When I discovered Google’s latest update to the Merchant Center, I was thrilled. They’ve added a ‘build to order’ option for vehicle listings, offering sellers like me a streamlined way to display customizable models that customers can factory-order.
I immediately saw how this attribute could revolutionize my listings. It’s designed for dealers who, like myself, don’t always have every model available on the lot. This addition allows us to tag vehicles that aren’t in stock but can be tailored and ordered. It’s a game-changer!
What needs to change. I’m aware that updating my listings involves two critical steps. First, I need to adjust my structured data by setting availability to BuildToOrder. Secondly, I must align my Merchant Center feed with the same availability code. Ensuring consistency is key to avoid listing disapprovals.
Instruction on when to use the availability [availability] attribute in GMC
Why we care. This update is a breath of fresh air for us sellers. Until now, conveying a vehicle’s unavailability for immediate pickup was challenging. Now, the ‘build to order’ option clearly mirrors the operations of modern automakers, especially those like Tesla and Rivian that offer direct-to-consumer customization. It helps set clear expectations for our customers and ensures our data is pristine for Google.
The fine print. Remember, if a vehicle is categorized as ‘build to order,’ it must have the condition attribute set to ‘new.’ If it’s listed as ‘used,’ it will be disapproved. Google regards build-to-order vehicles as newly configured, not pre-owned.
Bottom line. For anyone like me selling customizable or factory-order vehicles, this update is a more precise way to reflect vehicle availability. However, it only works if my feed, structured data, and condition fields are in synchronization.
I first learned about this update from Google Shopping specialist Emmanuel Flossie, who kindly explained how to implement it on his blog.
I’ve recently discovered an exciting development in Google Ads that’s set to revolutionize how we track and measure our advertising success. The platform is now testing a beta feature that allows us to link external data sources directly into the conversion action settings. This move aims to strengthen the bridge between our first-party data and campaign measurement.
How does this work, you might ask? In the conversion action details, a new section titled “Get deeper insights about your customers’ behavior to improve measurement” encourages us to connect our external databases to our Google tag, offering a seamless integration experience.
This integration supports platforms like BigQuery and MySQL, with the primary goal of enriching our conversion metrics and enhancing performance signals. Notably, this feature is highlighted within the data attribution settings and is gradually being rolled out in its Beta phase.
Why do we care? The ability to directly integrate these data sources reduces the hassle of syncing offline or backend data with ad measurements. This beta feature from Google Ads simplifies connecting first-party data to conversion tracking, improving our measurement accuracy and campaign optimization.
By harnessing the power of platforms like BigQuery or MySQL, we’re able to incorporate richer customer data into our signals, crucially offsetting any data loss resulting from recent privacy changes. In practical terms, this means smarter bidding, clearer attribution, and the potential for a stronger ROI.
Beneath the surface, embedding these data connections directly within conversion settings—rather than relying on separate pipelines—democratizes advanced measurement tactics, making them accessible not only to large enterprises but to advertisers like you and me.
As ad platforms compete for superior measurement accuracy, these native data integrations are emerging as a pivotal advantage, particularly for brands heavily investing in proprietary customer data.
I’ve noticed something quite unexpected happening with Google Ads lately. It seems that their system tool is re-enabling paused keywords automatically, which has led to increased campaign expenses without warning.
Some advertisers, including myself, have observed a Google Ads tool—created for low-activity bulk changes—unexpectedly switching paused keywords back to active. This unusual behavior has been a surprise to many account managers, like myself, who haven’t come across this issue before.
What’s happening? The activity logs are showing entries linked to Google’s ‘Low activity system bulk changes’ tool executing actions that enable previously paused keywords. These logs appear as automated bulk updates and, thankfully, have an ‘Undo’ option available.
In the past, this tool mainly paused inactive elements rather than reactivating them, so this change in behavior is quite perplexing.
What’s unclear? Google hasn’t issued any public documentation to explain this behavior, leaving us unsure whether it’s an intentional feature, a limited test, or a mere bug.
I find myself wondering what exactly triggers this reactivation and how widespread this phenomenon is becoming.
Why does this matter? If like me, you’re diligently managing your campaigns, unexpected keyword reactivation can change your campaign delivery in ways you didn’t plan for, impacting budgets, pacing, and overall performance—particularly if you’ve paused keywords for a specific reason.
For both agencies and in-house teams, this change is raising concerns about automated systems potentially overriding manual settings.
What steps should we take now? As account managers, we might want to regularly check change histories, be on the lookout for any unexpected keyword activations, and use the ‘undo’ function promptly if we notice unplanned changes.
Until Google clarifies the situation, more careful monitoring of campaigns relying heavily on paused keywords might be necessary.
First Alerted This issue was first brought to light by Performance Marketing Consultant Francesco Cifardi on LinkedIn.
Let me share a few valuable lessons I’ve learned about PPC advertising from seasoned experts. Even the most experienced among us encounter pitfalls—like hastily launching campaigns or leaving automation unchecked. Recently, I joined Greg Kohler from ServiceMaster Brands and Susan Yen from SearchLab Digital at SMX Next, where we candidly discussed the mistakes that catch us off guard.
Read on to discover the blunders that even the most seasoned marketers must navigate.
Never launch campaigns on a Friday
This is a well-known pitfall, yet it continues to happen. Susan Yen mentioned that due to client demands, campaigns often go live on Fridays, leading to weekend chaos if things go awry. A minor error like an inflated budget setting can cause significant issues.
Greg Kohler emphasizes the importance of reviewing setups with fresh eyes. Wait until Monday to launch; doing so may avert unnecessary problems. Even experts can become overconfident, only to be reminded of these lessons by a Friday crisis.
Takeaway: Avoid launching before the weekend or holidays and stand firm if clients push. It protects both your peace of mind and campaign performance.
Location targeting disasters
Greg shared an experience where an error in location targeting meant campaigns ran in the wrong timezone. By Saturday, ads intended for a U.S. audience accumulated thousands of views in Europe instead.
Takeaway: Configure location settings directly within the Google Ads interface to minimize risks and ensure precise targeting.
The search term report trap
Susan stressed that search term reports are essential for every campaign. Ignoring them can lead to wasted clicks and difficult client conversations later on. She advises checking these reports monthly to avoid irrelevant traffic.
Takeaway: Routine reviews help refine what to target or exclude, enhance performance, and maintain efficient account strategy.
Google Ads Editor vs. interface: A constant battle
The gap between the Google Ads Editor and the interface often leaves teams in a bind. Susan’s team preps in Excel before using Editor for bulk edits but prefers the interface to ensure accuracy in settings.
Takeaway: Use the interface for tasks requiring precision, like responsive ads or location targeting.
The automatically created assets problem
Automatically created assets often default to ‘on,’ requiring tedious navigation to disable. New types of assets can inadvertently apply to all campaigns.
Takeaway: Regularly review these settings. Set reminders to maintain control as new features roll out.
Importing campaigns from Google to Microsoft Ads
Yen warned of the pitfalls of importing Google campaigns directly into Microsoft Ads due to discrepancies in budget assumptions and automation settings.
Takeaway: Treat Microsoft Ads independently with a tailored strategy post-import for optimal results.
The App placement nightmare
A slip in excluding app audiences can direct spend to irrelevant categories. Yen advises vigilance, as settings to exclude these are often hidden.
Takeaway: Establish comprehensive exclusion lists to guard against inappropriate targeting.
Content exclusions and placement control
Applying content exclusions from the start helps avoid placement in irrelevant or inappropriate contexts, though manual follow-up remains necessary.
Takeaway: Consistent reviews ensure Google honors your settings, preventing unwelcome surprises.
Call tracking quality issues
Susan highlighted the importance of client communication in effectively tracking call quality, advocating for monthly check-ins focused on conversion metrics.
Kohler suggested distinguishing first-time from repeat callers in analytics to optimize automated bidding systems.
The promo date problem
Litner pointed out issues with scheduled assets appearing outside their promotional windows, urging manual checks to ensure proper timing.
Kohler echoed similar concerns with automated rules potentially misfiring.
Takeaway: Verify scheduled actions on their launch dates manually to prevent mishaps.
AI Max settings and control
The issues of AI-driven campaign settings defaulting to active require diligence in monitoring and fine-tuning each setting.
Takeaway: Despite AI advancements, practice consistent oversight to manage budget spend effectively.
Account-level settings that haunt you
Susan flagged the risk of overlooking critical account-level settings that can derail campaigns silently, suggesting a standardized checklist approach.
Takeaway: Establish and follow a thorough account setup checklist to catch any hidden conflicts with campaign goals.
Final wisdom
Here are several recurring themes from our discussion:
Always double-check automation; it’s not immune to errors.
New perspectives reveal potential errors.
Effective client communication prevents misunderstanding.
Manual reviews maintain balance as automation increases.
Keep updating exclusion lists to mitigate repeated issues.
The takeaway is that everyone makes mistakes. The difference lies not in avoiding them but in swiftly addressing them, learning from experiences, and creating systems to prevent recurrence. As Kohler notes, stay vigilant, question automation, and avoid the temptation of a Friday launch.
I recently discovered how crucial first-party data has become in the evolving landscape of AI-powered advertising. It’s fascinating to see how it shapes the optimization and measurement of automated ad campaigns.
During a chat with Search Engine Land, I learned from Julie Warneke, CEO of Found Search Marketing, about the profound impact first-party data has on profitable advertising, regardless of potential changes to Google’s third-party cookie policies.
Embracing first-party data means tapping into customer information that I own, typically stored in a CRM, like lead details, purchase history, revenue, and customer value collected from various touchpoints.
This type of data is distinct from platform-owned or browser-based data, over which I have limited control.
Digital advertising has evolved over the years. The shift from focusing on impressions and clicks to outcomes emphasizes profitable conversions, according to Warneke. Advertisers who provide AI systems with quality customer data gain a significant edge.
Although rising cost-per-clicks (CPCs) are inevitable in paid media, first-party data enhances conversion quality, revenue, and return on ad spend, making higher costs justifiable with better results.
By leveraging first-party data tied to revenue and customer value, AI bidding systems can target users resembling high-value customers, even beyond usual demographic or geographic signals, leading to better conversions.
Among campaign types, Performance Max (PMax) thrives with first-party data activation. It performs best when I shift from manual optimizations to feeding it accurate data, allowing the system to learn, as Warneke highlighted.
Even small and mid-sized businesses can leverage first-party data, as seen in Warneke’s examples of success with small customer lists. The challenge lies in setting up proper infrastructure for tracking, consent management, and data flow.
Common mistakes include weak data capture, where brands rely on browser-side tracking that falters on platforms like iOS, and broken feedback loops from sporadic CRM data uploads. Continuous data streams are crucial.
Warneke advises taking a step back to audit how data is captured, stored, and relayed to platforms. Incremental improvements can pave the way for significant long-term gains, even starting with a small portion of a budget as a test.
Ultimately, AI optimization reflects the quality of signals received. By refining first-party data, I can influence outcomes favorably, avoiding inefficiency risks.
When Google introduced Demand Gen campaigns in 2023, I saw them as a promising way to boost engagement across platforms like YouTube, Discover, and Gmail.
Initially, they felt experimental, straddling the line between awareness and performance, but they’ve come a long way since.
Now, the creative flexibility and enhanced audience control make Demand Gen a go-to campaign type for my ecommerce clients.
This strategy allows me to scale revenue in a controlled manner, maintaining brand consistency while testing creative approaches to drive conversions.
I’ve found that Demand Gen delivers the best results when strategically paired with Performance Max and Search campaigns.
Advertising with Demand Gen is ideal if you crave more control.
One major drawback of Performance Max is its lack of transparency and manual control.
If precise targeting, placement, or creative control is essential, Demand Gen stands out as the better option.
Performance Max auto-generates ads from your uploads, relying on Google’s AI to mix and match for the best performance.
This makes it crucial to provide top-notch creative assets.
For example, a fitness brand might create separate asset groups for products like leggings, shorts, and vests.
While this helps target relevant audiences, the control isn’t exhaustive.
However, Demand Gen offers far superior flexibility.
It allows me to upload, preview, and tweak ad combinations before launch, adapting each creative to its unique placement.
For instance, I can customize YouTube ads for in-feed, in-stream, and Shorts placements.
This control is perfect for ecommerce brands focusing on creative precision, message testing, and maintaining a strong visual identity.
Using Demand Gen alongside Performance Max can be incredibly effective if you leverage their roles within the customer journey. They enhance each other rather than compete.
Demand Gen builds awareness and sparks interest by reaching higher-funnel audiences before they actively start product searching.
Conversely, Performance Max focuses on converting lower-funnel users who are primed to purchase.
For example, a fitness retailer might utilize Demand Gen for lifestyle videos and discovery ads promoting their latest activewear.
When a potential customer begins to research or exhibit purchase intent, Performance Max engages with tailored Shopping and Search ads to finalize the sale.
I’ve set up feed-only Performance Max campaigns, providing only a product feed within the asset group.
This restricts Performance Max activities to Shopping placements, focusing it sharply on direct conversions.
Meanwhile, Demand Gen operates across platforms like YouTube, Gmail, Discover, and Shorts, covering the upper and mid-funnel with more visual, creative content focused on awareness.
This configuration minimizes overlap between campaign types while ensuring user engagement throughout the funnel, from brand discovery to purchase.
For larger accounts with flexible budgets, this dual structure drives holistic performance and clearer attribution.
In contrast, smaller accounts seeking efficiency should prioritize mastering high-intent campaigns before layering in Demand Gen once the core conversions are stable.
The diverse campaign types now offer advertisers more flexibility than ever, yet it requires understanding Google’s restructuring of video and discovery products.
It streamlines Google’s visual placements into one campaign type, including YouTube in-stream, Shorts, in-feed, Gmail, and Discover.
This change is significant. VAC was successful for ecommerce, particularly for conversion-centric video. Its removal underscores Google’s encouragement to embrace Demand Gen.
The advantage is that Demand Gen provides stronger creative control and diverse testing options across YouTube placements.
If you previously ran VAC campaigns, they are now under Demand Gen. Ensure your top-performing assets and audiences have migrated correctly, then use the new controls to optimize performance.
Audience control is a significant benefit of Demand Gen, and it’s a reason why I consistently use it for ecommerce.
Demand Gen allows precise audience creation, letting me decide who sees the ads.
I can select placements, merge audience types, and allocate the budget strategically.
It’s the only Google Ads campaign type supporting lookalike audiences, valuable for brands focused on acquiring quality leads.
While Performance Max utilizes audience signals over fixed targeting, Demand Gen excels for control, testing, and segmentation strategies.
In mid-2025, Google rolled out an open beta for advertisers to opt out of specific Demand Gen channels manually.
This means I can now control ad display, excluding Discover or YouTube Shorts if they don’t align with my objectives or creative format.
This small but significant update offers more control, a feature often lacking in many of Google’s automated campaign types.
In early 2025, Google introduced product feed integration for Demand Gen campaigns. This change allows me to link the Google Merchant Center feed, incorporating live product data directly into visual ads.
This development bridges performance and branding for ecommerce, enabling storytelling through creative visuals while displaying actual products.
For instance, a fashion retailer can showcase a new collection in a video advert while featuring shoppable product cards below.
This update positions Demand Gen as a hybrid between Shopping and Display, a much-anticipated capability among ecommerce advertisers.
Demand Gen typically demands a larger budget than other campaign types.
Google recommends starting at about £100 per day per campaign or 20 times your target CPA/tROAS, whichever is higher.
Practically, the £100-per-day baseline is a viable starting point for effective data collection and optimization. Lower budgets restrict data flow and slow progress.
Demand Gen complements your broader Google Ads strategy, rather than replacing Search or Performance Max.
It’s a premium, visually led campaign type that boosts awareness leading to conversions, particularly effective when you have accurate measurement, a clean product feed, and clearly defined audiences.
The table compares Demand Gen and Performance Max on key aspects that matter to advertisers.
Have you heard the news? Google has just launched the Universal Commerce Protocol (UCP), an innovative open standard that integrates AI agents throughout the entire shopping experience. From discovering products to making purchases and even receiving support after the sale, UCP facilitates it all.
In exciting developments for retailers, Google is also rolling out new AI tools. These include branded shopping agents and ad formats that enhance AI-driven discovery, making the shopping experience more streamlined and engaging.
About UCP
This protocol offers a common language for AI agents and commerce systems, greatly simplifying the need for custom integrations across different platforms.
UCP is compatible with existing standards like Agent2Agent and the Model Context Protocol.
The protocol was co-developed with prominent partners such as Shopify, Etsy, Wayfair, and Target.
It’s already endorsed by over 20 additional companies in the retail and payments sectors.
What’s Changing
The UCP is set to enhance the checkout experience for Google product listings via AI Mode in Search and the Gemini app. Shoppers can make purchases through Google Pay, with options to use saved payment and shipping details. Integration with PayPal is also on the horizon.
Google aims to lower cart abandonment and provide retailers with tailored integration options suited to their needs.
Upcoming features include loyalty rewards and personalized shopping experiences.
Business Agent
In tandem with UCP, Google is unveiling the Business Agent, a branded AI assistant that provides shoppers with direct interaction opportunities on Search. Think of it as a virtual sales associate offering real-time responses in your brand’s own tone.
Major retailers like Lowe’s, Michael’s, Poshmark, and Reebok are already on board. Future capabilities may include deeper customization, data training, and a seamless agent-led checkout.
Direct Offer
Google is also testing Direct Offers, a fresh initiative within Google Ads tailored for AI adoption. When AI senses that a shopper is likely to make a purchase, a special discount can be presented.
This pilot will soon expand to incorporate offers such as product bundles, complimentary shipping, and more enticing incentives.
Why It Matters
The rise of agent-led shopping reshapes where and how buying choices are made. Google’s new AI tools and protocols are taking the lead, allowing advertisers to influence these pivotal moments during an AI-driven shopping journey.
Tools like Direct Offers and branded agents create new pathways for advertisers to finalize sales efficiently, all while safeguarding profit margins. The balance between conversion improvements and losses in direct site traffic remains an open discussion.
Bottom Line
According to Google, agentic shopping is unstoppable. With innovations like UCP and its complementary retail tools, Google ensures that AI-driven commerce remains inclusive and accessible, keeping retailers engaged as agents transform the buying landscape.
Operating in niche markets with Google Ads presents unique challenges, and it’s something I’m navigating in 2026. While the search volume might be low, the potential for opportunity is significant.
I’ve noticed that in targeted markets, people might only search a handful of times each month for my solutions. It’s a stark contrast to other advertisers who can test a plethora of headline variations with ease.
Many niche advertisers mistakenly apply high-volume strategies to their ads. In my experience, without sufficient data, Google’s automation struggles, which can dampen or entirely stall results.
Through this guide, I’ve found out what actually works when dealing with low search volumes and extended conversion timelines.
Why Low-Volume Markets Challenge Google Ads
There are a couple of scenarios I’ve encountered:
I own my brand space: My distinctive brand ensures that when people search for my company, I appear prominently with unique industry terms.
I get washed out: Sometimes, my keywords compete with those of larger brands, making it tough to stand out. Here, I battle consistent keyword pollution.
Each situation requires a distinct approach to effectively manage my advertising strategies.
Smart Bidding strategies, like Target ROAS, require substantial conversions that niche environments often don’t produce solely from search traffic.
If my campaigns do hit those numbers, it’s usually due to a budget burn collecting low-quality data. It’s unsustainable for many, including myself.
However, I’ve found that automation remains viable by feeding Google the right signals differently.
Relying solely on Search campaigns has proven ineffective for me, especially as Google’s AI Overviews account for a significant percentage of queries.
Start with Search, then Move to Performance Max
Performance Max requires solid conversion data, focusing on qualified leads or paying customers to truly optimize results.
Audience signals guide me in allocating budgets wisely, ensuring I’m not wasting resources.
Performance Max has served me well once I’ve accumulated sufficient data. However, dealing with keyword pollution requires aggressive negative tactics.
Use Demand Gen for Awareness
Introducing Demand Gen has allowed me to reach users across YouTube and Gmail before they actively engage in search for my offerings.
This strategy builds awareness, paving the way for future branded searches.
Protect Your Brand Terms
While organic rankings are important, I maintain a dedicated budget to safeguard my brand’s terms, especially when keywords overlap with the competition.
Even during slower periods, maintaining control over brand terms remains a priority.
Based on my data from a niche B2B SaaS client, exact match keywords consistently deliver leads at a lower cost, showcasing the benefits of targeted campaigns.
Adopting a broad match approach without sufficient data may lead to unnecessary spending on low-converting searches.
After solidifying my match strategies, I start tight and carefully expand:
Initiate with exact match keywords on strong intent terms.
Incorporate phrase matches for variation while being wary of broad match until robust data guides me.
Broaden match scope after accumulating 30+ conversions.
Critical Search Term Mining
With niche volumes, Google may not always show which search terms directed traffic, but when available, these insights are invaluable for market comprehension.
The terms that do surface offer significant insights:
Valid searches leading to clicks but not conversions (adjust bids or landing pages).
Wasteful, irrelevant searches depleting budget (add instantly as negatives).
Incorporating new keyword variations identified.
Handling early funnel searches strategically.
In scenarios where brand terms are unique, I find broad match approaches more forgiving.
Conversely, with competitive keywords, a robust list of negative keywords is imperative before considering broader matches.
Full Utilization of Headline and Description Slots
With limited ad runs, maximizing headline and description slots provides ample opportunity for optimization and engagement.
Targeted Landing Page Design
Landing pages I design don’t just capture leads; they guide prospects through seamless self-qualification, emphasizing detailed specs or clear differentiation as necessary.
My pages prioritize standing out, expecting that visitors have explored competitor offerings.
Precision in demand gen campaigns is necessary, targeting custom market segments instead of industry-wide interests.
Immediate differentiation is crucial on landing pages, so prospects understand value quicker than with competing alternatives.
Strategies for Niche Advertising Success in 2026
In 2026, small budget advertisers win not by spending, but by leveraging quality signals, focusing on visibility and precision.
My focus remains on signal quality surpassing search volume expectations.
Visibility across multiple platforms ensures stronger engagement than singular strategies.
Precise audience targeting outweighs the advantages of simply broader reach.
Feeding Google automation with strategic, tailored data is essential to unlocking potential in niche advertising.
The key to success in niche markets is knowing which automation to implement at the right time, the patience to accumulate sufficient data, and the foresight to disregard outdated strategies.
Google Ads has introduced exciting updates to its Creator Partnerships, making it easier for me to manage collaborations with YouTube talents on a larger scale.
With the introduction of Creator Search, I can now effortlessly find YouTube creators by utilizing keywords or channel handles. This tool allows me to refine my search based on subscriber count, average views, location, and their availability for contact. It’s a game-changer, significantly cutting down the manual work involved in discovering and reaching out to creators.
In addition to the search feature, Google has unveiled a new Management section. This centralizes all communications with creators, allowing me to view their names, the status of inquiries, subjects, the latest updates, and scheduled response dates—all in one place with the convenience of direct email access.
Why this matters to me. As creator-led campaigns become a core aspect of media strategies, having better tools to identify the right collaborators and maintain organized partnerships is crucial. The latest enhancements to Google Ads’ Creator Partnerships (beta) cater to these needs perfectly.
First sightings. This update made headlines when Google Ads Specialist Thomas Eccel shared it on LinkedIn, making industry professionals eager to explore its capabilities.
The big picture. These upgrades are pushing Creator Partnerships closer to a comprehensive workflow tool, aiding teams like mine to manage creator collaborations with the same efficiency and accountability that we apply to other paid media endeavors.
Bottom line. By enhancing both discovery and organization, Google’s updates to Creator Partnerships empower me to execute creator campaigns at scale with ease.
This past year, PPC has been anything but static – it has evolved. As I explored the insights from 2025, I found these articles resonated deeply. They addressed crucial questions like maintaining a competitive edge, eliminating wasteful spending, collaborating with automation, and gearing up for the future.
Join me as I take you through the links to the top 10 most-read PPC columns on Search Engine Land from 2025, crafted by our incredible experts.
Though it might seem challenging, even the smallest businesses can carve out their niche and captivate customers. Discover the strategies that make this possible. (By Sophie Logan. Published Sept. 16.)
Update your optimization techniques for 2025 with innovative approaches to keywords, Performance Max, and audience targeting. (By Pauline Jakober. Published Feb. 6.)
With increasing CPCs, understanding the pace of this inflation and comparing it to the consumer price index is essential for shaping your ad strategies. (By Mark Meyerson. Published April 16.)
AI is bridging the gap between organic and paid search. Learn how integrating SEO and PPC can enhance your visibility and brand presence. (By Jen Cornwell. Published Oct. 6.)
PPC scripts have limitations, but with vibe coding, you can remove obstacles and transform complex seasonal data into practical planning tools. (By Frederick Vallaeys. Published Aug. 21.)
Streamline your ad creation process without losing your core message. Leveraging generative AI can help craft engaging, personalized copy that truly connects. (By Jason Tabeling. Published Aug. 1.)
Discover filtering techniques that refine targeting, reduce unnecessary clicks, and reveal new keyword opportunities. (By Menachem Ani. Published July 22.)
Enhance your campaign management with Google Ads scripts. Uncover insights, actionable tips, and use cases for leveraging automation to improve performance. (By Frederick Vallaeys. Published Jan. 9.)
As clicks become scarcer, maintaining visibility requires precise targeting and value-based bidding. Achieving this ensures your prominence in both paid and organic searches. (By Sarah Stemen. Published Oct. 7.)
With Google’s environment becoming more automated, some PPC tactics are now obsolete. Discover what to eliminate and what to focus on for the coming year. (By Sarah Vlietstra. Published Nov. 4.)
