Beyond Tools: A Google Ads Guide To Detecting And Preventing Click Fraud In Lead Generation

Click fraud in lead generation can drain your marketing budget and corrupt your data, leading to misguided strategic decisions.

While automated detection tools serve as a first line of defense, relying solely on them is not enough.

This guide presents practical, hands-on approaches to identify and combat click fraud in your lead generation campaigns in Google Ads.

Understanding Modern Click Fraud Patterns

Click fraud isn’t just about basic bots anymore. The people running these scams have gotten much smarter, and they’re using tricks that your regular fraud tools might miss.

It’s a big business, and if you think you are not affected, you are wrong.

Here’s what’s really happening to your ad budget: Real people in click farms are getting paid to click on ads all day long.

They use VPNs to hide where they’re really coming from, making them look just like normal customers. And they’re good at it.

The bots have gotten better, too. They now copy exactly how real people use websites: They move the mouse naturally, fill out forms like humans, and even make typing mistakes on purpose.

When these smart bots team up with real people, they become really hard to spot.

The scammers are also messing with your tracking in clever ways. They can trick your website into thinking they’re new visitors every time.

They can make their phones seem like they’re in your target city when they’re actually on the other side of the world.

If you’re counting on basic click fraud protection to catch all this, you’re in trouble. These aren’t the obvious fake clicks from years ago – they’re smart attacks that need smart solutions.

That being said, the good old competitor trying to click 50 times on your ad is also still existent and not going away anytime soon.

Luckily, it is safe to say that Google can spot and detect those obvious fraud clicks in many cases.

Google’s Click Fraud Dilemma: Walking The Revenue Tightrope

Google faces a tricky problem with click fraud.

Every fake click puts money in Google’s pocket right now, but too many fake clicks will drive advertisers away. This creates a conflict of interest.

Google needs to show that it’s fighting click fraud to keep advertisers happy and the ad platform and all of its networks healthy, but it can’t afford to catch every single fake click.

If it did, its ad revenue would drop sharply in the short term because it also runs the risk of blocking valid clicks if it goes in too aggressively.

But if it doesn’t catch enough fraud, advertisers will lose trust and move their budgets elsewhere.

Some advertisers say this explains why Google’s fraud detection isn’t as strict as it could be.

They argue Google has found a sweet spot where it catches just enough fraud to keep advertisers from leaving, but not so much that it seriously hurts its revenue.

This balance gets even harder as fraudsters get better at making fake clicks look real.

This is also why many advertisers don’t fully trust Google’s own click fraud detection and prefer to use third-party tools.

These tools tend to flag more clicks as fraudulent than Google does, suggesting Google might be more conservative in what it considers fraud.

The Over-Blocking Problem Of Third-Party Tools

Third-party click fraud tools have their own business problem: They need to prove they’re worth paying for every month.

This creates pressure to show lots of “blocked fraud” to justify their subscription costs. The result? Many of these tools are too aggressive and often block real customers by mistake.

Other tactics are to show lots of suspicious traffic or activities.

Think about it. If a click fraud tool shows zero fraud for a few weeks, clients might think they don’t need it anymore and cancel.

So, these tools tend to set their detection rules very strict, marking anything slightly suspicious as fraud. This means they might block a real person who:

  • Uses a VPN for privacy.
  • Shares an IP address with others (like in an office).
  • Browses with privacy tools.
  • Has unusual but legitimate clicking patterns.

This over-blocking can actually hurt businesses more than the fraud these tools claim to stop.

It’s like a store security guard who’s so worried about shoplifters that they start turning away honest customers, too.

Why Click Fraud Tools Are Still Valuable

Despite these issues, click fraud tools are still really useful as a first line of defense.

They’re like security cameras for your ad traffic. They might not catch everything perfectly, but they give you a good picture of what’s happening.

Here’s what makes them worth using:

  • They quickly show you patterns in your traffic that humans would take weeks to spot.
  • Even if they’re sometimes wrong about individual clicks, they’re good at finding unusual patterns, like lots of clicks from the same place or at odd hours.
  • They give you data you can use to make your own decisions – you don’t have to block everything they flag as suspicious.

The key is to use these tools as a starting point, not a final answer. Look at their reports, but think about them carefully.

Are the “suspicious” clicks actually hurting your business? Do blocked users fit your customer profile?

Use the tool’s data along with your own knowledge about your customers to make smarter decisions about what’s really fraud and what’s not.

In terms of functionality, most third-party click fraud detection tools are somewhat similar to each other.

A simple Google search on “click fraud tool” shows the market leaders; the only bigger difference is usually pricing and contract duration.

Tackling Click Fraud With Custom Solutions

After getting a first impression with third-party click fraud tools, it’s best to build a collection of custom solutions to tackle your individual scenario.

Every business has a different situation with different software environments, website systems, and monitoring.

For custom solutions, it’s recommended to work closely with your IT department or developer, as many solutions require some modification on your website.

The Basics: Selecting An Identifier

There are a handful of solutions to cover 80% of the basics.

The first way to do something against click fraud is to find a unique identifier to work with.

In most cases, this will be the IP address since you can exclude certain IP addresses from Google Ads, thus making it a good identifier to work with.

Other identifiers like Fingerprints are also possible options. Once an identifier is found, you need to make sure your server logs or internal tracking can monitor users and their identifiers for further analysis.

The Basics: CAPTCHAs

Another basic tool, which is often forgotten, is CAPTCHAs.

CAPTCHAs can detect bots or fraudulent traffic. Google offers a free and simple-to-implement solution with reCAPTCHA.

CAPTCHAs might seem like an easy answer to bot traffic, but they come with serious downsides.

Every time you add a CAPTCHA, you’re basically telling your real users, “Prove you’re human before I trust you.” This creates friction, and friction kills conversions.

Most websites see a drop in form completions after adding CAPTCHAs if they are set too aggressively.

Smart CAPTCHAs can limit the frequency, but not all CAPTCHA providers allow that option, so choose your provider or solution wisely.

The Basics: Honeypot Fields

Honeypot fields are hidden form fields that act as traps for bots.

The trick is simple but effective: Add extra fields to your form that real people can’t see, but bots will try to fill out.

Only bots reading the raw HTML will find these fields; regular users won’t even know they’re there. The key is to make these fields look real to bots.

Use names that bots love to fill in, like “url,” “website,” or “email2.” If any of these hidden fields get filled out, you know it’s probably a bot. Real people won’t see them, so they can’t fill them out.

Pro tip: Don’t just add “honeypot” or “trap” to your field names. Bots are getting smarter and often check for obvious trap names. Instead, use names that look like regular-form fields.

Advanced Validation Methods

Smart Form Validation: Email

Most businesses only check if an email address has an “@” symbol and looks roughly correct.

This basic approach leaves the door wide open for fake leads and spam submissions.

Modern email validation needs to go much deeper. Start by examining the email’s basic structure, but don’t stop there.

Look at the domain itself: Is it real? How long has it existed? Does it have proper mail server records?

These checks can happen in real time while your user fills out the form. It should be noted, however, that smart form validation usually requires some sort of third-party provider to check the details, which means you need to rely on external services.

A common mistake is blocking all free email providers like Gmail or Yahoo. This might seem logical, but it’s a costly error.

Many legitimate business users rely on Gmail for their day-to-day operations, especially small business owners.

Instead of blanket blocks, look for unusual patterns within these email addresses. A Gmail address with a normal name pattern is probably fine; one with a random string of characters should raise red flags.

For enterprise B2B sales, you expect bigger companies to sign up with their company domain email address, so blocking free mail providers might work.

Smart Form Validation: Phone

Phone validation goes far beyond just counting digits. Think about the logic of location first.

When someone enters a phone number with a New York area code but lists their address in California, that’s worth investigating.

But be careful with this approach – people move, they travel, and they keep their old numbers. The key is to use these mismatches as flags for further verification, not as automatic rejections.

The Art Of Smart Data Formatting

Data formatting isn’t just about making your database look neat. It’s about catching mistakes and fraud while making the form easy to complete for legitimate users.

Name fields are a perfect example.

While you want to catch obviously fake names like “asdfgh” or repeated characters, remember that real names come in an incredible variety of formats and styles.

Some cultures use single names, others have very long names, and some include characters that might look unusual to your system.

Modify Your Google Ads Campaign Settings To Tackle Click Fraud

Google offers multiple campaign options to increase reach, on the downside most of those options come along with an increase of click fraud activities.

App Placements

Performance Max campaigns can place your ads across Google’s entire network, including in apps. While this broad reach can be powerful, it also opens the door to potential fraud.

The challenge is that you have limited control over where your ads appear, and some of these automatic placements can lead to wasted ad spend.

Kids’ games are often a major source of accidental and fraudulent clicks. These apps frequently have buttons placed near ad spaces, and children playing games can accidentally tap ads while trying to play.

What looks like engagement in your analytics is actually just frustrated kids trying to hit the “play” button.

Another issue comes from apps that use deceptive design to generate clicks. They might place clickable elements right where ads appear, or design their interface so users naturally tap where ads are located.

This isn’t always intentional fraud. Sometimes, it’s just poor app design, but it costs you money either way.

Unlike traditional campaigns, where you can easily exclude specific placements, Performance Max’s automation makes this more challenging.

The system optimizes for conversions, but it might not recognize that clicks from certain apps never lead to quality leads. By the time you spot the pattern, you’ve already spent money on these low-quality clicks.

Excluding app placements is for almost all advertisers a must have. Very few advertisers benefit from app placements at all.

Partner And Display Network

Lead generation businesses face a unique challenge with Performance Max campaigns that ecommerce stores can largely avoid.

While ecommerce businesses can simply run Shopping-only campaigns and tap into high-intent product searches, lead gen businesses are stuck dealing with the full Performance Max package, including the often problematic Display Network.

The Display Network opens up your ads to a mass of websites, many of which might not be the quality placements you’d want for your business.

While Google tries to filter out bad actors, the display network still includes sites that exist primarily to generate ad clicks.

These sites might look legitimate at first glance, but they’re designed to encourage accidental clicks or attract bot traffic.

Some are specifically designed for server bot farms, as they run on expired domains and have no content besides ads.

Lead generation businesses don’t have this luxury. Their Performance Max campaigns typically run on all networks except shopping. This creates several problems:

  • The quality of clicks varies wildly. Someone might click your medical practice ad while trying to close a pop-up on a gaming site. They’ll never become a patient, but you still pay for that click.
  • Display placements can appear on sites that don’t match your brand’s professional image. Imagine a law firm’s ad showing up on a site full of questionable content – not ideal for building trust with potential clients.
  • Bot traffic and click farms often target display ads because they’re easier to interact with than shopping ads. You might see high click-through rates that look great until you realize none of these clicks are turning into leads.

All those are reasons to question PMax campaigns for lead gen, but that’s a decision every marketer has to make.

Advanced Google Ads Settings To Tackle Click Fraud

If the basics are implemented but there is still a higher amount of suspected click fraud, advanced solutions need to be implemented.

Besides excluding suspicious IP addresses, you can also build negative audiences.

The idea is to have a second success page for your lead generation form and only forward potential bots or fake sign-ups to this page.

To achieve that, your website needs to evaluate potential bots live during the sign-up process.

You can then setup a dedicated “bot pixel” on the second success page in order to send data of this audience to Google.

Once enough data is retrieved, you can exclude this audience from your campaigns. This approach is a little trickier to implement but is worth the effort as those audience signals are of high quality if enough data is supplied.

Make sure to only fire the “bot pixel” on the special success page and only there, otherwise you run the risk of mixing your audiences which would render the system useless.

Filtering Fake Leads With Conditional Triggers

Another tracking-based strategy is to set up condition-based conversion tracking. Combined with hidden form fields, you can modify the conversion trigger not to send data if the hidden field was filled.

In that scenario, you would filter out bots from conversion tracking, sending back only real conversion to your campaign, and therefore, also training the Google algorithm and bidding strategy only on real data.

You eliminate a majority of fake leads and traffic with this setup.

Making Sign-Ups More Challenging To Improve Lead Quality

Another advanced strategy is to make the sign-up process a lot harder.

Tests have shown that much longer forms are not finished by bots because they are usually trained on simpler and shorter forms, which require only mail, name, phone, and address.

Asking specific questions and working with dropdowns can dramatically increase the lead quality. It should be noted, however, that longer forms can also hurt the valid signup rate, which is a risk you want to take if you have to deal with bot and fraud traffic.

A fitting case was a car dealer I worked with. They had a form where people could offer their cars for sale and retrieve a price estimate.

A short form had almost three times the signup rate than before, but it turned out later that a lot of them were spam signups or even very low-qualified leads.

A shorter form leads to more spam because it’s easy to sign up. After switching to a longer form, the signups dropped, but quality increased drastically.

Almost 20 fields long, and potential clients had to upload pictures of their car.

It took a few minutes to finish the signup, but those who did were committed to doing business and open to discussing the sale, which also made it easier for the salespeople to follow up properly.

A Hard Truth About Lead Fraud

Let’s be honest: You can’t completely stop lead fraud. It’s like shoplifting in retail – you can reduce it, you can catch it faster, but you can’t eliminate it entirely.

The fraudsters are always getting smarter, and for every security measure we create, they’ll eventually find a way around it.

But here’s the good news: You don’t need perfect protection. What you need is a balanced approach that catches most of the bad leads while letting good ones through easily.

Think of it like running a store: You want security, but not so much that it scares away real customers.

The key is to layer your defenses. Use click fraud tools as your first line of defense, add smart form validation as your second, and keep a human eye on patterns as your final check.

Will some fake leads still get through? Yes. But if you can stop 90% of the fraud, you’re winning the battle.

Remember: Perfect is the enemy of good. Focus on making fraud expensive and difficult for the bad actors, while keeping your lead generation process smooth and simple for real prospects. That’s how you win in the long run.

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Featured Image: BestForBest/Shutterstock

Local SEO Schema: A Complete Guide To Local Structured Data & Rich Results via @sejournal, @rio_seo

Structured data markup can work diligently behind the scenes to help your local business shine online.

It can add eye-catching rich results to your search results, like review stars, FAQs, and breadcrumbs, that grab attention and encourage more clicks.

Structured data uses the standardized vocabulary of Schema to tell search engines – and even AI tools – exactly what your website is about, making it easier for customers to find you.

While it’s not a direct ranking boost, structured data plays a big role in making your business more visible, whether in traditional search results or AI-powered tools like Gemini or ChatGPT.

From a local ice cream shop to a hardware store, adding structured data can make a huge difference in boosting your local SEO and staying ahead in today’s ultra-saturated digital world. It often remains an untapped resource, despite its potential to significantly enhance your local SEO strategy.

This guide will equip you with actionable knowledge to use structured data markup to boost your local SEO and strengthen your visibility across search engines and AI platforms.

Why Does Schema Matter?

Structured data with Schema convey additional information to search engines so they can interpret and display your content more effectively, giving your business a competitive edge in search engine results pages (SERPs).

Google has consistently highlighted the importance of schema and structured data in delivering relevant, detailed information to users.

Implementing schema correctly can improve your visibility, attract more clicks, and even increase conversions.

Let’s clarify key terms related to schema and structured data markup.

Understanding Schema, Structured Data, Rich Results, And SERP Features

Local search marketers often use the terms “schema”, “schema markup” and “structured data” interchangeably, but there are differences to understand.

Structured Data

Structured data is the format for organizing and describing information on a webpage. By implementing structured data markup to a page, you convey additional information and make it easier for search engines to accurately interpret your pages and display relevant snippets in SERPs.

Schema

Schema is an open source standardized vocabulary used to markup structured data. There are other vocabularies, but the search industry uses Schema.org which is a collaborative initiative founded by Google, Bing, Yahoo, and Yandex in 2011.

This vocabulary enables webmasters to tag elements like business names, addresses, phone numbers, customer reviews, and services.

Pages using structured data with schema are eligible for rich results, which can significantly improve how your business appears in search results.

Rich Results

Rich results (also known as rich snippets) are enhanced search elements that provide more detailed and visually engaging information.

Rich results can also be referred to as “SERP features.” Examples include:

Rich results not only improve click-through rates but also help your business stand out in competitive local search results.

SERP Features

A SERP feature is a specialized element on a search results page that provides extra information or functionality beyond standard results.

Examples include featured snippets, local packs, and knowledge panels. It is a broader category covering various elements, while a rich result enhances individual listings using structured data.

Why Structured Data Matters

Structured data is an integral part of any business’s local SEO strategy for myriad reasons. Let’s explore each reason more in-depth.

Improved Search Engine Understanding

Structured data acts as a translator, turning your website’s content into a format that search engines can easily understand and classify.

This allows Google, large language models (LLMs), and other engines to identify key information such as your business hours, location, services, and customer ratings.

The better search engines understand your site, the more likely they are to display relevant information to users.

Enhanced SERP Visibility

Rich results generated from structured data are more visually appealing than standard search results.

For example, a local bakery using schema markup might appear with review stars, a photo, operating hours, and a “Place an Order” button directly in the SERPs.

This enhanced visibility can drive more traffic to your site and attract higher-quality leads.

Increased Click-Through Rates

Pages featuring rich results typically enjoy higher click-through rates (CTRs) compared to those with standard results.

By giving users detailed information upfront – such as pricing, availability, or reviews – you make it easier for them to decide to engage with your business.

Competitive Advantage

In saturated local markets, structured data markup can differentiate your business from competitors.

If your competitor’s listing only shows basic details while yours features rich elements like sitelinks or a star rating, potential customers are more likely to click on your result.

Voice Search Optimization

As voice search grows in popularity, structured data becomes even more important.

Devices like Google Assistant rely heavily on schema to deliver concise, accurate answers to voice queries.

For example, adding a “FAQ” schema to your site can make your business the top result when users ask questions like, “Where’s the best coffee shop near me?”

The Role Of Structured Data In Local SEO

As evidenced above, structured data serves as a vital tool for local businesses, helping search engines understand and present your information more effectively.

For businesses aiming to improve visibility in local search results, structured data provides an opportunity to display essential details in a highly appealing format.

With schema, businesses can highlight critical information such as:

  • Business hours, including holiday schedules.
  • Customer reviews and ratings.
  • Location details with maps and directions.
  • Product pricing and availability.
  • Events and promotions.

For example, a local bakery could use structured data to feature customer reviews, a “Place an Order” button, and seasonal promotions.

An event venue might showcase upcoming events with dates, times, and ticket links, making it easier for potential customers to engage directly from search results.

Practical Benefits For Local Businesses

Here’s how structured data benefits local businesses in practice:

  • Restaurant Example: A family-owned diner uses schema to display operational hours, reviews, and menu links, reducing barriers for diners looking for quick information.
  • Retail Example: A local bookstore features event details, such as upcoming author signings, directly in search results to attract customers.
  • Service Example: A home improvement company highlights service areas and customer testimonials, building credibility and attracting clicks from targeted local users.

These enhancements create a competitive edge by presenting detailed and relevant information before the customer even clicks on your website.

Data And Google Business Profile

Structured data on a location page doesn’t directly affect Google Business Profile (GBP) features like the Map Pack or reviews, but it enhances organic search features, such as rich results, by improving how search engines interpret your website.

While schema doesn’t directly impact GBP rankings, it complements them by ensuring consistent, accurate data across platforms, boosting credibility and visibility.

Including details like address, hours, and services in structured data helps Google associate your site with your GBP listing and can even fill gaps in unclaimed profiles.

Structured Data And Local Ranking Signals

Structured data is not a direct ranking signal in search engine algorithms, as confirmed by Google representatives like John Mueller.

However, it is essential for boosting a website’s visibility and engagement, both of which can impact search rankings.

By organizing information for easy interpretation, structured data improves how content appears in search results, encouraging clicks and interaction.

How Structured Data Impacts AI Results For Local Brands

The rise of AI in search engines and virtual assistants has redefined how structured data impacts digital visibility.

Once primarily a tool for helping search crawlers understand webpage content, structured data now plays a vital role in ensuring local landing pages perform well in AI-driven platforms like Gemini, Bing Chat, ChatGPT, and voice assistants such as Amazon Alexa and Google Assistant.

Structured Data: The Foundation For AI Optimization

Structured data is essential for AI systems like ChatGPT, helping them deliver accurate and relevant information.

Local landing pages using structured data, such as LocalBusiness or GeoCoordinates schema, provide a framework that AI can easily process for precise results.

For instance, structured data defining a business’s address, hours, and reviews allows AI platforms to seamlessly integrate this information into conversations.

Key Benefits Of Structured Data For AI

  1. Improved Contextual Understanding: Structured data helps AI systems understand relationships between key entities on a page. For example, linking a business’s name, address, and service area allows AI to provide more accurate answers for local queries like “electrician near me” or “top-rated gyms in San Diego.”
  2. Enhanced Rich Results: AI tools prioritize structured data to create detailed rich results. A local landing page with Review and AggregateRating schema can lead to AI displaying customer ratings and reviews directly in search results, fostering trust and engagement.
  3. Voice Search Optimization: Structured data enables voice assistants to deliver precise answers. For example, a local restaurant with schema data about its menu and hours will yield accurate responses to queries like “What time does Joe’s Diner open?”
  4. AI-Powered Features Integration: AI models like Google’s Search Generative Experience (SGE) synthesize content into conversational summaries. Local pages with detailed markup are more likely to be included in these overviews, giving businesses better visibility in AI-driven search environments.
Brand Retailer Local Page AI Overview ExampleScreenshot from search, Google, January 2025 – Brand Retailer Local Page AI Overview Example (webpages are utilizing advanced schema)

Localized Search Benefits Of Structured Data

AI search systems increasingly focus on localization, making structured data essential for businesses targeting specific geographic areas.

Key schema types that enhance localization include:

  • GeoCoordinates Schema: Ensures precise location information, allowing AI to integrate it into map-based results.
  • LocalBusiness Schema: Supplies essential business details like name, hours, and services offered.
  • Event Schema: Highlights local events and activities directly tied to the user’s location and query.

Practical Steps To Implement Structured Data For Local Pages

Structured data is essential for local business websites aiming to improve visibility in search engine results.

While many local sites have basic structured data enabled, implementing detailed and well-validated markup can significantly enhance search engine performance and qualify pages for rich results.

Below is a comprehensive guide to applying schema markup effectively.

Step 1: Select The Best Schema.org Category

Choosing the appropriate Schema.org category is critical for ensuring an accurate representation of your business in search results.

Schema.org provides various categories specifically tailored for local businesses. For example:

  • Ice Cream Shops: Use schema.org/IceCreamShop
  • Hardware Stores: Use schema.org/HardwareStore

If no specific category exists for your business, use the general schema.org/LocalBusiness.

Additionally, if you’re technically inclined, you can propose new categories via the Schema.org GitHub forum.

Recommended Local Business Schema for a Hardware StoreScreenshot from schema.org, January 2025 – Recommended Local Business Schema for a Hardware Store

Step 2: Implement Required Schema Properties

After selecting the correct category, include the following required schema properties to ensure validation and avoid disqualification from rich results:

  • url: The URL of the landing page.
  • name: Name of the business.
  • openingHours: Business operating hours.
  • telephone: Business contact number.
  • image: A relevant image (e.g., storefront).
  • logo: A link to your business logo.
  • address: Business address visible on the landing page.
  • geo: Geographical coordinates of your business.
  • areaServed: The service area, preferably specified as a ZIP code.
  • mainContentOfPage: The primary content of your landing page.

Step 3: Add Highly Recommended Schema Properties

These properties are not required but are highly recommended for enhancing visibility:

  • review: A review of your business (only if the local landing page has visible reviews).
  • aggregateRating: The overall rating based on multiple reviews. Ensure compliance with Google’s Review Rich Results guidelines.
  • FAQPage: Mark up FAQ sections with this schema to appear as FAQ rich results.
  • alternateName: Alternative names for your business, e.g., “Acme Inc.” vs. “Acme Stores.”
  • sameAs: Links to third-party profiles like Facebook, YouTube, or Wikipedia.
  • hasMap: A link to your business’s location on Google Maps.
  • breadcrumb: Structured navigation schema to improve rich results in SERPs.
  • department: Internal departments or services within your business.
  • priceRange: A general indicator of your pricing, such as “$$$.”

Step 4: Explore Advanced Schema Types

For businesses seeking even more advanced features, consider these schema types:

  • SearchAction: Formerly known as the sitelinks search box, lets users perform site-specific searches directly from the search engine results page (SERP), enhancing engagement and accessibility.
  • additionalType: Defines additional topical relevance, often using Wikipedia categories. For example, a sporting goods store might use the Wikipedia page for Sports Equipment.
  • headline: Helps local businesses optimize key pages—such as service offerings, promotions, and blog posts—by providing a clear, structured title that improves visibility in search results.
  • alternativeHeadline: Allows local businesses to add a secondary title variation, making content more discoverable for different search terms and customer queries related to local services.
  • significantLink: Highlights key pages that matter most for a local business, such as appointment booking, contact pages, or location-specific services, improving navigation and SEO.
  • contentLocation: Specifies the geographic area a business serves, helping search engines associate its services with a specific city or region, boosting local search rankings.

Step 5: Validate Your Schema Markup

Proper validation is critical for ensuring your structured data qualifies for rich results. Google provides several tools for this purpose:

  • Schema.org Structured Data Validator: Tests structured data directly by pasting your code into the tool. It flags both errors and warnings. While errors must be fixed, warnings are less critical and may not affect rich results.
Validated Schema Example (VALIDATED WITH NO ERRORS/WARNINGS) Screenshot from Schema Markup Validator, January 2025 – Validated Schema Example (validated with no errors/warnings)
  • Rich Results Test: Google’s official tool to preview which rich results can be generated by your structured data.
    Rich Results Test
  • Google Search Console Enhancement Reports: Monitors structured data across your site and provides enhancement reports, highlighting pages with errors or warnings. Notifications from Search Console should be addressed promptly to maintain performance.
    Google Search Console Enhancements Reporting ExampleScreenshot from Google Search Console, January 2025 – Google Search Console Enhancements Reporting Example

Step 6: Measure Rich Results Performance

Tracking your rich results’ performance helps you understand the impact of your schema implementation.

Third-party tools like Semrush offer “SERP feature” reports that show the aggregate rich results your site is earning. This data can be used to identify further optimization opportunities.

Semrush SERP Features Trend ExampleSemrush SERP Features Trend Example

You Can’t Go Wrong With Implementing Good Structured Data

Adding structured data to your location pages is a powerful way to enhance local SEO and improve how search engines and AI systems display your business.

Structured data is especially important for AI, as it helps models like ChatGPT and search assistants better understand and showcase your business details.

It also ensures your website’s information aligns with your Google Business Profile, even if your listing is incomplete or unclaimed.

By making key information easy to find, structured data benefits both AI systems and customers.

With better visibility, higher click-through rates, and a stronger online presence, schema markup is a must for local businesses. Add it to your location pages today to stand out and connect with more customers.

Key Takeaways

  • Selecting the right Schema.org category is crucial for accurate business representation.
  • Implement required and recommended schema properties to qualify for rich results.
  • Validate your structured data using tools like Google’s Rich Results Test and Schema.ord Structured Data Markup Validator.
  • Monitor performance through Google Search Console and third-party tools.

By following these steps, local businesses can maximize the visibility and effectiveness of their structured data, ultimately driving more traffic and engagement through enhanced search results.

Special thanks to Chad Klingensmith, Sr. SEO Strategist at Rio SEO, for his extensive contributions to this article. His in-depth knowledge of structured data ensures the accuracy and relevance of the insights shared here.

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Featured Image: pixadot.studio/Shutterstock

Mullenweg & Automattic Sued in Class Action Filing Over WPE Dispute via @sejournal, @martinibuster

A new lawsuit seeking class action status alleges that WordPress co-creator Matt Mullenweg and Automattic engaged in unfair business practices to harm managed WordPress web host WP Engine (WPE) and its customers.

According to the lawsuit:

“Plaintiff and the class seek equitable relief pursuant to Cal. Bus. & Prof. Code § 17203 to end Defendants’ wrongful practices including requiring Defendants to cease its tortious interference with contract.”

…Plaintiff and the class also seek an order requiring Defendants to make full restitution of all monies it received through its wrongful conduct, along with all other relief permitted under Cal. Bus. & Prof. Code §§ 17200 et seq.”

The lawsuit makes multiple claims against Mullenweg and Automattic:

  • That defendants interfered with access to WordPress resources, disrupting WPE customers.
  • Interfered with customers’ ability to manage their websites hosted on WP Engine (WPE).
  • The lawsuit claims that the actions were not legitimate trademark enforcement efforts but a pretext for degrading WP Engine’s services and pressuring customers to leave.
  • The complaint also accuses the defendants of monopolistic behavior, alleging that they wielded control over the WordPress ecosystem for financial gain, harming WPE customers.

According to the legal filing:

“Defendants deliberately wielded their power over the WordPress.org website like a cudgel, not only blocking access to the website but stealing resources like the ACF plugin, forcing visitors to click a checkbox asserting they are not associated with WPE, publishing WPE customer website addresses in an attempt to pressure customers to leave WPE, and repeatedly threatening future consequences including the risk of additional service disruptions for class members who did not leave WPE. “

Why the Lawsuit Seeks Class Action Status

The legal filing asserts that the lawsuit qualifies for class action certification based on allegations that Mullenweg and Automattic engaged in conduct that harmed not just the plaintiff but a broader group of WP Engine (WPE) customers. The plaintiff contends that the defendants’ actions, including interfering with WPE’s services, blocking access to essential WordPress tools, disrupting and degrading service, and pressuring customers to leave WPE, resulted in harm that, according to the lawsuit, meets the criteria for class certification under Rule 23. The lawsuit claims that WPE customers faced service disruptions, financial losses, and potential security risks.

The justification for the class action is outlined in paragraph 58 of the lawsuit:

“Plaintiff brings this action as a class action pursuant to Rules 23(a) and 23(b)(1)-(3) of the Federal Rules of Civil Procedure, on behalf of himself, his business and a Nationwide Class defined as:

All persons in the United States who had ongoing active WPE WordPress Web Hosting Plans on or before September 24, 2024 through December 10, 2024.”

The legal filing asserts that numerous public statements and court records, including filings related to WP Engine, support the allegation that the defendants caused harm to the plaintiff and the alleged class. It then details the plaintiff’s personal experiences as further evidence of the alleged harm.

Section III, ‘Plaintiff’s Experiences,’ outlines how the defendant’s actions harmed the plaintiff, Keller, including:

  • Service Disruptions
  • Business and Financial Impact
  • Personal Website Impact
  • Security Risks
  • Customer Relationship Concerns
  • Consideration of Alternative Hosting

The legal filing details the following:

“Defendants’ interference significantly impacted the business of Plaintiff Keller. While Plaintiff Keller was happy with WPE services and intended to continue using WPE services, the service disruption and degraded service, coupled with repeated public statements and threats made by Defendants, led Plaintiff to explore moving his website and all those operated by his business to another managed web host.

Plaintiff’s livelihood revolves around building and operating websites, and significant disruptions will impact his business including his own capacity to fulfill his contractual obligations to his own clients.

Plaintiff Keller’s websites were significantly impacted by outages despite WPE’s attempts to create workarounds.

Plaintiff Keller has had to spend significant time and expense responding to the service disruptions and degradations, preparing for moving his and his clients’ websites to a new host, and in investigating a new host environment after a long and successful prior partnership with WPE. He is not alone in the harm he has suffered.

Plaintiff Keller’s personal website was also significantly impacted. Access to the WordPress backend was available intermittently, and Plaintiff Keller received emails related to this downtime.

Plaintiff Keller pays WPE $3,300 per year for its “Scale Plan,” 2 additional websites, and GeoTargeting and Multi-Site services. Due to Defendants’ actions, Plaintiff Keller was unable to update his website in a standard marketing cycle adjustment. Plaintiff Keller had to spend time and expense to manage, update, and modify his website as a result of Defendants cutting off WPE
from the WordPress ecosystem and therefore, did not receive the benefit of his bargain with WPE as Plaintiff Keller had to do the work that he pays WPE for.”

A New Phase In Dispute Between Mullenweg/Automattic And WPE

This class action lawsuit is a new phase in the dispute between Mullenweg, Automattic and WP Engine. It expands the legal battle to include claims from individual customers. With allegations of unfair competition, monopolistic behavior, and deliberate service disruptions, the class action lawsuit adds another layer to a dispute that has led some in the WordPress community to call for a change in governance to the WordPress open source project.

Read the text of the lawsuit here: (PDF)

Featured Image by Shutterstock/BCFC

The New Era of Cookie-less Ad Targeting

Advertising technology has entered a new phase that pairs personal privacy with targeting.

For years, the ad industry has depended on third-party tracking cookies — tiny snippets of code downloaded to a user’s browser — to identify prospects, gather data about them, and employ that data for targeting. Consumers saw relevant ads, and advertisers enjoyed good, if not superb, returns.

Screenshot from Adobe Experience Cloud of a female holding a computer tablet

Adobe’s new real-time customer data platform is one of many innovations in cookie-less ad targeting.

Cookies

Unfortunately, cookie-based tracking has privacy problems. In contrast to first-party cookies, which store preferences, third-party tracking cookies aggregate, share, and thereby expose lots of private information.

Just this month, Wired magazine reported, “Google’s advertising ecosystem reveals that a wealth of sensitive information is being openly served up to some of the world’s largest brands…Experts say that when combined with other data, this information could be used to identify and target specific individuals.”

Privacy advocates recognized this and began railing against sharing personal and sensitive information across advertising networks. Technology companies responded. Mozilla’s Firefox browser, for example, stopped allowing tracking cookies back in 2019.

Google, which operates one of the largest ad networks in the world and has the most popular web browser in Chrome, nearly killed third-party cookies in 2024, as it planned to block them in Chrome and move all advertisers to alternative targeting methods — but it didn’t happen.

“Google heard the alarm bells from the industry that nearly 20 years of ad tech infrastructure cannot be recreated in six months,” said David Stein, then the CEO of the data firm Audigent, in an April 2024 email to Practical Ecommerce.

Those alarm bells could have been Google’s ad exchange customers, its ad tech partners, and the anti-trust regulators concerned that ending cookie tracking would give Google a performance advertising monopoly.

Hence tracking cookies remained in Chrome, but ad tech providers did not stop innovating.

Innovation

The same day that Wired published its report, Adobe announced the general availability of its real-time customer data platform (CDP).

“Brands have long relied on third-party audience signals to power tailored digital ads. As consumers play a more active role in customizing their privacy preferences, a move away from third-party data means new tools are required for brands to identify relevant audiences and deliver personalized ad experiences,” read the Adobe press release.

Adobe’s CDP allows advertisers and publishers to securely collaborate on first-party data to enhance ad targeting while respecting user privacy. This relationship is often called second-party data sharing, and resembles Shopify’s Audiences and similar products.

Methods

Second-party data sharing is one of six primary methods ad tech companies are exploring as they try to maintain or improve ad targeting efficacy without raising privacy concerns.

  • Second-party data sharing allows advertisers and publishers to collaborate, often sharing aggregate data.
  • First-party data is when a business uses its own data to target or retarget individuals or cohorts. Many companies are buying publications to advertise to known customers and prospects.
  • Unified ID solutions produce encrypted identifiers to share among systems. The Trade Desk’s Unified Solution is an example. Often, these IDs stem from an email address.
  • Data clean rooms make it possible for analysts to use data without privacy concerns.
  • Cohort-based advertising targets groups of shoppers with similar profiles instead of individuals.
  • Contextual targeting analyzes the context — web page, app, video, email — to deliver relevant ads to consumers without relying on personal data. Artificial intelligence makes this more successful.

Used individually or in combination, these targeting techniques have significant promise. Most reports suggest that results vary among advertisers, yet the techniques will likely work better than third-party cookies.

Ad Experiments

Listing the ad tech companies developing cookie-less targeting methods would fill pages. Thus advertisers seeking to acquire customers might find it wise to experiment.

For example, marketing platform Zeta Global recently purchased the email advertising company LiveIntent. Some in the industry believe Zeta Global valued LiveIntent’s ability to identify website visitors based on email interactions.

Could Zeta Global’s demand-side platform be worth a look?

Similarly, Paved, another email ad platform, expanded its programmatic network, permitting advertisers to target and retarget shoppers safely and privately.

In short, ad targeting is changing, and the best options may not be familiar platforms.