A website redesign is essential for remaining competitive, but for multi-location businesses, the risks are much higher. Stripping away the local relevance that drives traffic to location pages can cause rankings and online visibility to plummet.
Using localized content on location pages resulted in a 107% rankings lift, something businesses risk losing if a redesign hurts these pages.
To mitigate the risk of fallen local rankings and to get the most from your website redesign, you need to maintain good multi-location local SEO and take key steps for a successful redesign.
Prioritizing SEO during a location page redesign helps multi-location businesses stay competitive.
Technical SEO pre-redesign audit checklist
Before launching a new website redesign, it’s essential to perform a comprehensive audit to ensure that your SEO foundation is retained. Thorough auditing before launch can help prevent common mistakes and preserve your rankings.
Manage inventory: Document all business locations, Google Business Profile IDs, current URLs, organic rankings, and highest-converting queries.
Identify issues: Use a site crawler to uncover duplicate/thin content, poor Core Web Vitals, slow loading, mobile responsiveness, or accessibility gaps.
Conduct a technical crawl audit: Confirm crawl budget, indexing, updated sitemaps, and hreflang configuration on multinational sites.
Audit and enhance structured data: Ensure LocalBusiness schema is present and NAP is perfectly consistent. Validate canonical tags for duplicate prevention.
Expand structured data: Consider implementing review, FAQ, and service schema types for additional SEO coverage.
Set up robust tracking: Implement UTM tagging, conversion tracking, and phone call analytics to precisely measure local and national SEO performance
PageSpeed Insights can let you know how fast your website loads and indicate potential performance issues.
How to optimize site architecture and your URL strate
Once your pre-redesign audit is complete and you’ve identified areas for improvement, it’s time to shift focus to your site architecture for SEO. A solid foundation in site architecture ensures both search engines and users can navigate your website with ease.
Common structures include:
Subfolders (/locations/city)
Subdomains (city.brand.com)
Multisite frameworks
Dedicated microsites
Subfolders generally work best for centralizing authority and scalability, with a primary website that branches out into many pages, including one for each location.
Note that it’s crucial to maintain consistency with your URL structure. If the existing site already has a URL for each location within a subfolder structure, do not change it! Ensuring that the URL structure remains identical between the existing and new website design is essential for retaining your SEO value and preventing any loss in rankings.
Here are some other key considerations:
Canonical URLs: Identify canonical URLs that help mitigate the risk of duplicate content.
Sitemap strategy: Determine whether your site should implement an XML sitemap or an HTML sitemap, with XML sitemaps being more explicitly effective for site crawlers and SEO, while HTML sitemaps could help with user navigation.
URL templates: Use static URLs, they’re cleaner and more optimization-friendly design (e.g., example.com/services/dentistry/location/).
Location page content considerations
Technical SEO components are important, but so is content. When redesigning your website, it’s crucial to prioritize the content elements that impact the SEO performance of your location pages.
A successful redesign should seamlessly integrate these elements to preserve and boost your SEO efforts.
Unique H1 on each location page with city intent that targets a relevant keyword, such as “housekeeping services in [city]”
Full name, address, and phone number that’s consistent across all directory listings
Link to each location’s corresponding GBP page.
Business hours that are up-to-date and unique to each location, further aligning with directory information
Local phone number, preferably static to maintain consistency with NAP data
Service-specific content, including details about each of your offerings, with locally optimized keywords for each
Staff and team photos showing the people behind your business, potentially at each location
Local testimonials from satisfied customers, including review and schema markup for aggregate ratings
h1 optimized for location and main keyword with custom text and clear CTAs. Source
As you incorporate these essential content elements into your location page redesign, it’s critical to ensure each page is unique and tailored to its specific location.
Each location page should include a designated content block section where you can add customized details about that individual location. This will additionally help reduce duplicate content across your location pages.
Location page with h1 and copy optimization Source
Top design elements to consider for a multi-location website
Redesigning location pages can be challenging because it requires balancing brand consistency with the unique identity of each location. Achieving this balance involves the strategic use of design elements that appeal to both local audiences and the overarching brand.
Top design elements include:
Location-specific imagery: For brick-and-mortar locations, use high-quality images of the storefronts. For service-based locations, showcase custom visuals that reflect the areas they serve.
Interactive maps or location finders: Adding Google Maps or a custom location finder helps users easily find the nearest store or service center. This feature not only enhances usability but also provides a tailored experience for visitors.
Social media feed integration: Integrating a live social media feed on location pages adds dynamic content and more localized imagery. It also provides a space to showcase promotions, events, and local engagement, keeping the page fresh and relevant.
Team photos: Featuring photos of local team members helps humanize the brand and create a personal connection with your audience. It’s a great way to reinforce the idea that your business is part of the local community, building trust and authenticity.
Example of an optimized H1 with custom images on the team page. Source
Complete multi-location redesign audit checklist
Website redesigns often require several months of planning and execution. However, before you push the new site live, it’s essential to ensure it passes the following key tests if you want to retain your traffic:
Brand consistency: Ensure that branding elements, such as colors, typography, logos, and tone, are consistent across all pages and location-specific content.
URL mapping: Double-check that all important URLs are correctly mapped to the new design and are still functional, preserving the SEO value of your existing pages.
No URL structure changes: If you’re maintaining a subfolder structure, confirm that no URL structures are altered to prevent any loss of SEO rankings or broken links.
Site performance: Test the website’s speed to ensure it meets performance standards, passes Core Web Vitals, is mobile-responsive, and is free of any accessibility issues.
Clear CTAs: Ensure that each page features clear, concise calls to action (CTAs) above the fold to encourage user engagement and conversions from the moment visitors land on the page.
Analytics setup: Verify that all necessary analytics and tracking codes (e.g., Google Analytics, conversion goals, UTM parameters) are properly implemented to monitor site performance and user behavior across all locations.
Mobile optimization: Check that the site is fully optimized for mobile users, with responsive design elements that scale and display well on all devices.
SEO-friendly content: Review content for SEO optimization, ensuring that each location page is targeted with local keywords, meta descriptions, and proper header tag hierarchy.
Structured data implementation: Verify that all relevant schema markup (e.g., LocalBusiness, Service, Review) is correctly applied to each location page to support search engines in indexing your content.
Internal linking: Ensure that all location pages have strong internal linking, guiding users through the site, and boosting SEO by connecting related content.
User testing and feedback: Conduct user testing or gather feedback from stakeholders to ensure the new design is intuitive, user-friendly, and aligns with business goals.
Content uniqueness: Confirm that all location pages have unique, location-specific content to avoid any potential issues with duplicate content.
Legal and compliance checks: Ensure that the website complies with any industry-specific regulations (e.g., ADA compliance, GDPR, HIPAA) before launch.
Cross-browser compatibility: Test the website across various browsers to ensure it functions smoothly for all users, regardless of their preferred browser.
Backup and contingency plans: Create a backup of the current website before launching the redesign, and have a contingency plan in place in case issues arise post-launch.
By ensuring that these elements are in place, you can launch a multi-location website redesign that performs well across all locations and provides a seamless, user-friendly experience for your visitors.
Example of before website redesign and after a website redesign
The business case: search and revenue impact at scale
Partnering with a web design and development agency that truly understands the complexities of multi-location businesses, technical SEO, and CRO is essential.
Ignite Visibility is a prime example of this expertise. We implemented a performance-driven SEO strategy to help a home services franchise with over 60 locations across the U.S.
The team optimized city-specific landing pages, standardized keyword-rich updates across Google Business Profiles, and strategically matched high-intent keywords to local markets to maximize visibility.
The results speak for themselves. The Ignite Visibility approach doesn’t just maintain rankings – it creates massive growth opportunities.
If you’re ready to maximize the impact of your next website redesign and achieve measurable, scalable growth, reach out to Ignite Visibility. With our proven track record, we’ll help you stay ahead of the competition and deliver results that matter.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/10/Ignite-20251021-header-wFV29v.png?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-21 11:00:002025-10-21 11:00:00How to execute a multi-location website redesign without losing traffic by Ignite Visibility
Anchor text, which is also known as link text, is the visible, clickable text of a hyperlink. It usually appears in a different color and is often underlined. Good anchor text tells readers what to expect when they click and gives search engines valuable context about the linked page. Getting your anchor text right helps users navigate your content more easily, improves your internal link structure, and provides search engines with clues about your page relationships, which can positively influence your SEO.
Anchor text enhances user navigation and provides context for search engines, improving SEO outcomes.
Good anchor text clearly describes the linked content and avoids misleading or over-optimized phrases.
Different types of anchor text exist, each with specific use cases; mix them for variety and clarity.
Yoast SEO offers tools to analyze competing links and improve anchor text for better search engine ranking.
To enhance anchor text, ensure it matches the linked content, flows naturally, and clearly signals clickable links.
What does an anchor text look like?
Anchor text is the part of a link that describes the linked page. It guides both readers and search engines toward relevant information. For example, if we link to our post about keyword research tools, the phrase “keyword research tools” is the anchor text.
In HTML, it looks like this:
<a href="https://yoast.com/keyword-research-tools/">keyword research tools</a>
The first part is the URL, while the second, the visible text, is the anchor text. Ideally, the words you choose should naturally describe the content on the linked page.
Why are link/anchor texts important?
Links are vital for SEO. They show how your pages connect and help search engines understand your site structure. The anchor text in those links provides extra context.
When Google crawls your site, it uses link text as a clue to what each linked page is about. If multiple links all use the same focus keyphrase, Google might not know which page should rank highest for that topic, leading to competition between your own pages.
That’s why thoughtful, descriptive anchor text matters. It helps search engines interpret your site and helps readers decide whether a link is worth clicking. Over-optimized or misleading link text can confuse both.
Tip: Avoid using your main focus keyphrase in multiple anchor texts within one post, as it can create competing links. Your linking should always feel natural and avoid over-optimization.
An example of internal links with good anchor texts
Different kinds of anchor text
Anchor text applies to both internal and external links. External sites can link to your content in various ways, and each type sends a different signal to search engines:
Branded links: Use your brand name as anchor text (e.g., Yoast)
If Yoast SEO detects that one of your links contains your focus keyphrase or a synonym of it, then Premium users get a warning. The reason? You don’t want multiple pages trying to rank for the same phrase.
For example, say your focus keyphrase is potato chips. If you link to another page using that exact phrase, Yoast SEO will flag it as a competing link. You’ll see a notification in your SEO analysis, so you can adjust it before publishing. If you have Yoast SEO Premium or Yoast SEO for Shopify, the check will also look for the synonyms of your keyphrase.
The competing links check in Yoast SEO helps you improve your linking
How to improve your anchor link texts
If Yoast SEO alerts you about competing links, or if you simply want to improve the quality of your link text, here are some best practices to follow.
1. Create a natural flow
Your writing should feel effortless. If a link feels awkward or forced into a sentence, it probably doesn’t belong there. Always prioritize readability, as a smooth flow improves both engagement and SEO. For more advice on writing content that feels natural while still ranking well, read our SEO copywriting guide.
2. Match the link text to the linked content
Readers should immediately understand what to expect when they click on a link. For example, a link that says meta description should lead to a post explaining what a meta description is and how to optimize it. Clear, logical linking builds trust and helps users navigate your content with ease.
3. Don’t trick your readers
Never mislead readers with inaccurate or confusing link text. If your link text says, “potato chips,” it shouldn’t lead to a page about cars. Consistent and honest linking keeps readers engaged and signals quality to search engines.
4. Make it clear that the link is clickable
Use visual cues such as color contrast or underlining, so it’s easy to tell when text is a link. This not only improves usability but also helps people using assistive technology to navigate your content. To see more on writing accessible, well-structured posts, visit our blogging guide.
5. Bonus tip: put your entire keyphrase in quotes
When using long tail keyphrases, you might see a warning about links that include parts of your focus keyphrase. To avoid this, put your full keyphrase in quotes, for example, “learning how to knit.” This tells Yoast SEO to look for the entire phrase rather than matching individual words.
If you’d like to learn more about writing effective link text and improving your content for SEO, take our SEO copywriting course, which is included with Yoast SEO Premium.
Go Premium and get free access to our SEO courses!
Learn how to write great content for SEO and unlock lots of features with Yoast SEO Premium:
But internal links work best when you write good anchor text for them. Each link should serve a clear purpose and guide readers naturally to related topics. Avoid adding unnecessary or irrelevant links just for the sake of having more connections.
Thoughtful internal linking improves the user experience and helps search engines understand your site’s structure, which is essential for strong SEO performance.
This is anchor text
Anchor text remains a small but powerful element of SEO. It helps users decide whether to click, gives search engines valuable context, and supports a logical site structure.
Keep your anchor text relevant, natural, and transparent and avoid manipulative or over-optimized linking practices. Search engines are now smarter than ever at spotting unnatural links, especially in the era of AI and semantic understanding.
So stay genuine, link with intent, and use Yoast SEO to guide you along the way.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-20 12:00:002025-10-20 12:00:00What is anchor text, and how can you improve your link texts?
Have you noticed that your site analytics feel a little, well, off lately? It’s not just your imagination. We’ve found a subtle growing issue popping up across multiple clients, and it might be hitting your site, too.
It comes down to GTM tag priority and how these tags fire in relation to consent management. If tags load out of order or before the user gives proper consent, your tracking can break. This means lost sessions, broken attribution, and inaccurate conversion data.
We’ve seen this firsthand, but we’ve taken steps to fix it. Let’s break down what tag sequencing is and why it matters. In addition, we’ll give you some tips to help make sure your data stays clean and compliant without sacrificing its usefulness.
Key Takeaways
Poor tag sequencing can lead to missing data, inflated conversion rates, and inaccurate attribution.
Tag priority matters, especially when consent management platforms are in play.
We’ve seen clients lose up to 20% of reported traffic due to sequencing issues.
Fixes include loading the consent script first, mapping tags to categories, and blocking tags until consent is confirmed.
Regular audits are non-negotiable. One misstep in your CMP or tag manager setup can break your entire funnel.
What is Tag Sequencing And Why Is It Important?
Tag sequencing is the order in which tracking tags, like analytics, advertising, or personalization, fire on your website. While it sounds simple, it plays a big role in the accuracy of your data.
When you use a consent management platform (CMP), sequencing these tags becomes even more important. Some tags aren’t allowed to fire if users don’t give specific consent. Others rely on earlier tags to work correctly. If the order’s off or a critical tag doesn’t fire, your tracking capabilities break down, and so does your reporting. CMP triggers or blocks tags in the right sequence so only authorized data collection occurs. This preserves regulatory compliance and performance accuracy.
Tags load in the right area (keeping your data clean)
Your campaigns see proper attribution (keeping your ROI real)
If you ignore tag sequencing, you risk bad data. Even worse, you can lose conversions and break your customer insights.
The Impact of Tag Sequencing on Data Quality (and the bottom line)
When you fail to set your GTM tag priority correctly, it can distort your data (sometimes massively). We’ve seen this across major brands in finance, hospitality, and automotive industries. In each case, the same issue kept popping up: the first page of a user’s visit wasn’t being tracked.
That doesn’t sound like a big deal, but it is. That one misstep led to a massive ripple effect:
Traffic was underreported by as much as 10 to 20 percent.
Here’s why that’s a problem: broken data could also lead to broken strategies. You could be pulling budget from channels that are working or double down on content that doesn’t actually convert. Either way, your decisions are off base.
The scary part is that this isn’t always obvious unless someone digs into the tags and sequencing logic; if you’re not actively spending time in the sequence, you may not notice an issue.
The Causes Behind Tag Sequencing Issues We’ve Found
Most tag sequencing issues come down to one of five things, which are often more common than you’d expect. If you’ve noticed attribution issues, you might have the following issues:
Consent misconfiguration. Tags aren’t properly mapped to categories like analytics, marketing, or performance. Even if a user opts in, the right tags may not fire.
Network latency. If your consent platform loads too slowly, it could delay or block tags entirely.
Script placement. Tags placed above the consent script in the site header will run before user choices are processed.
Direct-to-page scripts. It’s important to note that not all scripts necessarily sit in GTM, for a variety of reasons. If the consent banner configuration on the site doesn’t fire before these scripts and the GTM tags, it will cause issues. This applies whether you implement tags directly in GTM or the site itself.
When these problems stack up, you can often get missing data or broken attribution. This skews performance and could impact your decisions surrounding future resource allocation.
How To Fix Your Tag Sequencing Before It Impacts Data Quality
Fixing tag sequencing isn’t complicated, but it is important. We’ve helped our clients clean up their setup and reclaim accurate tracking with the following best practices:
Load your consent script first. This should be the very first script in your header. Put it before any analytics, marketing, or tracker tags.
Use your CMP to block everything else until the user’s choice is known. See below for an example of how to use OneTrust CMP to create active group triggers.
Assign consent categories to every tag. These categories ensure your platform knows what to load and when.
Audit your tags regularly. Site updates, script changes, and even CMP updates can reset sequencing logic without any warning. These screenshots are from our partner, ObservePoint, that we utilize for scaled audits. This tool can help scale up consent audits and can help us validate user consent selections. The below example shows what categories of tags fire when a user opts in vs. opts out and can be a quick way to determine whether further investigation is needed – for example, if we expect zero analytics tags to fire when consent is not given, and we see analytics tags firing on 4% of pages scanned that are opt out, that would flag to us that there is an issue with configuration.
How does this work in action? Take a look at the below examples to show how we utilize OneTrust CMP and create groupings based on cookie types: ( Performance, Marketing, Analytics, etc.). Mapping cookie types to their corresponding cookie groups and then assigning them to appropriate tags within GTM so the users cookie choices map with what tags fire once consent is given.
Below, by assigning that active group trigger as an And statement to an existing tag, this ensures both values are present before the tag fires, avoiding the issue we’ve been seeing.
Failure to fix tag sequencing means you break your compliance and your data, which will inevitably trickle into every marketing decision you make.
FAQs
What is tag sequencing in GTM?
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It’s the order in which tags are triggered on your site. When using consent management, this sequence determines which tags fire—and when—based on user permissions.
How can bad tag sequencing affect my data?
If tags fire too early (or not at all), you’ll miss sessions, inflate conversion rates, and get unreliable channel attribution.
Can I manage tag sequencing without a developer?
Yes—tools like Google Tag Manager and modern CMPs make it easy to handle sequencing logic without code, as long as they’re set up properly.
How often should I check my tag sequencing setup?
Audit it quarterly, or anytime you update your website, CMP, or launch a new campaign. One misplaced script can throw off everything.
Conclusion
Tag sequencing may seem like a simple technical skill, but it’s so much more than that. It creates a backbone for reliable data that underpins many of your marketing decisions. Tags that fire out of order can break tracking, skew analytics, and cause you to miss valuable opportunities.
But it’s a fixable issue, and a few key adjustments to your GTM setup and consent platform can get things back on track and keep them there.
If you want to dive deeper into clean data, consider performing a technical SEO audit and explore how your site’s structure can impact your results. But if you’re still unsure whether your tag setup costs you conversions, let’s talk. Fixing it now can save you wasted spend (and effort) down the line.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-16 07:00:002025-10-16 07:00:00How Tag Sequencing Is Affecting Website Data Quality When Utilizing Consent Management
When someone asks ChatGPT for a product in your category, it doesn’t always crawl websites in real-time.
Its first move is to pull from what it already knows about you and your competitors from its existing knowledge.
Clear and recognizable entities in AI training data are just as important as having the most authoritative and optimized website.
This shift means your webpage might rank #1 in classic search, but if your brand isn’t well-structured for entities, AI might overlook you entirely in the answer.
The rules we’ve relied on for decades don’t fully apply when machines create answers. They draw on their own knowledge and real-time data from sites, including yours.
You’re about to learn what this means, why it matters, and what you can do about it.
What Are Entities in AI Search?
An entity is a “thing” that search engines and AI models can recognize, understand, and connect to other things.
Think of entities as the building blocks that AI uses to construct answers. In other words, gigantic relational databases.
Let’s use email marketing company Omnisend as an example.
Through the lens of a database, Omnisend isn’t just a website with pages about email marketing. It’s a network of connected entities:
Use cases: “welcome series,” “abandoned cart recovery”
Here’s what the entities look (hypothetically ) like to a large language model (LLM):
These records become the foundation for AI answers.
LLMs do more than just find keywords on your page. They also retrieve entities, place them in vector space, and choose the ones that best answer your question.
Vector space explained: It’s a mathematical method that AI models use to understand relationships between concepts. Imagine a 3D map where similar items group together. For example, “Apple,” the company, is close to “iPhone” and “Tim Cook.” Meanwhile, “apple,” the fruit, is near “banana” and “orchard.”
For example, ask Google: “What’s the best email marketing tool for my Shopify store?”
You’ll see brand entities like Klaviyo, Omnisend, Brevo, Mailchimp, Privy, and MailerLite mentioned. This makes sense because the entities are closely related in the AI’s understanding.
Notice: the brand mentions aren’t linked to the websites. It’s just building the answer and then linking to the brand SERP on Google.
Why Entities Matter More Than Websites
AI models are constantly mapping relationships between entities when serving up answers.
When someone types “best email marketing tool for Shopify,” LLMs spread out the query. They turn that one question into multiple related searches.
Think of AI doing lots of Google searches at the same time.
The system simultaneously explores “What integrates with Shopify?”, “Which tools handle abandoned carts?” and “What do ecommerce stores actually use?”
Your brand can appear through any of these paths, even if you didn’t optimize for the original query.
Classic SEO relied a lot on keyword density and page authority.
But AI uses dense retrieval, where it’s looking for semantic meaning across the web, not just word matches on your page.
Dense retrieval explained: AI systems focus on meaning, not just exact keywords. They find related content, even if different words are used.
A Reddit comment that clearly explains “We switched from Klaviyo to Omnisend because the Shopify integration actually works” carries more signal (assuming the model prioritizes authentic discussions) than a page stuffed with “best email marketing Shopify” keywords.
The AI understands the relationship between the entities (Klaviyo, Omnisend, Shopify) and the context (switching, integration quality).
PR folks have been fighting for this moment: mentions without links still count.
For the longest time, we’ve obsessed over backlinks as the currency of SEO.
But AI systems recognize when brands get mentioned alongside relevant topics, using these as relationship signals.
So when Patagonia appears in climate articles without a hyperlink, when Notion shows up in productivity discussions on Reddit, when your brand gets name-dropped in a podcast transcript — these all strengthen your entity in AI’s understanding.
Here’s a real example that clarified this for me:
Microsoft OneNote often shows up high in AI recommendations for “note-taking tools.”
In ChatGPT:
In Perplexity:
And in Google AI Overviews:
But EverNote dominates Google’s number one ranking spot for “note taking tools”.
Why?
OneNote’s integration with the Microsoft ecosystem means it gets mentioned constantly in productivity discussions, enterprise software comparisons, and Office tutorials. This creates dense entity relationships in AI training data.
Evernote, by contrast, has focused on SEO and earned strong backlinks that dominate traditional search rankings.
How Entities Get Recognized
So how does Google (and other AI systems) actually know that Omnisend is an email marketing platform and not, say, a meditation app?
The answer sits at the intersection of structured data, human conversation, and pattern recognition…at massive scale.
Entity Databases and Product Catalogs
Google maintains what they call Knowledge Graphs and Shopping Graphs.
Other AI systems have similar entity databases, just with different names.
The idea is the same: huge databases that map every product, company, and person along with their attributes and relationships.
When Nike releases the Pegasus 41, it doesn’t just become a new product page on Nike.com. It becomes an entity in Google’s Shopping Graph, connected to “running shoes,” “Nike,” “marathon training,” and hundreds of other nodes.
The system knows it’s a shoe before anyone optimizes a single keyword.
Human Conversation as Training Data
AI systems learn just as much from informal mentions as they do from structured markup.
When an Outdoor Gear Lab review casually mentions testing Patagonia’s Torrentshell 3L against the expensive Arc’teryx Beta SL, that relationship gets encoded.
When a podcast guest says, “I moved from Asana to Notion for task and project management,” this competitive link adds to the training data.
Reddit and Quora have become unexpectedly powerful for entity recognition. (Google explicitly stated they’re prioritizing “authentic discussion forums” in their ranking systems.)
A single comment on why someone picked Obsidian over Notion for knowledge management matters more than you might realize.
These platforms capture what websites struggle to do: real people sharing real decisions with real context.
Multimodal Recognition
AI systems extract entities from audio and video. They do this by turning speech into text through transcription.
Every mention in a transcript, every product on screen, and every comparison in a talking-head segment is processed.
A 10-minute YouTube review of project management tools turns into structured data that compares ClickUp, Notion, and Asana. It includes feature comparisons and maps out use cases.
The New SEO Power Dynamic
You can’t game entity recognition the way you could game PageRank.
You can’t manufacture authentic Reddit discussions. You can’t fake your way into natural podcast mentions. The system rewards genuine presence in genuine conversations, not optimized anchor text.
Think about what this means:
Your engineering team’s conference talk that mentions your product’s architecture? That’s entity building.
Your customer’s YouTube walkthrough of their workflow? Entity building.
That heated Hacker News thread where someone defends your approach to data privacy? Entity building.
We’ve spent the longest time optimizing for robots. Now the robots are optimized to recognize authentic human discussion. (Ironic.)
5 Ways to Optimize Your Brand for Entities (Not Just a Website)
Using Omnisend as an example, here are five approaches for evaluating and optimizing entity presence in AI-powered search results.
1. Assess Your Entity Foundation
To start, you need a baseline understanding of your current entity relationships.
For Omnisend, this means mapping how AI systems currently categorize them relative to competitors.
Begin by verifying schema markup across key pages.
Testing Omnisend’s homepage with the Schema Markup Validator shows they use Organization and VideoObject schema.
And the Organization schema is relatively basic.
Omnisends competitor, Klaviyo, uses Organization schema as a container for multiple software offerings.
Klaviyo’s approach maintains brand-level authority while declaring specific software categories and capabilities. This potentially gives them stronger entity associations for queries about email marketing, SMS marketing, and marketing automation.
Next, check your entity presence in major knowledge sources like Wikidata and Crunchbase.
On Wikidata, Omnisend’s records are OKAY.
There’s basic info, like what Omnisend does, the industry, inception date, URL, and social media profiles.
But Klaviyo, again, is all over it. They have multiple properties for industry, entity type, URLs, offerings, and even partnerships.
There’s a clear opportunity for Omnisend to update its Wikidata with more details.
2. Test Query Decomposition
AI systems break down queries into entities and relationships. Then, they may try multiple retrievals.
For example, in Google Chrome, I prompted ChatGPT:
“What’s the best email marketing tool for ecommerce in 2025? My priority is deliverability.”
In the chat URL, copy the alphanumeric sequence after the /c/ directory. For me, it was 68d4e99e-4818-8332-adbd-efab286f4007.
Note: You need to be logged into ChatGPT to get this sequence
Right-click on the page and click “Inspect”.
Choose the “Network” tab, paste the alphanumeric sequence in the filter field, and reload the page.
In the “Find” section, search for “search_model_queries“. Then, click on the search results.
Each decomposed query represents a different competitive pathway.
Omnisend might surface through deliverability discussions, but miss general tool comparisons.
Mailchimp could dominate broad searches while competitors own specialized angles.
This explains why you appear in AI answers for searches you never optimized for. The semantic understanding creates visibility through unexpected entity relationships rather than keyword matching.
You can check this yourself. Run the extracted queries in separate chats and note which brands appear where.
But maybe don’t build a strategy around exploiting this technique.
The methodology depends on undocumented functionality that OpenAI could change without notice.
Important finding: Simple queries produce simple results. When I prompted “Best email marketing tool for ecommerce,” it triggered exactly one internal search with basically the same language. No decomposition.
3. Map Competitive Entity Relationships
Traditional SEO competitive analysis asks “Who ranks for our keywords?”
Entity analysis asks “When do AI systems group us together?”
I tested this with Omnisend to understand when they appear alongside different competitors.
I ran 15 variations of email marketing queries through Google AI Mode to see which brands consistently appear together.
Note: I tested logged out, using a VPN set to San Francisco, in private browsing mode to minimize personalization bias.
I began with simple terms like “best email marketing for ecommerce” and “abandoned cart recovery tools.” Then, I tried different angles like “email automation for Shopify stores.”
Here’s what I found:
Query Context
Omnisend Present
Most Co-Mentioned
Klaviyo Present
Ecommerce email
5/5 queries
Klaviyo, Mailchimp
4/5 queries
General email
5/5 queries
Mailchimp, Brevo
2/5 queries
Deliverability focus
2/5 queries
Brevo, Mailchimp
0/5 queries
Omnisend appeared in 12 of 15 total queries — stronger entity presence than I expected.
But mentions shifted dramatically by context.
In ecommerce discussions, Klaviyo dominated as the top tool.
In general email marketing, Mailchimp took over as the main reference point.
The mention order revealed something important. Klaviyo appeared first in 5 of 5 ecommerce queries, with more positive language around their positioning.
Omnisend routinely ranked second or third. This suggests they’re part of the discussion but not at the forefront.
Here’s what’s interesting:
Klaviyo completely disappeared from deliverability-focused queries while Omnisend maintained some presence.
This shows entity relationships are radically contextual.
Being the leader in ecommerce email doesn’t mean presence in deliverability conversations.
4. Optimize For Entities in Your Content
Entity recognition works best when it has context-rich passages. This helps AI systems extract and understand information more easily.
Take generic descriptions like “Our automation features help ecommerce businesses increase revenue through targeted campaigns.”
An AI system may struggle to identify which product you mean, its automation features, or how it compares to others.
Compare that to: “Omnisend’s SMS automation integrates with Shopify’s abandoned cart data to trigger personalized recovery messages within 2 hours of cart abandonment, without requiring manual workflow setup.”
This version establishes multiple entity relationships (Omnisend → SMS automation → Shopify integration → abandoned cart recovery) within a single extractable passage.
LLMs prefer to use their training data for answers. But when they pull info from the web, strong entity connections help a lot.
You’re reducing friction for both bots and human readers.
As a test, run key passages from your most important pages through Google’s Natural Language API to see what entities get recognized. This can also be video scripts.
Content with strong entity density tends to get cited more often than content requiring additional context.
5. Build Strategic Co-Citations
Entity authority builds through consistent mention alongside relevant entities in trusted sources. This moves the focus from link building to building relationships where natural comparisons happen.
For Omnisend, this means being present in authentic discussions. It’s about genuine comparisons, not forced mentions, that strengthen specific relationships.
A Reddit thread comparing “Klaviyo vs Omnisend for Shopify stores” carries a different entity weight than appearing in generic “email marketing tools” content.
The specific context (Shopify integration) strengthens both brands’ association with ecommerce email marketing.
The most valuable co-citations happen in:
Reddit discussions comparing tools for specific use cases
YouTube reviews demonstrating multiple platforms
Industry roundups grouping tools by specialization
Podcast discussions of marketing technology stacks
This Reddit thread shows strategic co-citation in action. The original post creates dense entity relationships (Klaviyo → Omnisend → pricing → Shopify store). While the comment adds even more context (pricing concerns → business scaling → “pretty good” user experience).
The discussion goes way beyond optimized content. It’s genuine decision-making that strengthens both brands’ entity associations with ecommerce email marketing.
This approach emphasizes genuine participation. Your category is discussed and evaluated by actual users who make real decisions. This is better than having artificial mentions in content made mainly for search engines.
Moving Forward with Entity SEO
If you’ve built a strong brand across various channels, you’ve laid the foundation.
Quality SEO is still crucial.
Genuine mentions in industry talks, real customer chats, and multi-channel distribution matter too.
Begin with your key product line. Organize it well, track its appearances in AI responses, and then expand to other entities.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-15 15:25:072025-10-15 15:25:07Entity SEO in the Age of AI Search
Citations in AI search assistants reveal how authority is evolving online.
Analyzing results across 11 major sectors shows which domains are most often referenced and what that says about credibility in an AI-driven landscape.
As assistants condense answers and surface fewer links, being cited has become a powerful signal of trust and influence.
Based on Semrush data from more than 800 websites, the findings highlight how AI reshapes visibility across industries.
AI citation trends across industries
The analysis surfaced several clear patterns in how authority is distributed across industries.
Universal authorities
Some domains appeared in the top 50 cited URLs across nearly all 11 sectors, with four domains appearing in every one:
reddit.com (~66,000 AI mentions across 11 sectors)
en.wikipedia.org (~25,000, 11 sectors)
youtube.com (~19,000, 11 sectors)
forbes.com (~10,000, 11 sectors)
linkedin.com (~9,000, 10 sectors)
quora.com (~8,000, 10 sectors)
Other domains are sector-strong but globally influential:
amazon.com (ecommerce and five other sectors).
nerdwallet.com (finance-focused).
pmc.ncbi.nlm.nih.gov (health and academic citations).
Concentration and diversity by sector
Citation concentration varies by sector.
Most concentrated: Computers and electronics, entertainment, education.
Most diverse: Telecom, food and beverage, healthcare, finance, travel and tourism.
This means some sectors rely on a handful of go-to sources, while others distribute authority across a broader field.
Relationships between visibility and SEO metrics
AI visibility and AI mentions are strongly correlated (0.87).
Organic keywords correlate more strongly with AI visibility (0.41) than backlinks (0.37).
Keywords and backlinks themselves correlate at 0.79.
By sector, the coupling between AI visibility and backlinks is strongest in computers and electronics, automotive, entertainment, finance, and education.
In these sectors, the scale of authority clearly helps drive AI references.
Sector breakdowns
Finance
Media brands such as Forbes and Business Insider dominate citations, reflecting the importance of timely commentary and market analysis.
However, NerdWallet shows that specialized finance experts can achieve high AI visibility by building deep evergreen guides and comparison content.
This sector also shows one of the strongest correlations between AI visibility and backlink scale, suggesting that authority signals remain highly influential.
Healthcare
Academic and government domains are heavily cited.
The dominance of PubMed Central (PMC), CDC, and national health portals underlines the central role of trusted peer-reviewed or official information.
Wikipedia also appears consistently, often serving as a layperson-friendly entry point.
Diversity is lower here compared with consumer-facing sectors, reflecting the need for evidence-based references.
Travel and tourism
Citations are spread across government advisories (for example, gov.uk travel advice), booking platforms, forums, and user-generated communities.
This diversity reflects the mix of practical (visa, safety), inspirational (guides, blogs), and transactional (booking) content users need.
The sector’s Herfindahl-Hirschman Index (HHI) score is low, suggesting no single authority dominates, and visibility is earned by serving very specific user needs.
Entertainment
User-generated platforms dominate.
Reddit, YouTube, and Quora all appear near the top of cited domains, alongside reference sources such as Wikipedia and IMDb.
This highlights how conversational, community-driven content is central to how AI assistants explain and contextualize entertainment.
In this space, backlink counts are less predictive than breadth of coverage.
Education
Citations concentrate around reference authorities including Wikipedia, university portals, and open-courseware providers.
Specialist learning platforms and forums also feature, but the dominance of well-known academic sources creates a more concentrated citation environment.
Here, AI assistants lean heavily on authoritative, structured content.
Computers and electronics
Technology news and review sites dominate, with CNET, The Verge, and Tom’s Guide appearing prominently.
Wikipedia is again present, but the sector is notable for its concentration, with citations clustering around a few highly recognizable review hubs.
This sector also shows one of the highest correlations between AI visibility and backlink scale, underlining the competitive role of authority signals.
Automotive
A mix of consumer guides (for example, Autotrader, AutoZone) and publisher content.
Insurance and financing providers also receive citations, reflecting user queries that span from buying cars to managing ownership.
Citations are somewhat more evenly distributed, but AI assistants lean on a balance of transactional and informational sources.
Beauty and cosmetics
Influencer-led platforms and community discussion spaces are frequently cited alongside brand websites and review hubs.
The combination of user-generated content and brand authority makes this sector more diverse than average.
Here, social-driven citations compete with established publishing brands.
Food and beverage
Recipe hubs, nutrition authorities, and community cooking sites dominate.
Wikipedia also features, especially for ingredient-level explanations.
The sector has one of the lowest HHI values, meaning a wide diversity of domains are being cited.
Backlink totals are less correlated with visibility here. Instead, topical coverage breadth seems to matter more.
Telecoms
Citations are relatively diverse, ranging from provider help portals to tech media and consumer advocacy sites.
Forums like Reddit often feature in troubleshooting contexts.
The sector’s low HHI suggests no single authority dominates, but users’ practical questions drive AI systems to reference customer-support-style material.
Real estate
Cited domains include large listing platforms (for example, Zillow-type sites), financial services tied to mortgages, and government portals for regulation and housing data.
While concentrated, the sector also pulls from news sources when market conditions are being explained.
The patterns in AI citations carry direct lessons for brands and SEOs, highlighting:
How authority is built.
What types of assets AI prefers to reference.
Why traditional SEO levers now interact differently with visibility.
Reference assets matter
Evergreen guides, standards, and explainers attract citations from both search engines and AI models.
To compete with Wikipedia or government sites, brands need to publish authoritative, fact-checked material that others can comfortably reference.
Breadth of coverage drives visibility
Domains with a wide organic keyword footprint consistently show stronger AI visibility.
This means that covering an entire topic area comprehensively – not just optimizing for a handful of high-volume keywords – positions a brand as a reliable reference source.
Sector rules differ
Each sector rewards different authority signals. In healthcare, peer-reviewed or government-backed resources dominate.
In entertainment, community-driven and UGC platforms rise to the top. In finance, explainers and calculators from expert brands are frequently cited.
Brands need to adapt their content strategy to the trust model of their sector.
Fewer links, higher stakes
AI assistants often cite only a handful of sources per response.
Being included delivers disproportionate visibility.
Conversely, being absent means competitors capture nearly all of the exposure.
This concentration raises the bar for what counts as a reference-worthy asset.
Backlinks still matter, but less directly
While backlink scale correlates with AI visibility, the correlation is weaker than for organic keyword breadth.
This suggests backlinks remain an authority signal, but the breadth and relevance of content may be more critical in an AI-driven environment.
User intent alignment
AI assistants pull from sources that best align with the specific intent behind a query.
Brands that anticipate user needs – whether transactional, informational, or troubleshooting – stand a better chance of being cited.
Creating layered content (guides, FAQs, tools) that matches different intents strengthens visibility.
Becoming a referenced brand
Citations in AI search results reveal the trust networks that underpin the next wave of search.
Wikipedia, Reddit, and YouTube are universal reference points, but sector-specific authorities also matter.
For brands, the lesson is clear: to win visibility in AI-driven search, you need to be the page that others cite.
That means authoritative content, breadth of coverage, and assets designed to be referenced.
Analysis methodology
The analysis drew from AI citation data spanning 11 sectors and more than 800 domains, using responses from Google AI Mode, Perplexity, and ChatGPT search.
Two primary metrics were calculated:
AI visibility score: The average share of responses in which a domain was cited across Google AI Mode, Perplexity, and ChatGPT search.
AI mentions: The total number of times a domain was cited across those engines in a given sector.
These metrics were then enriched with:
Organic keywords (Semrush): The number of keywords for which a domain ranks in organic search.
Backlinks (Semrush): The total backlinks pointing to a domain.
Spearman correlation
To measure the degree of correlation between metrics, I used the Spearman correlation coefficient.
Unlike Pearson correlation, which assumes linear relationships, Spearman looks at whether the ranking of one metric moves in step with another.
In simple terms, if domains with higher keyword counts also tend to rank higher for AI visibility, the Spearman value will be high even if the relationship is not a perfectly straight line.
A value near +1 means the two rise together consistently, near -1 means one rises as the other falls, and near 0 means no clear pattern.
Concentration of the HHI
I then measured citation concentration using the Herfindahl-Hirschman Index, a metric borrowed from economics.
It is calculated by summing the squares of market shares, in this case, each domain’s share of AI mentions in a sector.
An HHI closer to 1 means a sector is dominated by just a few domains, while values closer to 0 indicate citations are spread more evenly.
For example, an HHI of 0.05 suggests a concentrated landscape, whereas 0.02 points to greater diversity.
By combining AI visibility, citation counts, SEO scale (keywords and backlinks from Semrush), Spearman correlations, and HHI concentration, I built a cross-sector picture of who holds authority in AI-driven search.
Let’s get one thing straight before the industry turns “GEO” into yet another three-letter source of confusion.
Generative engine optimization isn’t SEO with a new hat and a LinkedIn carousel. It’s a fundamentally different game.
If you’re still debating whether to swap the “S” for a “G,” you’ve already missed the point.
At its core, GEO is brand marketing expressed through generative interfaces.
Treat it like a technical tweak, and you’ll get technical-tweak results: plenty of noise, very little growth.
CMOs, this is where you step in.
SEOs, this is where you either evolve or get automated into irrelevance.
The question isn’t what GEO is – that’s been done to death.
It’s how to tell if your GEO is actually working.
The North Star: Share of search (not ‘share of voice,’ not ‘topical authority’)
The primary metric for GEO is the same one that should already anchor any brand-led growth program: share of search.
Les Binet didn’t coin a vanity metric for dashboards.
Share of search is a leading indicator of future market share because it reflects relative demand – your brand versus competitors.
If your share is rising, someone else’s is falling, and the future tilts your way.
If it’s declining, you’re mortgaging tomorrow’s revenue. That’s the unglamorous magic of it.
It isn’t perfect. But across category after category, share of search predicts brand outcomes with a level of accuracy that should make “awards case studies” blush.
And yes, GEO affects it, often through PR.
When an LLM recommends your brand (linked or not), some users still open a new tab and Google you.
Recommendation sparks curiosity. Curiosity drives search. Search is the signal.
Expect branded search volume to rise as generative usage grows, because people back-check what they see in AI results.
It’s messy human behavior, but it’s consistent.
Your first diagnostic: plot your brand’s share of search against your closest competitors.
Use Google Trends or My Telescope for branded demand, and triangulate with Semrush.
Watch the trend, not the weekly wobbles.
And do not confuse share of search with share of voice.
Different metric. Different lineage. Different purpose.
The two halves of the signal: Brand demand and buyer intent
Share of search has two practical layers for GEO diagnostics:
Brand search: The purest signal of salience. Are more people looking for you than last quarter, relative to the category? That’s how you know your brand availability is increasing inside generative engines and the culture around them.
Buyer-intent traffic: The money end. Of your non-branded search clicks, how much is clearly commercial or buyer-intent versus informational fluff? And how does your share of that buyer-intent traffic compare to competitors?
You won’t know a rival’s exact click-through rates – and you don’t need to.
Use Semrush to estimate non-branded commercial demand at the topic level for you and them, then compare proportions.
Export everything and segment aggressively by intent.
Where tool estimates diverge from your actuals, you’ll learn something about the noise in third-party data and the real shape of your market.
If your brand search is flat but buyer-intent share is rising, congratulations – you’re harvesting demand but not creating enough of it.
If brand search is rising but buyer-intent share isn’t, you have a conversion or content problem – your GEO is sparking curiosity, but your site and assets aren’t turning that into qualified traffic.
If both are up, pour fuel.
If both are down, stop fiddling with prompts and fix your positioning, advertising, and PR.
Competitors are winning in AI answers. Take back share of voice.
Benchmark your presence across LLMs, spot gaps, and get prioritized actions.
Compare share of voice and sentiment in seconds.
Category entry points: The prompts behind the prompts
GEO lives or dies on category entry points (CEPs) – Ehrenberg-Bass’ useful term for the situations, needs, and triggers that put buyers into the category.
CEPs are how real people think.
“I just left the gym and I’m thirsty.” That’s why there’s a Coke fridge by the exit.
“I’ve just come out of a show near Covent Garden and need food now.” That’s why certain restaurants cluster and advertise there.
These are not keywords. They’re human contexts that later materialize as words.
Translating that to GEO: your customers’ prompts in ChatGPT, Gemini, Perplexity, and AI Mode reflect their CEPs.
Newly appointed marketing manager under pressure to fix organic? That’s a CEP.
Fed up with a current tool because the price doubled and support disappeared? Another CEP.
Map the CEPs first, then outline the prompt families that those CEPs produce.
The wording will vary, but the thematic spine stays consistent: a role, a pain, a job to be done, a timeframe.
Once you’ve mapped CEPs to prompt families, you can evaluate your prompt visibility – how often and in what context generative engines surface you as a credible option.
This is a brand job as much as a content job.
LLMs don’t “decide” like humans. They triangulate across signals and citations to reduce uncertainty.
Distinctive brand assets, third-party coverage (PR), credible reviews, and consistent evidence of capability all raise your odds of being recommended.
Notice I didn’t say “more blog posts.” We’ll come back to that.
Once you’ve outlined your prompt families, test visibility systematically.
Run qualitative checks in the major models. Log the sources they cite and the types of evidence they appear to weight.
Are you visible when the CEP is “newly promoted CMO, six-month plan to grow organic pipeline”?
Are you visible when it’s “VP of ecommerce losing non-brand traffic to marketplace competitors, needs an alternative”?
If you’re absent, don’t complain about model bias – earn your spot with PR, credible case studies, and assets that reinforce what the engines are trying to prove about you.
Next, switch to the quantitative side.
In GSC, build regex filters for conversational queries – the long, natural-language strings (4 to 10 words, often more) that resemble prompts with the serial numbers filed off.
We don’t yet know how much of this traffic comes from bots, LLM scaffolding, or humans typing into AI-powered SERPs, but we do know it’s there.
Track impressions, clicks, and the proportion that are clearly buyer-intent versus informational.
If your conversational query clicks are growing and skewing commercial, that’s a strong signal your GEO is turning curiosity into consideration.
The two-second rule: Why informational content won’t save you
Here’s a hard truth for the SEO content mills: informational traffic is about to become even less valuable.
Most AI citations offer only fleeting exposure.
Brand recall takes more than a glance – in both lab and field data, you get roughly two seconds of attention to make anything stick.
Most sidebar mentions and AI Overview snippets don’t deliver that, and the memory fades fast anyway.
If your GSC export shows that 70% or more of your clicks come from “how-to” mush with no buyer intent, your GEO isn’t working.
It’s subsidizing the LLMs that will summarize you out of existence.
Fix the mix – shift your asset portfolio toward category entry points that actually precede purchase.
Here’s your weekly CMO/SEO standup. Four lines, no fluff.
1. Share of search (brand)
Your brand’s share versus your top three competitors, trended over 13 weeks.
Up is good. Flat is a warning. Down means it’s time to get comms and PR moving.
2. Share of buyer-intent traffic
Your estimated share of non-brand commercial clicks versus competitors (from tool triangulation), plus your actual buyer-intent clicks from GSC.
The gap between the two is your reality check.
3. Prompt visibility index
For each priority CEP, how often are you recommended by major models, and with what supporting evidence?
Track monthly.
Celebrate gains.
Fix absences with PR and proof.
4. Conversational query conversion
Impressions and clicks on 4–10+ word natural-language queries, segmented by intent.
Are the commercial ones rising as a share of total? If not, your GEO is a content cost center, not a growth driver.
How to read the scoreboard
If those four lines are improving together, your GEO is working.
If only one is improving, you’re playing tactics without strategy.
If none are improving, stop thinking you can “Wikipedia” your way to growth with topical-authority fluff.
The levers that actually move GEO
What moves the dial? Not more “SEO content.” GEO responds to the levers of brand availability:
PR that builds credible third-party evidence: Reviews, analyst notes, earned features, and founder or expert commentary with substance. LLMs love corroboration.
Customer-centered case studies: Framed around CEPs, not your product roadmap. “Marketing manager replaces X to cut acquisition costs in 90 days” beats “New feature launch.”
Tighter copy: Precise, functional language matched to CEPs and prompt families. Kill the poetry.
Experience signals: Your site must resolve buyer intent fast. The conversation from AI should land on pages that continue – not restart – the dialogue.
Content still matters, but only as support for these levers.
Most of your old blog inventory was never going to build memory or distinctiveness, and in an AI-summarized world, it certainly won’t.
Scrap the vanity spreadsheets. Build assets that make both engines and humans more certain you’re the right choice in buying situations.
Yes, content marketing is back in a big way – but that’s another article.
GEO isn’t just SEO
When AI modes become the default interaction layer, and they will – whether through chat, answers, or blended SERPs – the game rewards brands that are easy for machines to recommend in buying moments.
That is GEO’s beating heart: increasing AI availability.
Think of it like free paid search.
If you’re still obsessing over informational traffic and topical hamster wheels, you’ll be caught with the lights on and no clothes. Some of you already are.
SEOs who make the leap become organic-search strategists.
You’ll speak CEPs, buyer intent, and brand effects.
You’ll partner with PR, product marketing, and sales enablement.
You’ll still use the tools – Semrush and GSC – but you’ll use them to evidence strategy, not to justify content churn.
The rest of you? You’ll be replaced by an agentic workflow that writes better filler faster than you ever could.
The humbling truth about GEO
Marketing rewards humility.
You are not the consumer, and you are certainly not the model.
Stop guessing. Measure the four lines.
Map the category entry points.
Build the assets that make you easy to recommend.
Cross-reference tool estimates with your own data and let the differences teach you.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/10/How-to-know-if-your-GEO-is-working-AFtR26.jpg?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-14 12:00:002025-10-14 12:00:00How to know if your GEO is working
Yoast SEO is a free WordPress SEO plugin that helps your site perform better in search engines like Google. It also gives you the tools to bring your content to the highest SEO and overall readability standards. Here, we’ll explain how our plugin helps you build the best website possible!
Yoast SEO offers many tools and features to boost your SEO. Some of these features influence the SEO of your whole site, while others help you optimize individual posts and pages for search engines.
At Yoast, we believe in our mission, “SEO for everyone,” so you can access all the essential WordPress SEO tools in our free Yoast SEO plugin. But if you really want to boost your SEO, upgrade to Yoast SEO Premium. This upgrade gives you even more amazing SEO features, including great AI features like Yoast AI Optimize and AI Summarize! Keep reading to find out what Yoast SEO can do for your SEO!
SEO for your posts and pages
If you want your posts and pages to appear in the search results, you need to optimize them! So, when you use WordPress to create/edit posts, you’ll find a lot of Yoast SEO tools to help you draft and optimize great content. And if you think SEO optimization is all about keywords, think again. The tools and tips in our Yoast SEO plugins also focus on quality content and user experience. Trust us, because it will all help your rankings, directly or indirectly.
Here’s how the plugins will help you optimize your posts and pages:
Make sure you’re optimizing correctly (we’ll tell you if you aren’t)
After you’ve done your keyword research, you’ll have to start optimizing the pages and posts on your sites for the keywords and keyphrases you want to rank for. To do that, you can set a focus keyphrase for an article in Yoast SEO. Then, the plugin uses our content SEO analyses to determine how your content scores on different factors. It checks how many times you use your keyphrase, the length of your text, or whether you used any internal links.
The results of these analyses guide you in optimizing your post or page to rank with your chosen keyphrase. You’ll see red, orange, and green traffic lights to indicate how every factor scores. This gives you an overview of the overall score and what you can still tackle to increase your rankings!
We also give you tools to find out which keywords you can target successfully, and track how successful your content really is. For the keyword research part, we integrate with the leading online marketing platform, Semrush. For tracking the performance of your content in search, we integrate with the rank tracking platform Wincher.
The content SEO analysis tells you how to optimize your text for a certain keyword with the use of red, orange, and green traffic lights.
Guidance for writing high-quality content — in many languages!
Optimizing your content to rank with the right keyphrase is important, but don’t forget your reader! Even if you write amazing content for search engines, your audience won’t benefit from it if they don’t understand it. When a person doesn’t understand your content, the chance of them buying something from you is close to zero. The same is true for the odds of them sharing one of your articles with their friends. So, you must ensure your content is also easy to understand. And that’s where the readability features come in.
Our readability checks let you adopt the feedback in a way that suits you, without losing your personal touch. If you’re interested in all the factors that increase readability, you can read more about the Yoast SEO readability features. What’s more, you can optionally enable the inclusive language analysis alongside readability and SEO checks
The readability analysis tells you how to optimize your text to make it read easily using red, orange, and green traffic lights
All or most features are available in the following languages: English, German, Dutch, French, Spanish, Italian, Portuguese, Czech, Russian, Polish, Swedish, Hungarian, Indonesian, Arabic, Hebrew, Turkish, Norwegian, Japanese, Slovak, and Greek.* We support more languages at various levels. Check the overview for other languages.
* Unfortunately, it’s not possible to calculate the Flesch reading ease score for some of these languages. Check the overview below to see which languages.
Based on years of research
Yoast SEO’s readability features are well-researched analyses that give you feedback on how to optimize your writing. Now, this may sound strange, because the way you write can be very personal. Let us explain how it works.
The plugin uses an algorithm to check your content for factors that are proven to increase readability. We look at the use of transition words, the use of passive voice, sentence and paragraph lengths, word complexity, and more. However, we carefully crafted this algorithm to be as accurate as possible without being too strict.
Influence what Google shows in search results
Of course, you don’t just want your pages to appear in Google’s search results. You want your search results to look amazing, too! That’s why Yoast SEO has tools to let you plan and preview how each page will (probably) look when it appears on Google. This is probably something we can’t avoid here, as Google will occasionally decide it knows better and show something else instead. But by optimizing certain outputs on your page, you can indicate how Google should present your content to users. And that’s still something worth doing.
Titles and meta descriptions
With our plugin, you can specify an SEO title (the ‘headline’ of your search result) and a meta description (a short piece of text underneath your search headline, describing what users can find on your page) for each new page you publish. We’ll let you know if these are too long or if your keyword is missing. If you want to, you can also set defaults for all your pages.
The search appearance section of Yoast SEO shows how your content will look in the SERPs
You might have seen search results that contain extra parts beyond the usual headline-and-description format before. The example below contains recipes with extra information like reviews, cooking time, ingredients, and images, for instance. And that’s just one example. Extra information can be added for all kinds of results, including products!
A structured data-powered search result in Google for recipes
The way to get results like this is by using Schema structured data. We won’t lie: it’s complex, technical stuff. Luckily for you, you won’t need to know a thing about the tech wizardry behind it. Just having Yoast SEO installed means you’ll automatically have structured data output for your pages. All you need to do is select a few options to make sure it suits your needs.
Manage social outputs
Now, social media isn’t strictly a part of SEO. But when you make great content, you often want to share that content on your social feeds, too. That’s why Yoast SEO also comes with Facebook and X previews that you can adjust to make sure your content is always looking great, whoever is sharing it. You can set a specific title, description and OpenGraph image for each post. Again, if you prefer to set one standard structure for all posts, there’s an option to do that.
Technical SEO for your website
We’ve taken a look at what Yoast SEO can do for your posts and pages. But what can it do for your site overall? If technical SEO isn’t your strong suit, much of the following may not make sense to you. But don’t worry! Yoast SEOexists to make sure you don’t have to know all of these things.
Set up your site for SEO
The plugin settings are very sensible by default, and our first-time configuration also guides you through the steps to get your technical SEO settings right. Behind the scenes, our hidden features will also gear you up with an XML sitemap, a robots.txt file, site-level Schema structured data, and more.
The free version of Yoast SEO automatically generates XML sitemaps for your website, making it easier for search engines like Google to find and index your content. These sitemaps update on their own whenever you add or remove pages, so you don’t have to do any manual work. In addition, Yoast SEO gives you easy access to your site’s robots.txt file. From the plugin, you can view or edit this file to control which parts of your site search engines are allowed to crawl. Both features help search engines discover your content while giving you more control over your site’s visibility.
Thanks to Yoast SEO, you can now quickly and without additional cost add an llms.txt file to your site to guide AI systems toward your most valuable content. This simple text file helps AI tools identify and prioritize key pages efficiently, ensuring they focus on what matters most to your site.
Manage your content
As you write more and more content for your site, you’ll be looking for easy ways to manage it! The Yoast SEO plugin comes with a few features to help you manage your content well and avoid common SEO issues. For instance, when you make changes like deleting a page or changing a URL, if you don’t know what you’re doing, then things can get messy. And if you make a lot of similar pages, that can be a problem too, as Google doesn’t know which one it should direct users towards. To help you deal with SEO issues like these, Yoast SEO comes with two unmissable tools: canonical URL tags and the Redirects tool.
Canonical URLs
Canonical URLs are really helpful if you have a lot of similar content, such as a webshop with multiple variants of the same product, each having its own page. To make life easy for you, Yoast SEO automatically adds canonical tags to all content marked for indexing. All of the canonical tags will be taken care of in the background; in most cases, you won’t need to change a thing. If you do need to adjust your canonical URL tags, it’s easy to do so.
Managing redirects
Redirects are essential if you’re moving or removing content. The fact is, users will probably still find their way to the old URL, but the content they’re expecting won’t be there. That’s not only disappointing and frustrating for users, but it can also make it harder for Google to find and index your content, too. While advanced redirect management is part of Yoast SEO Premium, you can still handle basic changes using WordPress settings or other free plugins.
Managing redirects is easy with Yoast SEO Premium
Build your site structure and internal links
If you want findable content that really ranks, you need to take care of your site structure and internal linking. The Yoast SEO plugin comes with a few tools to help you manage how your content links together: there’s a text link counter, which will tell you how many incoming and outgoing internal links there are on a page, as well as an internal linking suggestions tool in Yoast SEO Premium (in the editor view), which can help you add more if necessary. These features help you build a strong site structure and make sure your important content is easy for visitors and search engines to find.
Even more technical features of Yoast SEO
By simply installing the plugin and following the steps in our configuration workout, you’re already fixing a lot of important technical SEO things for your site! We do these steps for you, so you don’t have to know about every little technical detail.
If you really want to know everything Yoast SEO can do for you, then take a look at the complete list of features. Additionally, if you are (a bit more) familiar with technical SEO, you might enjoy reading more about Yoast SEO’s hidden features that secretly level up your SEO!
Still need to learn about SEO? One of the biggest benefits of using the Yoast plugins is that they make it really easy to get started and learn as you go along! We’ll give you pointers to help you get everything right, as well as links to read more about how SEO works and how to do it.
If you want to keep learning about SEO, we also offer free training courses and resources in our Yoast SEO Academy and on our SEO blog. You can start with these basics to understand how SEO works and get more out of your website as you go.
A quick recap
In this article, we’ve shown you what Yoast SEO can do for your site. Our plugin helps you improve your content SEO by helping you set a keyphrase and telling you exactly how you can optimize your content to rank with this keyphrase. The plugin also helps you improve the readability of your content by providing feedback that you can easily incorporate into your own writing style. And last but not least, the Yoast plugin improves your technical SEO by taking care of a lot of technical things in the background.
Everything above is available in Yoast SEO’s free plugin, making it a great starting point for most WordPress users. If you ever want more advanced tools, you can always explore Yoast SEO Premium and its extra features.
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If you have ever run your writing through a readability checker like Yoast SEO, you have probably come across the Flesch reading score. This metric was developed more than 70 years ago and is still one of the most widely used ways to measure how easy your text is to read. But what does it actually mean, and how does it affect your writing for the web?
In this guide, we will explain how the Flesch reading score works, why it became so prominent in publishing and SEO, and how you can use it effectively today. We will also show you where it fits into the Yoast SEO plugin and why we have introduced new readability checks alongside it.
Reminder: We made changes to our readability analysis in Yoast SEO 19.3. We replaced the Flesch Reading Ease Score with the word complexity and sentence length assessments. You can find the Flesch reading ease score in the Insight tab, but we won’t use this assessment in our readability analysis anymore.
What is the Flesch reading score?
The Flesch reading score, also called the Flesch reading ease test, was created by Rudolf Flesch in the 1940s. His goal was simple: to give writers a quick way of checking whether their text was easy to understand. The formula combines three basic elements: sentence length, word length, and syllable count. When these figures are combined into the formula, which I’ll explain in just a moment, they generate a score between 0 and 100.
The highest scores are reserved for the easiest text. For example, a score in the 90s suggests that a typical 11-year-old child should be able to read it without any difficulty. A score of around 60 is closer to plain English that a high school student would be expected to understand. Scores under 30 are considered very difficult and are only really found in academic or legal writing.
Here’s a quick overview of the ranges and what they mean:
Score range
Readability level
Who can understand it
90–100
Very easy
An average 11-year-old student
80–89
Easy
Middle school students
70–79
Fairly easy
Teenagers aged 13–15
60–69
Standard
High school students
50–59
Fairly difficult
College students
30–49
Difficult
University graduates
0–29
Very confusing
Specialists, academics, or experts
Just for fun: this article itself scores around 63 on the Flesch reading score, which puts it in the “standard” range.
How the Flesch reading score is calculated
The formula behind the score looks intimidating, but don’t worry, it is surprisingly straightforward. In fact, it’s only based on two things. The total number of words divided by the total number of sentences, which gives us the ASL or Average Sentence Length, and the total number of syllables divided by the total number of words to get the ASW or Average Syllables per Word. Once we have these figures, we enter them into this formula:
206.835 – (1.015 × ASL) – (84.6 × ASW)
This will give us a score between 0 and 100. The longer your sentences and the more complex your words, the lower your score will be.
Let’s take a quick example by looking at this short text below:
“The cat sat on the mat. The dog barked.”
This has very short words and sentences, so it would score in the 90s, which means it is very easy to read.
Now compare it with:
“The domesticated feline reclined languidly upon the woven floor covering, while the canine produced a resonant vocalization.”
This is essentially the same meaning, but longer words and clauses drop the score dramatically, likely into the 30s.
This example shows why the Flesch reading score works well as a proxy for readability. It rewards writing that is concise and simple with a high score and wags a finger at writing that is dense and complex, ultimately giving it a low score.
Why the Flesch reading score became important
The Flesch reading score spread beyond classrooms into business and publishing because it answered a universal question: Is my writing easy to understand?
By the 1970s, the U.S. Navy was using it to ensure that training manuals were clear for recruits. Later, several U.S. states made it part of their official requirements for insurance documents and consumer contracts. Healthcare organizations also began using it to ensure that patient information was accessible.
When personal computers became common, Microsoft Word added the Flesch reading ease test to its spelling and grammar tools. Suddenly, anyone writing a school essay or business report could get instant feedback on readability. That mainstreamed the score and kept it relevant well into the digital age.
In the world of web writing, readability became even more critical. Online readers scan rather than study text. Research shows they decide within seconds whether a page is worth their time or not. That makes clarity a competitive advantage. Tools that included the Flesch reading score gave web writers a way to benchmark themselves and improve user experience.
The Flesch reading score in Yoast SEO
When Yoast introduced readability checks to the plugin, the Flesch reading score was one of the first tools we built in. We popularized the use of tools to score your content. It gave writers using WordPress an instant way to measure whether their content was accessible to a broad audience. You can still find the Flesch reading ease score inside the plugin today, in the insights tab.
This has helped thousands of users discover that shorter sentences and simpler words often improve how people engage with their content. While the score does not guarantee better rankings, it does contribute to a positive reading experience, which in turn can influence user behavior and SEO outcomes.
The Insights tab contains a lot of information, including your Flesch reading ease score
Why Yoast moved beyond Flesch
The Flesch reading ease score is a useful tool, but it has its limitations. For one, it only looks at sentence and word length, ignoring context, tone, and audience. A medical blog, for example, might score poorly even if it’s perfectly suited to its readers.
There’s another issue: the Flesch score combines two factors, sentence length and word length, into one number. If your score is low, you won’t know which part needs fixing. That’s why we added separate checks for sentence length and word complexity. Word complexity doesn’t just measure length; it also takes into account a few other elements, like how common a word is. Based on all these factors, it assesses the difficulty of your vocabulary, giving you clearer feedback.
This way, you can still use the Flesch score as a quick guide, but with sharper insights to refine your writing.
Should you still care about the Flesch reading score?
The Flesch reading score remains a valuable guide for writers who want to make their content more approachable. If your text scores very low, it may be worth shortening sentences or replacing long words with simpler alternatives. But you do not need to obsess over getting a perfect score.
Readability is about more than numbers. Think about your audience, their expectations, and the purpose of your content. Combine the Flesch reading score with other readability signals to create a text that is clear, engaging, and optimized for both humans and search engines.
How to use the Flesch reading ease score to improve your writing
We’ve come to the essential question. How can you use the Flesch score to improve your writing? Well, you write for an audience and know your audience the best. Before writing or editing, consider what kind of texts fit your readers. Do you sell clothes or organize photography workshops? Or do you write for a mom blog or make step-by-step DIYs? Your content should be relatively easy to read in all these cases since you are targeting a broad audience.
However, remember that you do not have to chase a high Flesch reading score at all costs. For example, you may write about complex, specialist topics for a specific, more knowledgeable audience. Or, perhaps you are an academic blogging about your research? It makes sense if the Flesch test produces a lower score in those cases.
Still, whatever your situation is, your text always benefits from concise language. So, if you want to benefit from the feedback the Flesch reading ease score gives you, focus on two things:
1. Shorten your sentences
Too many long sentences make your text difficult to read, while short sentences keep the subject clear. When the sentences in your text are short, you allow your readers to absorb the information in your text. As a result, they don’t need to use all their attention to decipher what you want to say. That is why we advise you to break down long sentences; your text will be much easier to read.
And please, don’t think that by using short sentences, you will oversimplify your text. Let’s compare two short texts to show you what we mean. First, we have this sentence:
My favorite place to visit during weekends is my grandparents’ house near the lake, where we love to fish and swim, and we often take the boat out on the lake.
Did you find this sentence easy to read? Wasn’t it too lengthy, confusing, and difficult to process? Breaking it into two or more sentences can make it much clearer:
My favorite place to visit during weekends is my grandparents’ house. It’s near the lake, where we love to fish and swim. We also often take the boat out on the lake.
These few short sentences are much easier to read. Yet, you give the same information as in the long sentence, so there is no oversimplifying. Using short sentences keeps the subject clear and lets your readers absorb the information you’re presenting.
Shorten your sentences with Yoast SEO
The Yoast SEO Readability analysis helps identify long sentences with its sentence length assessment. You can also use Yoast AI Optimize for sentence length for quick, automated improvements.
2. Limit your use of difficult words
Words with four or more syllables are considered difficult to read, so try to avoid them where possible. Or try not to use them too much. For example, try words like small instead of minuscule, about instead of approximately, and use instead of utilize. We have the word complexity assessment in Yoast SEO Premium to help you with that.
If you want to reach a broad audience, you should also try to avoid using jargon. If you’re a medical expert, you’re probably familiar with terms like analgesic, intravenous, and oophorectomy. However, keep in mind that most people aren’t. When you can’t find a better alternative, make sure to explain it for users who might not know the word.
Conclusion
The Flesch reading score has been around for decades, and it is not going anywhere. It still offers a quick way to test whether your writing is easy to follow, and it continues to play a role in Yoast SEO. At the same time, readability isn’t just about scores. Readability is about meeting your goals. By breaking down the Flesch reading ease score into clearer checks (like sentence length and word complexity), you get actionable feedback to refine your writing. That way, your content stays readable and effective.
So next time you write a blog post, take a look at your Flesch reading score. Use it as a guide, not a rule. The result will be content that your readers and search engines will thank you for.
TLDR
You should care about your score, but do not chase perfection. Balance readability with your audience’s needs
The Flesch Reading Score measures how easy a text is to read, using sentence length and word length
Scores range from 0 to 100: higher is easier. For example, 90–100 is very easy, 60–69 is standard, and 0–29 is very confusing
It became popular in education, government, and publishing before being integrated into tools like Microsoft Word and SEO platforms
In Yoast SEO, the Flesch reading score still exists in the Insights tab, but we now also use word complexity to provide more accurate feedback
Go Premium and get free access to our SEO courses!
Learn how to write great content for SEO and unlock lots of features with Yoast SEO Premium:
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Omnichannel marketing is a way to make your brand feel the same everywhere: website, email, ads, social, SMS, app, and in-store. People can start on their phone, switch to a laptop, and buy later without friction.
Why is this important?
Your customer doesn’t think in channels. They see one brand. If your ads, emails, site, app, and store don’t match, money slips through the cracks. Omnichannel marketing closes those gaps and moves more people to buy.
But how many more people are buying from omnichannel campaigns versus single-channel campaigns?
A lot, actually.
An Omnisend study found the purchase rate of omnichannel marketing campaigns to be 287% higher than single-channel campaigns.
Creating a seamless experience for your customers means better brand perception and higher revenue. It’s a real win-win.
This guide walks you through omnichannel marketing strategy benefits, best practices, and examples. By the end of it, you’ll understand what goes into creating an omnichannel campaign that drives results.
Key Takeaways
Omnichannel marketing creates a seamless customer experience across every touchpoint, including website, email, ads, SMS, social, app, and in-store.
Brands using an omnichannel strategy saw purchase rates 287 percent higher than single-channel campaigns in one study.
Unlike multichannel marketing, omnichannel connects your data and messaging across platforms so everything works together, not in silos.
Benefits include better customer experiences, stronger brand recognition, more personalization, higher loyalty, and increased revenue.
To get started, map your customer journey, centralize data, integrate your channels, and follow clear brand guidelines for a consistent feel.
What Is Omnichannel Marketing?
Omnichannel marketing is a marketing strategy that seamlessly integrates all of a business’s marketing channels to create a cohesive shopping experience for each customer.
As customers move through the sales funnel, an omnichannel strategy ensures all touchpoints seamlessly speak to each other so that no matter where a potential customer makes contact with your business, it feels like the same channel.
Here’s how it looks in practice.
A customer might check out a product on a brand’s website. They decide they’re not yet ready to make a purchase, but then they’re met with ads for that product across different social media channels. They can easily click through and buy the product, even though it’s not the same channel they initially used to shop.
This is what omnichannel looks like on a small scale. At enterprise scale, the same idea gets bigger. Your teams share a single customer profile, so service reps, store staff, and ads all see the same context. POS and ecommerce pull from the same inventory. Loyalty rewards apply online and in-store. Buy online, pick up in store just works.
That’s an omnichannel marketing strategy: connect data and creative across channels so customers move forward, and your revenue does too.
Omnichannel Marketing vs. Multichannel Marketing
Before we dive deeper into what omnichannel looks like, let’s talk about how it differs from a similar tactic called multichannel marketing. Both obviously occur across different channels. But they work slightly differently.
Omnichannel marketing uses multiple channels, but it ensures that all channels are integrated seamlessly, creating a connected experience. Meanwhile, multichannel marketing just occurs across different channels, treating them more as separate entities than trying to build an interconnected ecosystem.
Multichannel is useful for quick reach and simple campaigns. Think one-off promos, early tests, short cycles, or when tools and data are basic.
Omnichannel is best for cross-device shoppers, syncing online and in-store experiences, and longer, more complex customer journeys.
Bottom line: start with multichannel, then shift to an omnichannel marketing strategy when you’re ready to connect data and deliver one continuous experience.
Why Omnichannel Marketing Is Important
Your buyers don’t stick to one platform. They search on Google, watch a review on YouTube, see a Reel, ask ChatGPT for a product comparison, click an email, price-check on Amazon, and walk into a store. If you only optimize for organic search, you miss the moments that push customers to act.
Omnichannel marketing lets you show up at key points in the customer journey and connects those touchpoints so the experience feels cohesive. Your ad matches the email. The site matches the app. The cart follows the customer across devices. Service and store teams see the same history. That consistency builds trust and cuts friction, which leads to more sales.
An omnichannel marketing strategy also spreads risk. If one channel slows down, you still have paid social, SMS, marketplaces, and retail working together.
It improves measurement, too. Shared data tells you which mix drives first purchases, repeat orders, and higher order values.
People discover, compare, and buy across many platforms. Brands that coordinate messages and data across those platforms win more often. If you’re serious about growth in today’s digital world, build an omnichannel marketing strategy so your brand is clear, consistent, and present at every step.
Benefits of Omnichannel Marketing
Omnichannel marketing has a number of benefits. These advantages can provide your business with better results and happier customers.
Think of omnichannel marketing as the glue that holds your entire shopping experience together.
Improved Customer Experience
Omnichannel marketing focuses on creating an interconnected experience no matter where your customers are interacting with your business. Because of this, it creates a seamless customer experience that’s vastly better than if the different channels couldn’t speak to each other.
Here’s what that means for customers: progress carries over (carts, wish lists, support tickets), and context follows them from device to device. If they ask a question on chat, your email workflow resurfaces it. If they browse a size in the app, your site remembers.
Abandon cart emails are great examples of omnichannel marketing in action. A customer visits your website and adds an item to their cart. They leave your site without completing the purchase. That action is sent to and triggers an ‘Abandon cart’ workflow in your email marketing platform.
They receive an automated email with the item in their cart and some encouraging words and/or a discount to get them to complete the purchase.
An omnichannel marketing strategy reduces repeats, dead ends, and mixed messages so buyers feel understood and move forward faster.
Better Brand Awareness
Creating a consistent experience across platforms (including in-store) makes it easier for customers to recognize your brand. Plus, as more people have positive omnichannel experiences with your brand, they’re more likely to share it with their friends and family, boosting word-of-mouth referrals and awareness.
Consistency is a key component of a strong brand strategy. When people see the same appearance, messaging, and offers across channels, recall and trust in your brand grows. Pair that with targeted campaigns across search, social, and marketplaces, and your brand shows up more often for relevant terms with the same look and promise.
Personalization
When your marketing channels speak to each other, you’re presented with even more opportunities for gathering customer data that can be used to personalize experiences across all channels, and not just the ones they’ve used before. This personalization is just another way to improve the overall experience with your business, making it easier for customers to work with you.
Use customer actions, like product views, cart adds, and website searches to customize messaging. Recommend items that fit past behavior, pause promos after a purchase, and nudge at the right time (not just more often). Keep consent and preferences front and center.
Done well, omnichannel personalization feels like help, not hype.
Customer Loyalty
As customers discover how easy it is to work with your business, they’re more likely to stick around and continue to buy from you again and again. Why bother finding a competitor if your business has created such a seamless shopping experience?
Loyalty grows when every interaction feels smooth and familiar. Connect rewards across store and online, recognize returning customers, and close the loop on issues fast.
Use lifecycle triggers, like welcome, re-engagement, and win-back, to stay relevant without spamming. The easier you make repeat buying, the less tempted people are to price-shop elsewhere.
Competitive Advantage
Just like we mentioned, there’s no need for customers to shop around and test out your competitors if you’ve provided such a great shopping experience. Omnichannel marketing gives you a major competitive advantage, fueling more of your target audience to head straight to you rather than others in your industry.
Most teams still run channels in silos. You’ll move faster because your data, inventory, and messaging are already in sync. Creative can be reused, offers are consistent, and measurement is clearer. That speed compounds into lower costs and better customer outcomes, an edge that’s hard to copy without a true omnichannel strategy.
Higher Revenue and Conversion Rates
Naturally, if people are sharing their positive experiences, sticking around longer, and ultimately having a great relationship with your brand, you’re going to reap those benefits in the form of higher revenue and conversion rates. Which is the ultimate goal, right?
More relevance and less friction mean more adds to cart, more checkouts, and bigger orders. Omnichannel marketing also improves attribution, so you can double down on the mix that actually drives purchases and repeat business.
Over time, the flywheel kicks in: Better data leads to sharper targeting, which leads to stronger retention, which leads to higher revenue.
Best Practices for an Effective Omnichannel Marketing Strategy
Your goal is simple: build an omnichannel marketing strategy that feels consistent everywhere and moves people forward. Start with what customers do today, not what you wish they did. Then connect the channels and tools you already use, fill the gaps, and measure what actually changes behavior.
Follow along with these steps to learn more about creating an effective omnichannel marketing strategy that will boost your customer satisfaction.
Collect & Analyze Customer Data
Start by centralizing truth. Pull website analytics, email metrics, ad performance, POS data, support logs, and audience sentiment into one view so you can spot insights like:
The channels your customers prefer to use when interacting with businesses
Which devices your customers spend the most time on
The types of messaging that seem to resonate most with them
How your customers feel about your current shopping experience
Then, pick an attribution model that fits your business. Each model is tailored to different types of customer journeys and campaign goals.
For example, position-based tracking is better for businesses with longer sales cycles, like B2B and lead gen. And data-based attribution is great for omnichannel e–commerce strategies, marketplaces, subscription apps, and retailers with steady traffic.
Check out the graphic below for a full breakdown of attribution models you can use to measure the success of your omnichannel marketing efforts.
Map Out the Customer Journey
Your next step is to map out your current customer journey. Outline each step that a Your next step is to map out your current customer journey. Outline each step that a customer would have to take from first discovering your business all the way to becoming a repeat customer.
As Matthew Santos, SVP of Products and Strategy at NP Accel, explains, “Customer journey mapping involves visualizing a customer’s various touchpoints with your brand, from initial awareness to purchase and beyond. By understanding these touchpoints, you can identify which channels are most important at different stages of the journey.”
To create your map:
Identify your customers: Identify your customers’ names, addresses, and other demographic information. Look in your CRM or use a current buyer persona.
Understand their pain points: What drives your customers to make a purchase? What challenges do they want to solve?
Find out where they hang out: What platforms do your customers use during the purchase process?
Track the conversion path: How do most of your customers convert? Their path is unlikely to be straight. They might visit your website, view your Instagram reels, and then purchase in-person, in your store. Aim to define the most common paths.
In the end, your customer journey map might look something like this:
Now it’s time to identify and integrate your different sales and marketing channels, which could include:
Social media
SMS marketing
Email marketing
Your website and online store
A physical store
A mobile app
Make sure to include all channels that you’re currently using to reach your target audience plus any channels you’ve discovered your customers prefer.
For example, you might not have previously incorporated SMS messaging into your overarching marketing strategy, but your customer data analysis showed you that your target audience prefers that method of communication.
Once you’ve selected the different channels you’ll use to communicate, market, and sell to your customers, it’s time to get them to work together.
To properly integrate your marketing avenues and create a successful omnichannel strategy, you’ll need the right technology. Some tools to consider include:
CRM: A CRM can help you store customer information so that it’s accessible across channels. It can also help you segment out your audience to create even more tailored and personalized experiences. Omnisend is a great option for building out specific segmentations.
Marketing Automation Software: To build an effective omnichannel marketing strategy, you need marketing automation tools to engage more on social media, send scheduled emails, or move users through the conversion process. Many tools you already use, like email marketing, CRMs, and social media management, have built-in automation features. You can also use a tool like Zapier to build custom triggers.
Social Media Management Tools: This type of tool can make it easy to communicate with your audience across various platforms. Get access to a social inbox that puts all conversations across all platforms in one single messaging dashboard. Use auto-replies or canned responses that ensure communication is consistent across the board. Hootsuite and Sprout Social are both great options to consider for your social media management.
Customer Data Platforms (CDPs): A CDP pulls data from all your touchpoints—site, app, ads, email, POS—into a single customer profile. That unified view makes it easier to segment audiences, personalize campaigns, and keep experiences consistent across channels. Tools like Segment or mParticle help you clean, connect, and activate data without needing a dev team for every change.
Once you’ve set up the right tools and integrated all your channels, it’s time to make sure your teams are all on the same page. If your customer support team is using different messaging than your social media team, your overall strategy is going to feel disjointed.
By creating documented brand guidelines that cover how your customer-facing teams should be communicating with customers and talking about your products, you can ensure your channels feel connected.
Your brand guidelines should include things like:
Guidance for brand visuals, like logos, imagery, colors, and graphics
How to handle customer support issues or questions to create positive and consistent experiences
Tone and voice guidelines with “do’s and don’t’s” examples
Copy guidance with channel-specific examples (e.g. email subject lines vs. educational blog content)
Legal guidelines on what you can and cannot discuss, if applicable
Share your brand guidelines with your entire team and make sure everyone is familiar with them. Give constructive feedback when you see people straying.
Brand consistency is the glue that holds an omnichannel marketing strategy together.
Test & Measure Your Efforts
After sharing your brand guidelines across your company and implementing your omnichannel approach, it’s time to test everything out. Run through each of your marketing channels the way you might if you were a new customer to make sure the experience feels seamless from discovery to purchase.
Then, think about how you’ll measure success.
In omnichannel marketing, you need to consider metrics that touch every part of the funnel. For example:
Discovery: Impressions, educational blog traffic, mentions in the media
Consideration: Engagement on social media, product views, visits to company pages
Conversion: Orders, checkout rate, CPA
Loyalty: Repeat rate, time between orders, customer reviews
Use clean UTM rules, consistent naming, and dashboards that show both channel and journey views. Review the data weekly for anomalies, monthly for trends, and quarterly for bigger bets.
3 Examples of Omnichannel Marketing
Let’s look at a few examples of omnichannel marketing in practice so you can get an idea of what this could look like for your own business.
1. Sephora
Sephora offers an amazing omnichannel experience for its customers. First-time customers are able to sign up for a Sephora account using their phone number, and then keep track of all purchases there.
Customers can figure out what they’ve purchased before and when, which makes it easier for them to restock on the products they love. It also makes it easier for the marketing team to tailor messaging and special offers to each customer’s unique shopping preferences.
Sephora accounts also track customer rewards points, as well as when their birthday month is. Whether they make a purchase online or in the store, Sephora sends the customer a little sample-size product as a birthday gift.
This omnichannel strategy makes shopping with Sephora feel easy and personal, no matter where someone is making a purchase.
2. Starbucks
The Starbucks app makes for an amazing omnichannel experience that the coffee brand’s customers love. Not only can customers order through the app then pick up in a nearby store, they can also reload gift cards, pay in-store, earn and redeem rewards, and more.
The app also makes it extremely easy to find stores near you and personalizes its offerings based on the local weather. Starbucks is already a wildly popular coffee chain, but their omnichannel marketing strategy helps boost sales even more.
3. Target
Target is another great example of what omnichannel should look like. Again, customers can create an account and easily track past purchases so they can reorder products again and again with ease.
Target also has its own rewards program called Target Circle that allows users to rack up rewards they can put towards future purchases.
But one of the best things about Target’s omnichannel strategy is that customers can check online if a product is in stock at stores near them. And it’s wildly accurate, even during huge sales events like Black Friday.
The Future of Omnichannel
Omnichannel isn’t standing still. AI, automation, and privacy changes are reshaping how brands connect with customers. Search engines and social platforms now answer questions directly, sometimes before a click. In fact, nearly 60% of searches result in zero clicks.
So how does this apply to an omnichannel marketing strategy?
For marketers, it means two things.
First, you’ll need stronger first-party data—think email lists, purchase history, loyalty programs—to fuel your targeting as third-party cookies fade. Second, you’ll need systems that can use that data in real time, adjusting offers and content across every channel without manual work.
Expect channels themselves to keep expanding. Voice assistants, connected TV, chat apps, and even in-car systems are becoming part of the customer journey. The brands that win will be the ones that stay consistent across all of them.
The future of omnichannel marketing is smarter, faster, and more connected. Get your data house in order now so you can adapt as AI and new platforms evolve.
FAQs
What is omnichannel marketing?
Omnichannel marketing is the practice of connecting all your marketing and sales channels so customers get one seamless experience. Instead of each channel running in isolation, they work together. For example, a shopper might browse on mobile, add to cart on desktop, and finish in-store, with their data and offers synced across all steps. This consistency builds trust, reduces friction, and increases conversions by making every touchpoint feel like part of the same journey.
What is the difference between multichannel and omnichannel marketing?
Multichannel means using multiple platforms, but each runs separately. Omnichannel connects those platforms so the experience is unified, not siloed.
How to implement omnichannel marketing?
Start by collecting customer data, mapping the journey, and picking channels your audience uses most. Then integrate tools like CRM, automation, and analytics to sync messaging and measure results.
Create Your Omnichannel Marketing Strategy Today
Your customers want an omnichannel experience, so it’s your job to give it to them. Figure out how to make your channels work together so your customers get a personalized, consistent, and seamless experience every time they shop with your business.
Sounds like a lot, but if you follow the steps above, you can start to build a more cohesive journey for your customers. And if you’re looking for additional help, an omnichannel marketing agency like NP Digital can bring your strategy to life.
AI has infinitely sped up the hype cycle in marketing.
So when the term “vibe marketing” came onto the scene, you may have rolled your eyes for a moment before you said, “I have to try this.”
In basic terms, vibe marketing means using AI to run entire marketing workflows. Usually, this involves a combination of:
Vibe coding: No-code AI tools where you type what you want (e.g., “Build me a landing page”), and the tool spins it up
AI agents: Always-on assistants that handle background tasks, like checking your inbox for leads or updating your CRM
And whether or not they consider themselves “vibe marketers,” many teams are already doing this.
In a survey of marketing teams doing $100m+ in revenue, GrowthLoop found that more than a third of those teams use AI to optimize campaigns or predict customer behavior.
And those embedding AI into their processes report more effective strategies.
So, is vibe marketing the next wave of marketing methodology? Or just more AI hype?
In this guide, we’re diving into real-world case studies that show how marketers are using AI in their daily workflows.
Plus, we’ll test the hype against reality based on my own experiments and the perspective of industry experts.
Vibe Marketing vs. Traditional Marketing
With vibe marketing, things like campaigns, segmentation, and competitor analysis can happen in the background. So you can focus more on creative work and strategy.
Here’s how it stacks up against traditional marketing:
Task
Traditional Marketing
Vibe Marketing
Campaign creation
Weeks of strategy, briefs, handoffs, and approvals
Concepts, landing pages, and emails drafted in hours
Audience segmentation
Manual data exports and persona-building
AI builds real-time dynamic segments
Competitive analysis
Manual research on competitor websites, social feeds, reports
Automated data scraping and AI summaries
Performance reporting
Hours compiling data into slides
Real-time dashboards + plain-English insights
This all sounds incredible, and it’s all technically possible for marketing teams today.
But here’s the catch: AI workflows are still clunky and experimental.
Hootsuite reports that while 83% of marketers say their AI budgets have increased, 4 in 10 companies waste at least
10% of their AI budget on tools that didn’t deliver.
Bottom line: Don’t expect AI workflows to run your marketing overnight. Sometimes building them takes longer than doing the task manually (I learned that firsthand — more on that later).
So, what does vibe marketing look like when it does work?
6 Examples of Vibe Marketing in the Wild
Vibe marketing can seem like a vague concept.
But when we talk about using AI to automate social listening workflows, follow up with inbound leads, or run competitive analysis, all of a sudden this ambiguous concept takes on real-world meaning.
We’ll see six examples of brands using vibe marketing in their daily workflows.
Plus, how you can copy these ideas into your own strategy.
1. Build Enterprise-Level Campaigns Without Reliance on Technical Teams
The biggest slowdown in most campaigns isn’t the marketing work itself. It’s the wait for other teams to deliver what you need.
At the job site, Indeed, those delays stretched to an average of 3.5 months per campaign.
Even simple requests — like defining an audience segment — meant analysts had to pull data from their warehouse. Then, engineers had to reformat it before marketing could use it.
With vibe marketing, the team broke that bottleneck.
They used the AI platform GrowthLoop to turn raw customer data into ready-to-use segments.
Now, their team can type a plain-English prompt (e.g. “nurses in the U.S. who searched jobs in the last 30 days but haven’t applied”) and instantly generate that segment.
Instead of waiting a whole quarter to get in front of job seekers, the team can now react to hiring needs in almost real time.
Try It Yourself:
If you’re on an enterprise team already using a data warehouse tool, GrowthLoop’s makes it easy to type a goal, generate audiences, and send them directly into campaigns.
On the other hand, let’s say you keep customer data in a CRM or spreadsheet — names, emails, recent purchases.
With a tool like Clay, you can import those leads and use the built-in AI to enrich them with more data.
Then, you can create campaigns that automatically go out based on that enrichment.
For example, when a company has received funding in the last three months, they can be automatically added to a campaign.
In seconds, you’ve got a list ready to target.
What makes this powerful isn’t just faster data access.
It’s the AI layer that turns raw information into something marketing can actually act on, without waiting on anyone else.
2. Automate Social Listening Workflows
Getting a lot of mentions on social media is great — until it isn’t. Some social media managers can spend hours every day sifting through comments and posts that tag the brand.
More than just being a tedious task, this is completely unsustainable.
Which is exactly what Webflow’s two-person social team realized.
Between Reddit, X, YouTube, and forums, they faced 500+ daily mentions. But only a handful actually needed a human reply.
Finding those few was like looking for needles in a haystack.
So, they built an AI workflow to do the sorting for them.
The system scans every mention, tags it by sentiment and urgency, and pushes the important ones straight into Slack.
Out of 500+ daily posts, the team now sees just 10–15 that matter most — and responds within the hour.
Pick one high-volume channel — maybe Reddit, X, or even a busy community forum.
Use a tool like Gumloop or Apify to pull in mentions of your brand. Then, run them through an AI categorizer to flag sentiment and urgency.
Start small, check the tags for accuracy, and only then scale to other platforms.
Note: To take this workflow a step further, add a tool like ManyChat or Yuma.ai to generate automated responses to posts and DMs. Entrepreneur Candace Junée did this and saw a 118% increase in leads while saving 15 hours per month answering Instagram DMs.
3. Create On-Brand Content Assets
Ever tried to turn a 40-page technical document into a blog post or campaign copy?
The content is there, but shaping it into something clear — and in your brand’s voice and style — takes time.
At Pilot Company, with multiple sub-brands and channels to manage, that challenge multiplied.
Writers spent hours summarizing technical docs into usable briefs. Designers waited for copy that matched the right tone before prototypes could move forward.
And inconsistencies crept in across brands.
So, the team used Jasper to help build consistency in style and tone.
They used the tool’s summarizer to condense long technical documents into actionable outlines, and the brand-voice model to keep messaging aligned across sub-brands.
Designers could even pull realistic placeholder text without waiting on writers.
The result: Each team member saved 3–5 hours a week, freeing them up for strategy and storytelling instead of slogging through documents.
Try It Yourself:
With a tool like Jasper, you can add specific instructions about your brand voice, audience, and even include source material to show what great content looks like for your brand.
Then, you can use it to create copy and content for entire campaigns.
You can also use tools like Notion AI, Claude, or ChatGPT to turn long documentation into campaign content.
Start by inputting your brand voice, style, target audience, and any other details that might be useful. Then, upload documentation and ask the AI to turn it into specific pieces of content.
Test the tools to find your favorite. Make sure to give specific instructions on what kind of output you’re looking for.
Use AI to generate briefs, draft first passes, or speed up design prototypes — and reserve human time for the creative polish.
On paper, 500+ inbound marketing leads a day looks like a dream for a small agency.
But for Tiddle, a six-person influencer agency, it was a nightmare.
They were buried in the flood of messages, with only a few that were worth pursuing. Sorting through the noise ate up 6–8 hours a day — time that should’ve gone into client campaigns and outreach.
Instead of hiring more staff, they brought in AI.
Using Lindy, every inbound email was screened automatically.
Low-quality offers were politely declined, while promising ones were flagged and routed to the right person.
If terms weren’t a fit, the AI could even suggest counteroffers.
The team went from slogging through hundreds of emails to focusing only on the 10–15 real opportunities that mattered.
As Tiddle’s CEO, Mike Hahn, says, “Every deal we’ve closed in the last few months came from Lindy surfacing the right conversations.”
Try It Yourself:
Pick one channel where inbound volume is overwhelming (email, DMs, LinkedIn).
Define the “must-haves” for a qualified lead (budget, offer type, brand fit), then use a tool like Lindy or Clay to screen and tag incoming requests.
You can even set up conditional logic so the tool can change how it responds based on specific conditions.
Note: Small companies aren’t the only ones making use of AI for inbound leads. Ariel Kelmen, president and CMO of Salesforce, recently said that they use AI agents to handle interactive follow-ups with leads. And those agents manage the first 80% of the conversation.
5. Build Hyper-Personalization for Your Ideal Customer Profiles
“Hi [first name]…” personalization doesn’t cut it anymore. But manually tailoring every message to your ideal customer profiles (ICPs) is impossible to scale.
Oren Greenberg, a solo marketing consultant, faced this problem.
And since there was no system that fit his ideals of hyperpersonalization, Oren built his own.
He coded a workflow in Replit that filtered a 50,000-company dataset, excluded existing contacts, and generated outreach tailored to each company’s stage and challenges.
The result: outreach so specific it only makes sense for the intended recipient.
Pro tip: Hyper-personalization works only if you deeply understand your ICP — AI can’t do that thinking for you. But once you know who you’re selling to, it can scale bespoke messaging in ways you couldn’t manually.
Try It Yourself
If you’re a highly technical person with the skills and know-how to recreate something like this in a vibe-coding tool, then by all means have at it.
For the rest of us, using a tool like Clay is a fast path to get 80% of the way there.
Start by defining your ICP.
Then use Clay to pull in business data, filter it against your ICP criteria, and enrich it with extra context.
With that data in place, you can add an AI-powered column that drafts personalized outreach for each prospect.
Run a pilot batch of 50–100 and iterate until the system feels like true one-to-one messaging.
6. Run Competitive Analysis
New marketing roles often start with 30-60 days of slow discovery.
Who are the real competitors? What do customers actually care about? What language do they use?
Semrush’s former VP of Brand Marketing Olga Andrienko found a way to shortcut that process.
Before Day 1 at a new job, she suggests running an AI-powered competitive analysis.
Pull your site and the top competitors’ pages, transcribe the most-viewed YouTube reviews, and mine Reddit and forums for repeated complaints.
Then, feed that into an AI summarizer to surface frequent feature praise or criticism and real customer phrasing. Tools like Google Opal or Gemini help cross-link those insights into a positioning map.
Whether you’re stepping into a new role, launching a campaign, or scoping out a new market, the same workflow applies.
First, pick your brand and three competitors. With a scraper tool like Apify, get your website copy and grab a handful of top YouTube reviews and forum threads.
Then, feed those into a tool like Claude, Gemini, or ChatGPT to summarize and analyze the data.
Extract the top five pains and language customers use, and sketch a one-page positioning map you can bring to meetings.
That way, you start your campaign with clarity — not uncertainty.
My Disastrous Vibe Marketing Experiment (What I Learned the Hard Way So You Don’t Have To)
Giving you examples is great, but I wanted to put all this to the test and see if I could build a usable AI workflow for myself. (Spoiler: It did not go well.)
Goal: Save time replying to LinkedIn comments without losing my voice.
Constraints: Something I could test immediately, for free, and that would actually be useful.
Method: Build a workflow that scrapes comments, learns my style, and drafts replies I could approve before posting.
Time spent: 4+ hours
1st Attempt
First, I created an account in PhantomBuster, a tool that automates actions on social platforms like LinkedIn.
Then, I connected my LinkedIn account and set up the “LinkedIn Post Commenter and Liker Scraper” tool.
I asked it to retrieve only comments from my LinkedIn posts from recent days, which it did successfully.
Next, I created a new “Scenario” in Make, a no-code automation and AI agent tool, and added PhantomBuster as the start of that workflow.
Then, I built a Make AI Agent that would draw from my previous posts to learn my voice..
I added that Make AI Agent into the workflow, giving it instructions to analyze the comments scraped by PhantomBuster and produce a reply.
And finally, I added Google Docs as the final output. The idea was to create a document where I could see both the original comment and the AI-generated reply.
The whole workflow ran successfully, which I took as a win and closed up shop for the night.
But when I opened my laptop the next day to check all the wonderful replies my new AI buddy had written for me, all I found was this lovely Google Doc:
Still undeterred, I decided to try something different.
2nd Attempt
Along the same lines, I wanted to build an automated AI workflow that would scrape content from LinkedIn that I’m interested in. Then, write comments in my voice and style using my existing content as a foundation.
I used a similar workflow: PhantomBuster to scrape the content, Make AI Agents to analyze and write comments, and getting the final output in a Google Sheet.
Unfortunately, that gave me the exact same result (only this time in spreadsheet format, woohoo!):
What especially irked me was that the automations themselves were running successfully. But I still had no output.
So after more than four hours of work (and a lot of back-and-forth with ChatGPT), I finally gave up.
Could I have figured out this AI workflow eventually? Yes, I have no doubt.
But at that point, how much time would I be saving?
Does a little time saved on writing comments justify spending hours building an AI workflow (and what should’ve been a relatively simple one, at that)?
Here’s what I learned from this experiment:
If you’ve been secretly feeling a little skeptical about vibe marketing, you were right
The folks building vibe-coded apps and AI workflows in five minutes have years of practice. The rest of us can’t expect the same speed.
The tools that are currently available for vibe coding and AI automations aren’t ready yet for the average user to just jump in and build
If someone with a background in tech (me) struggled so much with a simple workflow, imagine the challenge of something more complex
And while it’s true that others are seeing success with vibe marketing (like the examples that we saw above), there are also clear downsides.
It’s Not All a Bed of Roses: The Caveats of Vibe Marketing
Vibe marketing is like any new marketing buzzword: We all love to join in the hype, even if we don’t quite get it.
The problem is, the hype can obscure reality.
After running my own experiments, I also talked with other experts in the field. What emerged was a clear pattern — vibe marketing is powerful, but the gaps between promise and practice are real.
It’s Harder Than It Looks
The idea that you can tinker around with AI for five minutes and produce a usable workflow just isn’t feasible for the majority of us.
And yet, that’s the promise we’re seeing over and over again:
This all sounds great, but we’re marketers: We know better.
Simple automations? Sure.
But robust, real-world systems usually need engineering support or serious AI chops.
Without that, you risk fragile prototypes that break the first time they’re stress-tested.
Oren Greenberg, the AI marketing consultant we talked about earlier, told me:
“The level of hype is out of this world. Vibe coding is cool, and there are a few people who’ve built a nice small business out of it. But it’s mostly the vendors who are minting cash.”
Here’s the point: Don’t get swept up in the hype. Check the source.
The Infrastructure Is Messy
AI workflows look slick in a demo. But in practice, you have to plug into your marketing stack.
And that’s where things get complicated.
For example, you might build the perfect AI agent to score inbound leads, only to realize that your CRM can’t accept the data the way you need.
As Austin Hay, Co-Founder of Clarity and MarTech teacher at Reforge, noted in a recent interview:
“Everyone’s excited about unstructured data, but unstructured data is useless when it needs to play nice with structured systems.”
For traditional marketing teams, this means your AI workflows may not play well with your company’s established martech systems.
And if your tech’s API documentation is outdated (or worse, nonexistent), it will be nearly impossible to vibe code your way to integrations between existing tools.
AI Can’t Invent Outside its Datasets
Another misconception around vibe marketing is that you can throw any messy, undefined problem at an AI agent and it will figure it out.
The reality is less glamorous.
AI thrives on patterns it’s seen before. Point it at a well-scoped, repeatable task, and it shines.
But ask it to invent outside of its training data — or solve a fuzzy, novel problem — and you’ll end up with loops, errors, and wasted hours.
Speed Only Works When You Know Where You’re Going
AI can help you move fast. But if you don’t know what metrics matter and where you want your workflows to lead, faster will just mean getting lost sooner.
Marketers who succeed with vibe coding are the ones who define the finish line first. AI then becomes a vehicle to reach those goals faster, not a substitute for setting them.
Kevin White, Head of Marketing at Scrunch AI, put it this way in a recent interview:
“AI multiplies the abilities of people who already know their craft. Treat it as a force multiplier for your expertise rather than a substitute for it.”
Vibe Marketing Tools Free Up Time…But for What?
As more marketers build AI workflows and vibe code their way to productivity, a philosophical question arises: why?
AI workflows and automations free up time (when they work). But, what are we freeing up time for?
By eliminating the busywork, we’ve saved only the most demanding tasks for ourselves. And while creating and strategizing may be what we enjoy most, it’s impossible for most people to do that kind of mentally-taxing work for eight hours straight.
“In conversations with CMOs, it’s clear that GenAI has become a core part of how modern marketing teams operate. What separates the winners is a commitment not just to scaling the technology, but to empowering the people who use it. Those CMOs investing in tools and talent are the ones rewriting the playbook.”
Ready to Try Your Own Vibe Marketing Experiment?
Vibe marketing isn’t snake oil. But it’s not a silver bullet, either.
The hype can make it feel like anyone can vibe code and automate their way to a marketing edge. But the reality is far more nuanced.
The marketers getting real value from vibe marketing are the ones with strong fundamentals, clear goals, and often a layer of engineering support behind them.
For the rest of us, the takeaway is simple:
Vibe marketing is worth experimenting with, but it won’t replace strategy, judgment, or hard-won expertise.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-10-03 14:08:552025-10-03 14:08:55Vibe Marketing: Hype, Reality, and Real Case Studies
