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Web Design and Development San Diego

Google Ads API update cracks open Performance Max by channel

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Is your account ready for Google AI Max? A pre-test checklist

As part of the v23 Ads API launch, Performance Max campaigns can now be reported by channel, including Search, YouTube, Display, Discover, Gmail, Maps, and Search Partners. Previously, performance data was largely grouped into a single mixed category.

The change under the hood. Earlier API versions typically returned a MIXED value for the ad_network_type segment in Performance Max campaigns. With v23, those responses now break out into specific channel enums — a meaningful shift for reporting and optimization.

Why we care. Google Ads API v23 doesn’t just add features — it changes how advertisers understand Performance Max. The update introduces channel-level reporting, giving marketers long-requested visibility into where PMax ads actually run.

How advertisers can use it. Channel-level data is available at the campaign, asset group, and asset level, allowing teams to see how individual creatives perform across Google properties. When combined with v22 segments like ad_using_video and ad_using_product_data, advertisers can isolate results such as video performance on YouTube or Shopping ads on Search.

For developers. Upgrading to v23 will surface more detailed reporting than before. Reporting systems that relied on the legacy MIXED value will need to be updated to handle the new channel enums.

What to watch:

  • Channel data is only available for dates starting June 1, 2025.
  • Asset group–level channel reporting remains API-only and won’t appear in the Google Ads UI.

Bottom line. The latest Google Ads API release quietly delivers one of the biggest Performance Max updates yet — turning a black-box campaign type into something advertisers can finally analyze by channel.

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Web Design and Development San Diego

How to build a modern Google Ads targeting strategy like a pro

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Search marketing is still as powerful as ever. Google recently surpassed $100 billion in ad revenue in a single quarter, with more than half coming from search. But search alone can no longer deliver the same results most businesses expect.

As Google Ads Coach Jyll Saskin Gales showed at SMX Next, real performance now comes from going beyond traditional search and using it to strengthen a broader PPC strategy.

The challenge with traditional Search Marketing

As search marketers, we’re great at reaching people who are actively searching for what we sell. But we often miss people who fit our ideal audience and aren’t searching yet.

The real opportunity sits at the intersection of intent and audience fit.

Take the search [vacation packages]. That query could come from a family with young kids, a honeymooning couple, or a group of retirees. The keyword is the same, but each audience needs a different message and a different offer.

Understanding targeting capabilities in Google Ads

There are two main types of targeting:

  • Content targeting shows ads in specific places.
  • Audience targeting shows ads to specific types of people.

For example, targeting [flights to Paris] is content targeting. Targeting people who are “in-market for trips to Paris” is audience targeting. Google builds in-market audiences by analyzing behavior across multiple signals, including searches, browsing activity, and location.

The three types of content targeting

  • Keyword targeting: Reach people when they search on Google, including through dynamic ad groups and Performance Max.
  • Topic targeting: Show ads alongside content related to specific topics in display and video campaigns.
  • Placement targeting: Put ads on specific websites, apps, YouTube channels, or videos where your ideal customers already spend time.

The four types of audience targeting

  • Google’s data: Prebuilt segments include detailed demographics (such as parents of toddlers vs. teens), affinity segments (interests like vegetarianism), in-market segments (people actively researching purchases), and life events (graduating or retiring). Any advertiser can use these across most campaign types.
  • Your data: Target website visitors, app users, people who engaged with your Google content (YouTube viewers or search clickers), and customer lists through Customer Match. Note that remarketing is restricted for sensitive interest categories.
  • Custom segments: Turn content targeting into audience targeting by building segments based on what people search for, their interests, and the websites or apps they use. These go by different names depending on campaign type—“custom segments” in most campaigns and “custom search terms” in video campaigns.
  • Automated targeting: This includes optimized targeting (finding people similar to your converters), audience expansion in video campaigns, audience signals and search themes in Performance Max, and lookalike segments that model new users from your seed lists.

Building your targeting strategy

To build a modern targeting strategy, you need to answer two questions:

  • How can I sell my offer with Google Ads?
  • How can I reach a specific kind of person with Google Ads?

For example, to reach Google Ads practitioners for lead gen software, you could build custom segments that target people who use the Google Ads app, visit industry sites like searchengineland.com, or search for Google Ads–specific terms such as “Performance Max” or “Smart Bidding.”

You can also layer in content targeting, like YouTube placements on industry educator channels and topic targeting around search marketing.

Strategies for sensitive interest categories

If you work in a restricted category such as legal or healthcare and can’t use custom segments or remarketing, use non-linear targeting. Ignore the offer and focus on the audience. Choose any Google data audience with potential overlap, even if it’s imperfect, and let your creative do the filtering.

Use industry-specific jargon, abbreviations, and imagery that only your target audience will recognize and value. Everyone else will scroll past.

Remember: High CPCs aren’t the enemy

Low-quality traffic is the real problem. You’re better off paying $10 per click with a 10% conversion rate than $1 per click with a 0.02% conversion rate.

When evaluating targeting strategies, focus on conversion rate and cost per acquisition, not just cost per click.

Search alone can’t deliver the results you’re used to

By expanding beyond traditional search keywords and using content and audience targeting, you can reach the right people and keep driving strong results.

Watch: How to build a modern targeting strategy like a pro + Live Q&A

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AI-Powered Functionality in Google’s SEO Tools

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Google’s been quietly upgrading Search Console and Analytics with AI. No fanfare. Just better data filtering. They sit quietly inside platforms you already use, like Search Console and Google Analytics, and they change how data is surfaced, filtered, and interpreted.

These updates don’t power AI Overviews or conversational search. They work behind the scenes in platforms you already use. Google is using AI to reduce manual analysis, surface issues faster, and help marketers understand complex datasets without exporting everything to spreadsheets.

Indexing patterns and performance trends are easier to spot, even if the underlying work still requires human judgment. Google’s automating the diagnostics. You still handle the strategy.

Key Takeaways

  • Google’s embedding AI into Search Console and Analytics 4 to cut down on manual data analysis. The AI handles filtering and pattern detection—you still make the decisions.
  • AI-powered features focus on filtering, pattern detection, and prioritization rather than execution.
  • Google Search Console AI helps surface performance insights faster.
  • Google Analytics 4 uses AI for anomaly detection, predictive metrics, and guided analysis.
  • Predictive metrics in GA4 (like churn probability) give you directional guidance, not guarantees. Use them to build hypotheses, not to replace analysis.

Why Google Is Embedding AI in SEO Tools

Google’s SEO tools have always produced more data than most teams can realistically analyze. As sites grow, so do performance reports and behavioral metrics. AI helps Google address that scale problem.

AI-Powered configuration in Google Analytics.

The main shift is from reactive analysis to proactive surfacing of insights. Instead of expecting marketers to manually filter reports, compare date ranges, and segment data, Google is using AI to highlight patterns and outliers automatically.

Search Console now groups issues more intelligently, with clearer prioritization, and more context around what matters. Analytics delivers automated insights, anomaly detection, and predictive metrics.

An example of Search Console grouping with AI.

The most practical benefit is time savings. AI-powered filtering lets you type what you want to see instead of clicking through multiple dropdowns. You can ask for specific trends, segments, or anomalies and let the system do the slicing for you. That alone removes a lot of friction from daily SEO work.

Your SEO expertise still matters. AI just handles the mechanical steps that used to slow you down. Google’s goal is to help marketers spend less time finding the signal and more time deciding what to do with it. For teams managing complex sites, this automation is table stakes.

If you want to understand how AI fits into broader SEO workflows, check out our guide on AI SEO.

AI Features in Google Search Console

Google Search Console has gradually introduced AI-assisted functionality that focuses on diagnostics and data interpretation rather than automation.

As a start, Search Console’s performance reporting benefits from smarter analysis. The platform highlights notable changes in clicks, impressions, and rankings without requiring manual comparison. This helps teams catch traffic drops or unexpected gains earlier, before they become larger problems.

Conversational-style filtering saves even more time. Instead of manually applying multiple filters, marketers can describe what they want to see, and Search Console narrows the data automatically. This reduces the time spent digging through reports just to answer basic questions.

Here’s how it works in practice: Instead of clicking Performance > Filters > Query > Contains > ‘product name’ > Apply, you type ‘show me queries for product pages with declining CTR.’ The AI interprets your request, applies the right filters, and shows you the data. That’s the time savings—going from five clicks to one typed question.

An AI query workflow.

Note: Conversational filtering is rolling out gradually and may not be available in all Search Console accounts yet.”

AI won’t fix your indexing issues or update your site. It finds problems faster so you can fix them yourself. The value comes from speed and clarity, not automation. For SEO teams, this shortens the path between detection and action without removing human oversight.

AI Features in Google Analytics 4

This is partly because GA4 handles more complex event-based data and cross-device behavior.

Analytics Advisor is the most visible AI feature. Currently in Beta and not available for everyone yet, It automatically flags unusual patterns, such as sudden traffic spikes, drops, or changes in engagement. These insights appear without manual configuration and are designed to draw attention to potential issues or opportunities.

Analytics Advisor in GA4.

Source

To access Analytics Advisor, click the lightbulb icon in the top right corner of any GA4 property. The insights refresh daily and highlight metrics that deviate from your baseline. You might see ‘Pageviews from organic search increased 47% compared to last week’ with a link to explore the affected pages. That’s faster than manually comparing week-over-week reports.

Predictive metrics add another layer. Examples include purchase probability, churn probability, and revenue prediction for eligible properties. These metrics help teams forecast outcomes based on historical behavior rather than relying purely on past performance.

Predictive metrics in GA4.

Predictive metrics require at least 1,000 positive and 1,000 negative examples of the target event over 28 days. If your site doesn’t meet that threshold, you won’t see predictions for purchase probability or churn. This makes the feature more useful for high-traffic e-commerce sites than small content publishers.

Another important use of AI in GA4 is automated anomaly detection. The platform monitors metrics continuously and alerts users when behavior deviates from expected patterns. This can surface tracking issues, campaign impacts, or site problems more quickly than manual review.

GA4’s AI points you toward what matters. You still handle the investigation. Teams still need to validate data quality, understand context, and decide how insights should influence strategy.

Other Google Tools Getting Smarter With AI

Beyond Search Console and GA4, other Google tools now have AI-supported features. Several other Google tools marketers use regularly now rely on machine learning to guide decisions and reduce manual work.

Google Analytics 4’s predictive metrics extend beyond reporting. They influence how audiences are built and activated, especially when connected to Google Ads. This allows marketers to target users based on likely future behavior rather than past actions alone.

Google Ads leans on machine learning to suggest budget shifts, adjust bids automatically, and test creative variations. You can accept or reject these suggestions, the control stays with you. These systems focus on optimization suggestions rather than forced changes, leaving final control with advertisers.

Here’s what matters: diagnostic AI explains what’s happening now. Predictive AI estimates what comes next. Diagnostic AI explains what is happening now and why. Predictive AI estimates what might happen next. Both influence how marketers act, but they serve different purposes. Understanding which type of insight a tool provides helps teams decide how much weight to give its recommendations.

This changes your daily workflow. Instead of checking reports manually and looking for problems, you respond to flagged issues. Instead of building audience segments from scratch, you refine AI-generated segments. The shift is from ‘find the problem’ to ‘validate the finding.’ That’s faster, but it requires trust in the system’s baseline accuracy.

Should You Trust AI to Support Your Reporting?

Google’s using AI to decide what you see first in your reports. That raises control questions. These tools influence what you see first, what gets flagged, and what feels urgent.

Trust the insights. Verify the recommendations. AI supports reporting by prioritizing information, not by defining truth. Understanding its role helps teams use it effectively without losing oversight.

Is AI Taking Too Much Control?

One concern is that AI-driven data points could push marketers into autopilot mode. When tools highlight issues automatically, it’s tempting to assume they reflect the full picture.

AI helps you see more. It surfaces technical problems and data anomalies that teams often miss because they’re buried in reports or obscured by volume. AI helps surface data anomalies that teams might miss due to scale or limited time. It reduces the chance that important issues stay hidden in reports.

Don’t follow every data point blindly. AI recommendations are based on models and thresholds that may not reflect business context. Treat insights as starting points, not final answers. Validation still matters.

Who Really Gets the Advantage?

People assume big brands with more data get better AI insights. Not true. Everyone has access to the same tools.

The advantage goes to teams that actually use the insights. A local contractor who spots a data anomaly flagged by Search Console and acts on it outranks a national franchise that ignores the same alert.

AI lowers the barrier to analysis, but it doesn’t guarantee better outcomes. Interpretation and execution still determine results.

FAQs

Does AI in GA4 replace manual analysis?

No. AI highlights anomalies and predictions, but analysts still need to validate findings and decide how to act.

Are predictive metrics in GA4 always accurate?

Predictive metrics are estimates based on historical data. They provide directional guidance, not certainty.

Conclusion

AI makes Google’s SEO tools more efficient. It doesn’t replace the need for strategy. You still need to validate insights, understand your business context, and decide how to act on recommendations. The teams winning with these tools treat AI as an assistant, not an autopilot. 

They use automated insights to find problems faster, then apply their own expertise to fix them. That combination (AI-powered detection plus human strategy) is what drives results. Start by exploring the AI features already available in your Search Console and GA4 accounts. Check what Analytics Advisor has flagged. Look at how Search Console groups your indexing issues. 

See if the insights align with what you’re already tracking manually. Then decide where automation saves you real time. 

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Recap: The January 2026 SEO Update by Yoast

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The January 2026 SEO Update by Yoast is part of our monthly webinar series covering the latest developments in search and AI. In each session, we review the most important news from the past month and explore what it means for your search strategy. Hosted by Carolyn Shelby and Alex Moss, this month’s update looks at key industry shifts and practical takeaways for staying competitive. Below is a recap of the topics discussed and what they mean for your strategy.

Here’s the recap video on YouTube

Watch the full recap on YouTube to hear Carolyn and Alex dive deeper into these topics, answer audience questions, and provide additional examples of how these changes could affect your work.

SEO and AI news from January 2026

SEO is shifting from rankings to selection

Microsoft’s recent guide on AEO (Agentic Engine Optimization) and GEO (Generative Engine Optimization) highlights a major change: the goal isn’t just to rank, but to be chosen by AI and users. Tools like Gemini and ChatGPT don’t just match keywords; they evaluate brand authority, structured data, and real-world mentions. If your content isn’t clear, well-organized, or trustworthy, AI may overlook it, even if it performs well in traditional search. To stay competitive, focus on structured data, fast-loading pages, and strong brand signals.

Agentic commerce is on the rise

Google’s Universal Commerce Protocol (UCP) is an open-source framework designed to help AI handle purchases. This means AI won’t just recommend products, but could also buy them for users. For businesses, optimizing for AI “selection” is now as important as ranking. If you sell products, prioritize product schema, fast load times, and a strong brand presence to ensure AI picks you.

Google’s core updates continue to reshape publishing

The December 2025 core update hit news publishers hard, particularly those relying on prediction-based content (like “2026 Oscar predictions”). Google is favoring original, authoritative reporting over speculative or AI-generated content. If you’re in publishing, EEAT (Experience, Expertise, Authoritativeness, Trustworthiness) remains critical.

YouTube is a growing force in AI search

Gemini is now pulling YouTube videos into its responses, even for non-video queries. If you’re not repurposing content for YouTube, you’re missing an opportunity. Optimize video titles, descriptions, and transcripts so AI can find and cite your work.

New tools are changing how we work

Anthropic’s Claude CoWork can organize files and automate tasks, while open-source tools like Moltbot (formerly Clawdbot) let you run AI agents locally. These tools aren’t just novelties, but signs of how quickly AI is integrating into workflows. For SEO, staying adaptable and testing new tools will be key.

Yoast is helping AI work for everyone

Yoast is building on Microsoft’s NLWeb framework to help AI systems better understand web content. The goal is to ensure small publishers and businesses aren’t left behind as AI-driven discovery grows. If you’re using WordPress, Yoast SEO’s existing tools—like schema markup and readability checks—already support this effort. We’ve also added Gemini and Perplexity to our AI Brand Insights tool, so you can track how AI models perceive your brand.

What to focus on in 2026

  • Structure your content so AI can parse it easily (schema markup helps)
  • Build brand authority across channels—social media, PR, email, and YouTube all send signals AI notices
  • Understand agentic commerce if you sell products. Fast, well-structured pages will help AI “select” you
  • Avoid AI-generated slop. AI can help draft content, but human insight and expertise are irreplaceable

Sign up for the next SEO Update by Yoast

The next SEO Update by Yoast is on February 24, 2026, at 4 PM CET (10 AM EST). Sign up to join the live discussion or get the recording. Don’t miss it!

The post Recap: The January 2026 SEO Update by Yoast appeared first on Yoast.

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New to Yoast SEO for Shopify: Enhanced pricing visibility in product schema 

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We are excited to announce an update to our Offer schema within Yoast SEO for Shopify. This update introduces a more robust way to communicate pricing to search engines, specifically introducing sale price strikethroughs. 

What’s new? 

Previously, communicating a “sale” was often limited to showing a single price. With this update, we’ve refined how our schema handles the Offer object. You can now clearly define: 

  • The original price: The “base” price before any discounts. 
  • The sale price: The current active price the customer pays. 

Why this matters 

When search engines understand the relationship between your original and sale prices, they can better represent your deals in search results. This update is designed to help trigger those eye-catching strikethrough price treatments in Google Shopping and organic snippets, improving your click-through rate by visually highlighting the value you’re offering. 

organic search results for cable knit hat, demonstrating how the strikethrough features look from the searcher perspective
Organic search results for ‘cable knit hat’ showing how the structured data appears on Google.

How to use it 

The schema automatically bridges the gap between your product data and the structured data output. Simply ensure your product’s “Regular Price” and “Sale Price” are populated, and our updated schema handles the rest. For more information about the structured data included with all our products, check out our structured data feature page.

Get started

If you are a Yoast SEO for Shopify customer, you can access your product schema by opening a product in the Yoast product editor in your Shopify store. If you are not a customer and want to learn more, you can start a 14 day free trial of Yoast SEO for Shopify from the Shopify App Store.

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Discord as an Engagement and Digital PR Platform

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Discord has moved far beyond its gaming roots. Today, it’s becoming a direct access channel for brands that care about real engagement and meaningful digital PR outcomes.

This isn’t a Discord 101 guide. Most marketers already understand what the platform is and how servers work. Most marketers don’t know how to use Discord for engagement and PR, even as email pitches fail and social algorithms tank reach.

Discord matters now because it removes friction. Brands get real-time access to fans, creators, journalists, and niche communities without algorithmic interference. Over 200 million people use Discord monthly, and brands from Shopify to The New York Times now run active servers. Conversations happen in the open, persist over time, and create context that traditional channels struggle to replicate.

Brands can show up consistently in spaces people actually want to join. That changes how relationships form and stories emerge.

In this article, we’ll break down how marketers and PR teams can use Discord to drive engagement, support press outreach, host event-style campaigns, and turn community activity into earned media.

Key Takeaways

  • Discord works best as a relationship channel, not a broadcast platform. Engagement comes from participation, not posting frequency.
  • PR teams can use Discord to build trust and shared context before any formal outreach happens.
  • Features like roles, private channels, and stages support controlled access for media and creators.
  • Event-driven engagement inside Discord often creates moments journalists and creators want to reference.
  • Earned media from Discord grows out of visible conversation, not promotional messaging.
  • Most brands fail on Discord by broadcasting instead of conversing. The platform rewards brands that facilitate discussion, respond quickly, and give members real access to decision-makers.

Why Discord Is More Than Just a Community Platform

Discord gets grouped with other community tools, but that undersells what it actually does.

Discord is an owned communication layer. Members opt in. Conversations persist. There’s no feed to fight and no algorithm deciding who sees what. Engagement teams tired of declining social reach find that valuable.

The Discord interface.

Source

The platform has also expanded into professional and brand-led use cases. B2B companies, SaaS platforms, media brands, and creator-led businesses now use Discord to host product discussions, feedback loops, and industry conversations. These servers often function as always-on focus groups where insight flows both directions.

Shopify hosts channels for developers and partners. Notion uses Discord for product feedback and feature requests. These aren’t gaming communities—they’re professional spaces where brands get direct access to customers, partners, and media without paying for ads or fighting algorithms.

For PR teams, Discord introduces something email can’t replicate: visible context. Journalists and creators don’t just receive a message. They see how a brand responds to questions, explains decisions, and engages with its community over time.

A tech journalist following a SaaS brand’s Discord sees how they handle bug reports, communicate delays, and support users. That context makes it easier to cover the company fairly when news breaks. Email alone can’t build that kind of ongoing visibility.

The Adobe Photoshop discord interface.

That ongoing presence builds familiarity before coverage is ever discussed. Discord blends access, continuity, and transparency into a single environment, which sets the foundation for both engagement and digital PR.

Core Features That Make Discord Ideal for Engagement and PR

Discord’s strength is ongoing conversation, not one-way distribution. That distinction changes how engagement and digital PR teams plan campaigns.

Chat channels stick around. Conversations don’t disappear after a day or get buried by new posts. Conversations don’t disappear after a day or get buried by new posts. A strong AMA thread, product debate, or media Q&A can remain active and searchable for weeks, giving journalists and creators extended context without repeated outreach.

Roles and access control make Discord viable for PR use cases. Teams can create press-only channels, creator lounges, or embargoed spaces tied to launches. Access feels intentional rather than promotional, which increases participation and trust.

Here’s how that works in practice: You can create a #press-only channel where journalists see embargoed announcements, background context, and Q&A access before public launches. A #creators channel might include early product access, collaboration opportunities, and direct messaging with your team. Fans see neither of these spaces—they get their own channels focused on community discussion and support. That segmentation makes Discord feel exclusive and valuable to each group.

Editing roles on Discord.

Events, stages, and AMAs introduce timed engagement bursts. Moderated formats work well for leadership conversations, briefings, and launches. These events concentrate attention while still allowing real interaction.

Stages support up to 1,000 listeners with interactive Q&A. That’s enough for most brand events without requiring webinar software or event platforms. The recording stays in the channel afterward, so people who missed the live session can still participate in the discussion.

Integrations extend Discord’s usefulness. Feedback tools, shared resource hubs, and workflow automations connect Discord activity to broader marketing and PR efforts. Instead of living in a silo, Discord becomes part of day-to-day operations.

The key advantage is flexibility. Discord lets teams design micro-environments around how people actually communicate.

Using Discord to Build Journalist and Creator Relationships

Most PR teams still rely on cold email, despite falling response rates. Journalists and creators increasingly prefer communication that feels conversational and contextual rather than transactional.

Discord makes non-pitch engagement possible. Skip the ask. Invite journalists and creators into private or semi-private channels first. These spaces offer early context, background discussion, or access to subject-matter experts without pressure.

Buffer runs a Discord server where journalists can ask the CEO or product team questions directly. No PR gatekeepers. No scheduling calls. Just post a question in the #media channel and get a response within hours. That accessibility makes Buffer easier to cover than competitors who require formal interview requests and two-week lead times.

Buffer's Discord Server.

Direct access to decision-makers changes expectations. Journalists can ask follow-up questions, clarify details, or observe how a brand thinks before deciding whether a story fits. Creators can explore ideas collaboratively rather than responding to a single brief.

Here’s a simple journalist outreach flow:

  1. Create a private #press channel with embargoed access
  2. Invite 10-15 journalists who cover your industry (not thousands)
  3. Share early context on product launches, company updates, or industry insights
  4. Let them ask follow-up questions async
  5. When a story fits, the relationship already exists

Over time, transparency and responsiveness in chat build trust faster than long email threads. When a pitch does make sense, the relationship already exists.

This approach works particularly well for tech, SaaS, and creator-driven industries where speed, access, and nuance influence coverage decisions.

This approach doesn’t work for every brand. Mass consumer brands or highly regulated industries might struggle with open-channel discussions. But for companies selling to creators, developers, or digital professionals, Discord shortens the relationship-building cycle from months to weeks.

Event-Based Engagement: How to Use Discord for Launches, AMAs, and More

Smart brands treat Discord like a live venue, not a static community.

Product launches often include countdown channels, staged reveals, and post-drop discussion. Leadership teams host AMAs. Engineers, designers, and product managers run Q&A sessions that surface both feedback and insight.

Source

Good events take prep work.. Clear goals, advance question collection, and active moderation improve outcomes and keep discussions focused.

Effective Discord events typically include:

  • Before the event:
    • Announce 3-5 days early with clear agenda
    • Create dedicated event channel
    • Collect questions in advance via Google Form or channel thread
    • Assign at least 2 moderators
    • Test Stage or voice channel setup
  • During the event:
    • Pin the event agenda
    • Start with 3-5 pre-submitted questions to build momentum
    • Let mods filter and prioritize live questions
    • Keep responses under 3 minutes each
    • Screenshot strong quotes for later use
  • After the event:
    • Post a recap with key quotes, decisions, or takeaways
    • Thank participants by name
    • Share recap as blog post or social content
    • Leave the channel open for continued discussion

Most effective Discord events run 45-60 minutes. Longer sessions lose energy. Shorter sessions feel rushed. Plan for 10-12 questions max, with flexibility for strong follow-ups.

Events focused on audience value beat pure announcements every time. These moments also create reusable assets. Quotes, insights, and screenshots often become blog content, social posts, or supporting material for PR outreach.

Driving Earned Media Through Discord Engagement

Growing your Discord server matters less than what happens inside it.

Active communities generate stories organically. Journalists reference AMA insights. Industry newsletters cite ongoing discussions. Blogs quote real community sentiment.

Community-driven narratives often outperform traditional press releases because they show participation rather than positioning. Readers trust stories that reflect real dialogue.

A transparent Q&A or high-energy discussion thread can become the foundation for coverage. Discord surfaces narratives that feel timely, authentic, and grounded in lived interaction.

To maximize earned media potential from Discord:

Make conversations screenshot-friendly. Clear usernames, well-formatted responses, and threaded discussions make it easier for journalists to reference your server.

Highlight notable members. When industry experts or recognizable creators participate in your Discord, that increases media appeal.

Track quotable moments. Assign someone to screenshot strong quotes, insights, or exchanges during active discussions. These become PR assets.

Pitch the conversation, not just the product. Send journalists a link to an active discussion thread, not a press release. Let them see the community energy firsthand.

Common Mistakes When Using Discord for PR and Engagement

The biggest mistake? Treating Discord like a broadcast channel.

Post links without conversation and your server dies.. Members expect response and interaction, not scheduled promotion.

Another issue is weak moderation. Servers without clear purpose or active moderators lose focus fast, which discourages journalists and creators from participating.

PR teams also create friction when they treat creators or journalists like captive audiences. Discord works because participation is voluntary and collaborative.

Guide discussion. Share insider context. Show up consistently. Respect the community’s time.

“Mistake #1: Broadcasting Without Responding Posting ‘Check out our new blog post!’ and disappearing doesn’t work. People expect you to discuss the post, answer questions, or explain why it matters. If you’re not ready to engage, don’t post.

Mistake #2: No Clear Server Purpose Servers that try to be everything—community hub, support forum, news feed, social network—confuse members. Pick 2-3 core functions and build around those. Zapier’s Discord focuses on automation discussion and customer success. That’s it.

Mistake #3: Treating Journalists Like Fans Journalists don’t want hype. They want context, access, and honesty. A press channel filled with marketing language gets ignored. Background information, data, and direct responses get used.

Mistake #4: Inconsistent Presence Posting daily for two weeks, then ghosting for a month, breaks trust. If you can’t maintain active engagement, don’t launch a server. Better to have no Discord than an abandoned one.

Mistake #5: Over-Moderation or Under-Moderation Too many rules kill discussion. No rules create chaos. Find the balance: clear guidelines, active mods who participate (not just police), and flexibility for organic conversation.”

Tools, Bots, and Setups to Maximize PR ROI

The right setup makes Discord manageable for small teams and scalable for larger ones.

Roles segment audiences cleanly. Press, creators, and fans shouldn’t share the same access paths. Clear onboarding channels explain where to engage and what matters.

Bots support efficiency:

  • Event scheduling and reminders
  • Moderation and automation
  • Engagement and activity tracking

Larger teams often use ticket-style workflows to route media requests or creator inquiries without cluttering channels.

The goal is structure without rigidity. Discord should feel organized, not over-engineered.

A Discord Bot.

Source

Here are the bots worth using:

For Events: Sesh – Schedules events with automatic reminders. Members RSVP directly in Discord, and the bot pings them 15 minutes before start time.

For Moderation: MEE6 – Auto-moderates spam, assigns roles based on activity, and sends custom welcome messages to new members. Free tier handles most small-to-mid sized servers.

For Analytics: Statbot – Tracks message volume, active members, peak engagement times, and channel-level activity. Shows which conversations generate the most participation—useful for PR teams measuring impact.

For Workflow: Zapier’s Discord integration – Connects Discord to Google Sheets, Notion, or your CRM. Auto-post media inquiries to a tracking sheet or notify your team in Slack when someone joins your press channel.

For Ticketing: Ticket Tool – Creates private support threads for media requests, creator pitches, or partnership inquiries. Keeps channels clean while routing requests to the right team member.

FAQs

How do you engage a Discord community?

Run regular events like AMAs, Q&As, or feedback sessions. Assign roles that give members status and access (not just colors). Recognize active contributors publicly. Create channels for member-led discussions, not just brand announcements. Give people reasons to return daily, like ongoing conversations or exclusive content drops.

How can you increase Discord engagement?

You can run a small server (under 500 members) with one dedicated person spending 30-60 minutes daily. Larger servers need at least 2-3 moderators to handle different time zones and maintain a consistent presence. Consider community volunteers once your server reaches 1,000+ active members.

What’s the minimum team size needed to run a Discord server effectively?

What’s the minimum team size needed to run a Discord server effectively?

Expect 3-6 months before Discord activity generates measurable earned media. Relationships take time. The first month focuses on setup and onboarding. Months 2-3 build conversation patterns. Months 4-6 typically produce quotable moments and media references. Results accelerate after you establish a consistent presence and trust.

How long does it take to see PR results from Discord?

Expect 3-6 months before Discord activity generates measurable earned media. Relationships take time. The first month focuses on setup and onboarding. Months 2-3 build conversation patterns. Months 4-6 typically produce quotable moments and media references. Results accelerate after you establish consistent presence and trust.

Conclusion

Discord rewards dialogue over distribution. That makes it a natural fit for engagement and digital PR teams focused on relationships rather than reach.

Brands that use Discord well create space for trust, transparency, and real participation. Those signals translate into earned media, stronger creator relationships, and long-term community value that social platforms can’t replicate.

Start small. Launch a focused server with clear purpose, maybe a press channel and a creator lounge. Host one monthly AMA or live event. See what surfaces organically before scaling up. The platform rewards consistent, genuine engagement more than polished campaigns.

Discord won’t replace your email list or social media presence. But for building the kind of relationships that lead to coverage, partnerships, and authentic advocacy, it’s one of the most effective channels available right now.

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Google AI Overviews follow up questions jump you directly to AI Mode

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Google will now jump you directly into AI Mode when you do a follow-up question from AI Overviews within Google Search. This makes the “transition to a conversation even more seamless,” Robby Stein, VP of Product, Google Search wrote.

Plus, Google AI Overviews are powered by Gemini 3 by default, globally.

AI Overviews jumping to AI Mode. We covered when Google was officially testing this back in December and also before Google confirmed the test in October 2025. The ask a follow-up question within the Google Search AI Overviews will jump you into a conversation directly in AI Mode.

Google said this is about “making the transition to a conversation even more seamless,” within Google Search.

Why is Google doing this? Google said that during its testing, it “found that people prefer an experience that flows naturally into a conversation – and that asking follow-up questions while keeping the context from AI Overviews makes Search more helpful.”

Here is how it works:

When you click on “Show more,” Google will overlay AI Mode directly over the search results. You can to click the X at the top right of the screen to go back to the search results. And all the sources are removed from this view, so much for sending more traffic to publishers and content creators…

Note, this is live on mobile only right now.

Gemini powering AI Overviews. Google also said that it is rolling out Gemini 3 as the default model for AI Overviews globally. Robby Stein said, “we’re making Gemini 3 the new default model for AI Overviews globally, so you get a best-in-class AI response right on the search results page, for questions where it’s helpful.”

This is different from his previous announcement about a week ago, where Gemini 3 Pro would power AI Overviews for complex queries for English globally for Google AI Pro & Ultra subs.

Now, Gemini 3 is the default model uses for AI Overviews globally.

Why we care. While Gemini 3 may provide better quality responses for AI Overviews, the bigger news is that Google officially rolling out that follow up questions go to AI Mode from Google Search’s AI Overviews.

This is a big deal, because this will likely result in even fewer clicks from Google Search to publishers and instead will drive more searchers into AI Mode.

AI Overviews show up at the top of the search results for many queries. It is hard enough to get clicks from those citation cards now, and it will be even harder as this new follow-up experience rolls out. Google is actively pushing those searchers from Search into AI Mode and not to your website.

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Yahoo debuts Scout, an AI search and companion experience

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Yahoo today launched the first version of its AI-powered answer engine, Yahoo Scout. Scout is available at scout.yahoo.com and is embedded across Yahoo’s network, including Yahoo News, Finance, Mail, and Search. Think of it as a Yahoo-branded AI companion designed to guide users directly within Yahoo’s properties.

What is Yahoo Scout. Yahoo Scout is Yahoo’s take on an AI search engine and companion, similar to Google’s AI Mode or OpenAI’s ChatGPT, but with a distinct Yahoo flair. The goal is to give Scout a real personality — fun, engaging, and easy for people of all ages to use and understand, Yahoo told me.

  • When you first visit Yahoo Scout, you’re greeted by a playful homepage with a search box, a catchy slogan, and an animated icon that makes the experience feel friendly and inviting.
  • Below the search box, Yahoo offers suggested searches, with filters for topics like news, finance, sports, shopping, and travel.
  • On the left, Scout shows your past queries, making it easy to jump back in where you left off.

Here’s a screenshot of the homepage. This one features a cowboy hat, but other versions include a crystal ball, a gold medal, a walking cartoon brain, and more.

Yahoo Scout’s advantage. The Yahoo Search team gave me early access to Yahoo Scout. While the interface feels familiar if you’ve used competing tools, the Yahoo-specific elements clearly set it apart.

Yahoo’s advantage over many AI search competitors is its massive, built-in audience across Mail, News, Finance, and Search. It has more than 500 million user profiles and deep data on queries, usage, intent, and behavior. Yahoo also maintains over one billion knowledge-graph entities and tracks 18 trillion consumer events and signals across its properties. Together, this gives Yahoo the ability to deliver more personal AI-driven search experiences and more accurately categorize queries.

Yahoo is the second largest email company and third largest search engine, the company told me.

Yahoo Scout can pull rich content from across Yahoo directly into its responses. This includes features like Yahoo Finance widgets, detailed financial data, tables and citations, weather, news, and more.

  • “Search is fundamentally changing, and our team has been inspired to use our decades of experience and extremely rare assets to create something uniquely useful for Yahoo’s hundreds of millions of monthly users. This beta launch is just the starting point. From search to our industry-leading verticals, Yahoo Scout will help our users accomplish their goals online faster and better than ever before,” said Jim Lanzone, CEO of Yahoo.

Sending traffic to you, the publisher. Scout is closely tied to Yahoo’s original mission: being a trusted guide to the internet, Lanzone said. From the ground up, Yahoo built Scout to honor the open web by driving traffic downstream to content creators.

Yahoo Scout responses use large, wide blue highlights across the text. When you hover over them, you can click through to the original source.

Each response also includes a “featured source” that’s easy to spot and select. Scout further emphasizes content with tables and imagery while surfacing relevant news articles and sources throughout its answers.

Early AI search engines did little to send traffic back to the sources behind their answers, Lanzone said. Yahoo wanted to set an example for how to do this the right way. There isn’t enough revenue for every publisher to rely on licensing deals with AI companies, and historically, the model that worked best was simple: send traffic back to the original sources.

Here’s an example of how Yahoo Scout links to its sources:

When you hover over the blue highlights, the source appears, and you can click through to visit it. The purple “Read more” featured-source section also aims to drive traffic downstream.

CTR expectations. I asked Yahoo about the expected click-through rate from Scout to publishers. They said they don’t know yet. Yahoo plans to learn from real-world usage once Scout goes public and iterate to improve downstream clicks. This is Scout’s first release, and real user data should be telling.

They expect queries in Yahoo Scout to be longer than in Yahoo Search, with lighter ad loads and a much higher click-through rate than the industry average.

Yahoo also told me it plans to give publishers access to impression and click data in the future, possibly through a Yahoo Webmaster Tools–style product. Crawling and indexing would remain separate, since that layer is still powered by Microsoft Bing.

Yahoo Scout in every Yahoo property. You’ll be able to access Yahoo Scout across all Yahoo properties.

  • Yahoo Mail will summarize emails with AI and extract actionable items, such as adding events to your calendar.
  • Yahoo Search will add AI summaries powered by Scout.
  • Yahoo News will surface key article highlights and include the daily digest audio summary.
  • Yahoo Finance will introduce a new Analyze button powered by Scout.

Examples of Yahoo Scout in action. Here are a few examples of Yahoo Scout. It’s not perfect, but for a six-month project, I’m impressed.

I asked Scout for help explaining how SEO works, and it delivered a solid response. SEO is complex, and not everyone will agree with every detail, but the answer was thoughtful and useful. There are citations throughout the summary:

I then asked it to share sources for finding content on the topic as a follow-up. There were clear missed opportunities to link out more, which I pointed out to Yahoo, and they agreed.

I asked Yahoo Scout how to navigate to the sources it mentioned, and at that point, it did provide links:

Here’s a screenshot of another citation that appears when you hover your mouse cursor over it.

Here are some other searches I tried:

  • Entertainment: Scout incorporates news articles, with larger graphics in clickable card formats.
  • Finance: Yahoo brings in Yahoo Finance. I was unable to generate stock charts, although in a demo I was given, I was shown that live. So maybe it was being worked on during my tests:
  • Weather: I was testing this Sunday morning, as the big snow storm was touching down in New York:

I was able to get a Yahoo Weather chart:

With tips on how to stay warm:

  • Sports: The Super Bowl is coming up, and I was hoping to get some predictions:

As a lifelong Jets fan, I asked whether the team has any chance of winning the Super Bowl in the next 10 years. The answer wasn’t encouraging, but I was happy to see a chart embedded directly in the response.

  • Shopping: And then Yahoo gave me some advice on how to dress during this weather:

Ads and commissions. Yahoo Scout will show ads at the bottom of some responses. It will also monetize commerce-related queries through affiliate commissions, a common web revenue model.

  • Yahoo told me the ads are still powered by Microsoft Advertising, but Yahoo controls how those ads appear within these interfaces.
  • These ads will be charged on a CPC basis, not an impression basis, as some other AI engines announced.

Here is a screenshot of a Progressive Insurance ad for questions about car insurance.

Here is a screenshot of product results that are labeled, “Yahoo may earn commission from these links.”

How Yahoo Scout came about. For about three years now, Yahoo has been hinting about making a return to the search game. In 2009, Yahoo made a deal with Microsoft to have Microsoft power Yahoo Search and that was the end of Yahoo building its own search technology. Literally, Yahoo has outsources Search since then and has not done its own search technology until now, with Yahoo Scout.

That is until now. About six month ago, Yahoo acquired Eric Feng’s company to lead up consumer search at Yahoo. Eric Feng is known for co-founding an online video platform startup called Mojiti, which was acquired by Hulu in 2007, in which Eric became the founding CTO and head of product at Hulu. But before that, he worked at Microsoft in the Research labs, working on solving problems with Search.

“Yahoo’s deep knowledge base, 30 years in the making, allows us to deliver guidance that our users can trust and easily understand, and will become even more personalized over the coming months,” said Eric Feng, Senior Vice President and General Manager of Yahoo Research Group, the creators of Yahoo Scout. “Yahoo Scout now powers a new generation of intelligence experiences across Yahoo, seamlessly integrated into the products people use every day.”

Jim Lanzone, the CEO of Yahoo, who in his own right has a long history in search, as the CEO of Ask.com for many years, told me that Eric Feng has been instrumental in building out Yahoo Scout in the past 6 months. And there is so much more to come, this is just the first public release and you can expect many more interations and improvements to Yahoo Scout in the near future.

Anthropic. Yahoo Scout is not built on its own LLM, Yahoo partnered with Anthropic to use Claude as Yahoo Scout’s primary foundational AI model. Anthropic is one of the top artificial intelligence companies in the market. It has arguably the best AI for coders and coding frameworks named Claude. Anthropic was founded in 2021 by former members of OpenAI, including siblings Daniela Amodei and Dario Amodei, who serve as president and CEO, respectively. In September 2023, Amazon announced an investment of up to $4 billion. Google committed $2 billion the next month. As of November 2025, Anthropic has an estimated value of $350 billion.

While the foundational AI models use Anthropic, Yahoo has customized it and incorporates Yahoo’s proprietary data to make it unique and useful. Doing these searches on Anthropic will not give you anywhere close to the same experience as you would get on Yahoo Scout.

“When you’re serving hundreds of millions of users, you need AI that can do more than retrieve information – it has to reason, synthesize, and explain. Yahoo is building toward a more personalized, trustworthy kind of search, and Claude’s ability to deliver that quality of guidance at scale is at the heart of Yahoo Scout,” said Ami Vora, Head of Product at Anthropic.

Microsoft Bing. Plus, Microsoft Bing data is also incorporated into Yahoo Scout. The underlining search index is from Bing, but the responses, ranking, and experience is all Yahoo. “Yahoo Scout also builds on Yahoo’s long-standing relationship with Microsoft by leveraging Microsoft Bing’s grounding API. By combining this API with Yahoo’s trusted data and content ecosystem, Yahoo Scout ensures that answers are informed by authoritative sources from across the open web, Yahoo wrote.

Plus, Yahoo is also joining Microsoft’s Publisher Content Marketplace pilot. Microsoft’s Publisher Content Marketplace can help support revenue for publishers, the company said. Yahoo wrote this is, “reflecting a shared commitment to expanding publisher reach, connecting original work with new audiences, and supporting sustainable revenue opportunities for publishers.”

Hallucinations. I asked about hallucinations and Yahoo told me they put in a lot of guardrails to prevent hallucinations as much as possible. The Yahoo entity graph, the news content, and other Yahoo-specific data are used to ground the responses so that communications should be minimal and less than some other AI engines. In fact, they believe the hallucination rate would be “very low” compared to other AI engines.

Agents. Many AI engines are releasing agentic experiences, AI agents, to complete tasks for you. Google, OpenAI and Microsoft are investing big time into this.

Yahoo Scout has added some elements of this including inside of Yahoo Mail to add calendar events, smart compose features and more. Yahoo promises a lot more to come on this front.

Why we care. It’s an exciting time for search. For someone like me who has spent more than 20 years in search, it’s nice to see Yahoo step back into the space. Watching industry veterans like Jim Lanzone, Eric Feng, and Brian Provost take on search with AI is making it fun again, and I’m excited to see what Yahoo does next.

Availability. The Yahoo Scout answer engine is available today in beta for U.S. users at Scout.Yahoo.com and in the Yahoo Search app on iOS and Android. For more about Yahoo Scout, see this help document.

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Is your account ready for Google AI Max? A pre-test checklist

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Is your account ready for Google AI Max? A pre-test checklist

AI Max is Google’s latest foray into semi-keywordless targeting. 

While you need keywords for the system to have a starting place, Google uses signals beyond keywords in deciding how to show ads to searchers.

In accounts with a strong history of broad match success, AI Max can be highly effective at finding new conversions. 

If accounts are not well-optimized or have not been successful with broad match, AI Max can be a huge money pit.

To clear up a rumor before we get into the data: you do not have to use AI Max to have ads appear in AI Overviews. 

Broad match keywords can show ads in AI Overviews regardless of your AI Max usage. 

We’re looking at AI Max as a conversion expansion option, not just an option to show in AI Overviews.

This article examines the review steps you should take before you decide to test AI Max.

What to check before enabling AI Max

Accurate conversion tracking 

Your conversion tracking must be accurate, deduplicated, and focused on business outcomes. AI Max optimizes toward what you have defined as success. 

If you aren’t tracking all your conversions, or if your conversions are inflated, AI Max will be working from inaccurate data and making poor decisions.

Automated bidding with a conversion-focused strategy 

Broad match only works well when you have a bid strategy that is focused on conversions, such as:

Our experiments with AI Max have shown that it is much more predictable with one of the target options (Target CPA or Target ROAS) than with the max bid options (Maximize conversion value or Maximize conversions). 

Since the Max conversion options are meant to get you the most possible, regardless of the CPA or ROAS, they will often continue to spend your budget when the next set of conversions could have exceptionally high CPAs or very low ROAS.

If you use AI Max with one of the max bid options, pay close attention to your budget and the AI Max data.

Conversion volume

Technically, you can enable AI Max without any conversions for a campaign. 

However, with under 30 conversions per month, AI Max has been highly erratic. 

At over 100 conversions per month, it has done well more often than not, assuming you have had success with broad match in the past. 

In general, you will want to test AI Max in campaigns that have at least 30 conversions per month.

If you are going to test AI Max, starting with non-brand campaigns that have a high conversion volume will usually give you a better introduction to AI Max’s possibilities for your account.

No impression share lost due to budget

If you’re already losing impressions due to your budget, your handpicked keywords will receive even less budget if you enable AI Max. 

The goal is to spend as much as you can on your top keywords, and then have AI Max experiment with the budget we can’t spend. 

If you are already losing impressions due to your budget, then enabling AI Max usually results in poorer performance.

Have proven broad match success

AI Max will treat all of your keywords as broad match, and then expand even further than your broad match keywords. 

If you haven’t successfully used broad match, then enabling AI Max will be a waste of money.

You should first ensure that broad match can work for you, which might require reorganizing ad groups, testing new ads, and optimizing your landing pages. 

Only after you have consistently seen good results with broad match should you try AI Max.

Dig deeper: How to tell if Google’s AI Max for search is actually working

Should you use URL expansion? 

When you enable AI Max, you can expand URLs to other pages on your website. 

This means that Google can pick any page of your website to use as a landing page when AI Max triggers an ad.

Google allows you to exclude URLs. Most sites should exclude:

  • Help files and support pages.
  • Pages not built for conversions.
  • Pages that do not have conversion tracking enabled.
  • FAQs.
  • Blogs.
  • Old landing page tests that are still live.
  • Old website designs that are still live.
Google Ads - Add URL exclusions

A few people have found success with using AI Max with blogs and support pages. However, these seem to be exceptions more often than the standard result.

AI Max has struggled when there are many geographic landing pages. 

We’ve seen accounts that target different geographies by campaign, and each campaign has its own set of landing pages. 

AI Max has routinely mismatched the campaign’s geographic target with landing pages intended for other geographies. 

For example, your California campaigns are sending all of their traffic to landing pages dedicated to Texas traffic.

If you want to use AI Max URL expansion, and you have landing pages dedicated to various geographies, you will need to exclude all the landing pages that are irrelevant to the geography of your campaign.

For companies that create dedicated landing pages for each campaign or ad group, I have yet to see an example of AI Max finding better landing pages.

In every example, AI Max’s URL expansion has needed to be turned off. Eventually, this option might work for advertisers, but I have yet to see that happen.

You can review the URLs that Google is using and exclude them. If you turn on URL expansion, you will want to regularly review these URLs.

Dig deeper: AI Max in action: What early case studies and a new analysis script reveal

Get the newsletter search marketers rely on.

See terms.

Should you try automatically created assets? 

My great hope for AI Max is the automatically created assets. 

I wish I could enable this only for extensions. AI Max can help you scale messaging tremendously. 

It can go through all of your ad groups and automatically create sitelinks and callouts at the ad group level. 

This level of customization is one that many advertisers never have time to fully explore.

We had a client who enabled this feature, and suddenly, all their sitelinks linked to pages that were irrelevant to the keywords. 

We’ve seen other clients use this feature, and their callouts improved dramatically. 

Google still has a ways to go in how they auto-create assets, but this is a feature I have high hopes for.

Unfortunately, you can’t enable this feature for only ad assets (extensions). If you enable automatically created assets, Google will create additional RSA assets for you.

These assets can cause customer confusion by:

  • Making promises your brand doesn’t meet.
  • Using messaging that isn’t compliant with the law for regulated industries or doesn’t follow your brand guidelines.

You can write guidelines for how you want your ads to appear and rules on what shouldn’t be used. 

If you’re going to have Google automatically create assets, you’ll want to add guidance on how the ads should be created.

Note that term exclusions and text guidelines (Google’s official names for these features) don’t appear to be enabled in all accounts right now and may still be rolling out to advertisers.

Overall, Google’s auto-generated RSA assets have a poor track record, and if you enable them, you will want to regularly review what Google is creating on your behalf.

How to test AI Max

Since Google has a history of matching broad match keywords to other brands and generic keywords, AI Max has been very inconsistent with brand keywords.

I’d suggest starting with your top non-brand keywords to test AI Max. 

For most brands, there are more conversions to be had in non-brand expansion than in finding more people who are already searching for your brand.

AI Max can be enabled at the campaign or ad group level. 

One of the best ways to run a limited test with AI Max is to enable it only in a few ad groups that have a lot of conversion data and a successful history with broad match.

In the interface, enabling AI Max for only a few ad groups is painfully slow. 

You have to enable AI Max at the campaign level, then go into every ad group and turn it off where you don’t want it enabled.

The Google Ads Editor lets you turn AI Max on or off at the ad group level.

Google Ads - Settings for AI Max

If you want to test AI Max in only a few ad groups, then use the editor for your initial setup.

Dig deeper: When to trust Google Ads AI and when you shouldn’t

Is your account ready to test AI Max?

Google has long sought a keywordless targeting option for search. Its first step was Performance Max. 

AI Max is another foray to introduce advertisers to the idea that they don’t have to choose every keyword in their search campaigns.

Like all Google Ads products, they usually perform poorly when first launched. 

After a few years of data gathering, refinement, and additional advertiser controls, these products often prove successful.

AI Max is still a new product. Some accounts have had success with it. Others have only found failure. 

As with everything Google Ads-related, you should test it before widely adopting it.

The best way to test AI Max is to find non-brand ad groups with high conversion volume and a successful history with broad match keywords. 

Perform limited tests in these ad groups. If you find success, you can expand the ad groups that use AI Max.

During your tests, you must review your search terms, URLs, and auto-created assets. 

If you are not going to add these tasks to your workflow, then you are not ready to test every AI Max feature.

AI Max’s potential is enormous. However, it isn’t a good solution for everyone. Its ad writing can be quite poor. 

The new search terms can be hit-or-miss. You must babysit it. However, the time savings and potential are undeniable.

While I believe there is a bright future for AI Max, you must first ensure you complete all steps to verify that your account is ready to test it. 

If you follow the steps outlined in this article, you’ll know if you’re ready to test AI Max and see what these new campaign options can do for you.

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Why Search and Shopping ads stop scaling without demand

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Why Search and Shopping ads stop scaling without demand

If you’ve spent any time in PPC communities, Reddit threads, Slack groups, or conference Q&As, you’ve probably noticed a recurring frustration: “Google Ads isn’t scaling. It’s not working, and we’re stuck.”

On the surface, everything looks fine. The campaigns are running, impression share is high, shopping feeds are clean, and budgets are flowing. But growth isn’t materializing.

This isn’t usually about “broken campaigns” – it’s about the limits of demand.

In niche markets or categories shaped by seasonality, growth is naturally capped.

Yes, running broad match or AI Max can expand your reach to adjacent queries, so impression share might not literally be 95%.

But these campaigns are still only capturing demand that already exists. Once you’ve covered the pool of relevant searches, you can’t spend your way into more.

That’s the uncomfortable truth: Google Ads doesn’t create demand. It captures it.

If fewer people are searching this month, or if your category naturally has a small audience, your results will reflect that.

You can dominate what’s there, but you can’t conjure demand out of thin air.

So when growth stalls, the real question isn’t “What’s wrong with Google Ads?” but “What are we doing to create demand that fuels future searches?”

Search and shopping = Demand capture, not creation

Let’s call Search and Shopping what they are: demand capture channels.

They’re excellent for getting in front of people when they’re ready to buy, or at least actively researching. But they are reactive by design.

Ads only appear once someone types a query. No query, no ad.

That’s why impression share (IS) can be deceptive.

A 90% IS looks like you’re winning (and you are). But if there are only 500 relevant searches in your market this month, you’ll never scale to 5,000 clicks just by raising bids.

Broad match and campaigns like AI Max can stretch coverage by surfacing adjacent queries.

But these still rely on intent. If nobody is searching for related terms, there’s nothing to match against.

Contrast this with platforms like Meta or TikTok, where more budget literally means more reach.

Search doesn’t work that way. It’s not a demand generator – it’s a closer.

Where demand really comes from

So if Search and Shopping can’t create demand, what does?

Marketers have long grouped channels into three buckets: owned, earned, and paid.

It’s old-school terminology, but it’s still the most practical way to break down where demand actually originates.

If Search and Shopping are just there to capture demand at the end, you need to understand which levers create it upstream.

Owned

These are the channels you control: your website, email, content, and CRM. They don’t usually create brand-new demand, but they’re critical for nurturing it.

Think of a D2C brand running a simple “VIP early access” sign-up before Black Friday. That list fuels branded searches once the sale goes live.

Or a SaaS company publishing an FAQ blog that shows up for early research queries, nudging prospects who later Google the brand directly.

Owned channels ensure that once curiosity is sparked, it’s effectively nurtured toward a search.

Earned

These are the channels you don’t directly pay for: PR mentions, SEO visibility, reviews, organic social, and word of mouth.

A product that lands in a holiday gift guide? Branded searches spike the next week.

A TikTok that goes viral organically? Google Trends charts it days later.

Positive Trustpilot reviews? They push people back to Google to check your site or compare pricing.

Earned channels matter because they carry credibility. They don’t just spark curiosity; they make people trust you enough to type your name into the search bar.

Paid

Paid media includes both demand-capture channels (Search and Shopping) and demand-creation channels.

Search and Shopping capture existing intent, but platforms like Meta, TikTok, YouTube, Pinterest, and Display create it.

These channels don’t wait for someone to type a query, they put your brand in front of people who weren’t already looking.

  • A TikTok showing your product in action.
  • A YouTube pre-roll highlighting your brand story.
  • A Pinterest ad that lands on someone’s gift board weeks before purchase.

These sparks generate curiosity, which later turn into branded searches.

While broad match and Performance Max might unearth “new” queries, they’re still intent-driven.

The real creation happens upstream, through paid channels designed to spark awareness.

Dig deeper: How paid, earned, shared, and owned media shape generative search visibility

The funnel without the fluff

You’ve likely heard this before, but it’s worth being specific about where Search and Shopping actually fit.

They’re strongest at conversion, but they also show up during the consideration phase of the buyer’s journey, when people are still comparing options.

Here’s how the funnel really works.

Awareness

This is the stage where people first notice you exist.

For example, a skincare brand could run TikTok ads showing its serum in action, or a B2B SaaS company might run YouTube pre-roll explaining a popular platform feature.

In retail, a promoted Pinterest pin could land on someone’s gift board long before purchase.

Tip: This is where Meta video campaigns, TikTok ads, YouTube pre-roll, Pinterest-promoted pins, PR placements, and influencer content live. These channels don’t wait for intent – they spark it.

Consideration

During this stage, people compare, research, and explore.

For example, that skincare shopper might read reviews, sign up for “early access,” and later search “best vitamin C serum.”

In B2B, a prospect could download a case study and then Google “top CRM tools for small businesses.”

Tip: This is where generic search campaigns (e.g., “best [product]” or “affordable [category]”), shopping ads with comparison queries, CRM nurture flows, SEO content, and retargeting via Meta/display/YouTube come in. This stage is about reassurance, education, and visibility while the prospect weighs their choices.

Conversion

The stage where people buy. For example, two weeks after first becoming aware of the brand, the skincare shopper searches “Brand X serum” and buys via Shopping.

After much comparison, the B2B prospect searches “[Vendor name] pricing” and completes a demo-request form.

Tip: This is where branded search, high-intent shopping queries, retargeting to cart abandoners, and PMax remarketing close the deal.

That’s why the funnel matters. If you only play at conversion, you miss those critical mid-funnel searches where people decide between you and your competitors.

Skip awareness and consideration, and your funnel isn’t a funnel at all – it’s a drinking straw. 

Get the newsletter search marketers rely on.

See terms.

What to do when search hits its ceiling

When growth stalls, the solution isn’t “spend more on search.” It’s fuelling demand earlier.

Here’s how to do exactly that, broken up by budget level.

If you’re working with smaller budgets, focus on high-leverage plays:

  • Grow your CRM list: Run simple lead-gen ads, like “sign up for early access” or “exclusive drops.” Even $300-$500 on Meta can build a list that costs nothing to email later.
  • Run warm-up campaigns: Low-cost video or carousel ads on Meta or TikTok build remarketing pools you can retarget with cheaper Google Display or YouTube Ads.
  • Optimize your site: Gift guides, FAQs, delivery cut-offs. A poor landing page wastes every click you’ve fought for.
  • Keep remarketing switched on: Display, YouTube, or PMax remarketing switched on is often cheaper than chasing new clicks in search.

If you’ve got bigger budgets, play full-funnel:

  • Run always-on awareness: Meta, YouTube, TikTok, Pinterest. Sequence your creative by teasing early, revealing mid-season, and then pushing offers when intent peaks.
  • Segment your CRM properly: VIPs deserve exclusives. Lapsed buyers need reactivation. Gift shoppers want bundles. Tailor the journeys.
  • Invest in influencers and PR: Gift guides, unboxings, trend-driven content. These placements fuel branded search demand faster than any keyword tweak.
  • Personalize your site: Recommendation engines and dynamic content keep people on the path to purchase.

Things everyone should check:

  • Check impression share: If you’re at 90%+, you’re near the ceiling. Broad match and AI Max might stretch coverage, but they won’t invent intent.
  • Track branded search: If branded queries aren’t rising, awareness is flat.
  • Keep remarketing on: It’s the lowest-hanging fruit.

Assets you need in place

Fix the basics before you pour money into awareness. Demand creation is wasted if your funnel leaks.

At a minimum, you need proper creative assets. Don’t just think about “a video” or “a few images.”

Different platforms require different formats and sizes, and if you don’t prepare variations, you’ll either be stuck with auto-cropping or miss placements altogether.

  • Meta: Vertical (Reels/Stories), square (Feed), and landscape (In-stream).
  • TikTok: Full-screen vertical, with captions/subtitles baked in as sound-off viewing is common.
  • YouTube: Horizontal 16:9 ratio for standard placements, but also vertical Shorts for mobile audiences.
  • Pinterest: Vertical lifestyle imagery tends to outperform product-only shots.
  • Display: Responsive formats mean you should plan both text + multiple image ratios so the algorithm has variety to test.

For small brands, this doesn’t mean expensive shoots. Scrappy user-generated content can be repurposed across platforms if you plan with aspect ratios in mind.

For bigger brands, building a creative matrix – every concept mapped across different formats and funnel stages – ensures consistency and saves on reshoots.

Landing pages

Don’t send awareness traffic to a generic homepage. Build pages that:

  • Answer FAQs
  • Highlight delivery cut-offs (critical in Q4)
  • Showcase bundles or gift guides for seasonal shoppers
  • For B2B: Tailor landing pages to industries or personas

CRM setup

Even a simple nurture flow is better than nothing. Capture the email at the awareness/consideration stage and follow up.

Larger brands should run segmentation and automated journeys:

  • VIPs: Exclusives.
  • Lapsed buyers: Reactivation flows.
  • Prospects: Educational sequences.

These assets make sure that when demand is created, it actually converts instead of leaking out of the funnel.

AI: Helpful, but not a shortcut

AI is everywhere right now. Tools like Performance Max, AI Max, and creative generators are powerful.

Used well, AI can save time and scale execution.

For example, generative AI can help brainstorm dozens of ad copy variations that you then refine for brand fit.

Or it can automate repetitive tasks, such as analyzing search term reports or adjusting bids, freeing you up to focus on strategy.

However, AI doesn’t change the rules of demand. It still relies on intent already being there. And if you let it run unchecked, you risk losing what makes your brand stand out.

Search Engine Land has repeatedly warned about this: over-reliance on AI can result in generic creative that lacks voice and originality, blending your ads into the crowd.

Think of AI as an accelerator: It can speed up execution, but it can’t define your brand, audience, or strategy. That still requires a human marketer.

Making it real for stakeholders, measuring demand creation

If you’re explaining this to a board or client, keep it simple:

  • Lead with this: Search responds to demand; it doesn’t generate it.
  • Show them impression share: If you’re already at 90%+, the problem isn’t coverage – it’s demand.
  • Point to branded search trends: Flat branded queries mean flat awareness.
  • Highlight competitor activity: Show where rivals are fuelling demand – Meta, TikTok, PR, or Pinterest. That’s why their branded search traffic is rising.

Don’t just show performance data. Show where the demand gap is.

Branded search is the clearest signal, but it isn’t the only one. Look at:

  • Direct traffic: More people typing your URL into their browser means brand awareness is working.
  • Organic search traffic (non-branded): If this grows, your content is pulling people in who may later convert via paid.
  • Social engagement and reach: Demand creation platforms build traction, even if the final conversion happens in Google.

Ultimately, owned, earned, and upper-funnel paid activity all create demand; Search and Shopping are there to capture it.

The ceiling isn’t Google Ads – it’s demand

The truth is, this is the direction PPC is heading.

Query growth is flattening, AI search is reshaping how results appear, and brand demand is becoming the real performance lever.

The next time someone says, “Google Ads isn’t driving traffic,” flip the question on them: Was there any demand to capture in the first place?

Because if you’re only running Search and Shopping, you can’t grow beyond the demand that already exists.

The brands that win aren’t the ones squeezing bids and obsessing over CPC swings.

They’re the ones consistently fuelling demand upstream: awareness, SEO, content, influencers, CRM, video, and social – all working together to prime the market.

So when growth stalls, the real question isn’t, “What’s wrong with Google Ads?” It’s “What are we doing to create demand that fuels future searches?”

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