Make 2025 the year you take home the highest honor in search

Winning an industry award can seriously impact how customers, clients, and colleagues regard your brand. Showcase your achievements and celebrate your professional excellence by entering the Search Engine Land Awards – the highest honor in search marketing!

For the past 10 years, the Search Engine Land Awards have honored some of the best in the search industry – including leading in-house teams at Wiley Education Services, T-Mobile, Penn Foster, Sprint, and HomeToGo – and exceptional agencies representing Samsung, Lands’ End, Stanley Steemer, and beyond.

This year, it’s your turn. The 2025 entry period is now open!

Here’s what you need to know:

  • This is the 10th anniversary of the Search Engine Land Awards, a program designed to celebrate individuals, agencies, and internal teams within the search marketing community who have demonstrated excellence in executing organic and paid search marketing campaigns.
  • This year’s program features 19 unique categories, from Best Use of AI Technology in Search Marketing to Agency of the Year… click here to explore them all.
  • Applying is easier than ever – send us an executive summary that showcases, in 750 words or less, the award-worthy work you and your team performed this past year.
  • Completing your application empowers you to reflect on an impressive year of work, featuring its successes and lessons learned – an invaluable exercise for you and your team.
  • Winning a Search Engine Land Award is a unique, rewarding, and cost-effective way to put your organization a step ahead of its competitors, gain well-earned publicity, boost company morale, and more.
  • Submit your application by May 23 to enjoy Super Early Bird pricing – just $395 per entry ($300 off final rates!).
  • Not sure where to begin? Check out this helpful collection of advice straight from past judges for insights on what makes a winning application.

Don’t miss your opportunity to participate in the only awards program recognized by Search Engine Land, the industry publication of record. Begin your application today! 

Read more at Read More

Google vision match vs. traditional search: Early insights on AI shopping tool

Vision match vs. traditional search: Early insights on Google’s AI shopping tool

With Google’s introduction of its vision match feature, users can now describe a product they’re looking for, and AI will generate suggestions similar to that item. 

The real kicker is that the product generated likely doesn’t exist. 

The AI will create something that you want, show you the product, and then try to match the AI product with items from the real world.

Google Shopping - Vision match

It sounds like a streamlined, user-friendly shopping experience that could revolutionize online shopping yet again. 

  • But does it actually enhance our shopping journey? 
  • Are these AI-generated results truly more effective than the product results we get from traditional Google search? 
  • What does this mean for advertisers? 

To find out, I tested the feature myself, comparing vision match results with standard search results for a few product categories. 

What I found may give you a new perspective on the role AI plays in online shopping.

Test 1: Vision match ‘suggested query’

To start, I choose one of vision match’s “suggested queries.”

  • Search query: “holographic platform boots with metallic highlights”

Vision match results

Vision match - holographic platform boots with metallic highlights

Sponsored shopping results

Sponsored shopping results - holographic platform boots with metallic highlights

Free listing results

Free listing results - holographic platform boots with metallic highlights

Interestingly, my AI-generated image results are more accurate than the “shop similar-looking product” results. 

While the product recommendations included some metallic holographic platform boots, they also included a mix of non-metallic boots and even a prom dress. 

So, what’s the point of the AI-generated images if they’re not actually helping me find the product I want but instead creating a fake version of it? 

Wouldn’t it be more sensible to expand the “Shop Similar” section beyond six products and give us more real options? 

What also stands out to me is the selection of retailers. 

I’ve never heard of most of these retailers. Some results come from resale platforms like eBay and Poshmark. 

And then there’s the cost difference. The average price of the AI-generated product recommendations? 

A whopping $230, with some listings going as high as $954. 

Meanwhile, the average price from a regular search? Just $75.

Looking at my shopping results, every product in the first carousel (and beyond) is a pair of holographic platform boots with metallic highlights and nothing else. 

Now, I’m not planning on attending a disco party anytime soon, but if I were, I’d know where to go: Google Search.

Contender  Grade
Vision match D+
Traditional search A

Next, I tried a broader query, hoping for more accurate results. 

Test 2: Non-specified search (statement piece)

  • Search query: “mens red button down shirt”

Vision match results

Vision match - mens red button down shirt

Sponsored shopping results

Sponsored shopping - mens red button down shirt

Free listing results

Free listing - mens red button down shirt

The first AI-generated image and product suggestions did show a red button-down shirt (though some may argue it’s an orange-red.) 

From there, I got a mix of red button-downs, some with patterns and textures. 

Overall, it wasn’t bad, but the price range was still all over the place.

I still find myself drawn to the traditional search results. 

When I search for “men’s red button-down shirt,” I get exactly what I asked for. 

No guesswork, no unnecessary variations. 

Plus, I’m given valuable details upfront, like:

  • Discount percentages.
  • Customer ratings.
  • Product attribute callouts (“comfortable,” “easy to clean”). 

These elements make the listings far more compelling and trustworthy, which incentives my click – unlike the AI-generated results, which feel more like a best guess than a true recommendation.

Contender  Grade
Vision match C
Traditional search A

Get the newsletter search marketers rely on.



Test 3: Brand search

You’d expect that searching for a specific brand name would surface products primarily from that brand’s official website, right?

Not quite.

I ran this search multiple times just to be sure I wasn’t imagining things – and still, less than 3% of the results actually came from Nike’s own site.

  • Search query: “Nike sneakers”

Vision match results

Vision match - Nike sneakers

Sponsored shopping results

Sponsored shopping - Nike sneakers

Free listing results

Free listing - Nike sneakers

Even worse, I was given additional irrelevant results – New Balance sneakers, socks, leggings, and blue polka dot blankets – definitely not Nike sneakers.

Sponsored shopping is a different story.

Since other major retailers carry Nike products, it makes sense to see them appear alongside Nike. 

However, when looking at the free listings, all my results come from nike.com. 

So, what does this mean for brands? 

If Nike, one of the world’s largest retailers, is hardly featured in the vision match results, what does this mean for smaller brands? 

Will they struggle even more to get visibility in vision match and possibly other future AI-generated product recommendations?

Contender  Grade
Vision match D-
Traditional search A+

Test 4: A trending search

For my final test, I wanted to see how AI would handle a fashion trend rather than a standard clothing item. 

Trends come and go quickly, creating a high demand for a short period of time, unlike staple pieces like a “men’s red button-down shirt,” which remain relevant year after year. 

This felt like an important test, given how fast fashion moves and how crucial it is for shopping tools to keep up with ever-changing styles.

  • Search query: “barrel jeans”

Vision match results

Vision match - barrel jeans

Sponsored shopping results

Sponsored shopping - barrel jeans

Free listing results

Free listing - barrel jeans

If you haven’t heard of the “barrel jean” trend, don’t worry; you’re not missing much in the vision match results because they’re completely wrong. 

I only included three screenshots, but after scrolling through everything, I didn’t spot a single pair of actual barrel jeans. 

Instead, I got jeans in every color and pattern imaginable, along with some random dress slacks.

Meanwhile, a simple Google Search gave me exactly what I was looking for: a variety of barrel jeans from well-known retailers available in different price ranges and washes. 

It’s pretty clear that when it comes to keeping up with fashion trends, AI might be trending, but vision match still isn’t fashion-forward.

Contender  Grade
Vision match F
Traditional search A+

The final verdict

In my experience, while vision match offers an interesting new way to search for products, it still has a long way to go in terms of accuracy and relevance. 

In each test, it struggled to provide precise matches for the products I was looking for, often offering unrelated items or a confusing mix of options. 

On the other hand, traditional search results from Google gave me exactly what I wanted: clear product options, price ranges, and relevant details that helped me make an informed decision. 

Let’s take a look at the final results of our test:

Contender  Grade
Vision match D
Traditional search A

I understand that these results are subjective, but anyone with search intent would agree that a D average is generous in this case. 

So, what does this mean for advertisers? 

As AI-generated results grow, advertisers must continue to adapt their strategies to ensure their products are accurately represented. 

However, with limited control over what’s featured in vision match, this will be very difficult. 

Given that the current vision match results seem subpar, users will likely still prefer the traditional search results, which continue to provide more accurate and relevant options. 

While vision match has potential, its current limitations likely won’t sway many users away from the search results for now.

Read more at Read More

Your 2025 playbook for AI-powered cross-channel brand visibility

Search Engine Land - Fractl Agents Header

AI is changing how people find and engage with content – but the core signals that drive visibility haven’t changed. 

This article shows how search marketers can stay competitive by combining proven SEO and content strategies with AI-powered workflows to build authority, trust, and reach across platforms.

Why authority still wins in the age of AI search

If you work in marketing, you’ve probably heard the same questions repeated throughout the past year:

  • “What’s AI’s impact on organic search?” 
  • “How can my brand appear in AI-driven search results?” 
  • “Is it safe to use AI in my content workflow?” 

While many agencies and experts are rushing to stake a claim in the new frontier of “AI brand visibility,” industry leaders are aligning around the idea that search engine and AI optimization rely on similar signals. 

Whether you’re using Google or ChatGPT, both platforms strive to surface the most authoritative, relevant content on a given subject. 

They do this by identifying which entities (brands or sources) have provided robust subject matter expertise (contextual relevance) backed by strong third-party authority signals (e.g., citations from trusted sources). 

In other words, the fundamentals that make your content rank highly on Google – expertise, authority, and trustworthiness – also increase your visibility in AI-generated answers.

If you’ve paid attention to effective content marketing strategies over the last decade, keep creating unique, valuable, educational, and engaging brand content enriched with proprietary data and expert insights. 

This approach:

  • Builds credibility and provides fresh expertise beyond what AI alone can produce, which all channels seek to surface. 
  • Earns coverage and citations from authoritative sources across diverse platforms.
  • Strengthens your brand’s authority, diversifies visibility, and drives qualified traffic and cross-channel conversions. 

Meanwhile, if you’re simply using ChatGPT to churn out regurgitated content for top-funnel informational queries – you might as well burn your marketing budget. 

In 2025, it’s critical not to get lost in another “SEO is dead, long live […AI]!” echo chamber. 

We’re 14 years into this recurring, sensationalized industry news cycle, yet search interest is still growing.

SEO is dead - Google Trends
SEO - Google Trends

If we slow down and look at the facts, Google now processes over 5 trillion searches per year (with a 20%+ YoY growth).

AI tools like ChatGPT are expanding search behavior, not replacing it. 

Up to 70% of ChatGPT prompts involve collaborative, custom tasks like code debugging or meal planning, per a recent Semrush study. 

These are things classic search wasn’t built for. 

Growth of Google searches, 2023-2024

Regardless of what we dub this era of “AI optimization,” one thing remains true: the value of cross-channel, inbound marketing reigns supreme, as it has since the dawn of digital. 

While we don’t always need a new industry buzzword, generative engine optimization (GEO) has grown in interest significantly over the last 12 months.

Agency goliaths are starting to invest in their own content strategies around it. 

Ian Lurie on Bluesky
Generative engine optimization - Google Trends

Most brand channels rely on similar ranking principles. 

So, instead of panicking about the latest platform shifts, challenge your team to pause and reflect. 

How do you use AI to scale effective, cross-channel marketing strategies and workflows to sustain your brand’s visibility?

Specifically:

  • How are we building content ecosystems that establish topic authority while earning trust and driving engagement across multiple platforms?
  • Have we done audience research to understand where our target market resides, and are we effectively using AI to scale cross-channel content syndication to those platforms? 
  • Where else should we seek to apply AI to automate our proven marketing workflows to improve efficiency, reach, and ROI? 

Here’s how my agency uses prompt engineering, custom GPTs, and proprietary AI agents to streamline digital marketing – and how your team can, too.

1. Using AI to create newsworthy campaigns with strong E-E-A-T

One of the highest ROI activities your brand can invest in now is proprietary research that produces insights AI can’t replicate. 

This type of content gets cited by publishers, builds domain expertise, and increases your chances of influencing AI training data itself.

You don’t need to build bleeding-edge agentic workflows to see real impact from AI in your marketing. 

Even teaching your team simple prompt engineering and having them build custom GPTs can help streamline your workflows. 

AI can handle tedious tasks – like deep research and data analysis – so your team can spend more time on strategy and creative thinking. 

Below are a few examples of AI-enhanced content workflows any brand can adopt. 

Reactive PR campaign prompts

Use AI to research and brainstorm campaign ideas based on breaking news that aligns with the brand’s vertical and target market. 

For example, you might prompt ChatGPT to take on a digital PR persona tasked with scanning breaking news in your industry from the past 24-72 hours and generating timely campaign ideas.

This kind of AI-assisted brainstorming ensures your content ideas are timely and poised to earn media attention without waiting for time-intensive human research and ideation sessions. 

Sample prompt 

  • Role: You are a digital PR strategist for [Brand], tasked with identifying trending, high-authority news stories in [Topic/Industry/Region] from the past 24-72 hours and generating timely, data-driven campaign ideas that use the brand’s expertise to secure mainstream media coverage.
  • Campaign criteria:
    • Trend-driven: Focus on viral/trending topics from major outlets, TikTok, Reddit, X, Google Trends.
    • Brand-relevant: Align with [Brand]’s domain expertise.
    • Timely and actionable: Campaign can be executed within 24-72 hours.
    • Data-backed: Use rapid methods – pulse surveys, social scraping, Google Trends, proprietary data.
    • Emotionally compelling: Ideas must be timely, educational, emotional, or entertaining.
  • Campaign structure:
    • Title: A concise, engaging campaign title.
    • Description: Explain the campaign idea, key insights/questions, target audience, and tie to current news + brand’s expertise.
    • Methodology: Outline how you will gather and analyze data (e.g., surveys, social scraping, government datasets, trends).

Dig deeper: Reactive PR and AI: How to capitalize on trending topics faster

Data journalism campaign prompts

Consider training a custom AI model on your own archive of successful content marketing campaigns (or case studies from your industry) to generate fresh campaign ideas. 

An internal ideation agent could be fed thousands of past campaign briefs, articles, or link building projects along with their performance outcomes. 

The AI can then generate new ideas tailored to your brand’s vertical, following patterns that historically earned high authority backlinks and engagement. 

You might guide it with criteria. For instance, the idea must:

  • Have a high likelihood of attracting authoritative .edu/.gov/.com links.
  • Be data-driven and unique.
  • Align with your business goals.
  • Be timely or seasonal.
  • Include a visually engaging component. 

This way, the AI isn’t pulling generic ideas from thin air – it’s remixing elements of proven hits to suggest the next big content piece. 

Sample prompt

  • Role: You are a creative data-driven PR strategist, tasked with generating newsworthy, high-authority campaign ideas that earn backlinks from top-tier media (.com), government (.gov), and educational (.edu) sites. You focus on creating unique, engaging, and data-backed campaigns tailored to [Brand]’s specific vertical (e.g., education, tax, aviation, hosting, creative industries).
  • Campaign criteria:
    • High-authority potential
    • Data-driven
    • Creative and unique
    • Aligned with goals
    • Timely 
    • Visually engaging 
  • Approved methodologies
  • Campaign structure:
    • Title 
    • Description 
    • Methodology 

Ideation scoring prompt

Another valuable use of AI is evaluating and refining newsworthy brand content at scale. 

Marketing teams constantly brainstorm ideas for data journalism campaigns, blog posts, and social content. 

Based on learned criteria, an AI agent can rapidly assess each idea for “newsworthiness” or virality potential. 

For example, you can program an AI to act as an editorial panel that:

  • Scores ideas on a scale for promotional viability.
  • Suggests which statistics or angles would make the idea more compelling to the press.
  • Even recommends how to execute the methodology more rigorously.

This doesn’t replace your decision-making, but it helps streamline a recurring process that has a proven framework that AI can help scale. 

Sample prompt

  • Role: You are a data journalism and PR expert tasked with evaluating the newsworthiness and promotional viability of data-driven campaign concepts, including surveys, studies, meta-rankings, and analyses. Your role is to rate the idea’s media potential, suggest the best promotional angles (headlines/takeaways), and refine the methodology to ensure data accuracy and media appeal.
  • Evaluation process:
    • Promotional viability score 
    • Potential headline-worthy takeaways
    • Suggested name 
    • Methodology recommendation

Beyond these examples, dozens of other AI applications can streamline your content workflow. 

Forward-thinking teams are deploying custom AI assistants for tasks such as:

  • Writing survey questions.
  • Building campaign briefs.
  • Identifying typos or brand guideline violations.
  • Discovering unique data sources or variables for new research.
  • And so much more. 

An AI agent can improve any repetitive or data-intensive part of content creation. 

Once you’ve used AI to assist in creating high-quality, E-E-A-T-rich content, the next step is to ensure that the content gets in front of the right audience. 

This is where AI can also play a game-changing role in distribution and PR.

2. Scaling digital PR with AI

Building your brand’s authority and trust through earned media has become more critical in an era of AI-driven search results. 

Google’s algorithm and AI models prioritize widely cited and trusted content, favoring brands with strong E-E-A-T signals. 

Digital PR helps secure high-authority backlinks and trusted media mentions that improve search rankings. 

These efforts also increase the likelihood of being featured in AI-generated results, as LLMs are trained on well-cited, newsworthy sources.

In short, earning mainstream news and authoritative, niche-relevant brand coverage simultaneously strengthens your visibility across search, social, and emerging AI platforms.

AI holds enormous potential for PR teams. It can:

  • Research journalists.
  • Personalize outreach.
  • Even draft pitches in seconds. 

Still, we must pair scale with skill.

Relying too much on automation can lead to spammy, robotic pitches that journalists ignore (or resent). 

Rather than blasting out “just another AI-generated pitch,” smart PR teams use an AI-powered, human-perfected workflow.

AI handles the heavy lifting – research, pattern-based tasks, and first drafts – while humans focus on strategy, messaging, and real relationship-building. 

The key is scaling the repeatable parts with AI and reserving human effort for creativity, judgment, and authentic personalization.

AI and humans in marketing

Here are a few high-impact ways PR professionals can use AI today.

AI pitch strategy prompt

One of the easiest prompts to create is a digital PR strategy generator that mimics the pitch templates your team uses to earn authoritative brand coverage.

Incorporating training guides, sample pitch templates, industry pro tips, and other proprietary knowledge is crucial. 

This is key to building a GPT or agent that helps your PR team stand out in a sea of sameness.

Below are the areas you should hone in and expand when designing a PR strategy prompt.

  • Role: You are PPS savant, a digital PR Expert specialized in generating a complete pre-pitch strategy (PPS) for data-driven PR studies and media outreach. Your job is to extract the most compelling statistics from a provided study or campaign and generate a fully developed, press-ready outreach strategy, including subject lines, email copy, and a targeted media list.
  • Distill:
    • Compelling statistics 
    • Subject lines 
    • Email pitch structure 
    • Follow-up pitch structure 
    • Targeted media outlets 
    • Tone and focus 

Media list builder

Finding the right outlets and contacts is a time-consuming part of PR that AI can dramatically improve. 

Instead of manually searching media databases (or paying for expensive platforms that quickly go out of date), an AI-driven media list builder can scan recent articles and news to identify journalists and publications relevant to your content. 

For example, given a summary of your campaign or a PDF of your research, an AI agent could compile a list of the 30–50 most relevant publishers and reporters, including:

  • The outlet name.
  • A link to a recent similar article (to prove relevance).
  • The journalist’s name and beat.
  • Even metrics like the outlet’s traffic. 

This increases the odds of getting interest and saves thousands of dollars that might have been spent on static media databases. 

Sample prompt

  • Role: You are a digital PR publisher expert who analyzes brand studies to identify the 40 most relevant, high-authority news outlets based on the provided resource. Your focus is on matching the content (attached PDF) to vertical-specific, top-tier outlets and ensuring maximum relevance and link potential.
  • Publisher recommendations should include:
    • Publisher name
    • Root domain (clickable URL)
    • Vertical section (e.g., “All Finance”, “Lifestyle”, “Health”, “Education”, etc.) 
    • Domain authority (DA) 
    • Site traffic 
    • Relevant post 

Blog search

Beyond mainstream media outlets, much of the “long tail” of PR success comes from niche blogs and industry influencers who syndicate or share your content. 

Here, too, AI can make a huge difference. 

To solve this, we built a “blog search agent” that runs a semantic search across 20,000+ active (non-spam) blogs from Kagi’s Small Web to help uncover niche-specific influencers who regularly update their smaller, mid-tier sites for highly relevant audiences. 

Blog search - AI agent

By using AI in these ways, PR teams can significantly increase the speed and quality of their outreach, leading to more authoritative coverage. 

Top brands already use these tactics to land stories in national newspapers and specialized trade publications.

More than algorithmic efficiency, effective PR requires credible, newsworthy content and authentic human relationships. 

AI can help you write 10 pitches in the time it used to take to write one.

Still, if the core story isn’t strong or you haven’t bothered to personalize it, journalists will delete your email. 

Get the newsletter search marketers rely on.



3. Streamlining social content syndication with AI

New search and social platforms will inevitably rise and fall

However, one principle remains constant: marketers must repurpose and syndicate their best content across the diverse platforms where their audience engages. 

In the age of AI, diversification is key for building defensible brand visibility and traffic. 

A blog post that earns links and ranks on Google can be adapted into an X thread, a Reddit post, a LinkedIn article, a TikTok script, or a YouTube video.

Each extension reinforces your expertise and reaches new pockets of your audience. 

Consistent cross-platform visibility boosts SEO and engagement and trains AI models to recognize your brand’s authority everywhere.

Share of social media referrals to the web

Many content teams excel at creating high-value content, but they often lack the bandwidth or distribution tools. 

By automating parts of the syndication process and optimizing content for each channel, AI ensures your work actually gets seen. 

Here are a few ways AI can amplify your cross-channel content strategy.

Reddit advice tool 

With Reddit dominating the SERPs, it’s a crucial time to evaluate this social platform as another avenue for your content syndication. 

This agent helps your social team:

  • Identify relevant subreddits for your brand content.
  • Develop suggested titles and justify why that style would resonate with each specific community.
  • Generate article summaries to get you started. 
Reddit advice tool 

AI image creation 

AI is making creating eye-catching graphics, illustrations, or photos to accompany your content easier than ever.

That said, the jury is still out on the best models and prompts that can make or break your brand’s output. 

A few of my personal favorites include DALL-E 3, Midjourney, and Stable Diffusion, which can produce custom images that were unimaginable a few years ago. 

Still, the key difference is the quality of your prompt engineering.

Often, the best prompt designers are those with a creative eye, like graphic designers, who will know how to coax the model toward a desired style or factual accuracy. 

The result: your content stands out in crowded feeds without the cost or time of a full photoshoot or graphic design cycle for every piece.

AI generated image post by John Mueller

Dig deeper: How to create images and visuals with generative AI

Diversifying and repurposing content across channels is no longer optional. It’s essential for building a resilient brand presence. 

AI makes this far easier by taking on the heavy lifting of format adaptation. 

Your most valuable content assets can live multiple lives: a research report can spawn dozens of social posts, videos, and media pitches. 

A single great insight can become an infographic, a blog, a webinar, and a Reddit AMA. 

With AI handling the transformation and distribution at scale, you can ensure that no piece of content potential goes untapped. 

The payoff is greater reach, more engagement, and a brand that appears ubiquitously wherever your audience (or the algorithms) might look.

AI tools and agents will transform 2025 marketing strategies and workflows 

If there’s one overarching lesson in all of this, it’s that AI isn’t replacing great marketers – it’s amplifying their proven workflows and freeing up time for even greater innovation. 

The brands that outpace their competition in the next 1–3 years will use AI to scale proven marketing workflows.

Humans will stay relentlessly focused on driving creativity, building community, and establishing trust. 

Forward-thinking teams are already investing in comprehensive AI toolkits that touch every aspect of marketing: 

  • Content research and clustering.
  • Content optimization.
  • Digital PR outreach.
  • Technical SEO analysis.
  • Social media scheduling.
  • Sentiment analysis.
  • And much more. 

These early adopters recognize that nearly every marketing workflow will have some element that AI can improve. 

By experimenting now, they’re building a foundation of AI-augmented processes that will be standard practice for everyone else a few years later.

The message for marketing leaders is clear: don’t wait. 

  • Encourage your team to pilot AI in different parts of your operation and see what boosts your efficiency or results. 
  • Create internal case studies of what works (and share these insights with peers, contributing to industry knowledge). 

Remember, the goal isn’t to hand everything over to machines. It’s to let machines do what they’re great at so that humans can do what they’re great at. 

The winning formula is AI + human, not AI vs. human.

In 2025 and beyond, success in SEO and cross-channel marketing will come down to this balance. 

The hype cycles will continue – new tools, algorithms, and platforms – but the fundamentals remain.

  • Know your audience.
  • Create real value.
  • Earn trust.
  • Be everywhere your audience is looking. 

AI is simply the newest (and arguably most powerful) set of tools to help you execute on those fundamentals at scale. 

Those who embrace these tools thoughtfully will:

  • Safeguard their brand’s visibility.
  • Reclaim precious time to focus on strategy and big ideas.
  • Foster the human connections that truly build brands. 

And that’s a winning playbook, no matter how search evolves.

Bottom line? 

AI will boost your growth strategy if you don’t shy away from being an innovator on the technology adoption curve. 

Innovators vs. laggards

Your 2025 brand goal is simple.

  • Repurpose your most valuable content to achieve cross-channel brand visibility, authority, and engagement where your target market resides.
  • Hedge against the rapidly evolving AI landscape that will reshape consumer behavior over the next 12-36 months.

Read more at Read More

Google Search Console updates its Merchant opportunities report

Google announced it has refreshed and renamed the Search Console report now known as the Merchant opportunities report. Previously, this report was named the Search Console Shopping tab listings report, when it was introduced in November 2022.

The Merchant opportunities report within Google Search Console can show you recommendations for improving how your online shop appears on Google.

What Google said. Google posted on LinkedIn about this report saying:

“Today we’re refreshing the Search Console Shopping tab listings report to also include details about payments methods and store ratings. To bring the report name in line with its functionality, we’re renaming it to be the “Merchant opportunities report”.

Check it out and make sure to add important info about your store, so customers can see it when shopping on Google.”

The report. Here is a screenshot of this report:

As you can see, this report will tell you what you are missing when it comes to Google Merchant Center and your fields in that area. The help document goes on to explain:

Adding store information can improve the display of your products and help people when they’re shopping on Google. If you’ve created and associated your Merchant Center account under Merchant opportunities in Search Console, you’ll see suggested opportunities, including: 

You can return to the report to see if your information is pending, approved, or flagged for issues that need fixing.

Why we care. If you sell product on your site, this is a report you want to make sure to review and see what opportunities you are missing with your e-commerce site setup. You can then plug those items and hopefully get more exposure within Google Search, Shopping and even local results.

Read more at Read More

The uncontested paid search problem—and what it’s costing you by Edna Chavira

Join us live!
Save your spot!

Are you paying too much for branded search ads, even when you’re the only one bidding?

A hidden flaw in Google Ads could be driving up your CPCs unnecessarily. You’re not alone. And you’re not imagining it. 

Join Jenn Paterson and John Beresford from BrandPilot AI for The Hidden Cost of Google Ads: Solving the Uncontested Paid Search Problem where they’ll reveal:

  • Why CPCs are inflated on branded terms—without active competition
  • How this self-bidding trap happens, and what it’s costing you
  • The true scale of wasted spend across paid search accounts
  • How to stop this problem and take back control of your brand budget

This is the insight your campaigns—and your budget—deserve. Save your spot here!

Read more at Read More

Advertisers pull back from TikTok, boost Meta amid ban uncertainty

TikTok search

Already facing a sale or ban order, TikTok faced additional pressure in Q1 as major brands scaled back advertising spending and shifted budgets to Meta, according to new data.

By the numbers:

  • TikTok’s U.S. cost-per-thousand-impressions (CPMs) dropped sharply, posting double-digit declines since January.
  • 8 of TikTok’s top 10 advertiser categories cut spending in Q1 2025 compared to Q1 2024.
  • User activity dipped in January during a temporary service blackout, further rattling confidence.

The big picture. Despite the turbulence, TikTok is expected to rake in $14.8 billion in U.S. ad revenue this year, according to eMarketer. That puts it behind Facebook’s $36.9 billion but ahead of YouTube’s $9.9 billion.

Behind the shift. Advertisers aren’t abandoning TikTok entirely, but many are hedging. They’re shifting parts of their budgets to platforms with less uncertain futures.

  • “No one’s acting like TikTok is gone – but no one’s pretending it’s business as usual, either,” said Raul Rios, head of strategy at independent creative agency Saylor.
  • “Brands that swiftly resumed advertising on TikTok post-ban are staying the course, but many remain hesitant, keeping media spend lower despite months of attractive incentives,” said Toni Box, EVP of brand experience at Assembly.

Meta’s moment. While TikTok wobbles, Meta is cashing in. Facebook and Instagram have leaned hard into short-form video:

  • Facebook and Instagram’s short-form video CPMs are rising fast as advertisers reallocate spend.
  • “It’s undeniable that Facebook and Instagram have made CPM growth a key initiative,” said Jason Krebs, GM of media at Varos.

Why we care. This shifting ad spend carries immediate financial risks and strategic disruption. TikTok’s lower CPMs may seem like a short-term bargain for brands. However, if the platform faces a full ban after mid-June, those investments could evaporate. For brands that have optimized for TikTok’s unique algorithm and culture, moving to other platforms could mean starting over – new content formats, new metrics, new audiences.

What’s next. All eyes will be on Washington and ongoing acquisition talks. If a deal saves TikTok, advertisers may return. If not, Meta’s gains could become the new normal.

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Google AI Mode lets you ask questions with images

Google has added multimodal capabilities to its new AI Mode feature, letting you ask your questions with the assistance of uploading an image. Plus, Google announced it is rolling out AI Mode to millions of more Labs users in the U.S.

AI mode with images. Google AI Mode now lets you upload an image via upload or your camera to ask AI Mode questions with images. Google calls this multimodal capabilities, which is launched years ago in other areas of Search.

“With AI Mode’s new multimodal understanding, you can snap a photo or upload an image, ask a question about it and get a rich, comprehensive response with links to dive deeper,” Robby Stein, VP of Product, Google Search wrote. He added:

“AI Mode builds on our years of work on visual search and takes it a step further. With Gemini’s multimodal capabilities, AI Mode can understand the entire scene in an image, including the context of how objects relate to one another and their unique materials, colors, shapes and arrangements. Drawing on our deep visual search expertise, Lens precisely identifies each object in the image. Using our query fan-out technique, AI Mode then issues multiple queries about the image as a whole and the objects within the image, accessing more breadth and depth of information than a traditional search on Google. The result is a response that’s incredibly nuanced and contextually relevant, so you take the next step.”

What it looks like. Here is what it looks like in action:

Millions more gain access to AI Mode. Google said, “we’ve now started to make AI Mode available to millions more Labs users in the U.S.” I mean, I am not sure if this is new. We saw Google expand access to those who do not have Google One AI Premium subscriptions a couple of weeks ago. And then last week, Google invited a third batch of users to AI Mode.

So maybe Google is opening up a fourth batch of invites today?

Why we care. Google’s new AI Mode does feel like the future of search, in many ways. So it is important that you all try it out as soon as you can, and watch it as it adapts.

Soon you may all be looking for ways to get traffic from AI Mode as opposed to just Google Search and AI Overviews.

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Dealing with Google Ads frustrations: Poor support, suspensions, rising costs

Dealing with Google Ads frustrations: Poor support, suspensions and rising costs

Google Ads has 718 reviews on TrustPilot with a 1.1-star rating.

That’s a shockingly low score for a platform that has helped countless businesses grow and created entire careers in digital marketing.

Let me preface this by saying that this isn’t meant to be an angry rant. 

Google Ads has provided incredible opportunities, but the overwhelming number of negative reviews clearly shows that advertisers face serious frustrations daily.

Poor support, unexplained account suspensions, rising costs, and a lack of transparency have left many users feeling helpless. 

These aren’t just isolated issues – they’re widespread problems that need attention.

So, what exactly is going wrong? And more importantly, how can it be fixed?

Here’s a breakdown of the most common complaints about Google Ads – and what could be done to improve the platform.

Poor customer support

Users frequently report that customer support is unresponsive, slow, or provides generic, unhelpful responses.

Many of us have experienced the customer service loop of Google Ads: 

  • Contact support.
  • They submit a ticket.
  • Ask you to allow 3-5 days for a resolution. 

After eight days, you contact support again, and the process repeats with no resolution. 

Several weeks or months later, the issue may be resolved – or not.

It’s unclear what the internal protocol is for Google Ads support; it doesn’t seem to follow the standards of most major companies. 

There appears to be a lack of account notes and follow-up. 

Users report contacting support for the same issue, opening a ticket, but receiving no further response. 

Another ticket is then opened, and the cycle continues. 

If a customer support representative remembers, they may send an email with the reference number. 

When contacting support a second time, little to no information can be provided using the reference number. 

Support often says, “There is no update on your ticket; please allow 3-5 more days.”

This is a nightmare for business owners, freelancers, and ad agencies trying to manage their Google Ads accounts and resolve issues quickly.

If Google Ads consistently sent feedback surveys, it could significantly improve customer support. 

However, many users are no longer receiving the surveys – either after a phone call or because the link is not sent after a live chat.

If you do receive a survey via email or see one pop up in your account, be sure to fill it out thoroughly. 

We can’t expect to improve customer service without providing constant feedback.

Account suspensions

Account suspensions without clear explanation and slow response times are common complaints with Google Ads.

While Google Ads needs to suspend accounts that blatantly violate their policies, they should be handled more quickly for accidental violations that can be resolved with a simple ad rewrite.

Many new accounts are suspended quickly but approved slowly, often taking weeks or months, if ever – despite the issues being corrected to comply with Google Ads’ policies. 

When accounts are suspended, the explanation is often vague.

Customer support representatives typically just read what’s on the screen, offering no further explanation, resolution, or assistance.

A frequent reason for account suspensions or ad disapprovals is a “Policy Violation,” but the specific policy is rarely cited. 

Even after the user resolves the issue, the account or ad may still be delayed in approval, sometimes taking weeks or months. 

For advertisers in sensitive categories (i.e., mental health services, supplements, housing, employment, recruiting, technical support services, or financial services), quick suspensions and slow resolutions can be devastating. 

These businesses often have everything in place to comply with Google Ads’ policies but may have made a minor mistake during ad setup.

Another common suspension reason is “Circumventing Systems Policy,” but once again, the explanation is unclear, causing frustration over the lack of transparency in enforcement. 

This often happens with businesses that hire multiple agencies or freelancers over time, leading them to be unaware of how many Google Ads accounts were set up under their name. 

Even worse, Google Ads support typically fails to explain this situation clearly, making it difficult for businesses to track who created all the accounts that got suspended. 

If these agencies or freelancers are responsible, are they now banned from running ads on Google across any account? 

This policy and review process urgently needs rethinking.

Agency owner and PPC expert Menachem Ani shared:

  • “Reps can no longer help with some of the things they were able to help with in the past. For example, we have a client whose account was suspended – but our reps can’t do anything to help us.” 
  • “While I believe that Google’s intentions are good, the reality is that many accounts get suspended incorrectly with no recourse.”

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Lack of results

Many reviews complain about a lack of results with Google Ads. 

This often stems from a lack of understanding of how to use the platform effectively. 

Basic strategies – such as choosing the best keywords, writing effective ads, controlling bidding and budgets, building relevant landing pages, and adding negative keywords – could have helped prevent these negative reviews.

Google Ads can improve by following the lead of other software companies and offering in-depth tutorials to help users get the most out of the platform.

Collaborating with industry experts outside Google to create tutorials would also help users make informed decisions about their ad spend.

Currently, Google’s advice often contradicts guidance from industry-leading publications.

Instead of conflicting guidance, open collaboration could align best practices, ensuring users who invest time in learning Google Ads can actually apply their knowledge effectively.

The running joke is that learning how to run Google Ads from Google is like learning how to play Blackjack from the casino – they don’t have your best interests in mind. 

PPC industry leader Brad Geddes specifically calls out “Recommendations I always ignore,” which, ironically, are the same recommendations that Google Reps and account notifications often advise users not to ignore. 

A collaboration between industry experts and Google Ads could be mutually beneficial, helping both the platform and its users. 

If new users take Google’s tutorials and certifications only to lose substantial amounts of money on Google Ads, they may not continue investing in the platform.

It’s unclear why the worst advice on running Google Ads comes directly from Google Ads and its reps.

Rising costs

Advertisers have also voiced concerns about the rising costs of Google Ads, which have become even more problematic in recent years. 

Search Engine Land’s Danny Goodwin reported on Google Ads’ price manipulation:

  • “The U.S. Department of Justice hammered Google over search ad price manipulation and more in its closing statement on search advertising.” 

Many business owners, freelancers, ad agencies, and industry experts are worried about these rising costs and the lack of transparency.

Boris Beceric, Google Ads consultant and coach, remarked:

  • “Google is a monopoly that’s raising prices without telling advertisers about it.” 

Google Ads’ newest update for double service ads now allows the same business’s ad to appear twice on the same page. 

Will this cause further issues for advertisers concerned about rising costs, or will it help boost results?

PPC expert Navah Hopkins also noted:

  • “Google is officially making it fair game to have more than one spot on the SERP. I have thoughts on this, but I want to see how performance actually shakes out in Q2.” 

We will have to wait and see if this helps with rising costs or hurts them. 

Issues with Google reps and Teleperformance

Many Google Ads users also express frustration with Teleperformance, Google’s outsourced customer support team. 

Complaints often include poor advertising results due to Google Reps’ advice, overly aggressive outreach, and generic or scripted responses.

Advertisers also report trust issues with Google reps, particularly after one made unauthorized changes to a business’s Google Ads account. 

Andy Youngs, co-founder of The PPC People, highlighted this, discovering a recent instance where a Google rep altered an account without approval.

TrustPilot reviews, Reddit, and nearly every social media channel are filled with complaints about Google reps.

However, Google Ads has not made significant changes to the program. 

Matt Janaway, CEO of Marketing Labs, stated:

  • “We get calls daily from reps that have been assigned to our client accounts. It’s very convoluted, and when we don’t engage – because we can’t possibly engage them all – they try to go directly to our clients instead!” 
  • “This happens regularly. And the scare tactics they use are quite ludicrous.”

The simple solution for Google Ads would be to train their reps to provide useful advice and assign them to a smaller number of accounts. 

An even simpler solution might be to remove the program entirely, given the overwhelming amount of negative feedback.

So, what can we do?

Direct feedback is the best way to push for change.

While posting frustrations online might feel satisfying, it’s unlikely Google Ads will see or act on them. 

Instead, be sure to complete the surveys Google sends via email or within your account, offering detailed and constructive feedback.

If you want to voice concerns publicly, you can share them on platforms like TrustPilot (Google Ads TrustPilot page), Reddit, industry forums, or social media – but always keep it professional and solution-focused.

For direct communication, use Google’s official feedback and support forms:

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Google credits Gemini for better detection of fake business reviews and maps spam

Google is crediting its AI advancement, such as Gemini, to help detect and remove fake reviews and listings within Google Maps. “AI has been a pivotal tool in helping us stop scammers in their tracks, and we’re now using it to scale our protections even more,” Google wrote.

The metrics. Google shared these metrics for its battle over Google Maps spam:

  • Google blocked or removed more than 240 million policy-violating from 2024. Google added that “the vast majority of which were removed before they were seen.”
  • Google blocked or removed more than 70 million policy-violating edits to places on Google Maps.
  • Google removed or blocked more than 12 million fake Business Profiles.
  • Google placed posting restrictions on more than 900,000 accounts that repeatedly violated our policies.

When you compare the metrics to last year’s report, Google removed about 40% more policy-violating reviews.

Disabling reviews. Google also spoke about its newish feature to disable the ability to post reviews on some business profiles. The notice says “Posting reviews is turned off for this place” and was actually launched in December 2023, from what I can tell. But Google seems to be mentioning it now.

Google said it “rolled out alerts in the U.S., U.K. and India to let you know if we’ve recently removed suspicious five-star reviews in certain circumstances. These warnings — which will expand globally starting next month — help you understand quickly if a place may be engaging in unfair review practices.”

Here is what it looks like:

Crediting Gemini. Google said:

“AI has been a pivotal tool in helping us stop scammers in their tracks, and we’re now using it to scale our protections even more. Last year, we removed over 10,000 listings managed by a group of bad actors who impersonated real locksmiths to take over unclaimed Business Profiles and overcharge unsuspecting customers. Beyond removing the fraudulent content, we filed a lawsuit against the bad actors and are actively applying what we learned to enhance our detection systems.”

“This new model has already helped us block thousands of suspicious Business Profile edits this year,” Google added.

Why we care. If you are in the local SEO space, none of this is probably new to you. You’ve all seen the swarm of complaints about business edits placing a business in a suspension, reviews not being able to be added to a business profile, listings confusion and so much more.

Much of this is likely associated with Google’s new methods to detect and fight spam on Google Maps. Some of these changes may be a bit overzealous but Google has a tough job with fighting spam on Google Maps.

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Integrating SEO into omnichannel marketing for seamless engagement

Integrating SEO into omnichannel marketing for seamless engagement

With customers now discovering content across traditional search engines, LLMs, social media, and beyond, the need for an integrated, omnichannel strategy is more important than ever.

Relying on isolated channel strategies no longer works. 

Customers engage with brands across multiple touchpoints before making decisions, and they expect seamless, personalized experiences. 

An effective omnichannel approach aligns all marketing efforts – ensuring consistency, maximizing visibility, and driving meaningful interactions.

As omnichannel marketing continues to evolve, integrating SEO across all channels is essential for sustained growth.

This article explores why a unified strategy is critical and how SEO can work across channels to enhance the customer journey and drive results.

Why an omnichannel approach to SEO is critical in 2025

Here are seven trends that make an omnichannel approach vital to business success and growth.

Why an omnichannel approach to SEO is critical in 2025

1. The shift away from third-party cookies

The decline of third-party cookies has made it harder for brands to track users across the buyer journey. 

An omnichannel approach to data collection and centralization helps mitigate these challenges and lays the foundation for an effective strategy.

2. Growth of LLMs and AI-powered search

The growth of alternate avenues for audiences to find information adds to the complexity of the buyer’s journey. 

This presents additional attribution challenges. 

3. Zero-click searches and decreasing top-funnel traffic

Due to the rise in zero-click searches, traffic to websites from top-of-the-funnel information-seeking terms is declining. 

4. Importance of SEO

Despite the growth in zero-click searches, SEO remains the primary source of traffic for most businesses and the channel with the highest long-term ROI. 

AI Overviews and AI-generated results mainly pull information from the top organic results.  

5. Search is multi-modal

This means written content is not the only content you need to optimize. 

To effectively saturate SERPs, you must optimize all your digital assets, including images, videos, and PDFs. 

6. Personalized experiences

Personalization is key to customer engagement. Up to 71% of consumers expect it, while 76% find generic content frustrating, per a McKinsey study. 

Businesses that prioritize personalized marketing can see up to a 40% increase in revenue. 

An omnichannel approach ensures marketers focus on customer intent rather than marketing channels.  

7. Unified customer experience with agent economy

The growth of artificial intelligence has resulted in the emergence of an agent economy, where AI agents are beginning to revolutionize marketing and digital experiences. 

They can easily connect dots across multiple channels to deliver a unified customer experience.

Tackling the visibility dilemma in customer journeys

With all the changes in the industry, consumer behavior, and technological advancements, we need to answer important questions that marketers are confused about. 

  • How can you learn about audience intent even when they do not visit the site after a search?
  • How do you gather data on your audience’s behavior after they leave your site if they do not convert during their first visit?
  • How can you develop effective SEO, paid, zero-click, and content strategies with limited visibility into the customer journey and insights into customer intent and personas?
  • How can you provide personalized experiences without third-party data, limited traffic, and visibility into your customers’ journeys?

This is where an omnichannel approach can help businesses enhance visibility, drive meaningful interactions, and create a seamless path to conversion.

Building blocks of an omnichannel strategy

A true omnichannel strategy is no longer limited to traditional marketing channels like SEO, paid, email, social media, etc. 

Today, it is about delivering a unified experience at every stage in the customer journey at every touchpoint. 

It includes effectively using channel-agnostic strategies and tactics, such as personalization, AI agents, conversion optimization, A-B testing, and co-optimization. 

Here are five building blocks for creating an omnichannel strategy that truly engages your audiences consistently across touchpoints in an AI-powered world.

 omnichannel-strategy-building-blocks

Reliable data

Ensure you have the necessary infrastructure to gather and segment customer data accurately. 

AI can then be layered to:

  • Build audience cohorts.
  • Predict user journeys.
  • Deliver real-time personalized experiences. 

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

Artificial intelligence

Having an organizational AI strategy is key to ensuring the effective use of AI, not just for content generation but also for improving:

  • Efficiency.
  • Process automation.
  • Customer data segmentation.
  • Forecasting.
  • Real-time personalization at scale.
  • And more.

Dig deeper: 4 pillars of an effective enterprise AI strategy

Digital assets

Having a digital asset manager that lets you centralize, optimize, and distribute all your digital assets across marketing channels is key to ensuring consistency and reducing duplication. 

Dig deeper: Visual optimization must-haves for AI-powered search

Infrastructure

Search-friendly infrastructure and content management system are crucial for effectively crawling and indexing your content, and delivering an engaging, personalized experience to your visitors. 

Dig deeper: How to select a CMS that powers SEO, personalization and growth

Structured data and entity optimization

All search engines, including LLMs, detect entities within your content to understand what your content is all about.

Structured data – or schema markup – helps search engines detect entities and all your digital assets. 

This helps maximize your content visibility and SERP saturation. 

Dig deeper: Future-proof your SERP presence: 6 areas to focus on

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9 steps to integrating SEO into an omnichannel customer journey

9 steps to integrating SEO into an omnichannel customer journey

You can start developing your omnichannel strategy while closing any gaps you have identified in the building blocks.

Step 1: Audience and intent mapping

Start with your audience and intent. Identifying target audience personas and their intent is the first step in audience mapping. It is important to review:

  • Content performance: Evaluate performance of page types or templates to understand gaps in content strategy (e.g., category pages vs. product details pages vs. location pages vs. blog content).
  • Search engagement insights: Search console data can help identify high-intent terms with low click-through rates. This information can inform zero-click and CTR optimization strategies. 
  • Channel overlaps: Identifying how visitors overlap across channels is key to crafting an integrated and unified experience. For example, paid and organic channels must work together to saturate the full funnel and maximize ROI from both channels.  
  • Conversion optimization: Content with high engagement can provide insights into visitor intent. This can help define A-B tests, UI/UX enhancements, and personalization strategies.

Step 2: Define clear strategic goals

The next step is to have clear and smart goals that you want your omnichannel strategy to achieve:

  • Set specific, measurable business objectives (revenue growth, customer retention, growing market share, etc.)
  • Establish key performance indicators (KPIs) for channel-specific and overall performance. For example, if the goal is to improve visibility, the primary KPIs should be around impressions, clicks and rich results visibility. Traffic or conversions can be secondary KPIs but should not be the primary success criteria.
  • Create baseline metrics to measure improvement against current performance.
  • Develop a measurement framework that accounts for cross-channel attribution challenges.

Step 3: Map the customer journey across all touchpoints

Traditional funnel is changing rapidly. 

Brands should be ready to respond to customers across all touchpoints fast and with quality.  

 customer journey across all touchpoints

Develop a comprehensive understanding of how customers interact with your brand:

  • Create detailed personas representing your target audience segments.
  • Identify patterns in cross-channel journeys using path analysis in analytics and create common use cases.  
  • Aggregate and centralize data across customer touchpoints (website analytics, CRM, sales data, app usage, etc.)
  • Segment customers based on behavioral patterns rather than just demographics.
  • Quantify the value/attribution as a combination of different journey paths and touchpoints.
  • Measure channel preference and effectiveness across different customer segments.

Step 4: Omnichannel audit

Based on your goals and journey maps, evaluate your current channel gaps and capabilities:

  • SEO audit: Analyze search visibility metrics, technical health scores, and overall SEO performance.  
  • Content audit: Measure content performance data, topical and entity coverage, competitive gaps, engagement rates, conversion impact, and cross-channel content effectiveness.
  • Local presence assessment: Evaluate local search visibility metrics and location-specific engagement.
  • Experience audit: Analyze drop-off points and measure cross-channel friction.
  • Data and technology assessment: Evaluate data collection and measurement framework to optimize your data infrastructure.
  • Full-funnel audit: Learn from your visitors. Past visitor data can provide meaningful insights into audience segments, what visitors engage with, and where they drop off in the conversion funnel. This can help identify opportunities for co-optimization, A-B tests and delivering personalized experiences across channels.

Step 5: Develop your integrated channel strategy

Here, focus on aligning your channels to ensure they work together seamlessly and support your overall business goals.

  • Prioritize channels according to attribution data and customer value metrics.
  • Leverage machine learning and predictive analytics to forecast the impact of each channel.
  • Use predictive analytics to determine the optimal channel mix.
  • Set channel-specific targets that ladder up to overall business objectives.
  • Create frameworks for continuously testing and validating channel effectiveness.
  • Define how channels will complement and support each other across the customer journey. 

Step 6: Content orchestration strategy

While a content strategy focuses on what content is needed, a content orchestration strategy also encompasses distribution frameworks that enhance audience interaction with your content.

Friction analysis

Analyze how your audience engages with your content to identify friction points. This process helps you identify, rectify, and optimize:

  • Inconsistencies.
  • Intent misalignments.
  • Delivery mechanisms (text, images, video, etc.).

Content intelligence

Assess the performance of your existing content across various channels and identify competitive gaps and opportunities based on audience personas and business goals. 

Here are a few steps to evaluate content gaps and refine your strategy:

  • Identify underperforming content for optimization.
  • Spot gaps in content that need to be addressed across channels and stages of the customer journey.
  • Recognize cross-linking opportunities to create content hubs.
  • Prioritize new content to close competitive gaps and achieve business goals.

Cross-channel content strategy

After identifying friction points and content gaps, develop a tailored content strategy for each channel, prioritizing based on business goals:

  • Broader informational content to enhance awareness during the discovery stage of the customer journey (e.g., social media, blog content).
  • Comparison content for the consideration stage (e.g., product pages).
  • Landing pages focused on specific buying-intent terms during the conversion stage.

Content optimization

Optimizing content extends beyond targeting the right keywords. Your content optimization strategy should include:

  • Closing topical gaps in content that create friction.
  • Developing an entity optimization strategy to maximize content discoverability.
  • Implementing a click-through rate (CTR) strategy to enhance traffic from discovered content.
  • Optimizing visual content.
  • Establishing an engagement and conversion optimization strategy that includes personalization, calls to action optimization, A/B testing, messaging strategies, UI/UX optimization, and conversion rate optimization (CRO).

Dig deeper: The complete guide to optimizing content for SEO (with checklist)

Step 7: Infrastructure and technical SEO

To give your content the best chance of being crawled, indexed, understood, and featured in search results for the right terms, focus on the following:

  • Fix technical SEO issues related to crawling, indexing, and user experience.
  • Ensure mobile optimization across all digital properties.
  • Deploy nested schema markup to enhance search visibility.
  • Improve page speed for all web properties and optimize Core Web Vitals.
  • Test cross-device compatibility.
  • Implement proper canonicalization for multi-regional brands.
  • Prioritize web accessibility by following ADA and WCAG guidelines to enhance user experience and search visibility.

Step 8: Engagement and conversion optimization

Utilize unified customer data to enhance user engagement and drive conversions:

  • Deliver personalized content at scale for each audience segment in real time. Personalization strategies can be based on various factors such as marketing channel or campaign, visitor location, search intent, and past behavior. 
  • Identify and deploy AI agents that assist audiences in quickly finding information, engaging in meaningful interactions, and making real-time decisions.
  • Develop remarketing strategies informed by visitor behavior.
  • Implement A/B testing across channels, ensuring consistent test and control groups.
  • Measure performance across channels and optimize based on business goals and success KPIs. 

Step 9: Continuously test, measure, learn, and optimize

Refine your strategy through ongoing testing and data-driven adjustments to improve performance across all channels.

  • Monitor performance metrics across all channels. Establish BI dashboards that connect and integrate data across channels.  
  • Implement attribution models that effectively account for complex customer journeys.
  • Regularly test new channel integrations and enhancements to the customer journey.
  • Gather feedback from customers regarding their cross-channel experiences.
  • Refine your strategy based on evolving search engine algorithms and changing customer behavior.

SEO’s role in delivering a unified, cross-channel experience

Integrating SEO into the omnichannel customer journey isn’t simply for improving search presence. 

Ultimately, it’s about creating discoverable, unified, and personalized experiences that guide customers naturally toward conversion. 

By implementing this nine-step framework, you can:

  • Break down departmental silos.
  • Align cross-functional teams around customer needs.
  • Build truly seamless engagement models that drive sustainable growth.

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