Ad Fraud

If you’re running a PPC campaign, check your analytics data.   Do you see a rapid curve of increase in click traffic, while your installs or events remain low?   This is one of the classic signs that you need to get your ad traffic vetted, as it might be under the radar of ad fraud perpetrators.   Over time fraudulent parties in the digital ecosystem have evolved and indulged in sophisticated fraud techniques to gain maximum benefit. The techniques have become more human-like and difficult to detect.   As a result, these fraudulent techniques not only impact the bottom line of a digital brand but also weaken the efficiency of the campaigns. From driving bot traffic to breaching the walled gardens, they have perfected their practices over time. One of them has been PPC fraud techniques which are not just limited to web but also app campaigns.   As the spending on mobile app marketing increases, it has become a gold mine for fraudsters to dig for money Types of in-app PPC Advertising Fraud Unlike web campaigns, app-based PPC fraud operates in an opaque environment. Fraudsters manipulate in-app interactions at various levels, but the most alarming issue is that advertisers often rely on flawed measurement systems that don’t validate traffic effectively. This is where many advertisers fall into the trap of trusting impressions and clicks at face value.  The fraud manifests in multiple ways: -Click Spamming: Fraudsters flood attribution systems with click spamming which is to generate fake clicks to wrongfully claim credit for organic installs.  -Click Injection: Malware-infected apps hijack install events by sending a fraudulent click at the exact moment an app is installed.  -Bot Traffic: Automated scripts mimic human behavior, generating clicks and even fake in-app events.  -Organic Poaching: Fraudsters hijack organic user traffic by injecting random clicks and falsely claiming attribution.  -Acquisition Poaching: Fraudsters manipulate attribution models by faking user engagement to appear as legitimate traffic.  The Importance of Click-Level Validation The biggest flaw in many app advertising strategies is that they trust data provided by Mobile Measurement Partners (MMPs) without validating it beyond the impression level. MMPs typically attribute installs and in-app events based on the last-click attribution model, but they don’t analyze whether that click was genuine in the first place.  Without click-level validation, advertisers are left vulnerable to: -Wasted budgets: Paying for fraudulent clicks that never convert into real users.  -Distorted performance metrics: Misattributed installs and engagement rates create misleading reports.  -Poor down-the-funnel optimization: Advertisers end up optimizing for fraudulent traffic rather than genuine user acquisition.  How PPC Fraud Impacts Down-the-Funnel Metrics Fraudulent clicks don’t just impact the initial stages of a campaign; they create a ripple effect down the funnel. Consider this:  If your PPC campaign generates fake clicks, your CPI (Cost Per Install) skyrockets because installs may not be genuine.  Fraudulent installs inflate your DAU (Daily Active Users) numbers artificially, leading to poor LTV (Lifetime Value) calculations.  Since bots or hijacked installs don’t engage meaningfully, your retention and conversion rates drop, creating misleading insights for future optimizations.  Real Case Study: How a Quick Commerce Brand Tackled PPC Fraud A major quick commerce platform in India discovered severe PPC fraud issues within their app advertising campaigns. They were running retargeting campaigns to increase engagement, but conversions remained low despite their significant ad spend. Upon investigation, they found:  -High levels of fraudulent traffic: 58% of clicks and 46% of events were fraudulent.  -Organic Poaching: Fraudsters injected random clicks to claim credit for organic installs. The click-to-conversion time gap for Publisher A on January 11th was 35% longer than usual, indicating hijacked organic traffic.  -Acquisition Poaching: Engagement partners falsely re-attributed already acquired users by forcing fake re-engagement clicks instead of waiting for real user activity.  By implementing click-level validation and actively monitoring traffic sources, the brand:  Identified and eliminated fraudulent publishers.  Reduced misattribution of organic traffic.  Saved $1.9 million in a single month by stopping invalid ad spend.  This case highlights how unchecked PPC Ad fraud can drain budgets while inflating performance metrics, making it crucial for advertisers to validate traffic beyond surface-level analytics.  Combatting PPC Fraud: Steps Advertisers Must Take Tackling PPC fraud in-app campaigns requires a proactive approach. Here are the most effective strategies:  Validate Click Traffic in Real Time   Use solutions that verify click authenticity before attribution.   Look for abnormal patterns like excessive click-to-install times or multiple clicks from the same device. Go Beyond Last-Click Attribution Model Validation  A last-click model alone doesn’t provide the full picture.  Compare click timestamps and engagement across different sources to detect anomalies.  Monitor Post-Install Behavior  Genuine users interact with an app differently than bots or fraudulent installs.  Analyze session depth, retention rates, and in-app purchases to flag anomalies.  Use Third-Party Fraud Detection Tools  Many MMPs lack comprehensive fraud prevention mechanisms.  Implement third-party ad verification tools to cross-check data integrity.  Blacklist Fraudulent Sources  Identify ad networks or publishers that repeatedly send suspicious traffic.  Blacklist them proactively to reduce the impact on down-the-funnel metrics  Way Forward PPC fraud in apps is a silent budget killer that can cripple your campaign performance if left unchecked. The key to protecting your ad spend is to go beyond surface-level analytics and validate clicks at a granular level.  If advertisers treat click validation like a security checkpoint—ensuring every click is a legitimate entry rather than an impersonator—campaign efficiency will soar, and wasted ad spending will be reduced.   Want to safeguard your app campaigns from fraud? Start by validating your ad traffic data, leveraging the advanced ad fraud solution that go beyond surface level check, and make every click count. Want to get a demo of how we do it? Contact our team today  

Picture this: The marketing team proudly delivers a new batch of leads, convinced that these prospects are primed for conversion. Meanwhile, the call center team rolls its eyes once again, they’re fielding complaints from uninterested or unqualified contacts. Frustration rises, fingers are pointed, and the age-old question resurfaces: Who’s responsible when leads don’t convert—marketing or the call center?  This debate often boils down to one critical issue: junk leads. While the marketing team may generate impressive volumes of leads, not all are created equal. Junk leads—those unqualified, uninterested, or even fraudulent frequently sneak into the funnel, wasting time, resources, and ultimately, opportunities for both teams. In this article, we explore the “real reason” behind this endless marketing vs. call center debate, emphasizing how a continuous filtering system can align both teams, save time, and improve results.  The Junk Lead Challenge: Why Leads Aren’t Always What They Seem  On the surface, a lead might appear promising. It might tick the right boxes in terms of basic demographics or initial engagement. However, a closer look reveals that not all leads are created equal. Junk leads are often generated through non-intent-driven clicks impertinent, low-quality traffic sources, or unverified information. These leads lack genuine interest and intent to buy, leading to a series of issues that drive the marketing and call center divide:  Marketing’s Perspective: “We Hit Our Numbers”  Marketing’s goal is often centered on generating high lead volumes. Performance is measured by metrics like click-through rates, form submissions, and lead counts, creating pressure to hit targets. However, these numbers can sometimes reflect quantity over quality, as invalid clicks and junk leads skew results.  Call Center’s Perspective: “We’re Wasting Our Time”  The call center team deals with these leads firsthand, engaging in time-consuming follow-ups only to find disinterested, unreachable, or unqualified contacts. For call center agents, these engagements lead to burnout and frustration, impacting their morale and effectiveness.  This disconnects between the two teams not only impacts productivity but also consumes valuable resources. For a business focused on conversion and growth, the junk lead issue becomes a costly barrier, resulting in wasted time, reduced efficiency, and strained internal relationships across departments.  The Hidden Impact of Junk Leads  Junk leads are more than just data in the CRM; they create a cycle of wasted efforts for both teams:  -Lost Time on Unproductive Calls: Call center agents spend precious time on leads that lack any genuine interest in the product, draining their morale and productivity. It’s frustrating for agents to encounter frequent rejections, impacting their motivation and performance.  -Strain on Marketing Resources: For marketing, the push for high numbers of leads can come at the expense of quality. Campaigns are evaluated on how many leads they generate, even if many are unlikely to convert. This can lead to a misplaced focus on quantity over quality, which ultimately fails both teams.  -Unmet Conversion Goals: For both marketing and the call center, junk leads directly affect the bottom line. Marketing sees low ROI on its campaigns, and the call center fails to hit conversion targets. In the end, this hurts the business by diverting resources from potential sales opportunities to unqualified leads.  Focus on Lead Quality Over Lead Quantity  To resolve the marketing-call center debate, it’s essential to shift the focus from sheer lead volume to lead quality. By implementing more rigorous lead qualification and filtering practices, companies can prevent junk leads from clogging the sales pipeline. Here’s how:  –Establish Clear Lead Qualification Criteria The first step in aligning both teams is to set clear standards for what defines a “qualified lead.” This could include factors like purchase intent, behavior on the site, engagement with marketing content, and demographic relevance. By standardizing these criteria, marketing can better identify high-potential leads before they’re sent to the call center, ensuring agents aren’t left cold-calling uninterested contacts.   -Leverage Behavioral Data for Better Lead Insights  With digital tools, marketing can capture and analyze data on each lead’s behavior—such as time spent on key pages, interaction with offers, and responses to email campaigns. Leads showing high levels of engagement signal a stronger interest and are more likely to convert. Sharing this behavioral data with the call center gives agents deeper context, helping them prioritize leads more effectively.  -Segment and Score Leads Before Hand-Off  Segmentation and lead scoring can transform a CRM from a dumping ground of all leads into a well-organized system that prioritizes quality over quantity. With segmentation, marketing can assign different levels of interest to leads, grouping them by their likelihood to convert based on factors like recent interactions, browsing patterns, and demographic fit. Lead scoring, on the other hand, uses these criteria to rate each lead’s conversion potential, making it clear which leads warrant follow-up.  –Optimize Follow-Up Process for Different Lead Types  Once leads have been segmented, the call center can adjust its follow-up process based on each group’s engagement level. For instance, leads with high engagement scores can be prioritized for immediate, frequent follow-ups, while lower-scoring leads might benefit from a more gradual approach or even additional nurturing from marketing before being passed to sales. This ensures that agents are spending their time where it’s most likely to yield results.  -Implement Continuous Feedback Loops  To maintain alignment, marketing and the call center need open lines of communication. A continuous feedback loop allows the call center to provide insights on lead quality back to marketing, helping refine future campaigns. Over time, this feedback can guide marketing’s strategies to target more qualified leads, improving the overall quality of leads entering the funnel.  How mFilterIt can help marketers remove junk leads?    mFilterIt’s  Ad fraud solution empowers advertisers by collecting and analyzing crucial data—such as website behavior, CRM inputs, and conversion metrics—through advanced AI & ML algorithms. The system’s proprietary rule engine scores lead based on user intent (high, moderate, or low), helping advertisers swiftly identify and filter out junk leads. This enables sales teams to focus on quality prospects, improving efficiency and conversion rates. With mFilterIt’s analytics-driven approach, advertisers gain actionable

Imagine launching a re-engagement campaign with the confidence that you’re targeting existing, familiar users—an audience that’s supposed to be fraud-proof. It seems logical, doesn’t it? After all, why would fraudsters bother with users who are already in your database?  Unfortunately, this assumption couldn’t be more misleading. Re-engagement campaigns are not only impacted by fraud but are also increasingly targeted by sophisticated fraudulent techniques. Fraudsters see these campaigns as low-hanging fruit, exploiting weak attribution systems and leveraging the widespread myth that re-engagement is safer than acquisition of new customers. Re-engagement campaigns are undeniably valuable. They help brands reconnect with dormant users, boost retention, and drive long-term growth. But failing to recognize the lurking threat of mobile ad fraud can turn these campaigns into a costly trap. In this article, we’ll uncover the hidden risks, types of digital ad fraud affecting re-engagement efforts, and how brands can protect themselves. It’s time to rethink what you know about re-engagement campaigns and ad fraud.  Common Misconceptions About Fraud in Re-Engagement Campaigns  Belief that targeting existing users reduces the likelihood of fraud: Marketers often assume that fraud is less of a threat in re-engagement campaigns because the target audience consists of users already familiar with the brand. Perception that fraudulent activities are more prevalent in acquisition campaigns: While acquisition campaigns are a common target for fraud, re-engagement campaigns are equally at risk due to their high-value budgets and relaxed monitoring.  Types of Fraud in Re-Engagement Campaigns  – Organic Poaching  Organic poaching occurs when fraudsters manipulate attribution systems to take credit for users who would have naturally re-engaged with the brand. These are genuine users who, due to their liking for the brand, were likely to return on their own. Fraudsters intercept their activity by inserting click be, before the user’s click making it look organic. This artificially inflates the campaign’s performance metrics, and the attribution platform marks this as an organic activity.   – Acquisition Poaching  In acquisition poaching, fraudulent reengagement partners take advantage of attribution windows to falsely categorize newly acquired users as re-engaged ones. For instance, they may manipulate data to claim credit for a user who has just downloaded an app or made a first purchase, even though the individual was not part of the re-engagement audience. This not only wastes the re-engagement campaign budget but also blurs the distinction between acquisition and re-engagement efforts, leaving marketers with misleading insights.  – Event Spoofing  Event spoofing involves fraudsters simulating user actions after a re-engagement campaign, such as fake logins, purchases, or app interactions. These fabricated events create the illusion that the campaign successfully drove meaningful engagement. However, these activities lack any real user intent or value, resulting in wasted ad spend and unreliable performance data. Event spoofing is particularly harmful because it often goes undetected until a deeper analysis reveals discrepancies between reported metrics and actual user behavior.  Impact of Fraud on Re-Engagement Campaigns  Financial Losses and Wasted Ad Spend: Re-engagement campaigns are designed to maximize ROI by targeting users who are already familiar with the brand. However, when fraudsters interfere, ad budgets are wasted on fake actions that provide no real value. For example, event spoofing may create the illusion of reactivated users completing high-value actions, such as purchases or logins, while in reality, no such engagement has occurred. This not only drains resources but also diverts funds from genuine opportunities to re-engage actual users. Misleading Campaign Performance Data: Fraudulent activities in re-engagement campaigns can significantly distort performance metrics. Organic poaching and acquisition poaching, for instance, lead to inflated figures, making campaigns appear more successful than they truly are. When marketers rely on these skewed insights, they risk misallocating budgets, overestimating campaign effectiveness, and losing the ability to optimize future strategies effectively. Inefficiency in Targeting Actual Users: Fraud doesn’t just waste money; it also undermines the core objective of re-engagement campaigns—reconnecting with dormant users. Fraudulent actions skew targeting systems, making it harder to identify and reach genuine inactive users who could bring long-term value to the brand. Instead, marketers end up chasing fake interactions, missing out on real opportunities to reignite meaningful customer relationships. Why You Need to Invest in an Ad Traffic Validation Solution: Real Cases   Case 1: Abnormal Click to App Open Rate   In normal case, most users get reattributed immediately after opening the app.  In the above case, about 60% of the clicks made by users on retargeting ads did not result in the app being opened immediately and it is done after 06th Hour, which clearly indicates large amount of click spamming to capture users opening the app organically.  Case 2: Repetitive Orders from Same GAID   Repetitive orders are getting placed from same GAID on the same time frame and same store also, all order is on Cash on Delivery. Refer below sample for the same, there are 212 such orders placed. This is a clear case of spoofed events.   Takeaway  Re-engagement campaigns are important for marketers to reengage their past users and be present in their minds. However, to increase the potential of these retargeting campaigns, marketers must also address the hidden risks of fraud to increase the potential of the campaign and reach maximum users. By implementing robust ad fraud solution like Valid8 by mFilterIt, monitoring campaign data meticulously, and staying informed about the emerging fraud patterns can help to safeguard the re-engagement efforts and ensure that your ads reach the right audience.   Want to get a demo of how we do it? Contact our team today  

When running online ad campaigns, it’s not just about getting clicks—it’s about getting the right clicks. Many advertisers face the challenge of differentiating between genuine clicks and accidental or low-quality clicks. This is where mFilterIt’s click validation comes in. Click validation helps to ensure that the clicks on your ads are from real, engaged users who are genuinely interested in your product or service. How does click validation work, and why is it so important? Tracking   >>>  Analyzing  >>>  Improving -Tracking Click Behavior: The first step in click validating is tracking user interactions with your ads. Tools like pixels or tracking URLs allow you to monitor exactly what happens after someone clicks on your ad. Are they bouncing right away, or are they exploring your website further? If someone clicks on an ad and immediately leaves, it might suggest they were not genuinely interested. This kind of data is key to identifying poor-quality clicks. -Analyzing Engagement: Clicks don’t tell the whole story. By validating the quality of each click, you can assess how much time visitors spend on your site, what pages they visit, and if they complete any desired actions (like signing up or making a purchase). For example, if a user clicks on your ad but doesn’t interact with your site, it’s a sign they might not be a valuable lead. Click validation helps you focus on users who engage deeply with your platform and are more likely to convert. -Improving Ad Targeting: Click validation allows you to fine-tune your targeting strategy. By identifying which clicks are more likely to convert, basis geo, behaviour, scroll pattern, etc.., you can adjust your campaigns to reach users who show genuine intent. Over time, this leads to higher quality leads and a better return on investment (ROI). In conclusion, ad fraud solution isn’t just about tracking clicks—it’s about understanding the intent behind those clicks and optimizing your campaigns for better results. If a bot is just clicking your ads your campaign will never deliver conversions, since bots doesn’t buy or fulfil a successful lead. It’s the genuine user who counts, hence your campaign optimization should focus more on learning your user behaviour and adopting necessary findings to improvise campaign conversions. To start your click validation connect with mFilterIt.

Ad fraud has become the most talked about thing in the digital ecosystem in the last one decade. Over the years it has become sophisticated and led to huge losses for the advertisers. According to the last measured stats, the potential loss due to ad fraud in 2024 will be around $100 billion.   And if marketers who are running impression campaigns are thinking that ad fraud is not impacting their ad campaigns, take a look at your campaign data.   If you see unusual traffic from sources outside your targeted area, there is one red flag for you to check. And like this, there are many more.   Impression validation is as crucial as validation of other hard key performance metrics. It helps advertisers get transparency at the beginning stage of the ad campaign and help them stop it at the root before it impacts the entire campaign, especially metrics like installs and events (like subscription, or first transaction) where the cost is higher.   Let’s understand in detail how impression fraud validation is essential for app marketers and how MMP’s are hiding the actual impact of fraudulent impressions.   MMP’s are hiding the full picture from you   Mobile Measurement platforms or MMPs often play a significant role in app marketing. They help the advertisers track the last click attribution of their ad campaigns and track app performance. There are a few MMPs who also provide ad fraud detection tool bundled with their attribution services. However, ad verification by MMPs have their own limitations.   -Focus on Attribution, Not Validation: Their core services are limited to attribution and not validation. MMPs get paid on the number of attributions made and when they detect fraud on these attributed sources, it directly impacts their revenue creating a conflict of interest. Therefore, they detect only 10-12% of the fraud and the rest of the fraudulent traffic remains undetected.  -Limited Scope of Fraud detection: The MMP’s don’t have the capability of doing deeper checks. They can detect fraudulent traffic based on basic checks and they often miss sophisticated fraud techniques.   -Lack of Real-Time Fraud Insights: The attribution platforms cannot provide real-time fraud insights to advertisers. Their usual timeline for generating ad fraud reports is D+7, where if the fraud is detected by the 20th, the advertisers will receive the report by 28th of the month. This further delays the preventative measures which the advertiser could have taken against these fraudulent sources.   Why App Advertisers Need to Look for an Advanced Ad Fraud Solution?   In comparison to the fraud detection done by MMPs, mFilterIt’s Valid8 solution uses a more holistic approach against the sophisticated fraud techniques. Some of the differentiating factors which will help you realize the difference:   -Transparency on real % of fraud: When MMPs detect less % of ad fraud, the advertisers are not aware of the actual number of fraudulent traffic sources. This further impacts the efficiency of the ad campaigns, and the advertisers end up losing money twice. First, on the invalid traffic interacting with their ads before validation, and second when the actual number is not reported by MMPs. With mFilterIt, brands can transparency at the source-level and identify which traffic sources are skewing the metrics.  -Provides real-time analytics and blocking: Using mFilterIt’s ad fraud detection solution, the advertisers can get real-time analysis of the fraudulent traffic and block them in real-time. This helps advertisers to save money on both invalid traffic on ads and attribution cost for these traffic sources to MMPs.   -Give full funnel protection: Unlike the MMPs, our ad fraud verification tool protects the campaign holistically. Our full-funnel coverage not just validates traffic at impression-level, but also at the install and event level to reduce the impact of fraud. This ensures that cleaner traffic reaches the end-of-the-funnel, resulting in a better conversion rate.   A Real Case  Here is a real case of a brand which was running an install campaign. By partnering with mFilterIt the brand was able to identify the impact of invalid traffic at the impression level. Upon further analysis we found two specific reasons for invalid traffic – impression spamming and traffic coming from incorrect region. We identified the cause and started blocking invalid traffic which resulted in an increase in organic traffic at the install level.    Takeaway  Ad fraud is evolving, and it can easily bypass the basic checks by MMPs. For advanced fraud techniques, you need an advanced ad fraud detection tool in your tech stack. While looking for an ad fraud verification vendor for your app campaigns, don’t believe the surface level reports and checks. It is time to ask for transparency and ensure that your entire ad campaign is protected, thereby your ads are seen by a genuine audience resulting in better conversions.   To get details on how we do it, get in touch with our experts  

For digital marketers, walled garden is not a foreign word. However, we will take a quick minute to throw light on it.   Walled gardens is a term coined in digital marketing for closed advertising environment where all the operations are controlled by the ecosystem provider. Some of the major players ruling this landscape are Google, Meta, and Amazon. They offer the advertisers access to a large set of audiences and comprehensive data analytics.  Due to the nature of walled gardens, these platforms are often perceived to be a protected space for advertisers. This means that the traffic is assumed to be high quality.   However, reality is not exactly black and white. It is grey.   Let’s find out.   The Myth is – Walled Gardens don’t have bot traffic   When advertising on walled gardens, the advertisers often perceive that their ads are receiving filtered traffic, due to the close nature of the walled garden ecosystem.   The walled gardens claim robust proprietary technologies and algorithms that filter out suspicious or bot-driven activity, leading advertisers to believe these environments are more secure.   However, this “black box” approach also means that advertisers must trust the platform’s own reporting and assurances. Independent verification is limited, so advertisers often accept the platforms’ claims at face value. The perception of reduced bot traffic is partly an outcome of this reliance on self-reported data, alongside platforms’ reputations and massive resources dedicated to tech infrastructure and security. These walled gardens can detect and safeguard from general invalid traffic, however the bots have also become sophisticated over the years. Its ability to mimic human behavior makes it easy to bypass basic rule-based checks. Due to opaque reporting, the advertisers are unaware of the quality of their ad traffic and who is watching their ads. Sophisticated Bots penetrate walled gardens  Sophisticated bots are designed by fraudsters to mimic human behavior in ways that they can mask their movements to evade detection. These bots are capable of taking actions like clicking, scrolling, and even fill forms, which makes it difficult to identify then and differentiate from real users.   These sophisticated bots can even adapt with platform-specific platforms, adjusting their patterns to avoid suspicion. As walled gardens restrict access to third-party ad fraud detection solution, resulting in limited visibility and transparency for advertisers, these bots use this opportunity. Signs of a Sophisticated bot activity   Repetitive visits from a single device  In this case, visits came repeatedly from a single device in a short span of time, indicating abnormal traffic.    Multiple visits in short time span from a single device  In this case, the visits are coming in a short time from the same device fingerprinting, indicating a bot traffic.  Impersonation of a specific device   In this case, the fraudsters impersonate the identity of a specific device. This technique is used by fraudulent affiliates to exhaust the ad budget. Due to this no event (lead/purchases) come from this device. In this case, the visits are coming from a single device, where the user agent at client and server are different, indicating abnormal behaviour.     Partner with an ad fraud validation tool for walled Garden  No platform is immune to bot traffic, including walled gardens. To get full transparency of their ad traffic, advertisers need an advanced solution that can identify sophisticated bots patterns effectively and block them proactively.   The benefit of blocking bot traffic is not limited to clean traffic, but it also helps to improve conversion rate of the ad campaigns. To ensure that the sophisticated bot traffic doesn’t bypass the detection methods, we at mFilterIt use a full-funnel approach along with identifying device signals, behavioral and heuristic checks.   Unlike traditional ad fraud solution vendors, mFilterIt goes beyond the impressions and clicks level to identify sophisticated bot traffic. Our solution detects suspicious traffic at the visit level where more sophisticated patterns can be detected and blocked.   Therefore, protection at just the impression and click level is not enough. Advertisers have to look beyond that to ensure their campaigns on walled gardens are protected from bot traffic.   How did an automobile player improved their conversion rate using Valid8 by mFilterIt?   The major automobile player was running Google search campaigns to bring traffic to their website from various meta platforms. But despite substantial spending, the conversion rate was suspiciously low. Upon identifying suspicious ad traffic patterns, we started the blacklisting process. This resulted in cleaner clicks and lead, improved conversion rate and a savings of $0.47 million for the brand.   Refer to the images below to see the results:   A 13% drop in click fraud and 11% drop in lead fraud rates  A 1.75x increase in conversion ratio  Start Blocking Bot Traffic on Walled Gardens   While walled gardens are trusted for their controlled and secure environment, the reality is that they are not bot-free. To protect ad campaigns from the sophisticated patterns of bot, the advertisers need an additional layer of protection by partnering with ad fraud detection vendor with advanced technology to ensure their ad budgets are consumed to attract genuine audience instead of bots. As bots continue to evolve, advertisers need transparency to evaluate where their ads are shown and who is watching their ads to better assess the quality of their ad traffic and maintain campaign integrity. Get in touch with us today to see how Valid8 by mFilterIt can help you uncover and eliminate hidden fraud in your walled garden campaigns.

Imagine a bucket with a small but constant leak. You pour water daily, yet the water level barely rises. Running lead campaigns with junk leads in your CRM is similar.   You’re investing resources, yet the actual value doesn’t grow. Junk leads, like leaks, waste resources, and hold back growth, leaving your team stretched and chasing unqualified prospects.  For a digital brand investing heavily, the pain point is clear: valuable marketing and call center resources are wasted on unproductive leads, reducing campaign efficiency and conversion rates. One of the sure-fire methods is lead punching used by fraudulent publishers to get money out of advertisers.   The only catch here is – Lead punching only helps these publishers get money, the advertisers are only left with false, or junk leads.   What is Lead Punching? Lead punching is one of the fraudulent practices used by dishonest publishers or affiliates to deliberately submit false lead information, using real names, phone numbers and email ID of a person. This information is easily accessible across multiple sources at a minimal cost, which makes it easy for fraudsters to exploit. They use this data to fill out lead forms, ensuring the details appear legitimate.   However, in reality the real person is not aware of filling in the lead form or even having interest in the service. Therefore, when the sales team follows up, these supposed leads deny submitting any form or even knowing about the company.    This forms easily 30-40% of the total leads which a typical client receives. So not only is the advertiser losing media budget by paying for these junk leads, but they also end up burning call center costs in calling up these leads. Marketing teams also add these leads into a CRM and do Email / WhatsApp marketing on these. Now they waste further money in reaching people who have no interest in their products.   Many advertisers try to implement CAPTCHAs and OTP to prevent bot-driven leads. However, these techniques can also be bypassed. Using disposable phone numbers, OTPs can be bypassed. There are also Captcha solvers available at just one click.  Therefore, implementing these checks cannot guarantee clean leads.   How does it impact CRM health?   – You waste marketing spend on irrelevant leads When marketing budgets drive unqualified traffic, a significant chunk of that spend is essentially wasted. Over time, these costs add up, creating a heavy financial toll on lead generation campaigns that fall short of delivering qualified prospects.  – Your call center team spends time calling irresponsive and irrelevant leads Junk leads consume precious time, especially for call center teams and sales representatives. Every call, follow-up, and email sent to an unqualified lead diverts resources from real prospects, reducing the efficiency and morale of your team.  – You miss the 5-minute rule According to this rule, the chances to connect with a prospect increases 100 times when connected within 5 minutes instead of waiting for an hour.  With resources tied up on low-quality leads, high-potential prospects might get lost due to delayed follow-ups or overlooked engagement. Junk leads indirectly lead to missed revenue opportunities by diverting the attention of your team.  – Your brand name loses credibility Repeatedly reaching out to leads who lack interest can be a poor reflection on your brand. In some cases, it may even create negative associations if potential customers perceive your company as inattentive or misaligned with their needs.  Strategies to Eliminate Junk Leads and Focus on Quality  Taking control of your lead quality requires a well-structured approach, integrating technology and a clear strategy at each step of the funnel. Here’s a roadmap to clean up your lead pipeline and prioritize high-value prospects.  1. Clean Traffic and Fraud Prevention  Start by eliminating invalid traffic sources and preventing fraud with real-time validation tools. Filtering out traffic that doesn’t meet quality standards early on ensures that only leads with genuine potential enter the funnel. By removing these invalid visits at the start, you create a cleaner foundation, setting the stage for more effective lead nurturing and conversion efforts.  2. Intent-Based Visit Analysis  Once you’ve ensured traffic quality, dive deeper by analyzing the intent behind each lead’s visit. Look at the behavior of leads on your website—time spent, pages visited, and actions taken. This stage is crucial for gauging how interesting a lead truly is. Intent-based analysis lets you sort out window-shoppers from those genuinely interested in your product or service, allowing your team to prioritize leads that show clear signs of potential.  3. Lead Scoring and Validation with CRM Integration  For an optimized lead funnel, integrate your CRM with automated lead scoring tools that assess demographic data, engagement level, and previous behavior. Leveraging AI and ML-based technology, you can assign scores to leads based on these criteria, making it easy to prioritize high-potential leads. With a streamlined CRM, your sales team can focus their follow-ups on leads more likely to convert, saving time and increasing productivity.  4. Funnel Optimization and Junk Lead Filtering  With a system in place to identify quality leads, refine your funnel by regularly reviewing and tweaking the criteria that classify leads. By tightening filters and adjusting scoring parameters, you can progressively reduce the entry of junk leads, creating a cycle of continuous improvement in lead quality.  How mFilterIt validate leads on the CRM?   mFilterIt’s solution empowers advertisers with transparent, data-driven insights into CRM data. By collecting key metrics—such as website behavior, sales funnel, revenue, and attribution data—this mechanism uses advanced AI & ML algorithms to analyze each lead’s journey. The unique rule engine provides in-depth conversation and attribution analytics, categorizing users by intent (high, moderate, or low). This user-intent scoring, combined with visit analytics, gives advertisers clarity on lead quality and helps optimize campaign efforts. The solution enables brands to focus on high-intent leads, ensuring accurate reporting and maximizing ROI from their CRM data.  Clean Your CRM with Advanced Technology  For marketers, the focus shouldn’t just be on generating leads but on ensuring the quality of each one. By investing in