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Case Study





Prevent 90% of Spam Form Submissions: How to Improve Lead Quality With AI Tools, Form Strategies, and Offline Conversions


monthly ad spend


ad spend ROI



Case Study Summary

The Challenge

The Solution

The Results

The Challenge

Our client, a B2B database development firm, faced a significant challenge in their advertising efforts, particularly in the context of B2B PPC (pay-per-click) advertising campaigns on platforms like Google, Bing, and LinkedIn.

High Volume of Spam Form Submissions

The primary issue revolved around the pervasive and disruptive presence of spam, emanating from spam bots and spam click farms — real people in foreign countries being paid (likely by competitors) to click on a company’s ads and submit lead forms. This spam not only posed a nuisance but also resulted in substantial financial losses.

The company's industry was plagued by an abundance of spam activities. These spam activities artificially inflated ad engagement metrics, making it challenging to gauge the true performance of their PPC campaigns.

Up to 40% of Leads Unqualified

In addition to the primary challenge of dealing with spam, a secondary issue emerged concerning the quality of leads filling out forms.

About 40% of leads came from individuals seeking help with personal projects, student work, and various other individual requirements. As a B2B software development and consulting firm, these were all unqualified leads that wouldn’t lead to worthwhile engagements.

This secondary challenge added complexity to the lead generation efforts, as it required us to discern between genuine B2B leads seeking professional services versus leads seeking help with personal or academic projects.

Up to 60% Wasted Ad Spend

As a direct consequence of the rampant spam and unqualified leads seeking assistance on personal projects, our client found that a substantial portion (up to 60%) of their ad spend was being wasted on fraudulent and unqualified clicks and impressions.

This misallocation of resources was detrimental to the company's marketing budget and its ability to reach qualified clients effectively.

Limited Visibility: The prevalence of spam and irrelevant leads skewed the performance data, making it difficult for our client to assess the actual reach and visibility of their advertisements among genuine potential clients. This issue hindered their ability to make data-driven decisions to optimize their PPC campaigns. Low Qualified Conversion Rates: Despite appropriate investment in PPC advertising, our client experienced low qualified conversion rates. The presence of spam and unqualified leads not only wasted budget and company time but also hindered the ability to connect with and convert high-value B2B prospects into clients.


The Solution

To combat the challenges posed by spam and unqualified leads in their PPC advertising campaigns, we took a series of strategic steps to identify and mitigate these issues. These solutions were crucial in restoring the accuracy of data and improving the overall effectiveness of our marketing efforts.

In-Depth Analysis of Session Recordings

We initiated our efforts by conducting a comprehensive analysis of user sessions generated from PPC clicks. To do this, we used a tool called Inspectlet — they offer free pricing tiers for up to 2,500 session recordings per month and reasonable paid plans for websites with larger monthly traffic volumes.

We scrutinized various data points, including IP addresses, time to submission, bounce rates, user agents, and form content. This allowed us to identify patterns associated with spam and unqualified leads.

A critical turning point was when we started rewatching user sessions on their website. This hands-on approach provided valuable insights into how spam bots were interacting with their site and showed us that click farms with real users behind them were also being used to fraudulently fill out the forms with spam.

We took a three prong approach:

  1. Prevent click farms from being able to submit lead forms.

  2. Mitigate automated bots from being able to engage with the site, submit forms, and waste precious ad dollars.

  3. Minimize the number of unqualified leads clicking on ads and submitting lead forms for personal projects.

Tactics for Preventing Click Farms

To counter the challenges posed by click farms and real user spam, which are inherently more intricate due to their blend of human involvement and automated software, we adopted a series of strategies to strengthen our PPC campaigns against these threats.

Offline Conversion Tracking: As an initial starting point, we implemented offline conversion tracking to establish a seamless data flow, sending lead stage information from the CRM back to Google Ads that would help focus our budget on leads that convert into paying customers. We separately tracked spam and personal project leads and set them as “observation” conversions with $0 value assignment so that Google, Bing, and LinkedIn wouldn’t use these leads as signals to optimize our ads. In short, our campaigns wouldn’t focus any of our budget on trying to get spam or personal project leads. More importantly, leads that progressed through various qualified stages of the sales cycle were tracked as offline “primary” conversions used for campaign optimization, attributed with higher values as they advanced. This signaled Google, Bing, and LinkedIn to target similar users who were more likely to convert into paying customers. Although this approach didn't produce immediate results in resolving our core issues, it laid a strong foundation by equipping our campaigns with the necessary data points to optimize our advertising for qualified leads that convert into paying customers. Invisible Honeypot Field: Initially, we experimented with an invisible honeypot field to detect the use of autofill spam software commonly employed by click farms. While invisible to genuine users, this field was designed to be recognized by autofill software. If triggered, the submission would be blocked from reaching our CRM. However, this approach had an unintended consequence – it also hindered some legitimate users who relied on autofill plugins for convenience. Recognizing that this approach blocked too many genuine users, we sought a more refined solution. Dynamic Form Field for Email Domains: To differentiate between click farm spammers and genuine users, we introduced a dynamic form field strategy. If a user's email domain matched a list of known fraudulent domains, as well as those from previous fraud attempts, a specific form field would appear during the submission process. This form field presented the user with two options to get in touch with us. Click farm spammers, driven by the goal of completing forms quickly, often failed to read the form question carefully. While they believed they had successfully completed the form, in reality, the content from their submission never reached our CRM. This intelligent approach significantly reduced click farm spam while preserving the user experience for legitimate visitors. Form Content Machine Learning Prevention using OOPSpam: The ultimate and most effective solution we implemented was the integration of OOPSpam, a machine learning tool specifically designed to analyze the content of form submissions before forwarding them to the CRM. OOPSpam assigned a fraud likelihood rating to each submission, allowing us to fine-tune the tool's settings for optimal results. This powerful tool proved highly effective in identifying and blocking spam leads, particularly click farm operators. It served as the final line of defense against spam submissions while still enabling genuine users to submit their information seamlessly. In order for this to work effectively, you need to be on a paid plan and require at least a comment or free-text field to be filled in your forms. Spam, bots, and click-farms often use latin text or gibberish which makes it easier to identify the lead as spam.

Tools for Preventing Spam Bots

Preventing spam bots that operate entirely through automation is a task that can be more manageable, thanks to the abundance of readily available software solutions designed for plug-and-play use.

In contrast to the intricate nature of other spam challenges, these automated bots rely primarily on software scripts, making them susceptible to targeted countermeasures.

reCAPTCHA: The first proactive measure was to implement reCAPTCHA on their website. This added a layer of security to their forms by requiring users to complete a CAPTCHA challenge before submission. This alone significantly reduced the total amount of spam bots that were not human. ClickCease: We complemented reCAPTCHA with ClickCease, a specialized tool designed to detect and block fraudulent clicks. While we’ve had mixed results using ClickCease across client accounts, for this account in particular, it worked wonders in combination with reCAPTCHA — preventing the majority of spam coming directly from bots.

Form Strategies to Reduce Unqualified Leads

Another critical aspect of our strategy was to tackle the issue of leads seeking help with personal projects or academic tasks, which constituted a significant portion of the inquiries.

Notably, we observed that approximately 70% of these leads were associated with either personal or .edu email domains, indicating their non-commercial intent.

To effectively address this challenge, we devised a method to qualify leads using these email addresses by dynamically inserting an additional qualifying question into our lead capture process.

Dynamic Qualifying Form Field: To filter out leads primarily seeking help with personal or academic matters, we compiled a comprehensive list of personal email domains (gmail, yahoo, hotmail, etc). We then implemented a dynamic qualifying form field, designed to prompt users who either input a personal email domain or used an .edu email address with an additional multiple-choice question. This question presented users with options based on historical data from previous irrelevant leads, including assistance with personal databases, student work, email access, password reset, and the qualifying choice of corporate databases. Users who selected that they needed help with their company database had their information seamlessly forwarded to the CRM, where our client’s services were best suited to assist them. 

In contrast, users who chose any of the alternative options were redirected to a separate confirmation page that clearly stated that our client does not provide support for those specific topics. This strategic approach significantly reduced the overall number of users entering the CRM seeking assistance with personal issues or academic tasks while maintaining accessibility for users with genuine corporate database needs.


The Results

The comprehensive strategies and solutions implemented to address the challenges faced by our client in their PPC advertising campaigns yielded remarkable and quantifiable results. These results not only significantly mitigated the issues of spam and irrelevant leads but also led to substantial improvements in key performance metrics.

90% Reduction in Spam and Unqualified Leads

Perhaps the most notable achievement was the substantial reduction in spam and unqualified leads. Through a combination of targeted measures, we successfully eliminated approximately 90% of spam and unqualified leads, providing our client with a cleaner and more valuable lead pool.

2.5x Increase in ROAS (from 195% to 498%)

One of the most significant benefits was the optimization of Return On Ad Spend (ROAS). With up to 60% of ad budget originally going to spam, we effectively redirected our budget towards reaching authentic potential clients, thereby increasing ROAS from 195% to 498% with $912,000 in new client revenue over an 18 month period.

3x Increase in Customer Acquisition

As the level of spam diminished, coupled with the reduction of unqualified leads, our ability to connect with and convert qualified B2B prospects into paying customers saw an improvement from 2 new customers per month to 6 new customers per month (customer values between $7,500 up to $80,000 per customer).

Enhanced Data Accuracy

With the reduction of spam and unqualified leads, the accuracy of data improved substantially, thus allowing us to gain clearer insights into the genuine performance of their PPC campaigns, enabling us to make more informed decisions on success and growth avenues.

User Experience Preservation

Importantly, the strategies implemented to combat spam and unqualified leads were designed to preserve the user experience for genuine visitors.

The implementation of Inspectlet, reCAPTCHA, ClickCease, dynamic form fields, and the use of OOPSpam’s machine learning tools for content analysis ensured that legitimate users could submit their information seamlessly while minimizing intrusive tests, whereas spam bots, click farms and unqualified leads were mitigated.



spam reduction


increase in ROAS


client revenue

About the Author

raphael tosti founding partner headshot

Raphael Tosti

Founding Partner and Technical Lead

@Mookie Digital

Raphael founded Mookie Digital after training with Ex-Google partners and leading internal systems development and paid marketing for Bosch.

He leads tracking integrations, landing page design and development, video/image asset creation, analytics, and co-leads all advertising operations.

Date Published: 02.02.2024

Date Modified: 02.02.2024

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