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The future of paid search: 3 predictions for Google Ads in 2025

Google announced the public beta of Display & Video 360 API v4 last week, alongside significant updates to v3.

Key changes in v4.

  • Mandatory optimization objective field for new insertion orders
  • Removal of Campaign and InsertionOrder resource targeting management
  • Renaming of FirstAndThirdPartyAudience to FirstPartyAndPartnerAudience

Additional features in v3 and v4.

  • Asset-based creative support
  • Integral Ad Science quality sync integration
  • Expanded geographic region targeting options

Why we care. The beta release of Display & Video 360 API v4 and new v3 features gives advertisers enhanced capabilities for programmatic advertising management.

Between the lines. The mandatory optimization objective requirement suggests Google is pushing for more structured and purposeful campaign setups.

What to watch. Google warns that v4 may undergo breaking changes during the beta period, with updates documented in release notes.

Bottom line. Advertisers need to update their client libraries to access new features and should consider following Google’s migration guide when moving to v4.

How to prevent PPC from cannibalizing your SEO efforts

If you manage both SEO and PPC, striking the right balance is key to maximizing efficiency and ROI. 

When paid search campaigns compete with high-performing organic listings, brands end up spending more while gaining little additional traffic. 

Keyword cannibalization dilutes search performance, inflates costs, and reduces overall marketing effectiveness.

This guide will help you recognize the warning signs of PPC cannibalization, test its impact, and implement strategies to ensure both channels work together for optimal results.

Signs your PPC campaigns are cannibalizing your SEO rankings

Declining organic click-through rates

If your organic rankings remain stable but CTRs are dropping, your paid ads might be stealing traffic from your organic listings. 

This is usually the result of branded or high-ranking keywords being simultaneously targeted in PPC campaigns.

It’s also important to note that additional SERP features, ad placements, and AI-driven search results have contributed to a general decline in organic CTRs across the board.

Increased PPC clicks with no overall traffic growth

If PPC campaigns drive more paid traffic, but total website visits remain unchanged, your ads may be diverting clicks that would have otherwise come from organic search.

Google Analytics 4 (GA4)’s Traffic Acquisition Report makes identifying this issue easier. You can compare period-over-period traffic changes by channel side by side.

GA4 Traffic Acquisition report

Organic conversions declining while paid conversions increase

If paid search conversions are rising but overall conversions remain flat or decline, PPC may be cannibalizing organic conversions rather than expanding your reach.

This is especially common with Performance Max (PMax) campaigns, which often prioritize branded terms for their higher ROI. More on that later.

Dig deeper: How to maximize PPC and SEO data with co-optimization audits

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3 steps to prevent PPC from cannibalizing your SEO

1. Audit PPC and SEO keyword overlap

Not all overlapping PPC and SEO keywords cause cannibalization. 

However, to safeguard your top-ranking keywords, exclude them from your PPC campaigns.

To speed up your analysis, filter organic search terms where your website ranks position 4 or below – since most clicks go to pages ranking in positions 1-3.

Additionally, sort search terms by click volume to identify phrases most susceptible to cannibalization. 

Then, cross-reference your organic search terms with your Google Ads Search Terms report to pinpoint where you’re paying for traffic you’d otherwise get for free.

2. Use negative keywords to exclude strong SEO performers

If certain terms already perform well organically, you can use negative keywords to prevent them from triggering paid ads. 

By applying exact-match negative keywords, you avoid cannibalization while still targeting related peripheral phrases in your ads.

Google Ads Negative Keyword tool

Dig deeper: How to use negative keywords in PPC to maximize targeting and optimize ad spend

3. Refine brand bidding strategies and implement brand exclusion lists

Bidding on branded terms is often unnecessary since users searching for a brand already intend to visit its website.

Paying for traffic that would otherwise be free is rarely a good investment.

However, PPC brand bidding becomes essential when competitors target your brand.

In such cases, recapturing your brand space is a necessary expense – but fortunately, it’s much cheaper than bidding on a competitor’s brand.

The importance of brand exclusion lists

Brand exclusion lists help prevent wasteful spending on branded queries where organic listings already dominate. 

This ensures PPC budgets are focused on non-branded, high-intent searches rather than duplicating organic traffic. 

This is especially critical for PMax campaigns, which aim to drive positive ROI, often through low-cost branded visibility with high conversion potential.

One example of branded cannibalization my team identified involved a branded PMax campaign that inadvertently paid for an estimated $500,000 in organic revenue. 

Since PMax campaigns receive premium visibility – even in areas where results may not be highly relevant – this campaign bid on nearly every branded term, running unchecked.

A major issue arose when a shopping carousel for the company’s two most-searched branded phrases appeared above all other SERP features. 

This pushed the usual search ad lower on the page and forced the organic homepage listing completely out of view without scrolling. 

As a result, impressions dropped by 12%, and organic clicks fell by 33%.

If you haven’t yet taken steps to prevent your campaigns from bidding on your brand, make sure to check Google’s guide to brand exclusions

Benchmark your SEO performance on branded terms before launching PMax campaigns to make identifying cannibalization easier.

Dig deeper: Google brings negative keyword exclusions to Performance Max

Special considerations for Performance Max campaigns and targeting options

PMax campaigns use AI-driven automation to serve ads across Google’s entire inventory, including Search, Display, YouTube, Discover, Gmail, and Maps. 

Unlike traditional PPC campaigns, PMax lacks detailed keyword-level control, making it difficult to prevent overlap with organic rankings.

How PMax can cannibalize SEO traffic

  • Broad matching across multiple channels: PMax may automatically target keywords where your brand already ranks well organically, leading to unnecessary ad spend.
  • Limited transparency on search terms: Without keyword-level reports, identifying overlap with organic rankings is challenging.
  • Competing with organic listings: PMax can push organic results further down by occupying both paid search and shopping ad placements.

Dig deeper: Performance Max vs. Search campaigns: New data reveals substantial search term overlap

Mitigating SEO cannibalization in Performance Max

  • Use account-level negative keywords: Google now allows negative keywords for PMax – exclude high-performing organic keywords to reduce redundancy.
  • Optimize asset groups and search themes: If certain categories already perform well organically, ensure PMax focuses on different product lines or services. Since PMax is designed for maximum reach, precise targeting is essential.

Tests to confirm PPC is cannibalizing SEO

  • Run a PPC pause test: Temporarily pause PPC ad groups or use exact-match negative keywords for strong organic terms. If organic traffic, CTR, and conversions improve, PPC may be cannibalizing SEO.
  • Compare pre- and post-bid adjustments: Lower PPC bids on high-ranking organic keywords and track shifts in paid and organic performance.
  • Analyze assisted conversions in Google Analytics: Determine whether PPC ads drive conversions that organic search alone wouldn’t achieve. If not, adjustments may be needed.
  • Monitor organic CTR changes: Use Google Search Console to analyze CTR fluctuations for top organic keywords before and after PPC campaigns launch.

Aligning PPC and SEO requires careful keyword management and strategic bidding

Reduce ad spend where possible and avoid paying for traffic that would otherwise be free.

For Performance Max campaigns, mitigating SEO cannibalization through negative keywords and refined targeting ensures a balanced approach. 

A well-coordinated PPC-SEO strategy improves efficiency and maximizes the value of digital marketing investments.

From search to AI agents- The future of digital experiences

We rely on search engines to find information every day, but what if there was a better way? 

Instead of manually gathering details from multiple sources, AI agents can do the heavy lifting for you. 

They don’t just retrieve information. They analyze, organize, and personalize it in real time.

This article explores:

  • How AI agents help businesses create more personalized customer experiences.
  • The key components and frameworks behind AI-powered agents.
  • How multi-agent systems can collaborate to solve complex tasks.

From information retrieval to intelligent problem-solving

AI agents represent a fundamental shift in how we interact with AI. 

As brands, we are moving beyond passive information retrieval – a slow process of manually collecting data from various websites – to active problem-solving, where multimodal data seamlessly adapts to a preferred interface in real time.

Imagine a world where multiple independent AI agents collaborate to complete complex workflows. 

Industry experts anticipate significant transformation due to AI agents. Here’s what they have to say:

  • Satya Nadella: AI agents will proactively anticipate user needs and assist seamlessly.
  • Bill Gates: AI agents are driving the most significant software transformation since graphical user interfaces.
  • Jensen Huang: IT departments are managing AI agents the way human resources manage employees.
  • Jeff Bezos: AI agents act as digital copilots, enhancing daily interactions.
  • Gartner: Search engine volume will decline by 25% by 2026 as AI chatbots and virtual agents revolutionize customer interactions.

Today, brands have a significant opportunity to leverage AI agents as intelligent virtual teammates, enabling businesses to deliver hyper-personalized experiences.

As AI agents and technology evolve, we are moving away from the time-consuming effort of manually gathering information. 

In the future, AI agents will interact with one another, collect relevant data, organize it to match user preferences, and deliver it seamlessly – creating a faster and more efficient experience.

ai-agents-impact-on-humans.

Dig deeper: Mastering AI and marketing: A beginner’s guide

To understand how AI agents deliver these intelligent, real-time experiences, we need to break down their core components. 

Let’s explore the anatomy of AI agents and how each layer contributes to their functionality.

Anatomy of AI agents 

AI agents are designed to enhance the capabilities of LLMs by incorporating additional functionalities. 

Agents have four layers:

  • Foundation layer.
  • Application layer.
  • Management layer.
  • Data layer. 
anatomy-of-an-agent

An AI agent typically consists of the following components:

  • Memory: Stores past interactions and feedback to provide contextually relevant responses. Memory resides in the data layer.
  • Tools/Platform: Retrieves real-time data and interacts with internal databases. The chosen tools and platforms are part of the application layer.
  • Planning: Uses reasoning techniques to break down complex tasks into simpler steps.
  • Actions: Executes tasks based on insights from LLMs and other sources.
  • Critique: Provides a feedback loop for actions based on different use cases to ensure accuracy.
  • Persona: Adapts to different roles, such as research assistant, content writer, or customer support agent.

Planning, actions, critique, and persona identification occur in the management layer.

Frameworks for building AI agents

There are many frameworks available for building AI agents and multi-agent systems, each catering to a different need:

  • AutoGen (Microsoft): Focuses on conversational AI and automation.
  • CrewAI: Designed for role-playing agents that collaborate effectively.
  • LangGraph: Structures agent interactions in a graph-based model.
  • Swarm (OpenAI): Primarily for educational purposes.
  • LangChain: A popular framework enabling AI agents to work with LLMs and other tools.

Each platform offers unique advantages based on the task’s use case, scalability, and complexity.

Multi-agent AI systems and their importance

multi-agent-application-examples

A multi-agent system consists of multiple AI agents working seamlessly, each performing a distinct function to collaboratively solve problems.

These systems are particularly useful for handling complex scenarios where a single AI agent might struggle. 

Below is a simple example of a multi-agent system:

  • Query processing agent: Breaks the question into multiple parts.
  • Retrieval agent: Fetches relevant data from internal sources.
  • Validation agent: Verifies the response against various parameters such as brand voice and query intent.
  • Formatting agent: Structures the response appropriately.

This structured approach to distributing responsibilities among agents ensures more accurate and intelligent responses while reducing errors.

Before exploring how AI agents deliver real-time personalization, let’s look at why traditional methods are no longer enough.

Dig deeper: AI optimization: How to optimize your content for AI search and agents

Why AI-powered personalization is essential

As data availability declines and user expectations rise, businesses can no longer rely on traditional methods to understand customer intent. 

The shift away from third-party cookies, the rise of zero-click content, and the demand for real-time, tailored experiences have made AI-driven personalization a necessity.

AI enables businesses to analyze behavior, predict intent, and deliver dynamic, personalized experiences at scale – from search and social to email and on-site interactions. 

Unlike static personalization, AI adapts in real time, ensuring relevance across every customer touchpoint.

With traditional strategies losing effectiveness, AI agents offer a smarter, more scalable way to engage and convert audiences.

Dig deeper: How to boost your marketing revenue with personalization, connectivity and data

Delivering personalized experiences with search and chat agents

Modern websites are no longer one-size-fits-all. They provide immersive experiences tailored to each visitor’s intent. 

AI agents enable this through two key approaches:

Search agents 

Traditional site searches relied on keywords and filters, which have limitations with multimodal searches (like voice or visual) and long-tail queries. 

They also require more user clicks, increasing the likelihood of search abandonment. 

AI-powered search agents overcome these challenges by delivering a more intuitive and efficient on-site search experience.

Chat agents

Early AI chatbots responded using pre-programmed scripts or existing website content. 

Today, advanced chat agents offer personalized experiences using audience data. They can:

  • Build detailed user profiles.
  • Understand user intent by analyzing historical interactions and purchase data.
  • Learn from similar interactions to ask relevant follow-up questions.
  • Adapt on-site experiences in real time based on user behavior.
  • Inform cross-channel marketing strategies – such as email, social, paid, and retargeting – using insights gathered from user interactions.

AI agents also offer industry-specific personalization. Brands can implement:

  • Digital marketing automation agents.
  • Customer support chat agents.
  • Specialized solutions, like:
    • Financial risk assessment agents.
    • Automotive inventory management agents.

Personalize or perish

Many businesses still view personalization as optional. 

In reality, without personalized experiences, traffic and conversions will decline, leading to higher marketing costs and lower ROI as more spending is needed to attract, engage, and convert visitors. 

To improve efficiency, AI-powered personalization offers a scalable, intelligent, and adaptive solution.

Dig deeper: Hyper-personalization in PPC: Using data to deliver tailored ad experiences

Join experts from OneTrust and Snowflake for an exclusive look into how modern organizations are integrating privacy and consent management into their data ecosystem. In this session, Snowflake and OneTrust will share real-world use cases and insights into how organizations are activating consent for marketing purposes, all while streamlining compliance at scale.

Tune in on March 4 to learn about:

  • The intersections between consent, privacy, and data governance
  • How enterprise brands integrate privacy and consent management with Snowflake
  • OneTrust’s new Native App for accelerating compliance workflows within Snowflake

This session is perfect for marketers, data governance professionals, and anyone looking to improve their data privacy practices with real-world examples. Here is the link to learn more and register >>

The Details

Webinar:
How Privacy-First Marketers Leverage OneTrust and Snowflake for Consent Management at Scale

Date: March 4, 2025
Time: 10 am PT / 1 pm ET

Link to register: Here!

Why traditional keyword research is failing (and how to fix it with search intent)

After 25 years of working in SEO, I’ve seen firsthand how traditional keyword research methods fail to keep up with Google’s advancements. 

In my SMX Next presentation, I challenged SEOs to go beyond outdated keyword methodologies and embrace an intent-driven approach. 

Here are six key insights from that session.

1. Traditional keyword research is failing us

Traditional keyword research is no longer enough. 

We’ve relied on tools that provide data on competition, search volume, and relevance, but they don’t uncover the hidden context behind searches.

For years, SEOs have prioritized high-volume, low-competition keywords, assuming this would drive results. 

While this may have worked for the simpler, lexical-based Google algorithm of the early 2000s, this approach falls short because it ignores search intent.

For example, a keyword like “solar panels” may have high search volume. 

But without context, it’s impossible to determine whether users are looking for products, financing options, or general information. 

Without understanding intent, marketers risk attracting traffic that never converts. 

Today, success depends on moving beyond search volume and focusing on search intent.

Dig deeper: How to optimize for search intent: 19 practical tips

2. Google is an AI search engine

Google isn’t one monolithic AI algorithm – it’s a collection of AI systems working together to:

  • Understand queries.
  • Classify content.
  • Deliver the best results.

Here’s what’s changed:

  • Google has improved its understanding of keywords and content.
  • There is a strong emphasis on user experience, with Google prioritizing content that is easy for users to consume.
  • Google ranks pages based on relevance to intent, even if the exact keywords are missing.

For SEOs, this means that content must align with search intent – not just keywords. 

Well-structured, high-value content that directly addresses users’ questions will outperform pages optimized solely for keyword density.

Dig deeper: Content mapping: Who, what, where, when, why and how

3. The best way to uncover intent? Read the SERPs

The number one way to understand search intent is to study the search engine results pages (SERPs).

Rather than guessing what a keyword means, analyzing what Google is already ranking provides a clear picture of the dominant intent behind a query.

For example, I once worked with an ecommerce company selling biscotti cookies. 

Initially, they targeted high-volume keywords like “chocolate biscotti,” expecting strong results. 

However, a quick SERP analysis revealed that most top-ranking results were recipes, not product listings.

This indicated that searchers weren’t looking to buy biscotti – they wanted to bake it. 

Instead of chasing high-volume terms with mismatched intent, the company shifted its focus to lower-volume keywords with strong purchase intent, ultimately improving conversions.

Blindly following keyword tools without SERP analysis can lead to content that attracts traffic but fails to convert.

Get the newsletter search marketers rely on.



4. Prioritize search intent over keywords

The real question isn’t just what keywords people are searching for – it’s why they’re searching.

As Google increasingly prioritizes intent over keywords, SEO strategies must evolve accordingly. A three-step process can help align keyword research with search intent:

Identify target intents

Before diving into keyword research, define 5-6 core search intents that align with business goals. Examples include:

  • “Compare mortgage rates” (for financial services)
  • “Best protein powders for weight loss” (for fitness brands)

Filter keywords by intent

Rather than focusing solely on search volume and competition, filter keywords based on clear purchase or action intent. 

This approach refines traditional keyword research to focus on what actually drives conversions.

Choose content formats that match intent

Content should match the searcher’s intent, which often requires moving beyond standard blog posts. Some high-performing content formats include:

  • Comparison articles (“Best budget vs. premium running shoes”)
  • Niche buying guides (“How to choose an ergonomic office chair”)
  • Interactive tools (e.g., mortgage calculators, pricing estimators)

By aligning keywords with intent and content formats, SEOs can dramatically improve engagement and conversion rates.

Dig deeper: Rethinking your keyword strategy: Why optimizing for search intent matters

5. Invest in content formats that convert better

Middle-of-the-funnel content – like comparison pages, niche buying guides, and Q&A pages – tends to rank better and convert more effectively than generic blog content.

With AI-driven search results delivering direct answers, traditional educational blog posts are losing traction. 

To stay competitive, marketers must create high-value content that serves the searcher’s next step.

Some of the best-performing content types include:

  • Comparison content (“Best DSLR cameras under $1,000”).
  • Niche buying guides (“Ultimate guide to ergonomic keyboards”).
  • Interactive tools (e.g., ROI calculators, pricing estimators).
  • Video-first content, which improves engagement and differentiation.

Shifting to intent-driven content formats can significantly boost both rankings and conversions.

Dig deeper: Writing people-first content: A process and template

6. Use AI wisely, but prioritize customer insights

AI tools are valuable for analyzing SERPs and understanding search intent, but they are not a substitute for real customer insights.

The best way to understand what searchers want is to talk to actual customers. Conversations, chat logs, and feedback from sales teams offer deeper intent insights than AI alone.

For those who don’t have direct access to customers, speaking with sales representatives can be just as effective. 

Sales teams repeatedly hear the same customer questions, making them an excellent source of content ideas and keyword strategy insights.

Dig deeper: How to optimize your 2025 content strategy for AI-powered SERPs and LLMs

[Watch] Next-generation SEO keyword research: Shift from traffic to search intent

Want to take your SEO strategy to the next level? Watch my full SMX Next 2024 session here.

Content marketing in 2025: 6 strategies you can't ignore

As marketers, we love to explore emerging strategies and trends to stay ahead of the curve.

However, what’s relevant and effective is always changing, despite countless case studies and think-pieces predicting the next big trend.

Content marketing, in particular, is highly susceptible to speculation and testing because it is fluid and heavily influenced by consumers’ behaviors and interests at any given moment. 

This makes it interesting, innovative and challenging.

So, what are the predictions for content marketing in 2025? Let’s dive in.

1. Spark inspiration with ‘visionary’ content

Robert Rose recently covered an emerging trend – visionary content.

Inspired by Matthew McConaughey’s TED Talk, where the actor shares his sources of motivation and inspiration, Rose relates these themes to the content.

Specifically, that content should not only appeal to the needs of one’s target audience but inspire, by giving them:

  • Something to look up to.
  • Something to look forward to.
  • A (common) hero to chase.

Whereas much recent content has focused on addressing consumers’ challenges and pain points, visionary content is more aspirational, future-thinking, and goal-oriented. 

It provides users with a vision of the future, an appetite for new ideas, and a call to look beyond their current condition. 

In Rose’s words, visionary content “lights the spark of inspiration.” For example, this could be: 

  • A sustainability brand sharing its vision of a zero-waste future.
  • A financial service company talking about the benefits of decentralized finance and what that might mean for society.

Visionary content allows brands to shape industry conversions rather than react to them. 

It helps nurture a loyal and engaged audience that looks to the brand for innovation, inspiration, and guidance. 

For brands looking to capitalize on visionary content, this means creating content that’s future-thinking, often conceptual and gives users a vision of what’s possible. 

2. Leverage short-form video for maximum reach

Short-form video formats like Instagram Reels and YouTube Shorts are nothing new, but their prevalence and importance are expected to ramp up in 2025. 

This is due in no small part to the “fast-paced nature of online consumption,” as highlighted by Forbes. 

Today’s users consume content at a rapid pace, looking for digestible information that’s easy to watch and even easier to share. 

Delivering value in bite-sized videos has allowed brands to reach more eyes in less time and increase the virality of their content. 

An economical way to create more short-form videos at scale is to repurpose long-form videos into soundbites. 

This often involves creating videos for YouTube (where there is evergreen, organic value) and then circulating shorter clips via Shorts, Reels, TikTok, etc.

Industry disruptor Gary Vee is a prime example of this, as he routinely publishes long YouTube videos, cuts clips of these videos, and reposts them on social media. 

If you manage multi-channel campaigns for clients, you can leverage a similar approach without creating unique, short-form videos.

From scriptwriters to video editing software, AI tools will make it easier for brands to generate short video content at scale.  

Dig deeper: The future of SEO content is video – here’s why

3. Optimize content for large language models (LLMs)

Until recently, SEO largely focused on optimizing for search engines like Google. 

However, with the emergence of large language models (LLMs), there’s more “digital real estate” to optimize and maximize organic traffic. 

This shift has given rise to LLM SEO, which focuses on enhancing content visibility and ranking within AI-driven search engines.

The results of LLM SEO mechanics can be seen when you conduct a Google Search and Google Gemini (Google’s AI model) surfaces summarized results. 

These results are pulled from websites that may be purposely (or inadvertently) utilizing LLM SEO.

What does that mean for you?

In addition to traditional SEO efforts, it may be beneficial to deploy LLM-specific strategies. 

While this area of marketing is still in its infancy, some strategies that have emerged include:

  • Implementing structured data markup in website content to help search engines and LLMs better “read” and interpret the information.
  • Incorporating contextual “cues”, via keywords (focus on semantic relevance and authoritativeness), in your content for LLMs to better understand what your content is about and how it relates to a user’s search. 
  • Consistently citing relevant and reputable sources via links, with up-to-date information from legitimate publications. This can increase the “trust” factor in SEO, making it more likely that LLMs will assess your content as reputable. 

Stay attuned to developments in LLM SEO to maximize your content’s ranking and traffic potential.

Dig deeper: Decoding LLMs: How to be visible in generative AI search results 

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4. Build high-performance content teams

The true power of content performance lies in the team. 

Without passionate and experienced people driving the strategy, even the best tactics can fall flat. 

People bring everything together – from conceptualization to execution to measurement and improvement.

Marketers rated having “high-performing team members” as the second leading factor in their content marketing success (second only to “understanding [one’s] audience”), per CMI’s recent report.

CMI survey on content marketing success

The same study reported that 86% of marketers have a dedicated content marketing team or staff person.

Building the right content team is a top priority for marketers and brands heading into 2025. 

Over-reliance on automation, tools, or contracted writers can lead to a fragmented strategy.

It’s essential to have someone steering the content’s focus, goals, and priorities.

What should you be looking for when it comes to building a team?

For one, diversity of experience. 

Look for team members who bring diverse skills, from SEO to copywriting to social media marketing, and can apply this experience to develop a robust content marketing plan.

Additionally, seek out team members who are collaborative and encouraging. 

You will want a content team that feels empowered to share new ideas, support each other, and stay attuned to emerging trends in your space. 

5. Apply psychological concepts to content

Personality psychology has many applications in content creation and marketing. 

By understanding key psychological principles, you can tailor messaging to better meet the needs of specific consumer profiles.

The study of personality types can help predict user motives, understand behavior, and craft more effective messaging. 

This leads to content that resonates more deeply with target audiences, boosting engagement and driving conversions.

In 2025, I expect psychology to play a bigger role in marketing, from analyzing Google search behavior to crafting compelling stories and influencing user actions. 

Explore psychological insights to better understand how users navigate the web and make purchasing decisions – and how to apply this knowledge to content marketing.

Dig deeper: Content creation: A psychological approach

6. Differentiate your brand by balancing AI and human content

AI-generated content has been a hot and controversial topic in recent years.

You’ll find countless technologies that leverage AI-driven algorithms and concepts, expanding across sectors like SaaS, data analytics, and SEO. 

Meanwhile, content purists remain resistant to AI-generated videos, art, blog posts, and more.

And then there’s everyone else in between.

Amid these polarized views, a growing trend is resistance to AI-generated content. 

Some consumers are put off – or even jaded – by AI content that lacks originality, personality, and authenticity. 

Conduct a casual search for conversations around AI, and you’ll find many articles and posts demonstrating the same. 

One report found that half of consumers see the use of AI as a “turnoff.”

AI-assisted content creation isn’t going away. It has its place. 

However, rejecting it could become a competitive differentiator for brands. 

Some may take an ethical stance against AI – promising never to use AI-generated content – which could resonate with audiences who prefer human-created work. 

For example, Dove has stated that they will never use AI to represent human bodies in their ads.

Each brand must decide if this stance aligns with their goals and values, as neither choice is inherently better. 

However, given the ongoing debate, more brands are likely to take a stand on AI content soon.

While these trends are not set in stone, there are clear signs they will be relevant in 2025. Only time will tell how they will unfold. 

Stay curious, keep testing, and listen to real-world conversations – often, the best insights come from the people we aim to serve.

Google had this really visible bug over the past week, where the number of reviews shown on a Google Business Profile, was showing fewer reviews than it should have. In short, Google was not adding up the reviews accurately but no reviews were actually removed from the business listing.

That being said, Google posted an update that it has resolved the bulk of the issues but there still may be some that are not fully restored yet. The remaining reviews count should be fixed within the coming days, Google said.

What Google said. Victoria Kroll from Google posted an updated statement last night in the forums saying:

Most affected profiles now display accurate ratings and reviews. However, while we have made significant progress, some profiles may still experience a temporary lower count. These profiles should recover to pre-issue levels over the next few days. No reviews were unpublished due to this issue. If your review count does not return to the level it was before this issue in the next few days, please contact support.

What to do next. If you notice your review count is not back to normal but Tuesday of next week, then it may be time to reach out to support. You can reach out to support over here, either in the forums or by the contact us options in the footer of that page.

More details. On Friday, I reported on the issue on the Search Engine Roundtable, not knowing if it was a bug or a feature. I noticed dozens and dozens of complaint threads popping up in the Google Business Profiles forums from concerned small businesses and local SEOs. Google began rolling out a fix for this issue this past Tuesday.

Many businesses were concerned that their hard earned reviews were gone forever. But it was just a review count issue and the reviews were still showing on their profiles.

Why we care. Reviews are an important part of your businesses online reputation and can lead to you getting a visit or phone call, or not. So having positive reviews is important.

Losing those reviews caused a lot of concern and stress for small businesses and the local SEOs who service them.

Google has fixed most of them and will continue to work to restore the rest by the weekend.

Google has updated its Merchant listing structured data guidelines to add a new beta for member pricing priceType, aka validForMemberTier property. Google also clarified the active prices, sale prices, strikethrough prices with more examples and instructions.

What Google said. Google added examples and instructions for using the priceType property and new beta validForMemberTier property to encode active prices, sale prices, strikethrough prices, and member prices in JSON-LD to the Merchant listing structured data guidelines, the search company announced.

They did this to “make it easier for merchants to specify complex pricing through structured data and bring parity with price features in Merchant Center,” Google said.

Member pricing. The member price is the price at which the product is offered to a member of a particular loyalty program.

These prices are encoded using price specifications under the Offer object (with the exception of the active price, which can also be encoded at the offer level). The respective price specifications are identified by the price specification properties priceType and validForMemberTier, which must not be used together:

  • Active prices have neither a priceType nor a validForMemberTier property.
  • Strikethrough prices set the priceType property to StrikethroughPrice (for a transition period, ListPrice is also allowed) and cannot have a validForMemberTier property.
  • Member prices are marked with a validForMemberTier property and cannot have a priceType property.

Active price. The active price is the price at which the product is currently offered.

Strikethrough price. The strikethrough price is the the price during a sale, the higher regular price at which the product is normally offered. It may be displayed as a struck-through price to draw attention to a lowered active price.

Why we care. If you offer member loyalty pricing, then this beta is something you may want to give a try. If you want to better understand the various pricing types offered in this structured data, you should review the Merchant listing structured data guidelines again.

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Google released comprehensive answers to the most frequent questions about Performance Max, based on feedback from webinars, advertiser roundtables, and account team interactions.

The big picture. Performance Max has become a central piece of Google’s advertising ecosystem, but marketers have expressed concerns about its “black box” nature and effectiveness across different business goals.

Why we care. As advertisers grapple with Google’s AI-powered Performance Max campaigns, the company addresses crucial questions about transparency, lead quality, and campaign optimization. With some of their latest updates released this year, Google has made new updates to this guide that they started creating last year.

Key concerns addressed:

  • Channel-level reporting transparency
  • Lead quality optimization
  • Brand safety and guidelines
  • Campaign structure best practices
  • Branded query control
  • Creative requirements, including video assets
  • Customer acquisition vs. remarketing
  • Geographic targeting
  • Integration with Demand Gen campaigns

Between the lines. The FAQ release suggests Google is actively working to address advertiser skepticism while maintaining the AI-driven approach that powers Performance Max.

What’s next. Google indicates this is an evolving document, with plans to add more FAQs based on continued advertiser feedback and platform updates.

Bottom line. While Performance Max remains a powerful tool for cross-channel advertising, Google acknowledges the need for greater clarity and control to help advertisers maximize their results.

Go deeper. Advertisers can check back regularly for updated responses as Google continues to expand its FAQ documentation.