now. It restores SEO to a place of clarity and control where value is obvious, and investment is earned.

The industry has been waiting for this. And now, it’s here.

From PPC Dependence to Organic Dominance — Now Backed by Data

Search budgets have long been upside down, pouring billions into paid clicks that capture a mere fraction of user attention, while underfunding the organic channel that delivers lasting value.

Why? Because SEO lacked attribution.

That’s no longer the case.

Today, agencies and SEO professionals have the tools to prove what works, forecast what’s next, and get paid for the real value they deliver. It’s a shift that empowers agencies to move beyond bidding-war PPC management and into a lower cost & higher ROAS, performance-based SEO.

This isn’t just a new service mode it’s a rebalancing of power in search.

Organic is back. It’s measurable. It’s profitable. And it’s ready to take center stage again.

The only question is: will you be the agency or brand that leads the shift or watch as others do it first?

Citations

Get Your Predictable SEO Plan

Image Credits

Featured Image: Image by Market Brew. Used with permission.

In-Post Image: Images by Market Brew. Used with permission.

Ecommerce MGMT 0 Comments

Jul 23 2025

Don’t Overlook Mid-Funnel Prospects: AI PPC Strategies For Business Growth via @sejournal, @LisaRocksSEM

Marketers tend to prioritize top-of-funnel awareness and bottom-funnel conversion efforts.

Yet, the mid-funnel stage is where prospects actively weigh options and is crucial for sustained growth and profitability.

Overlooking this critical stage can reduce revenue potential. Using AI-driven paid media for nurturing and retargeting can bridge this gap, converting high-quality leads into profitable customers.

Importance Of Mid-Funnel Engagement

Prospects in the mid-funnel have already expressed interest and are ready to move to action.

They are conducting detailed comparisons, attending webinars, downloading whitepapers, and critically evaluating their choices.

Despite this intense engagement, advertisers often overlook this critical phase, causing leads to drop off.

Common challenges at this stage include generic content that fails to resonate and intrusive retargeting campaigns.

The lack of personalized campaigns and ad copy further undermines mid-funnel marketing. It’s important now for marketers to reassess their strategies to better engage prospects.

Understanding The Customer Journey: Top-, Mid-, And Bottom-Funnel Behaviors

To effectively target prospects, we have to understand their journey through the marketing funnel.

As we explore AI’s impact on the mid-funnel, let’s first look at how prospect behaviors evolve from awareness to conversion.

For PPC strategists and chief marketing officers, aligning paid media tactics with each funnel stage is key to maximizing AI’s potential in campaigns.

To illustrate how PPC strategies should evolve with the prospect’s mindset, consider the following breakdown of PPC tactics for each funnel stage.

Funnel Stage	Prospect Mindset & Goal (PPC Lens)	Common PPC Keyword/Query Types	Key PPC Ad Focus	Core PPC Tactics & Ad Formats
Top-Funnel (Awareness)	“I have a problem or need.” Seeking general information	Informational keywords: “how to solve problem” “what is” “benefits of”	Educate and inform. Position your brand as a helpful resource. Highlight helpful content.	Broad match keywords Display Network ads (interest, affinity audiences). YouTube. General search campaigns.
Mid-Funnel (Consideration/ Evaluation)	“I understand my problem and am looking for solutions.” Comparing options, detailed info on specific solutions.	Comparison keywords: “compare [product A] vs. [product B]” “best product category for [a specific need]” “[product name] reviews” “alternative to [competitor]” pricing	Features and benefits. Demonstrate unique value, highlight differentiators. Offer solutions to specific pain points.	Exact/phrase match keywords. Retargeting (website visitors, video viewers, content downloads. Custom Intent, In-Market audiences. Dynamic Search Ads (for specific solution pages). Google Shopping (for products being compared). Focus on lead capture.
Bottom-Funnel (Decision/ Purchase)	“I’m ready to buy, need to choose who from.” Making a final decision, seeking confirmation, or a specific offer.	Transactional keywords: “buy [product name]” “[product name] pricing” “demo” “get a quote” “deal on [product]” “sign up for [service]”	Call-to-action and urgency. Offer direct value, limited-time deals, or compelling reasons to choose now. Focus on immediate conversion.	Highly targeted exact match keywords. Remarketing to cart abandoners or demo form abandoners. Competitor Conquesting (very specific terms) Google Shopping (specific prod SKUs). PMax with strong final URLs. Lead Form Assets. Focus on direct sales.

Mid-Funnel Potential

In the “consideration” phase, advertisers now have new ways to engage, segment, and nurture mid-funnel audiences with AI and innovative PPC targeting tactics.

Here are three AI-powered mid-funnel tactics to integrate into the paid search plan.

1. AI-Driven Prospect Targeting

This tactic uses AI to analyze huge amounts of user data signals to identify which specific prospects are most likely to take action (convert) at mid-funnel.

The ad platforms may look at past website interactions to demographic signals to predict who are the most qualified new customers.

Smart Bidding and targeting tools allow advertisers to focus ad budget and messaging on the most effective, hot leads.

In one example, Google Ads segments out new customers, calling it the “New customer acquisition goal.” This lifecycle goal prioritizes bidding to reach and acquire new customers.

Key Advantages:

Maximizes budget efficiency: Uses AI to identify high-intent prospects within your paid ad campaigns.
Improves overall conversion rates: By prioritizing higher-intent leads, you naturally see a better chance of converting them into valuable customers down the line.

PPC Features Supporting This Tactic:

Performance Max (Google Ads and Microsoft Ads): This powerful campaign type leverages AI across all channels (search, display, email, etc) to find converting customers. It prioritizes users showing high-value signals, optimizing your bids and placements to capture them.
Smart Bidding Strategies (Target CPA, Target ROAS): While often used for bottom-funnel sales, these can be set to optimize for mid-funnel conversions. The AI learns which users are more likely to complete these specific actions and bids accordingly.
Custom Segments (Audience Manager): Combine your valuable first-party data (like customer lists of qualified leads) with Google’s audience signals to create highly targeted segments. AI can then optimize towards these prequalified groups.

2. Dynamic Ad Creative

AI automation can generate personalized ad creatives in real-time, enhancing relevance and engagement.

This means prospects see ads that are custom for their specific interests and previous interactions, in real-time, making the ads feel more relevant and personal.

Key Advantages:

Ad relevance: Ads feel personal and directly address the user’s observed interests, grabbing attention and increasing engagement.
Reduces ad fatigue: Users see varied, interesting ads instead of the same old creative repeatedly, preventing boredom and annoyance, which keeps them engaged longer.
Improves engagement metrics: You’ll see higher click-through rates (CTRs) and potentially better ad quality scores because the ads are well-matched to user intent.

PPC Features Supporting This Tactic:

Responsive Search Ads (RSAs) and Responsive Display Ads (RDAs): You provide multiple headlines, descriptions, and images. Google’s AI then mixes and matches these assets in real-time to find the best-performing combinations for each unique search query or individual users based on their search query, device, location, and other signals.
Dynamic Retargeting/Remarketing Ads: For ecommerce, these ads automatically showcase products a user viewed on your site. For B2B, they can dynamically display relevant content, case studies, or solutions based on specific pages visited on your website.
Google Ads’ Asset Library and AI-Driven Creative Suggestions: These tools help you generate a wide variety of diverse assets, then utilize them effectively to create countless ad variations.

3. Value-Based Bidding For Mid-Funnel Conversions

Shift your focus from conversion volume to conversion value with AI-powered bidding strategies that prioritize high-value leads.

Advertisers can assign a higher monetary value to actions that signify greater intent or higher potential lifetime value, like a demo request vs. a download.

The AI then prioritizes bids and focuses the budget on acquiring more valuable leads.

Key Advantages:

Optimizes for profitability, not just volume: Ensures your ad spend is directed towards acquiring profitable leads.
Improves budget allocation: AI intelligently allocates bids based on anticipated lead quality and potential revenue, not just the number of conversions, leading to more efficient spending.
Aligns PPC directly with business key performance indicators (KPIs): This strategy directly ties your ad performance to revenue goals and bottom-line impact. By focusing on value, PPC becomes a clear contributor, proving its worth directly.

PPC Features Supporting This Tactic:

Target ROAS (Return On Ad Spend) for Lead Generation: While often seen in ecommerce, an advanced use case is to apply it to lead generation campaigns. By assigning monetary values to different lead types, you tell the system the ROAS you want, and AI bids to meet it.
Maximize Conversion Value Bidding: This bidding strategy tells the AI to get the highest possible total conversion value within your budget. This requires a proper setup where you assign different values to each mid-funnel conversion action in your account. Without those values, the system can’t differentiate between the worth of different conversions.
Offline Conversion Import: This is a secret weapon! By importing your customer relationship management (CRM) data information about which leads converted to sales into your ad platforms, you teach the AI which mid-funnel actions are most likely to result in a high-value closed deal, allowing it to optimize bids efficiently.

Ready To Make The Mid-Funnel A Strategic Priority?

Rethink your approach to the mid-funnel, where valuable engagement opportunities often go untapped.

By using AI-driven strategies like those discussed, you can reconnect with high-intent prospects and guide them toward conversion.

For CMOs and senior marketers, optimizing the mid-funnel is a strategic opportunity to grow the customer acquisition pipeline.

More Resources:

Featured Image: N Universe/Shutterstock

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Jul 11 2025

How To Calculate Your ROAS & Ways To Use It via @sejournal, @coreydmorris

Return on ad spend (ROAS) is a common metric or key performance indicator for paid search campaigns. PPC managers and digital marketing executives have been using it for a long time.

In fact, it isn’t even novel to just digital marketing.

While calculating and connecting the dots with attribution for full end-to-end digital marketing is ideal, using ROAS within PPC and SEM specifically can be powerful as a quality metric that scales.

ROAS is a pretty straightforward equation to calculate on the surface.

Return on ad spend = total revenue generated by ads, divided by the cost of ad spend

However, it seems that no metric, KPI, or outcome is as easy to configure and measure nowadays, given the volume of changes in Google Ads, reporting software, and measurement platforms alone.

Beyond that, there’s no one-size-fits-all benchmark or result you’re looking for. A “good” ROAS is different for every business, and what defines good or successful is up to the business to determine.

Whether you’re confident calculating ROAS, need help with knowing how to use it, or fall somewhere in between, I encourage you to dive into the ways to use it in your own PPC efforts.

1. Setting Expectations

PPC is a great channel for getting quick results and to impact a business.

However, even with the best research on the front end, it can often lead to missed expectations.

PPC expectations can vary wildly and be subjective. ROAS provides the opportunity to set a benchmark for what success looks like.

An effective PPC manager can pull different levers to drive more traffic, spend more budget, or try to find a sweet spot in between.

By establishing a ROAS goal tied to profitability, the PPC team can utilize that metric as a key in their decisions and performance overall.

And, profitability needs to factor in the cost of software, people, and things that go beyond just the cost of an ad or media budget – but that’s for another article.

2. Budgeting

ROAS can serve as a great tool in factoring budget decisions.

Like setting expectations, ROAS can serve as a benchmark, helping teams go beyond just looking at bid, budget, click, and conversion ceilings. It is a quality metric.

Use ROAS to determine where the law of diminishing returns applies and ensure it is included in projections. When looking at real past performance, it can be used to help determine ideal budgets and ranges that are acceptable.

In most cases, I have found clients are okay with not capping the budget and looking at the ROAS number solely to determine how much to spend.

If the spend can be increased and still exceed the target ROAS, then keep spending all day, every day, as we know we’re in profitable territory, assuming we’re not creating inventory, fulfillment, sales capacity, or other operational issues.

I love this type of thinking and decision-making, as it is linked to ROI versus budget or a mindset that marketing and ad dollars are an “expense.”

3. Bid Decisions

Getting more granular, bid decisions can also be made based on ROAS.

The ROAS can be calculated at a detailed level and not just at a high level for aggregate or total spend.

When we break down our campaigns into categories like campaign, ad group, ad type, topic, etc., we can get more granular control and insight.

For example, If we’re running Google Shopping Ads which appear on Google Shopping search results pages, we can treat those as a distinct advertising format. This allows us to measure their performance separately and calculate the return on ad spend (ROAS) they generate.

Going even deeper, we can drill down to the individual product level to see how different products produce ROAS.

By knowing what the ROAS is at different levels, we can advise and optimize our bid strategies and have more control over what is driving the overall ROAS and positively impact the whole.

The ability to roll up performance drill down to the product detail level allows for measuring toward broader business goals while also providing an opportunity to test and get things dialed in over time when launching and optimizing new campaigns and ads within an account.

4. Ecommerce

One of the first types of businesses that comes to mind when thinking about ROAS and its use is ecommerce.

With a lot of the great tools and integrations available, many shopping cart platforms automatically feed revenue data back into Google Ads and Google Analytics.

By using these metrics, we can quickly arrive at our ROAS by taking total revenue divided by total spend.

Note that getting ROAS is likely the easiest part. Determining what an acceptable ROAS overall takes more time and work.

That part includes determining profit margins for products, calculating overhead, and determining the full aspect of ROI to back out what the ROAS needs to be.

5. Lead Generation

A trickier business goal type for calculating ROAS is lead generation. ROAS might be tougher to back out and measure itself.

However, in most cases, lead generation campaigns have more attention to detail on the ROI side of things and know their sales cycles and overhead.

This makes arriving at ROAS goals easier, while ROAS itself might take more time to calculate based on the length of time from conversion to final sale, if that’s how ROAS is truly calculated.

When you want to look at ROAS as a meaningful metric for lead generation, you need to have a solid definition of what a lead is.

By default, if a conversion action in Google Ads (or other platforms) is what you use to calculate this metric, you might end up off-track from what your sales team or broader effort cares about.

ROAS matters, but if the “lead” isn’t right or something you can track, you can run into trouble with the definitions of “return,” “leads,” and your overall attribution.

In most cases, the deepest you can track and attribute a lead to a sale and actual revenue is best. If you can’t get that deep, ask questions and probe. The dots should be connected from impression to customer/client.

6. Awareness & Other Campaigns

ROAS can be measured in other business goals and applications as well.

Whether it is awareness generation, page views, or other secondary goals, it can still apply.

Although, it might take more work to define the return for awareness campaigns and would need measurement through attribution modeling. But, it can still be achieved with the right work to back out the sales metric.

As a note, in B2B lead gen, attribution windows can be long, and offline conversion tracking is needed for accuracy.

An example of ROAS for an awareness campaign can look very different from one for ecommerce or lead generation.

If your goal is to create awareness for a topic, brand, or other subject matter, then you’re not as focused on direct sales or leads. You may want to cast as wide of a net as possible for your target or potential audience (even if the broader general public).

In that sense, you have to find a key metric to tie ROI to. You have the most open-ended challenge here – you have to determine the ROI for your organization. What does awareness contribute directly to ROI? How do you define it, measure it, and attribute it?

7. Beyond ROAS

While ROAS is a great benchmark and quality guide for paid media, it isn’t the end of the story. In some cases, it is just the start.

With customer retention, recency, frequency, monetary value (RFM), and lifetime value metrics that are known in businesses, we can take it even further.

Tying ROAS to other metrics beyond the sale can lead to incredible insights for use outside of media spend management.

Getting More From ROAS

Again, I know that ROAS might seem like a basic metric and be something reported on by default in so many dashboards and reports.

While in some cases, it may be simple to calculate, but using it as a metric takes more work.

Getting the foundation right, knowing what a good target ROAS is, how it scales, and that the “return” you’re getting is profitable, is the key to seeing it be a key benchmark and goal-focused KPI in your set of digital marketing metrics that ultimately map out to your business outcome results.

More Resources:

Featured Image: voronaman/Shutterstock

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Jul 9 2025

Stop Paying the Google Ads Tax Without Realizing It [Webinar] via @sejournal, @hethr_campbell

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.

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Jul 8 2025

Why Google Ads Fails B2B (And How to Fix It)

This post was sponsored by Vehnta. The opinions expressed in this article are the sponsor’s own.

Why isn’t Google Ads working for my B2B marketing campaigns?

How do I improve lead quality in B2B Google Ads campaigns?

What’s the best way to scale Account-Based Marketing (ABM) using Google Ads?

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.
Create separate campaigns for different buying stages with stage-appropriate conversion goals.
Start Performance Max with limited budgets (20-30% of total spend) until optimization stabilizes.

Phase 2: Configure B2B-Specific Signals

Upload customer lists with consistent firmographic data as audience signals.
Set up similar audiences based on highest-value customers, not highest-converting leads.
Monitor search terms weekly and add negatives aggressively.
Use custom conversion goals weighted toward pipeline contribution, not form submissions.

The Easy Way

Vehnta accelerates campaign optimization, enabling precise targeting and performance tracking across your entire B2B account list.

With its Similarity feature and AI-powered Keyword & Ad Generator, you can create high-performing, B2B-optimized campaigns in minutes, avoiding wasted spend on low-value conversions.

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.
Focused paid ad spend on high-intent, high-fit prospects.

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 by 60% 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.

Book a demo: boost leads, cut costs.

Book A Demo

Image Credits

Featured Image: Image by Vehnta. Used with permission.

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Jul 4 2025

What Is Paid Media: The Different Types & Examples via @sejournal, @brookeosmundson

Paid media is often treated like a checklist item in a marketing plan: launch a few search ads, run a Meta campaign, maybe test YouTube if there’s budget left.

But not all paid media is created equal, and treating every channel the same is a fast way to burn through budget with little to show for it.

Whether you’re working in-house or managing campaigns for clients, understanding the different types of paid media (and what each one is actually good for) can help you prioritize the right tactics, set realistic expectations, and answer the dreaded question: “What are we getting out of this?”

This article breaks down the main types of paid media with real-world examples so you can make smarter decisions about where to spend your money.

What Is Paid Media?

Paid media is any type of marketing where you pay to get in front of your audience. That includes things like search ads, social ads, display banners, video pre-roll, and even influencer sponsorships.

While paid media is often used interchangeably with the term cost-per-click (CPC), it’s important to note the differentiation.

It’s the part of your marketing strategy that gives you scale and control. You’re not waiting for someone to discover your blog post or share your Instagram reel organically.

You’re putting money behind your message to drive attention right now.

Paid media works best when it’s tied to a clear goal, like driving leads, sales, or downloads. Without a strategy, it’s just noise with a price tag.

The Difference Between Earned, Owned, And Paid Media

Think of paid, owned, and earned media as different ways to get your message out. You need a mix of all three, but each serves a different purpose.

Paid media is when you pay for attention. Think of tactics like search ads, social ads, sponsored posts, affiliate placements, etc.
Owned media is what you control. Think of assets like your website, blog, email list, and social channels.
Earned media is what others say about you. This often comes in the form of reviews, PR coverage, social shares, and more.

Some examples of earned media include:

Social sharing from customers.
Customer reviews.
External media coverage (public relations).

Owned media examples include:

The overlap matters, too. A paid campaign might drive traffic to a landing page (owned media), which then gets shared by a happy customer (earned media). When these channels work together, your efforts go further.

Types Of Paid Media Channels

Now that we’ve identified the definition of paid media, let’s take a look at the different types of paid media channels and the purposes they serve.

Before we dive into the different paid media channels, it’s also important to note the difference between ad formats and ad channels.

Ad formats are the type of ads shown in a particular channel. An ad format example could be:

So, while ad formats are important and will depend on the channel, below we will focus on the channels themselves.

There are other types of paid media channels available that are not listed here, such as more traditional methods like direct mail or billboards. These paid media channels have a more physical presence.

Here, we will focus on digital channels.

Paid Search

Paid search puts your ads at the top of search results for specific keywords. It’s often the first paid channel marketers try because it targets people already looking for what you offer.

Platforms like Google Ads and Microsoft Ads let you bid on search terms so your ad shows when someone types in something relevant.

Google is the leading search engine in market share, with its sites generating 60.4% of user searches in the United States.

It’s high-intent, measurable, and scalable. But, it’s also competitive, especially in industries like legal, finance, or ecommerce.

Success here depends on more than just bidding. Your landing page, ad copy, keyword match types, and conversion tracking all matter. You’re not just paying for clicks – you’re paying for the opportunity to convert interest into action.

Paid Social

Paid social platforms let you reach people based on who they are, not just what they search.

Many of the platforms offer detailed targeting based on demographics, interests, behaviors, and even job titles.

Some of the most common paid social platforms include:

Meta (Facebook).
Instagram.
LinkedIn.
TikTok.
Pinterest.
Snapchat.
X (Twitter).

The most common ad format in social channels is placed within a user’s newsfeed as they scroll. These ads will either consist of one (or more) static images or a video as the main visual.

It’s not just about brand awareness. Many brands use social to drive signups, sales, or downloads. You can run video ads, carousels, static images, or Stories, depending on what fits your brand and goal.

Some paid social platforms are more beneficial for B2B companies than for B2C brands.

For example, LinkedIn advertising consists mainly of B2B brands marketing their product or service to other professionals.

Other platforms like TikTok and Snapchat may be better suited for B2C or ecommerce brands.

The tricky part? Creative fatigue is real.

If you’re not refreshing your assets often or testing different hooks, performance will drop fast. Social ads require constant iteration, but the upside is speed: you can test ideas and get feedback quickly.

Programmatic & Display

Display advertising is what most people think of as “banner ads.” These are the visual ads you see on news sites, blogs, or apps, usually managed through platforms like the Google Display Network or programmatic buying platforms.

The upside is scale. You can reach millions of people across the web without relying on social platforms. The downside? Banner blindness is real. If your creative isn’t compelling, people will scroll right past.

That’s why display works best for remarketing or supporting a broader campaign. Use it to stay top of mind, promote limited-time offers, or drive awareness ahead of a product launch. Just don’t expect cold traffic to convert on the first click.

Affiliate Marketing

Affiliate marketing is a way to scale your reach by letting others promote your product for you. You only pay when they drive a sale or lead, which makes it one of the lowest-risk paid media options available.

This model works especially well in industries like fashion, tech, travel, and finance, where bloggers, influencers, or content sites already have built-in audiences.

The key to making affiliate work? Vet your partners. A bunch of low-quality traffic from coupon sites won’t move the needle.

Look for affiliates who create content, have authority, or drive meaningful referral traffic.

And keep an eye on attribution. Affiliate-driven sales often overlap with other paid efforts, so tracking needs to be tight.

Examples Of Paid Media

This is where the ad formats are married to the paid media channels.

Below are examples of paid media ads from the popular channels listed above. These examples can help provide context when deciding what types of paid media to run.

Search Examples

When searching for [top parental control apps] in Google, the first three positions are examples of search ads.

Screenshot from Google search for [top parental control apps], Google, May 2025

While conducting the same search on Microsoft Bing, the ads look slightly different.

There’s even a section above the sponsored ads showcasing different brands and a brief description about what they do.

Screenshot from Bing search for [top parental control apps], Microsoft Bing, May 2025

When searching for a product like [nike shoes for women], the ads below are a shopping ad format.

Screenshot from Google search for [nike shoes for women], Google, May 2025

Paid Social Examples

Each social platform’s ad formats look different within their respective newsfeeds.

Here is a LinkedIn newsfeed example:

Screenshot from author’s LinkedIn newsfeed, desktop ad, May 2025

A Facebook ad newsfeed example:

Screenshot from author’s Facebook newsfeed, desktop ad, May 2025

Instagram also offers ads in its “Stories” placement. An example from Fountainhead is below:

Screenshot from author’s Instagram Stories feed, Stories ad, May 2025

Display Examples

Display ads can be in all shapes and sizes, depending on the website or app.

Below is an example of two different display ads shown on one webpage.

Screenshot from author, May 2025

Affiliate Examples

Sometimes, affiliate ads can be difficult to spot.

For example, “Listicle” articles, where a publisher is paid by other brands to be included in a “Top” product article.

Screenshot from FamilyOnlineSafety.com, May 2025

However, if you take a closer look at this example’s “Advertising Disclosure,” you’ll notice that this publisher is paid by the brands for exclusive placement:

Screenshot from FamilyOnlineSafety.com, May 2025

Summary

Paid media doesn’t have to be a guessing game. When you understand the role each channel plays, you’re in a much better spot to build campaigns that actually drive results, not just impressions.

From keyword-targeted search ads to affiliate partnerships and social retargeting, each paid media type has its own strengths. Use them deliberately.

Think about where your audience is, how they like to interact, and what action you want them to take.

Remember: success isn’t just about being present on every channel. It’s about showing up with the right message, in the right place, at the right time.

More resources:

Featured Image: Lana Sham/Shutterstock

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Jun 30 2025

The Strategy Gap: Social Video Is Not PPC Video via @sejournal, @LisaRocksSEM

Video is dominating online across PPC ads and social media channels. Unfortunately, many advertisers still repurpose social videos for paid campaigns.

What works organically on TikTok or Instagram often falls flat in performance-driven environments like YouTube Ads or Performance Max.

This could lead to low engagement and poor conversions.

To compete in today’s attention economy, PPC video needs its own strategy that is built from the ground up with performance in mind.

This article explores why CMOs and senior marketers must treat video as a creative asset, that is, a conversion-driven engine and platform-specific.

The Disconnect Between Social Video And PPC Video

Some marketers start with social video and “cut it down” for paid. However, the two formats fundamentally differ in purpose, intent, and delivery.

Social video is built for engagement, likes, shares, and storytelling that captures attention in a feed.

PPC video, on the other hand, is engineered for a conversion action. It must capture attention, communicate value quickly, and drive a specific action with a call-to-action (CTA) statement.

Repurposing social content for PPC assumes that the creative context uses the same strategy for driving engagement.

Social videos often rely on trends, audio cues, or slow storytelling arcs. Those don’t translate to skippable, conversion-focused ad formats where you have just a few seconds to inform and impact.

The following table outlines the fundamental differences between social and PPC video.

Category	Social Video	PPC Video
Purpose	Brand building, storytelling, and community engagement	Lead generation, sales, and performance-driven metrics
Viewer Intent	Passive browsing, entertainment	High intent, research, or decision-making mindset
Format & Delivery	Organic feed content, often square or vertical	Paid ad placements; needs variation for 16:9, 4:5, vertical, etc.
Sound/Audio	Often relies on music, trends, or narration	Must perform without sound; strong visuals are needed
Calls-to-Action	Often implied or delayed	Immediate and repeated; click-through or conversion-focused
Performance Metrics	Likes, shares, video views, engagement rate	CTR, conversion rate, ROAS, CPA

Best Practices For PPC Video

PPC video ads should be intentionally created to drive conversions, not just views.

Below are key creative best practices that directly influence campaign outcomes, keeping in mind the details of different platforms:

1. Hook The Viewer Within The First 3 Seconds

Front-load your story arc by getting to the point of the video early, which often involves presenting the value proposition and the desired action.

You only have a moment to make viewers stop scrolling or delay the skip button. Use bold text, motion, or a strong question right away.

Example: “Spending too much on ads? Here’s a fix that saved our client $10,000.”

2. Format Video For The Platform

Each platform has different specs and user behaviors that require a custom approach for each. This is a perfect example where “one size does not fit all.”

YouTube standard videos typically requires horizontal (16:9), aligning with a sound-on viewing environment, while YouTube Shorts are vertical and platforms like Meta often favor square or vertical.

TikTok favors vertical, full-screen videos for sound-off autoplay. Develop your creative asset with this in mind.

3. Include A Clear Call-To-Action Early And Repeat

Don’t rely on a single CTA at the end. Video ads are built for direct response. Reinforce the action you want throughout the video.

Example: Start the video with “Click to get the offer,” and show it again midway and at the end.

4. Lead With The Benefit, Not The Backstory

People want to know what’s in it for them and how you solve their problem. Skip the warm-up and start with a direct benefit or result.

Example: Instead of “Our team spent weeks testing this,” say, “This ad strategy cuts CPC in half.”

5. Design With Platform Audio In Mind

For platforms with silent autoplay (TikTok, Instagram Reels, Facebook Feed): Prioritize visual communication. Many users watch without sound, so ensure your message still lands visually.

Use animated captions and highlight product features with motion text, so nothing is lost without audio.

For YouTube: Recognize that ads often play while users have the sound on.

While strong visuals are still important, leverage sound effectively through voiceovers, music, and sound effects to enhance your message and brand experience, as highlighted in YouTube’s Playbook for Creative Advertising [PDF] under the “Build for sound on” principle.

These elements influence how your video is served, watch time, and whether they take action.

Platform-Specific Video Strategies

Not all platforms serve video in the same way. Understanding how your content is delivered, measured, and optimized across each environment is critical to making PPC video work.

YouTube Ads

YouTube is a high-intent platform, with users actively choosing to watch content. Your ad will most often appear before or during another video.

The key here is overcoming the viewer’s “skip” behavior.

Maximize the impact of the skippable first five seconds. Use a bold visual or a clear problem-solution hook to immediately capture attention and provide value, making viewers want to watch more.
Build a narrative that fits intent. Educational formats, product demos, or expert commentary perform well here. Consider longer-form content that addresses pain points thoroughly or showcases product features in detail. Leverage storytelling to connect with viewers who are actively engaged.
End with a strong call to action. Take users to a landing page or offer page that extends the message.
- Example: A productivity software brand opens with “Wasting time switching tabs?” then shows how its tool solves it with a single view, ending with “Try it for free today.”

Performance Max

Performance Max distributes video across placements like YouTube, Discovery, and Gmail. This requires a flexible, creative approach built to adapt to various ad spaces.

Upload multiple lengths: At minimum, include 6-second, 15-second, and 30-second versions. Varying lengths allow Google’s AI to test and serve the most effective creative for each placement and user.
Include strong product visuals: Use the dedicated headline and description fields within the PMax asset library to deliver your primary marketing messages and calls to action. This allows Google’s AI to optimize the pairing of text and video for different platforms and user behaviors. Ensure key messages and branding are visually prominent and understandable without audio.
Create for automation: Google optimizes based on performance. Give the algorithm assets that can stand alone, yet are also easy to mix and match. This includes various headlines, descriptions, and calls to action that can be paired with your video assets, allowing Google’s machine learning to find the most effective combinations.
Leverage vertical image ads for YouTube Shorts: Google Ads now supports full-screen vertical (9:16) image ads specifically for YouTube Shorts within Demand Gen campaigns. This allows you to repurpose existing vertical image assets from platforms like Meta to reach users in this rapidly growing short-form video environment. Recommended size: 1080×1920.
- Example: A clothing brand uses 15-second vertical videos with close-up fabric shots and pricing overlays so the system can serve based on what performs.

Meta Video Ads (Facebook And Instagram)

These platforms autoplay silently in-feed, so your creative must speak visually before sound is ever involved.

Front-load motion or emotion. Start with an action or a relatable facial expression. Think about creating a visual hook that stops the scroll and intrigues users enough to tap for sound.
Use large text overlays and branded visuals. This keeps the message clear and recognizable at a glance. Keep text concise and easy to read on smaller mobile screens. Ensure your branding is integrated early and consistently.
Mobile-first approach. Vertical or 4:5 ratio works best for in-feed and Stories. Utilize the full vertical space to immerse viewers and avoid the cropped look of horizontal videos on these platforms.
- Example: A skincare brand opens with a smiling woman applying cream, with large text: “Sensitive skin? See instant calm.”

Optimize your video creative for the unique consumption habits and delivery methods of each platform, and increase the likelihood of engagement and better performance from your PPC video campaigns.

Making The Business Case To CMOs

CMOs and senior leaders often see video as a single, limited asset: make once, use everywhere.

Now, with the increasing sophistication of digital advertising platforms and the different ways video is consumed, the same approach is not cost-effective or performance-driven.

The increase of short-form video, dominance of mobile, and the emphasis on ad quality across platforms are driving a more strategic approach to video creative.

Consider:

Repurposed social content is likely to underperform in PPC environments because it was not created with the same goals in mind.
Dedicated PPC video would be expected to increase return on ad spend by aligning creative with media placement.
A video designed for PPC would (in theory) have higher engagement. Therefore, should have a higher ad quality score and higher delivery.

Making the business case means shifting from “video as a campaign extra” to “video as a campaign must-have.”

CMOs are ultimately looking for measurable results and a strong return on investment from their advertising spend, and a platform-specific video strategy is the key.

Conclusion: PPC Video Is No Longer Optional

The days of treating all video the same are over, and it’s time to embrace this new approach. Video is now a powerful strategy for driving measurable ad results.

Advertisers should strategically build video with a clear understanding of each platform’s unique environment, their target audience’s intent, and the business goals.

Investing in creative that has a performance-first approach for each platform opens up opportunities for a stronger return on your advertising investment.

The future of successful PPC hinges on your team’s ability to master platform-specific video creation.

More Resources:

Featured Image: Hryshchyshen Serhii/Shutterstock

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Jun 23 2025

Google AI Mode And The Future Of Search Monetization: Ads, Prompts, And The Post-Keyword Era via @sejournal, @siliconvallaeys

Google AI Mode, which officially launched in May 2025 and is now available to all U.S. users without a waitlist, represents a significant step forward in how we engage with search.

Powered by Gemini 2.5, this new interface moves beyond AI Overviews by introducing a persistent, conversational assistant that blends AI-generated insights with traditional search results.

Users can toggle between classic results and AI-driven summaries, follow up on queries, and explore longer, more exploratory conversations, all within a single interface.

Unlike AI Overviews or the earlier Search Generative Experience (SGE), which provided a single AI-generated answer for a traditional search query, AI Mode is more similar to ChatGPT in that it fosters a conversational approach to finding answers.This marks a change in how people interact with search, moving from short, isolated keywords to more natural prompts that sound like how we talk and think.

AI Mode supports rich interactions and longer queries, encouraging a deeper and more nuanced engagement with information. And when user behavior shifts, advertisers must adapt how they reach users with relevant solutions and offers.

Think back to how Enhanced Campaigns forced advertisers to get ready for the explosion in mobile device usage.

We’re now at another junction where advertisers and Google must work together to evolve how we operate to remain successful. That means reconsidering everything from targeting and attribution to monetization and ad design.

An example of Google AI Mode to research running shoes

AI Mode Interface (Screenshot from Google, June 2025)

In this post, I share my thoughts on what AI Mode signals for the future of search, how it challenges long-standing digital advertising models, and why marketers need to adapt fast or risk being left behind.

Strategic Motives: Innovation Vs. Defense

Is Google pushing AI Mode because it sees an opportunity or because it’s responding to pressure from OpenAI and others? The answer is likely both.

Google’s technical leadership is well-established.

DeepMind, a Google company, helped invent the transformer model that underpins GPT. Its Gemini family of models has matured rapidly.

At Google Marketing Live 2025, Sundar Pichai stated that Gemini had taken the lead as the top-performing model, a claim supported by LM Arena’s leaderboard.

Still, Google moves cautiously. As a market leader under regulatory scrutiny, it can’t afford missteps.

The innovation is real, but so is the strategy to protect its dominance by making AI part of its core products before others can take the lead.

I believe Google’s technology is among the best in the world. However, as the company is in the spotlight, they have to be more measured.

Regulatory scrutiny, scale, and legacy expectations mean it can’t move as fast as emerging players, but that doesn’t mean it will always be chasing the lead.

Prompt Complexity And Memory: The Challenge Of Targeting

How users like to find answers is changing from clicking around on a search results page to interacting with an AI assistant.

This evolution from search engine to answer engine introduces a new layer of complexity for advertisers. Prompts in AI Mode aren’t just text; they’re conversations rich with personal context and memory.

Take a user engaging in a long session with AI Mode. Their conversation might include several prompts in a row like this:

“I’m running my first marathon in LA and need good shoes. What do you recommend?”
“By the way, I have plantar fasciitis. I’m not trying to break records, I just need something that won’t wreck my knees.”
“I’m not a fan of bland colors. What brands have something more vibrant in their current line-up?”

The assistant understands the goal and tailors responses to match medical considerations, intent, and emotional tone.

It might include surface stability shoes, recommended inserts, and even factor in training timelines or the expected weather in the city where the marathon will take place.

Now contrast that with a short prompt: “running shoes.”

Simple on the surface, except the assistant remembers that just yesterday, I was at the Adidas store talking to a clerk about shoe fit via my bee.computer wearable, and I used my Ray-Ban Meta glasses to snap a few images of colors I liked.

While this use case is not quite there yet in the real world, I am personally using this technology now, and it’s just a matter of time until all the pieces are connected and the advertiser scenario I described will become real.

Then we’ll see the assistant pick up right where I left off, using multimodal memory to enrich the response with past conversations and visual preferences.

Neither of these interactions can be matched with traditional keyword-based targeting. The assistant’s memory and personalization turn every query into a unique moment.

For advertisers, it’s not just about what was typed; it’s about what the assistant knows.

This creates a richer opportunity for advertisers, but there is a challenge related to targeting because Google Ads was built for keyword advertising, not prompt advertising – and this creates a disconnect.

From Keywords To Prompts: Why The Old Model No Longer Fits

Google Ads was initially built around a simple idea: Match ads to user searches through keywords.

Advertisers bid on terms users might type into the search bar (like “running shoes” or “cheap flights”), and the system will serve relevant ads based on those inputs.

But AI Mode is changing the language of search. Instead of short, isolated keywords, users are starting to use full, conversational prompts that reflect how they naturally speak.

These prompts are often longer, more specific, and packed with nuance that the original ad system wasn’t designed to handle.

To keep things running, Google has introduced a behind-the-scenes workaround: “synthetic keywords.”

These are machine-generated representations that attempt to map modern prompts back into the keyword framework advertisers still rely on. It’s a clever patch, but ultimately a temporary one.

As prompts continue to evolve in complexity and variety, and as memory and personalization shape every query, the keyword as a stable targeting anchor is becoming harder to rely on.

That puts pressure on the entire ad ecosystem. The old model is still functioning, but it’s increasingly out of sync with how people search.

A new system, one built natively for prompts, context, and memory, will eventually need to take its place.

Rethinking Ads In AI Mode: What Comes After Clicks?

The shift toward AI-assisted browsing brings another major challenge: fewer clicks.

If users get what they need from the assistant itself, the need to visit websites diminishes, weakening the foundations of the cost-per-click (CPC) business model.

User engagement on ads when using copilot in search

Slide by Microsoft at Accelerate Roadshow LA, June 2025

But clicks will be more relevant because, unlike in the past, where a click was a user’s initial exploration of your offer, they will now be better informed and further along in their research by the time they visit your site for the first time.

Microsoft research found that purchasing behaviors increased by 53% within 30 minutes of a Copilot interaction, underscoring just how powerful, timely, and AI-embedded suggestions can be.

To stay relevant, ads must feel like part of the conversation. They can’t be disruptive or detached. They need to be embedded, responsive, and helpful, appearing when and where they make the most sense.

Newer performance data shows that ad engagement doubled in some formats when served through Copilot, especially in PMax-powered Shopping and Multimedia Ads.

Crucially, Microsoft has dialed back the volume of ad impressions in Copilot, choosing instead to show ads only when they’re predicted to be highly relevant and useful.

The result? Fewer, better-placed ads that drive stronger outcomes, a model that hints at where Google AI Mode could be headed.

Google has done this before. Its introduction of AdWords transformed ads from flashy banners into useful information. AI Mode demands a similar evolution, one that turns helpfulness into performance.

So, if the traditional way Google makes money becomes broken, let’s look at some options for how they might bridge the gap.

Conversion Inside The Conversation: The Rise Of Affiliate Models And Agents

The most frustrating part for consumers using AI agents to find something to buy is the final step after determining what they want.

Now, they need to hunt for where to buy it, enter a credit card, and deal with the usual minutiae of buying something online.

A better user experience, especially for smaller purchases, would be to tell the agent, “I like it, buy it!” and have the item arrive at your doorstep the next day.

While this zero-click scenario is the best user experience, it is also the most problematic in a CPC world.

This opens the door for reconsidering affiliate and commission-based advertising models. Instead of paying for attention, advertisers pay for action.

Ads become decision-making partners, not just traffic generators. It’s a better fit for how assistants work: focused, efficient, and user-first.

While this wouldn’t be Google’s first attempt at commission-based monetization (previous efforts, such as Buy on Google, Shopping Actions, and Google Express, ultimately shut down due to limited merchant adoption and weak consumer uptake), those models lacked the personalized context that AI Mode now enables.

Even vertical-specific experiments like commission bidding for Hotel Price Ads (retired in 2024) followed the same pattern: strong in theory, but missing the behavioral depth to sustain engagement.

With memory-driven prompts, real-time user needs, and multimodal signals in play, the conditions may finally be right for performance-based pricing to scale in a meaningful, consumer-aligned way.

Monetization Models: Why Subscriptions Aren’t The Future

Monetizing AI-powered search is a hot topic. Startups like Neeva by Sridhar Ramaswamy (Former Google Ads Chief) attempted to replace ads with subscriptions, but user adoption fell short.

Even OpenAI, with its paid ChatGPT Pro tier, sees a vast majority of users opting for free access.

The pattern is clear: Most users won’t pay for general-purpose search tools. Even companies leading in AI anticipate that advertising will remain the dominant revenue stream.

Google’s ad model, tested and refined for decades, is still the best-positioned approach – if it can evolve to match the new user behavior.

Ads In AI Mode

Google has already said it will have ads in AI mode.

To maximize the likelihood of your ads appearing in this environment, it’s advisable to utilize Google’s AI-centric tools, including AI Max in search campaigns, Performance Max, and Demand Gen.

Employing broad match keywords is also crucial, as they facilitate connections with conversational prompts rather than traditional keywords.

However, with the potential decrease in click-through rates, a pertinent question arises: Can fewer clicks on ads sustain the revenue model?

Despite this challenge, I anticipate that advertising will remain the primary revenue stream, even within AI Mode.

It’s noteworthy that OpenAI’s CEO, Sam Altman, has expressed reservations about incorporating ads into AI experiences.

In a conversation with Ben Thompson, Altman stated:

“Currently, I am more excited to figure out how we can charge people a lot of money for a really great automated software engineer or other kind of agent than I am making some number of dimes with an advertising-based model… I kinda just don’t like ads that much.”

Similarly, Google’s co-founders, Larry Page and Sergey Brin, initially opposed the idea of advertising on their search engine. In their 1998 research paper, “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” they wrote:

“We expect that advertising-funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers.”

Despite these initial reservations, both OpenAI and Google have recognized the practicalities of monetization. Google makes nearly 78% of its revenue from ads as of 2024, illustrating its evolution from the original stance of its founders.

So, while the methods and philosophies around advertising in AI experiences have evolved, the necessity for effective monetization strategies remains paramount.

Conclusion: Betting On AI-Powered Ad Innovation

Soon, helping consumers at the moment of relevance won’t be about search and keywords anymore; it’ll be about context, and AI-powered interactions driven by memory, intent, and dialogue.

The early signals are promising: Users respond better when ads are useful, not intrusive.

Microsoft’s experience with Copilot shows that when generative systems deliver fewer but more relevant ads, engagement and conversions rise.

Google’s opportunity is to take those lessons further, baking utility and timing into its AI-native monetization engine.

It’s not about building the flashiest assistant; it’s about earning trust at the moments that matter.

If the assistant can deliver value and drive outcomes without breaking the flow, that’s the model that wins.

I have no doubt that Google and other ad platforms will find ways to appropriately monetize these advertising opportunities, even if there will be fewer impressions for each consumer journey.

The fundamentals of advertising at the moment of relevance haven’t changed, but our tactics will need to evolve fast. Prompts, not keywords, are the new starting point – and that changes the game.

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Featured Image: Lana Sham/Shutterstock

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