Durgesh Rathore

Durgesh Rathore, Head of the App Business Unit at mFilterIt, brings 10+ years in digital marketing with expertise in paid media and user acquisition. She drives growth for global app brands, delivering ad fraud prevention solutions and leveraging data to power clean, scalable app performance.

What is Click to Install Time? Why Advertisers Need to Map this to Detect Mobile Ad Fraud?

Bots are becoming sophisticated and more human-like every passing day. And with the emergence of AI, it is becoming a dominant force for shaping online traffic.   According to Imperva BadBot Report 2025, 51% of the internet traffic is driven by bots, which is further amplifying with the introduction of AI and LLM. Unlike the basic bot traffic showing abnormal signs like high number of clicks/installs etc., the sophisticated bots can mimic human behaviour, therefore bypassing the validation checks.    As a precautionary measure and to check if your campaigns are impacted by bots/invalid traffic, there are signs that you can look for in your campaign data.   One of them being Click to Install Time to identify invalid installs in your mobile app campaigns.  In this blog we will breakdown how CTIT can be seen as a signal to identify invalid traffic and how marketers can use it to take proactive action against mobile ad fraud.   What is Click to Install Time? How to Identify Invalid Traffic Evaluating CTIT?  Let’s simply breakdown what CTIT means before moving forward to understand the kind of patterns that reveal exploitation of mobile ad fraud and click to install time. Click Time: The moment a user clicks on your ad.  Install Time: When the app actually finishes installing.  Click-to-Install Time (CTIT): The time gap between these two.  It is basically a metric used in mobile advertising to map the time it takes for a normal user to download an app after clicking on an ad.   This gap varies naturally. Real users don’t install apps instantly every time; there can be delays, pauses, network differences, and human behaviour involved. What a genuine user’s install journey looks like  This process takes time, usually a few seconds to a few minutes, depending on network speed and app size.  However, fake installs show different timing patterns.   Here’s are the two types of abnormal CTIT patterns we observed recently that clearly indicate towards install fraud:  Examples of Abnormal CTIT Patterns   Case 1: Extremely short click-to-install time (click injection)  This snapshot compares the click time and install time for multiple installs coming from the same publisher. The gap between click and install is consistently just 1–3 seconds, and in several cases, the values are identical or nearly identical.  Why it is a problem? A real user cannot click an ad, get redirected to the Play Store, download the app, complete the installation, all within a few seconds, repeatedly.   This pattern strongly indicates click injection, where fraudsters:  Detect that an app install is already in progress  Inject a click at the last possible moment  Steal attribution credit for a genuine install  mFilterIt insight: Why this matters? Although these installs appear valid in attribution reports, the timing exposes manipulation. Extremely short and repeated click-to-install times are a strong indicator of high-risk fake attribution, not real user engagement.  Learn more about common techniques of install fraud here. Case 2: Google Play install begins before the user clicked on an ad  In this snapshot, the timestamps reveal something even more concerning. The Google Play install begin time occurs before the recorded ad click time. This results in a negative click-to-install time, meaning the install process started before the user supposedly clicked on the ad.  Why is it a problem? This breaks the basic logic of attribution. A real user cannot start installing an app first and then click an ad for the same app afterward. When install activity precedes the click, it clearly indicates:  Manipulated or falsified timestamps  SDK tampering or fabricated attribution signals  This is not caused by reporting delays or tracking errors; it points to deliberate attribution manipulation.  mFilterIt insight: Why this matters? Any case where the install begins before the ad click should be treated as install fraud by default. These patterns strongly indicate fake attribution attempts, even if the installs are being credited by attribution platforms.  Signs to Identify Abnormal CTIT Patterns CTIT mapping should be approached in two layers: what you can validate manually and what requires advanced detection at scale.  As an advertiser, the following click to install time red flags should immediately raise concern, especially when they appear repeatedly.  Installs within 1–3 seconds of a click  Real users need time to reach the app store, download the app, and complete installation. Consistently instant installs are not normal human behaviour patterns.  Identical CTIT values across multiple installs Human actions vary. When multiple installs show the same or near-identical timing, it often points to automated or scripted activity.  Long delays followed by sudden attribution This pattern is commonly associated with click spamming, where random clicks are generated and later receive credit when an install happens.  Negative CTIT values If an install begins before the recorded ad click, it breaks basic attribution logic and strongly indicates manipulated timestamps or fake signals.  How Advanced Mobile Ad Fraud Detection Solutions Help Mobile ad fraud is often distributed across campaigns, publishers, and devices, making it difficult to detect without advanced analysis.  Attribution platforms answer one primary question: Who gets credit for the install? They do not answer whether the install journey itself was genuine or a fake one. While they work on assigning credits rather than behavioural validation, brands need an advanced mobile ad fraud detection solution to ensure campaign efficiency. Here’s how it helps:  Source-Level CTIT Pattern Analysis – Know who is installing your app Advanced solutions analyze click-to-install time across all campaigns and channels simultaneously. This makes it easier to spot publishers or sources that consistently show unnaturally fast or uniform CTIT patterns. It also helps identify install fraud patterns that may look normal in isolation but become obvious when viewed across the entire account.  Analysis of CTIT with Click Behaviour – Don’t let sophisticated bots slip by Click-to-install time is evaluated alongside click signals such as click frequency, burst patterns, and timing alignment. This helps distinguish genuine user clicks from injected or spammed ones.  Correlation with Device and Environment Signals – Differentiate between bot & human Advanced

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Bot Traffic Spotted

Bot Technique Spotted: How Unusual App Version Patterns Signal Bot Traffic & Fake Installs

One of the common pain points our clients have expressed is that their number of installs doesn’t match the number of conversions. They see a high volume of installs happening, but this doesn’t convert into outcomes.   There is not just one reason behind an unusual spike in installs. It can be bots, or something more advanced which a human eye might miss easily. In one of a recent campaign data we evaluated, we observed that a new and unusual technique is used to hide invalid traffic driving fake app installs from Android mobile versions.   In the sections ahead, we’ll break down how fraudsters are hiding their trails by spoofing device related information – like mobile app versions and why it matters more than you think.   What We Found: Unusual App Version Patterns at Device-Level Validation Real Android applications follow a consistent version structure that looks like 3.1.1, 3.1.2, 3.1.3 (dots/separators placed at the bottom).  However, malicious application versions or bot-generated installs fail to replicate this accurately. These unusual app version patterns appear as 3·1·1, 3·1·2, 3·1·3, where dots/separators are placed in the middle instead of the bottom.   In legitimate mobile app versions:  The separators follow a standard baseline.  Formatting is uniform across devices.  This structure cannot vary from user to user.  But fraudulent installs often contain mobile app versions where:  The separators appear significantly higher than the baseline.  The structure does not match any valid release patterns.  These occur when bots simulate installs without replicating the technical precision of real app metadata.  Moreover, this pattern has been noticed across multiple publishers working with advertisers. Despite high install counts, purchase rates remain very low, confirming a clear metadata-level signature of bot traffic and app fraud.  Learn about the signs you might be experiencing device fraud. How These Unusual App Version Patterns Impact Campaign Performance While this technique might look very low impact, the consequences are not limited to just monetary.   Inflated Install Numbers Bot-generated installs boost the number of total installs, making campaigns appear to be high-performing. This masks real performance and prevents marketers from spotting underperforming channels early.  Misleading Optimization Decisions Fraudulent activity creates false engagement patterns. Due to this, marketers end up shifting budgets toward traffic sources that appear effective but are actually driven by bots, wasting spend and hurting long-term growth.  Unreliable Funnel Metrics Fake installs never convert, engage, or retain. This skews entire funnel data, making it harder to understand real user behavior and accurately measure the quality of your audience.  Misleading Attribution and Affiliate Payouts When bots generate fake installs, publishers or affiliates receive credit for traffic they didn’t actually deliver. This results in unfair payouts and inaccurate performance evaluation.  Lower ROI and LTV Ratio Fake users add no revenue or long-term value, which pulls down overall ROI and LTV benchmarks. This leads marketers to overestimate channel performance while significantly underestimating the actual cost of acquiring genuine, high-quality users.  Therefore, one technical discrepancy like a misplaced dot can impact your entire growth strategy.  How Does mFilterIt Identify this Mobile Ad Fraud Technique? Our ad fraud detection solution conducts a deeper analysis on every traffic source, to differentiate between human and bot-driven data. Some of the parameters used to identify these anomalies:   Analyses metadata that your dashboards can’t see Studies deep metadata—mobile app versions, OS details, device integrity, APK sources, and user-agent patterns thoroughly, revealing subtle bot traffic signals that dashboards and attribution platforms cannot identify independently. It also helps confirm whether the installs came from trusted channels/sources or not.  Identifies abnormal OS-version distributions and mobile ad fraud clusters It compares device versions against normal population patterns, flagging spikes in outdated or scripted versions, common in bot-driven installs operating on obsolete or emulated environments. It also maps recurring inconsistencies, like identical malformed app versions, repeating device signatures, or tight timestamp groupings, to uncover coordinated bot activity rather than isolated technical errors.  Assesses IP reputation and network behaviour Our app fraud detection tool also checks whether installs originate from proxies, VPNs, or data-centre networks, revealing non-consumer routes often used by bots to mask location, identity, and device validity.  Analyses timing behaviour to detect injection patterns By examining click-to-install and event timings, the tool identifies unrealistic timelines, signaling forced installs or automated triggers that do not follow natural user behaviour, generated by affiliates solely to achieve targets and earn payouts.  Blocks invalid traffic before attribution Through pre-MMP and post-MMP checks, the app fraud detection tool stops fraudulent installs in real time, preventing bot traffic from entering analytics, inflating KPIs, or misleading optimization decisions.  Know why attribution platforms miss mobile ad fraud.  Way Forward Unusual app version patterns are just one of many techniques fraudsters use to manipulate installs, which can be used as a red flag to identify an anomaly in your campaign data. However, mobile ad fraud involves multiple evolving techniques that often go undetected in surface-level checks. Identifying these signals is only the beginning. Advertisers need deeper, continuous ad fraud validation to detect anomalies across devices, metadata, networks, and user behaviour. Using an advanced app fraud detection tool enables advertisers to optimize confidently, prevent budget leakages, and build campaigns on clean, trustworthy data.  Strengthen your campaigns. Connect with mFilterIt experts and secure your traffic quality today.

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Referral Wins as Genuine

Are Your Referral Wins as Genuine as They Seem?

You launch a referral program with the intention to acquire new users to your app. When analysing your campaign progress, you see that your referral champion is a single user who somehow ‘invited 200 people overnight’.    You feel confident to spend more on these campaigns. On your dashboard there are 200 people, but upon deeper analysis you see that only a few retain as users. That’s a sign that something is not right. It’s not the usual invalid traffic, but a more advanced and difficult version of ad fraud. Referral and coupon fraud are advanced types of mobile ad fraud which impacts the action driven KPI’s and can skew your data. In this blog, you will discover –  In this blog, you will discover –  What is referral and coupon ad fraud?  How does it happen?   Impact of referral and coupon fraud on campaigns?   How can advertisers protect their referral campaigns?  Real case of a Referral coupon fraud   What is Referral and Coupon Fraud? Referral and coupon fraud are among the most common affiliate marketing fraud that can significantly drain a brand’s paid marketing efforts. Referral Fraud Referral fraud happens when people exploit referral programs to earn rewards without bringing in genuine new users.  What leads to referral fraud?  Creating fake accounts to claim referral bonuses  Using bots or emulators to trigger installs or sign-ups  Sharing referral codes on unauthorized platforms to mass-farm rewards  Coupon Fraud Coupon fraud occurs when fraudsters including dishonest affiliates use invalid codes, promo offers, or counterfeit coupon to claim false monetary benefits without enabling campaign to reach to the new audience.  What leads to coupon fraud?  Using expired or unauthorized coupon codes  Creating multiple accounts to repeatedly use new user offers  Manipulating apps/websites to redeem the same coupon multiple times  Circulating leaked internal or partner-only promo codes  How does Referral and Coupon Fraud happen? In affiliate marketing, referral and coupon ad fraud can happen at large scale. Here’s how each of these tactics contributes to fraud –  First-Time User Fraud This is the most common form of referral fraud. Referral codes are usually meant for new users only, but fraudsters reuse these codes by creating multiple fake accounts. They rely on bots, simulators, device farms, fake emails, and virtual phone numbers to look like new users each time.  Example: In ride apps like Ola or Uber, people often create fake accounts just to claim first-ride promo codes, which drains the advertiser’s budget and inflates fake new-user number.  Self-Referral Fraud In this type of fraud, the same person acts as both the referrer and the referee. Instead of genuinely referring a new user, they use their own information in different combinations such as multiple email IDs or different phone numbers to claim both rewards. Sometimes, they even reuse the same number with minor variations just to game the system.  Fraudulent Coupon Codes Fraudsters misuse promo or referral codes by circulating fake, unauthorized or expired coupon. Users who try to redeem these, end up disappointed when the brand cannot honor them, leading to mistrust and damaging the brand’s credibility. This type of fraud turns simple reward programs into a loophole for illegitimate incentives.  App Cloning (Parallel Space / Dual Apps) App cloning or parallel space gives an advantage to the user to log into two different user accounts simultaneously by creating a separate parallel space on Android devices. This enables them to create multiple accounts, refer themselves, and repeatedly redeem referral rewards. Ride-hailing apps, gaming apps, and social apps often become the targets of this trick.  Gift Card & Return Fraud Losses Fraudsters misuse gift cards, exploit refund loopholes, and combine them with referral rewards to extract illegitimate value leading to revenue loss and compromised program integrity.  Bots, Emulators & VPN/Proxy Abuse Fraudsters rely on automated tools and device manipulation to fake new users. Using bots and emulators, they reinstall apps, regenerate device details, and pretend to be different users. VPNs and proxies hide their real IP addresses or fake their location, making detection difficult. Advanced bots can even use real user information to redeem referral benefits without being caught.  Impact of Referral and Coupon Fraud on Brand The impact of such deceiving tactics falls on brand in the form of –  Wasted Ad Budget: Fraudsters generate fake users, false installs, and invalid coupon redemptions, causing the advertiser’s referral budget to drain quickly.  Lower ROI: Campaign performance looks inflated, but the actual return drops sharply because none of the fraudulent activity contributes to real growth.  Damaged User Trust: Genuine users lose confidence when fraudulent coupon misuse prevents them from accessing the benefits they were promised.  Poor Customer Experience: When rewards fail or referral codes don’t work, both new and existing users feel frustrated and disengaged.  Brand Reputation Hit: Ongoing fraud creates the impression that the brand’s referral or reward system is unreliable, negatively affecting long-term loyalty.  How Advertisers Can Protect Their Referral and Coupon Campaigns When tactics of fraudsters evolve at an alarming pace, protecting referral and coupon campaigns for brands become more important –  Start with Basic Manual Checks Advertisers can begin by reviewing phone numbers, email IDs, and domains used in referral or coupon redemptions. This helps identify obvious patterns like repeated domains, suspicious email formats, or invalid phone numbers. While this offers quick surface-level detection, manual checks cannot catch sophisticated bot activity, device manipulation, or high-volume fraud operations.  Strengthen Protection with a Fraud Detection Solution To truly safeguard referral and coupon campaigns, advertisers should work with a dedicated ad fraud detection provider. Advanced platforms look beyond simple IP repetition and analyze the entire device environment. This includes detecting bots, emulators, disposable emails, virtual phone numbers, app cloning, and suspicious domains, ensuring clean and legitimate referral traffic.  Use Deep Validation & Real-Time Blocking Integrating advanced solutions like an SDK for apps and DSS for websites allows advertisers to validate traffic at every touchpoint. Key checks such as device IDs, email authenticity, domain hygiene, digital reputation, phone number legitimacy, cloning flags, and IP behavior, help identify fraud instantly. Advertisers receive real-time fraud scores and can automatically block fraudulent device IDs before they drain budgets or degrade user experience.  How mFilterIt Safeguard Against Sophisticated Referral and Coupon Fraud mFilterit’s ad fraud protection tool Valid8 enables advertisers and brands to have a keen look on whether the traffic is coming from a legitimate source or not. Here’s how the right solution tackles referral and coupon fraud –  Validates Every User at a Device-Environment Level Valid8 goes beyond basic IP checks and analyzes the complete device environment. It detects

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Ad Fraud Detection: Why It Should Be a Strategic Priority for Businesses

Ad Fraud Detection: Why It Should Be a Strategic Priority for Businesses

Ad fraud is not a myth anymore. It has been there for a long time now, and with the emergence of AI and automations, it is only going to increase.   Moreover, ad fraud is no longer limited to fake clicks and impressions. It now infiltrates every stage of the funnel, from impressions and installs to leads and even post-install events. Many marketers think they’re getting real users, but they’re actually getting fake leads and misattributed conversions.  This means performance marketers and advertisers are not only losing money to bot traffic at top of the funnel also to fake leads and fraudulent installs in web and mobile app campaigns, respectively.   This is why ad fraud detection for brands cannot be seen as a checkbox activity anymore. It has become a strategic necessity to protect budgets and ensure real business growth with clean traffic.  The Real Cost of Ignoring Ad Fraud  The financial losses from ad fraud are massive, but the hidden costs are even greater:  1. Wastage of budget  Every click, lead, or install lost to bots or fraudsters is money that could have been spent acquiring real customers. Over time, this budget leakage eats away a significant portion of marketing budgets.  2. Misleading data and decisions Fraudulent impressions, clicks, and leads distort campaign metrics, making it hard for marketers to judge what’s really working in their favor. This leads to wrong campaign optimizations, wasted investments, and strategies built on unreliable performance data.  3. Missed opportunities  Each fake lead or user acquired represents a genuine customer lost to competitors. Ad fraud not only drains resources but also blocks real growth opportunities, slowing down acquisition and reducing overall market share.  4. Brand trust and reputational risks Fraudsters often place ads in unsafe environments, damaging brand credibility. Fake affiliates and impersonation tactics can also misuse brand assets, leading to long-term erosion of consumer trust and loyalty.  5. Lower campaign efficiency and ROI  Campaigns optimized on fraudulent signals end up favoring poor-performing channels. This lowers efficiency, increases customer acquisition costs, and reduces ROI, making brands spend more for less real business impact.  6. Wasted sales and operational resources – Fake leads clog CRMs, forcing sales teams to chase invalid prospects. Time, effort, and operational costs are wasted on unqualified data, reducing team productivity and slowing down real pipeline conversion.  7. Distorted customer acquisition and LTV metrics Fraudulent activity inflates acquisition numbers while delivering no genuine value. This skews CAC and LTV calculations, misleading teams into thinking growth is sustainable when in reality it’s based on fake signals.  8. Eroded stakeholder and investor confidence – When financial reports are built on inflated numbers, stakeholders and investors lose confidence in performance claims. Over time, this damages credibility and makes it harder for brands to secure future investment.  Explore our latest ad fraud guide to learn about various types of ad fraud tactics used today.  Why is Ad Fraud Detection a Strategic Necessity?  Ad fraud detection is a strategic necessity for brands who want to grow profitably in today’s complex digital ad ecosystem. Every rupee or dollar invested in advertising should deliver measurable business outcomes, not vanish into fraudulent traffic, fake clicks, invalid leads, or bot-driven installs.  Effective fraud prevention empowers brands with clean, reliable data, enabling sharper targeting, accurate optimization, and smarter decision-making. This integrity of data ensures that campaigns are scaled based on genuine performance, not misleading signals.  Ad fraud detection also creates a competitive edge for brands that helps minimize wastage, reallocate budgets to winning campaigns, outperform competitors, and strengthen market position. While fraudsters continuously evolve their methods, proactive monitoring becomes essential to stay ahead of emerging threats. Know how ad fraud impacts every stage of the funnel  Why Relying Only on MMP’s Bundled Ad Fraud Services is Not Enough? MMPs are built for measurement and tracking last-click attribution, not fraud detection or prevention. Here’s why relying solely on them is risky:  MMPs payouts are released basis on the number of attributions sources. When fraud is detected, it reduces the sources impacting their primary revenue thereby creating a conflict of interest.   Attribution tools often miss sophisticated fraud tactics such as click flooding, click injection, device spoofing, event spoofing, etc.  MMPs have limited coverage capabilities. They can track activity but struggle to differentiate between bot-generated, fraudulent, and real users at scale.  That is why brands need to shift towards independent and advanced ad fraud detection tools to ensure brand and marketing budget safety and accountability across channels.  What to Look for in an Advanced Ad Fraud Prevention Solution? To truly protect growth, brands need solutions that go beyond surface-level checks. Here’s what to look for:  Full-Funnel Coverage – Protection across all stages of the funnel, impressions, clicks, installs, leads, and post-install events.  Early Detection & Prevention – Catching fraud before budgets are wasted.   Advanced Bot Pattern Recognition – Detecting spoofing, click flooding, and behavior simulations based on various parameters.  Cross-Channel Protection – From Google and Meta to programmatic, affiliates, and apps.  Transparent Reporting – Log-level insights that empower marketers with clarity and control.  This is where we help. Our advanced ad fraud detection solution, Valid8 by mFilterIt ensures only clean traffic enters your CRM data by detecting all types of generic and sophisticated fraud tactics proactively.   Also read in detail: What marketers should look for in a click fraud prevention tool  How Proactive Ad Fraud Detection adds a Competitive Edge? Proactive ad fraud detection isn’t just about saving money. When brands move from reactive checks to proactive fraud prevention strategies, the advantages multiply.  By eliminating this invalid traffic, fake clicks, and installs, brands ensure that every dollar spent goes toward acquiring genuine customers, reducing overall CPA/CPI, and improving campaign efficiency.  Proactive ad fraud detection also helps ensure only authentic leads enter the funnel, enabling sales teams to focus on qualified prospects and close more deals with higher success rates.  Marketers only target real users, leading to stronger engagement, better retention rates, and higher ROAS across digital channels.  Clean, fraud-free data ensures accurate

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Every Brand Needs an Affiliate Monitoring Audit Checklist for Fraud-Free Growth

Affiliate Monitoring Audit Checklist: Every Brand Needs for Fraud-Free Growth

If you’re running an affiliate program, chances are you have seen both sides of the story. On good days, affiliates bring in new customers, drive sign-ups, and help you scale faster than you imagined. But on bad days, you notice ad spends rising, driving minimal value, organic traffic dipping, or complaints from customers who clicked on an “official offer” that never came from you.   This is the reality for many performance marketers and affiliate program managers today. Affiliate marketing may be one of the most powerful growth channels for industries like ecommerce, fintech, and travel, etc. But it is also one of the most unpredictable if left unmonitored.   A single fraud affiliate can misuse your brand name, bid on your own keywords, or send traffic from unsafe domains, leaving you with inflated costs, lost revenue, and damaged brand credibility.  That is why the industry focus has now shifted to not just running affiliate campaigns but also monitoring affiliate performance closely.  Regulatory bodies like the Advertising Standards Council of India (ASCI) have been tightening disclosure norms and ad monitoring guidelines, signaling that brands are supposed to take complete accountability for how affiliates promote them.   Therefore, monitoring your affiliate ecosystem isn’t just a best practice anymore, it’s becoming the standard for sustainable growth.  So, here’s the big question: How do you keep affiliates in check without slowing down the performance they bring?  In this blog, we’ll walk through what a structured affiliate monitoring audit framework looks like and how brands can implement it to protect their budgets, brand reputation, and long-term growth.  Here’s What an Affiliate Monitoring Audit Checklist Looks Like  Affiliates often exploit loopholes to earn quick payouts using various affiliate fraud techniques like brand bidding, misuse of promo codes, duplicate listings, etc. To avoid this, we have curated an extensive affiliate monitoring audit checklist to help you evaluate your affiliate partner’s performance and take proactive decisions. Check out here:   1. Are affiliates using your brand assets and claiming to be your “official partner” without approval? Your brand name is your most valuable asset. Yet, some fraudulent affiliates often misuse it in ad copies, metadata, or promotional creatives to attract users without being directly associated with the brand. These unauthorized claims like “official partner” or misuse of logos not only confuse customers but also trigger legal complications.  How to audit and identify trademark violations:  Regularly scan ad copies, metadata, and landing pages for your brand name, variations, or misspellings.  Check that logos, product images, and creatives are only used with explicit brand approval.  Verify that affiliates don’t claim false associations like “official partner” unless authorized.  2. Do you often see other landing pages ranking on your brand keywords? Affiliates often bid on your brand keywords, driving up cost-per-click (CPC), hijacking search intent that anyway belongs to the brand organically. They also use techniques like typosquatting, like “Amazn deals” or “Flipkrt offers”, to divert users and earn commissions that eventually inflate your spend.  How to monitor affiliates for brand bidding:  Monitor search engines for affiliates brand bidding on your brand keywords.   Look for typosquatting errors and usage of competitor or brand keyword combinations.  Restrict affiliates from inflating CPCs by competing with your own campaigns.  Read this blog to know the signs you’re losing budget for unauthorized brand keyword bidding.  3. Are affiliates running campaigns using fake websites you don’t know about?  Fraudulent affiliates create lookalike websites resembling official sites (e.g., myntra-deals.in). Customers often mistake these for genuine pages, only to be scammed, amplifying further risks.  How to audit links for domain spoofing or IP squatting:  Identify lookalike or spoofed domains mimicking your brand (e.g., myntra-offers.in).  Audit affiliates to ensure all operating domains and subdomains are disclosed.  Prohibit the use of brand trademarks in domain names unless approved.  4. Do you find your brand ads placed on unsafe content websites? Affiliate ads sometimes end up on sites promoting adult content, gambling, drugs, or politically sensitive material. This misplacement not only harms the brand reputation but also leads to regulatory backlash.  How to audit unsafe affiliate ad placements:  Block affiliate traffic from adult, gambling, drug, piracy, or politically sensitive sites.  Use automated filters to prevent placements near hate speech, fake news, or unsafe content.  Continuously audit ad networks for brand-safe inventory.  5. Is your brand voice being manipulated with low-quality or AI-generated content?  Affiliates often generate content, blogs, reviews, or social media posts, to promote offers. But some use AI-generated text or plagiarized material, diluting brand voice and sometimes sharing misleading claims, creating confusion among customers.  How to monitor affiliate programs for content integrity:  Require affiliates to disclose AI-generated content.  Audit affiliate blogs, reviews, and posts for originality and compliance.  Prohibit plagiarism and ensure all content aligns with your brand voice and regulatory standards.  Learn how affiliates use AI-generated sites to game attribution models.  6. Are affiliate links exposing your users to malware sites or phishing attempts? Fraudsters exploit affiliate links through cloaking, forced redirects, or even malware injection. Customers may land on unsafe pages, creating cybersecurity threats and broken user journeys.  How to audit affiliate campaigns for unsafe linking practices:  Audit affiliate links for transparency and clarity (no cloaking, forced redirects, or hidden tracking).  Ensure links route only through secure, brand-approved channels.  Validate that links don’t lead to malware, phishing attempts, or unsafe redirects.  How do you enforce affiliate compliance and blacklist bad actors proactively? Affiliate fraud techniques are moving fast and adapting faster than most compliance teams. A one-time audit cannot prevent ongoing abuse. Without advanced enforcement and proof, even detected violations may continue.  How to enforce affiliate compliance:  Set up continuous monitoring for violations across ads, domains, and links.  Maintain an active blacklist of non-compliant affiliates, domains, and IPs.  Withhold payouts from affiliates breaching compliance rules.  Conduct quarterly audits to proactively identify risks.  How mFilterIt Helps Strengthen Your Affiliate Monitoring & Compliance Strategy  Running affiliate campaigns without continuous monitoring is like leaving your brand vulnerable to affiliate fraud activities. You may not notice the risk immediately, but affiliate campaigns,

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Leverage affiliate monitoring to prevent fraud & boost ROI

Affiliate Marketing Campaigns: Know How Smart Affiliate Monitoring Drives Growth

The global affiliate market continues to expand at an annual growth rate of nearly 8%, with brands investing heavily in affiliate programs to drive performance and reach new audiences.  But here’s the catch — rising spend doesn’t always equal rising returns.  As affiliate programs scale, the need for transparency and accountability across every click, install, and conversion has become critical. Consider this scenario: one affiliate is driving a surge in installs, but downstream conversions remain flat. Without evidence of what’s happening behind the scenes, how do you explain this performance gap — let alone fix it?  This is where the disconnect lies. Dashboards may glow with inflated numbers, yet real business impact lags. Budgets leak, brand reputation is put at risk, and marketers are left with more questions than answers.  To truly maximize the value of affiliate partnerships, brands need visibility into traffic quality, confidence in partner compliance, and the ability to direct spend toward affiliates that actually drive growth.  In this blog, we’ll unpack:  The most common affiliate fraud and violation techniques. Why traditional tracking often falls short.  How brands can safeguard ROI with deeper monitoring and smarter optimization.  The Blind Spots You Can’t Ignore: Common Affiliate Fraud and Violation Techniques Without active monitoring come hidden risks. As affiliate programs scale to include multiple partners, from influencers, coupon sites, and ad publishers, brands often lose visibility into where and how their campaigns are being run. And without visibility, small issues can quickly snowball into wasted budgets, poor-quality leads, and even damaged brand reputation.  Here are some common affiliate fraud techniques every marketer should know about, along with some real-world affiliate use cases detected by mFilterIt.  1. Brand Bidding A major blind spot is when affiliates bid on your branded keywords. In such cases, you end up paying for customers who would have anyway reached you organically.  Example: A user searches for a brand name on Google and clicks on a sponsored ad from an affiliate pretending to be the brand’s official site. This results in a commission payout for a user who would have converted anyway.      Watch for: Inflated CPCs on brand-specific keywords and affiliate-attributed conversions that come mainly from branded queries.  Impact: You end up paying twice, once for the ad and again for affiliate commissions, with no added value.  2. Ads Placed on Harmful Sites Sometimes affiliates place ads in environments that are completely misaligned with your brand values, such as adult sites, piracy platforms, MFA sites, or counterfeit marketplaces (in case of ecommerce brands).  Example: A family-oriented or financial service app being promoted via banner ads on explicit content sites, often completely unknown to the advertiser.      Watch for: Customer complaints or unexpected mentions of your brand in unsafe spaces.  Impact: Even one misplaced ad can damage years of earned trust, as audience perception is built basis the kind of content they see you besides.  3. Fraudulent Traffic Fake clicks, bots, or incentivized traffic spikes from unfamiliar geographies or domains inflate numbers while delivering zero business impact and making further optimizations even more difficult.  Example: An affiliate running click farms that generate thousands of automated clicks on ad campaigns, resulting in high engagement but no actual sales or customer value.  Watch for: Sudden spikes in traffic or leads from unusual locations or sources that don’t align with real customer behavior.  Impact: Fraud distorts performance data, wastes ad spend, and even manipulates further optimizations.  4. Trademark Violations Affiliates may misuse brand assets like trademarks, logo, images, tagline, etc, run ads in restricted regions, or push creatives that were never approved by the brand.  Example: An affiliate creates a fake offer banner using the brand’s official logo and runs display ads or push notifications directing users to another landing page.      Watch for: Sudden conversions from unrecognized sources.  Impact: It creates confusion and distrust among customers and weakens your brand message or identity.  5. Counterfeit & Fake Offers Some affiliates drive sales through tactics that attract one-time buyers using deceptive offers or counterfeit promotions with no repeat value.  Example: A cashback banner offering ₹200 cashback for downloading an app that actually provides no such benefit, causing consumer frustration and support complaints.        Watch for: Affiliates with high conversion rates but low repeat purchase or retention.  Impact: Your reports may look positive, but customer lifetime value (CLV) stays weak.  Why Traditional or Manual Checks Aren’t Enough? Affiliate payouts are based on performance. Marketers often rely on contracts, affiliate network agreements, and occasional audits to keep their programs in line. But in today’s real-time, ever-evolving digital ecosystem, and increasing use of AI, these safeguards fall short.  1. Contracts & T&Cs are reactive: They define what affiliates shouldn’t do but rarely prevent violations before damage occurs.  2. Manual audits are too slow: By the time discrepancies are spotted, affiliates may have already pocketed commissions and moved on.  3. Affiliates adapt quickly: What worked yesterday may already be replaced by new tactics designed to bypass outdated checks.  It is impossible to manually keep track of fraudulent tactics that affiliates use to earn commissions. That is why most brands are shifting towards a smarter data-driven affiliate monitoring strategy to safeguard their marketing budget and brand reputation before it hits the bottom line.  The Smarter Approach: Advantages of Using an Affiliate Monitoring Solution While self-audits help you identify surface-level red flags, they often fall short when it comes to detecting sophisticated affiliate fraud and ensuring long-term compliance. By combining automation, data intelligence, and compliance checks, it offers brands a smarter way to manage affiliates and protect investments. Key benefits to the brand are:  Enhanced Transparency – Clear visibility into affiliate activities and contributions.  Improved ROI – Optimize affiliate spending by focusing on genuine, high-performing partners.  Brand Protection – Safeguard brand reputation through compliance monitoring.  Market Competitiveness – Stay ahead of competitors by leveraging advanced fraud detection and compliance tools.  Regulatory Compliance – Ensure adherence to global and local regulations to avoid legal penalties.  How mFilterIt Helps: Affiliate

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brand-bidding-blog

Brand Bidding Monitoring: Improve Campaigns & Reduce CPC by 21%

Marketers spend heavily on building a brand presence both organically and with paid search campaigns. However, despite creating a holistic approach with well-crafted ads, optimized landing pages and targeted brand keywords, their efforts are giving desired results, and they see a high a cost-per-click (CPC). One of the causes can be bidding on branded keywords by competitors or even worse your affiliates or ad networks. And the surprising fact is that this scenario is quite a common practice. A well-known skincare brand recently faced similar challenges when they saw their CPCs skyrocket due to their ad networks partners outbidding them on their own branded keywords, impacting their profitability and scalability. In this blog, we’ll dive deep into the consequences of affiliate brand bidding and offer key takeaways for performance marketing managers running search campaigns on branded keywords. The Problem: Rising CPCs and Decreasing ROAS When you’re running a branded search campaign, you expect to see a high return on investment. After all, these are the keywords that directly relate to your brand name, so the traffic is highly relevant. But in many cases, what you don’t expect is for ad networks and fraudulent affiliates to target your branded keywords, pushing up the cost of each click and impacting the efficiency of your campaigns. This was the case for a leading skincare brand that faced inflated CPCs due to their partnered ad networks bidding on their branded keywords. As ad networks began competing for these highly intended branded keywords, the price of their own brand keywords became highly competitive, resulting in a 25-30% increase in CPCs, especially during high-demand periods like sales events. This not only eroded the brand’s profitability but also made it more difficult to scale their search efforts. The Impact of Brand Bidding on Ad Campaigns When ad networks or affiliates bid on your branded keywords, they effectively raise the bid price, driving up the cost of your own ads. Here’s why these matters: -Increased CPCs: Higher CPCs can eat into your budget, especially during high-demand sales periods when competition intensifies. A rise of 25-30% can drastically reduce the number of clicks you can afford and negatively affect your ad spend -Decreased ROAS: With higher CPCs, your ROAS takes a hit. You’re paying more for each click but not seeing the same level of return, making your campaigns less profitable and harder to scale. -Loss of Control: As ad networks and affiliates continuously bid on branded terms, brands lose control over their own brand’s visibility in search results. Their ads become buried beneath competitors, decreasing the chances of appearing at the top of search results and gaining quality traffic. -Sustainability Issues: Without addressing brand bidding, you may face challenges in scaling your search efforts. The higher your CPCs are, the more you spend to maintain performance, limiting your ability to expand your campaigns or reach new audiences. The Solution: Brand Protection and Proactive Monitoring In the case of this skincare brand, the solution lay in leveraging a holistic brand safety solution for affiliate campaigns that could monitor and restrict unauthorized bids on branded keywords. By partnering with mFilterIt, they were able to implement a comprehensive strategy to reclaim control over their search campaigns. Here’s how the solution worked: -Real-Time Detection: The brand protection solution identified competitor bids on branded keywords in real time, enabling the brand to take immediate action before their ad spend was impacted further. -Detailed Reporting: Regular, detailed reports provided the brand with visibility into where and when competitors were bidding on their keywords, giving them the opportunity to restrict such bids and prevent escalating CPCs. -Proactive Action: Armed with real-time data, the brand was able to act swiftly, limiting unnecessary costs and optimizing their campaigns to ensure maximum ROI. Key Results and Benefits: -Cost Reduction: After implementing the brand protection solution, the brand saw a 21% reduction in CPCs within just a month. During a peak sales period, the brand was able to optimize its search campaign and reduce unnecessary ad spend. – Enhanced ROAS: With the cost of clicks under control, the brand saw an increase in their ROAS, regaining profitability and improving their overall performance metrics. – Significant Savings: The brand saved close to ₹40,000 per day by preventing competitors from bidding on their branded keywords. These savings could then be reallocated to other marketing efforts, contributing to more sustainable growth. Takeaways for Performance Marketing Managers Running Branded Search Campaigns – Monitor Brand Keyword Bidding Regularly: You need to stay vigilant and constantly monitor your branded keywords. If you’re not tracking who is bidding on your brand keywords, you could be unknowingly inflating your costs. Regular monitoring ensures that you remain in control of your search budget. – Take Immediate Action Against Unauthorized Bidding: As soon as you detect that competitors or affiliates/ad networks are bidding on your branded keywords, take immediate action to restrict them. A proactive approach can help you minimize additional spending and protect your brand’s search visibility. – Leverage Brand Protection Tools: A brand protection solution provides the real-time insights and detailed reports necessary to effectively manage brand keyword bidding. These tools can help you act quickly, prevent unnecessary costs, and optimize your campaigns for better efficiency. – Understand the Impact of Rising CPCs on Scalability: As CPCs rise, your ability to scale campaigns becomes limited. If your search campaigns become too expensive, you may find it difficult to maintain the same level of growth. By managing brand bidding, you can keep CPCs in check and scale your campaigns more effectively. – Prioritize Sustainable Growth: High CPCs are not only a short-term issue—they can affect your long-term campaign sustainability. Addressing brand bidding issues early on allows you to allocate resources effectively, ensuring that your campaigns remain profitable over time. Way Forward Brand bidding is a silent campaign killer, but it doesn’t have to drain your ad spend or ruin your ROAS. By understanding the impact of competitor bids on your branded keywords and implementing proactive brand protection

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Ad-Fraud

Is Having OTP Validation Sufficient to Protect Your Brand Campaigns from Ad Fraud?

Brands run lead-generation campaigns to get people interested in their products/services. They often incorporate form submissions to acquire personal details for callbacks and address lead inquiries. In marketing terminology, a Single form submission is called a ‘punch-in. Brands frequently incorporate OTPs in such forms to validate that a human is submitting them. All industries, including BSFI, Ed-tech, OTT, E-com, Gaming, etc., are acquiring leads through form-filling and OTP validation. But unfortunately, fraudsters have found a method of OTP bypass. Fraudsters collate personal details of real users, such as names, phone numbers, email IDs, etc., from different sources. Fraudsters use bots to fill user information in forms and punch them as leads. Unfortunately, brands don’t realize whether the information was filled in by a BOT or by a genuine user. On the other hand, the advertiser assumes that an actual person filled the lead. As a result, the sales team contacts the lead to convert it into a potential customer. The unconsented call receiver gets irritated because the person was never interested in the brand to begin with. These are commonly referred to as ‘fake leads’. The consequences can be near fatal as ad budgets are drained without generating any ROI and the brand reputation is put at stake. Repercussions of OTP Bypass Cybercriminals use bots for bypassing OTPs and submitting forms. The brands connect with the actual user; however, the lead gets irritated because the submitted details were unconsented. Hence, a real person is no longer interested in the brand and wants to disassociate from it. Another disadvantage of OTP bypass is the loss of marketing budget to fraudsters. Cybercriminals use form-filling or lead-generation bots to submit the wrong user information. Alternatively, fraudsters even submit duplicate user information after altering names, surnames, and emails while keeping the same phone number. The permutation and combination of altering user information could be endless. As a result, brands waste valuable time and money connecting with “fake leads.” Brands lose valuable marketing budgets to fraudsters because they never vetted the traffic sources of their affiliates or used an ad fraud elimination solution like mFilterIt. Alternatively, they increase their marketing budgets to get high campaign performance which most likely leads to increasing the “cost-per-lead”. Fraudsters code bots to click ads and then visit a landing page for submitting forms. As a result, an additional drawback of form-filling bots is an exponential rise in click fraud. Moreover, cyber criminals hide their ongoing CVR, i.e., 100%, by continuously using sophisticated invalid traffic (SIVT) on ads during specific time intervals. The spiked traffic also transforms the click-to-visit and visit-to-conversion ratio into believable percentages. As a result, brands think that increasing the budget for the CPL campaign would help increase revenue. But, by doing so, they lose even higher amounts to fraudsters. Many cybercrime experts advocate two-factor authentication that can safeguard brands against form-filling bots. However, bypassing OTP during a CPL campaign for form submission eliminates this myth. Moreover, this is a severe breach as it is sent to a user’s device for a specific duration. Furthermore, it means that the fraudster has found a method to breach the “user device” and read the messages. Therefore, user safety is hampered and can even cause severe issues like ATO, as the fraudsters have device access and can reset passwords. Last year, OTP and message breaches had already happened in India and were reported in the news. So, brands facing such issues lose reputation and consumer trust, directly impacting revenue or growth opportunities. Moreover, these practices can diminish ad fraud but never eliminate it. Therefore, the need for an ad fraud elimination service provider like mFilterIt has risen drastically across continents. Here is an example of our exemplary work with a single client: Case Study of a BFSI Company One of our leading BFSI clients running regular performance campaigns involving product offerings became a victim of fake leads. The brand used multiple new landing pages/micro-sites based on the occasion’s theme, like festive campaigns, home loan campaigns, etc. Moreover, the client regularly ran diagnostic checks on their website; but they often failed to test the new landing pages.   Fraud affiliates took advantage of the loophole by doing high-volume lead punch-ins through OTP bypass. One of their methods involved filling multiple leads using a single device. These fraudulent activities substantially affected the campaign’s performance resulting in financial losses in terms of marketing spending happening to these ad fraud activities.   Our analysts have found that brands have witnessed 25-30% fraud in lead generation campaigns involving form submissions with OTP validation. The victims (brands) have lost nearly $130,000 or more through this fraud in a month.   mFilterIt helped the brand identify such fake leads and optimized the call center cost by helping the brand detect and eliminate fraud. After analyzing similar instances, we have found that the average monthly punched leads ratio across affiliates ranges from 28 to 42 percent. Moreover, we have witnessed that two types of lead punching are widespread: ● Basic Lead Punching Affiliates punch all leads from the same device and don’t change anything (cookies and properties). The average number of leads received from these devices in a month is ~4k from one device. ● Advanced Lead Punching Affiliates change device properties like cookie and IP but use the same device, and the repetition is as high as filling 400-500 leads/day from the same device. Conclusion Detecting loopholes in CPL campaigns is essential for preventing ad fraud. Moreover, brands can face significant drawbacks due to form-filling bots, which could easily be avoided by mFilterIt’s ad fraud elimination solution. The solution uses data science, AI, and ML for checking analytical anomalies and verifying fraud activities on the targeted landing pages. Moreover, brands receive real-time alerts as the solution works 24×7. Protecting the ad campaigns through mFilterIt’s ad fraud elimination solution can also offer advantages like more real leads, connection with real human traffic, higher revenue, etc., especially on CPL campaigns. Get in touch to learn more about the Ad Fraud.

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