Guide - mfilterit

Affiliate Growth vs Brand Infringement: How BFSI Brands in MENA Can Stay Protected

Guide, Brand Protection / mFilterIt Experts

The affiliate economy in the Middle East and Africa is scaling fast; valued at USD 370.24 million in 2024 and projected to grow at a CAGR of 7.7% through 2031. For BFSI brands, this isn’t just growth; it’s a fundamental shift in how customer acquisition happens. (Source) The numbers clearly indicate that affiliate partnerships and Direct Selling Agents (DSAs) have become foundational to BFSI growth across MENA. Yet, the same ecosystem driving acquisition can impact compliance posture and customer trust often without immediate visibility. Previously, we explained the factors polluting campaign metrics with a real analysis of campaign data. Read Here But fixing performance without addressing partnership risk is only a partial solution. Because even clean metrics can sit on top of brand impersonation or non-compliant messaging. In a region as vast, linguistically diverse, and fast-moving as MENA, these risks do not surface easily. They secretly slip into digital noise, adapt to local contexts, and scale faster than most teams can track using traditional methods. In this guide, we break down: How affiliates and DSAs can misuse marketing programs intentionally or otherwise How brand infringement in MENA is rising faster than most brands realize What BFSI brands must do to build visibility, control, and trust across their partner ecosystem How Affiliates Manipulate BFSI Campaigns and Attribution While the stats reflect brand’s reliance on affiliate programs, one thing that they cannot afford to ignore is the misuse of marketing programs by brand’s own partners. Some partners very strategically claim the conversions of traffic they did not influence on the first page. Here’s how it happens – Brand Bidding Violations Under brand bidding, brands bid on their keywords so that if users search for a product/service, their website ranks on search engine, making user journey to your website, seamless. In this, the core purpose of affiliates is to attract organic traffic to brand’s website that later converts and adds value to the revenue. However, many affiliates divert that organic traffic through brand bidding violations. These affiliates quietly bid on brand’s keywords causing two-fold impact on brand – First, it increases the cost of the brand’s keyword bids, making paid search campaigns more expensive. Second, it diverts traffic that was already likely to reach the brand organically, forcing the brand to pay twice for the same user, once through higher acquisition costs and again through affiliate commissions. Real World Use Case This is what we found in one brand’s case where an affiliate ad was running under brand’s name for a keyword the brand had already bid on. When a user clicks on the affiliate ad, they are redirected to the brand’s website through an affiliate link, allowing the affiliate to claim credit and commission for traffic that would have reached the brand organically. This is also called organic hijacking. Browser Extension Another method that affiliates opt to claim wrongful attribution is dropping cookies in user’s browser extensions. Here’s how it goes a user has an extension (like coupon or deal tools) that silently triggers affiliate link without user’s permission. Hence, if a user makes any purchase from brand’s website, this link attributes the purchase to that affiliate. How Brand Infringement Is Increasing Across MENA Brand infringement is yet another very crucial factor for BFSI brands that they cannot overlook especially in a sensitive area like MENA. In markets, where digital adoption is growing at an unprecedented pace, even a single instance of fake listings, impersonation, or misleading brand communication can have far-reaching consequences. Let’s know in what more ways the impact surrounds brands by creating a false angle around brand name. Fake social media handles Fraudsters create pages and profiles that closely mirror official brand accounts, matching names, logos, and messaging styles. These handles are used to push fake offers, fraudulent helpline numbers, and phishing attacks, misleading customers who engage in good faith believing they’re talking to the real brand. Real world use case Suspicious social media handle of renowned bank of Dubai was discovered on Facebook where fraudsters were manipulating customers by using bank’s digital assets. APK copycat apps Cloned mobile apps replicate a brand’s interface, name, and user experience to deceive users into downloading them. Distributed outside official app stores, these fake APKs are used to steal login credentials, financial information, and sensitive personal data, posing a serious risk in markets where mobile is the primary touchpoint. Phishing websites Lookalike websites replicate official pages and login portals with enough accuracy to deceive users who aren’t scrutinising every detail. A minor domain variation is often sufficient. For BFSI brands especially, where customers routinely submit sensitive data through digital forms, the damage from a single phishing attack can be swift and far-reaching. Logo misuse Unauthorised use of brand logos and visual assets across rogue websites, affiliate pages, and social platforms lends false credibility to scams and fraudulent promotions. The familiar look is enough to make a scheme appear legitimate at first glance and repeated misuse gradually erodes the trademark’s legal strength and brand reputation. Deepfakes and Synthetic identities AI-generated videos, cloned voices, and fabricated identities are now being used by fraudsters for brand impersonation where these synthetic personas spread false investment advice, fake announcements, and scam communications at scale and by the time the content is debunked, the reputational damage is already done. Misinformation and fake narratives False claims, fabricated complaints, and manipulated stories about a brand can spread across digital channels faster than any correction can follow. For BFSI brands, misinformation around policy changes, rate updates, or security incidents can significantly dent public trust and algorithms keep surfacing these narratives long after they’ve been disproved. For BFSI brands, where trust is the foundation of every customer relationship, any misdirect can invite irrecoverable repercussions. The stats below highlight exactly this, the severity of brand infringement in MENA – 48% of infringement cases lead to revenue loss across BFSI and ecommerce sectors 72% of consumers lose trust after encountering fake or misleading brand content 7 in 10 MENA consumers hold the brand responsible, not the platform, for counterfeit or scam listings These numbers highlight a simple but important reality: consumers rarely separate the platform from the brand being impersonated. When they come across fraudulent or misleading content, the loss of trust is directed at the brand itself. What BFSI Brands Must Do to Bring Transparency in Affiliate Ecosystem The reality is this: partnerships aren’t the problem; blind spots are. Brands today are walking a tightrope. On one

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What Are Performance Max Campaigns? Are They Vulnerable to Ad Fraud?

Guide, Ad Traffic Validation / Jyoti Kalra

Google positioned Performance Max campaigns as a way to simplify campaign management for marketers. But it also created new areas that can be exploited if not monitored closely. One campaign covered every Google channel. The AI handles everything from where your ads show up, who see them, how much you bid, to which creative runs where. You just goal, upload your assets , and let AI do the rest. And honestly, Performance Max made running ads across Search, Display, YouTube, Gmail, Discovery, and Shopping genuinely simpler. Marketers moved their budgets in, trusted the system, and watched the reach numbers grow. But here’s the red flag nobody talks about enough: when you hand everything over to an AI, you also hand over your ability to see what’s really going on. Not being able to see what’s happening with your money is exactly the kind of gap that fraudsters exploit. Therefore, every performance marketer needs to understand how ad fraud impacts performance max campaigns, what it costs, and what you can do about it. What Are Performance Max Campaigns? Before we move to the ad fraud side, let’s talk about Performance Max campaigns and how it works. In a regular Google campaign, you can pick your placements, adjust bids by audience, and control where your budget goes. On the other hand, Performance Max is a type of Google campaign where you provide your ad creatives (images, videos, headlines, text), your target goals (like getting leads or sales), and some hints about who your audience might be. From there, Google’s AI takes over completely. It decides which ads to show, who to show them to, on which platform, at what price, and in what format. This is where the problem begins. AI learns from the signals it receives, clicks, form fills, and conversions. If the signals come from real people genuinely interested in your product, great. But what if they’re coming from bots and fake traffic sources? The AI doesn’t know the difference. It just sees activity and calls it “performance.” This is what people mean when they call performance max a “black box.” In traditional programmatic advertising, if brands deal with invalid traffic, across Search, mobile, and display channels, marketers have access to tools that surface placement data, flag suspicious traffic, and allow manual intervention. However, in the case of performance max campaigns, much of that visibility is not even available. Hence, ad fraud slips in. How Ad Fraud Happens in Performance Max Campaigns? One of the most important things to understand about ad fraud in performance max campaigns is that it isn’t limited to a single stage or technique. Ad fraud occurs at every level, from the moment your ad loads to the moment a “lead” is generated. And with automation in place, here’s what the fraud risks actually look like: Ad placements that put your brand at risk Automated placement decisions often send ads on MFA sites, placing ads besides adult content, piracy sites, or hate speech networks. Such sites exist purely to inflate ad impressions and earn revenue from advertisers. They have little to no real content, but generate a huge amount of impressions or clicks coming from low-intent users or bot traffic. Moreover, bots mimic real user behaviour and visit websites (even low-quality websites). This means your ad “loads” on a page, but no real human ever sees it. The result? Inflated reach metrics, misplaced ads, compromised brand safety, distorted frequency data, and a campaign algorithm that gets trained on fake signals. Clicks that drain your budget but are not high intent & don’t convert Click fraud is one of the most common types of ad fraud that performance campaigns are vulnerable to. It happens when clicks on your ads come from click farms, competitors trying to drain your budget , accidental clicks on display ads, or automated bots generating large volumes of invalid traffic. The impact is twofold. First, every invalid click directly wastes your ad spend without delivering any real value. Second, it misleads the algorithm. These fake clicks make poor-quality traffic sources appear effective, causing the system to allocate more budget toward them, hurting campaign performance even further. Fake journeys, visits, and leads that distort entire campaign metrics Visit and lead fraud causes the most downstream damage. Sophisticated bots are now programmed to simulate the complete conversion journey. They click on ads, land on pages, browse content, and submit lead forms. This generates fake leads that appear legitimate in reporting. The more conversion fraud goes undetected, the more your campaign AI actively optimizes toward the sources producing it, pulling spend away from placements that might actually reach real people. The damage here is threefold: ad budget is spent acquiring fake leads, sales teams waste time chasing non-existent prospects, and the CRM is polluted with junk data that corrupts future targeting. Furthermore, every fake conversion further trains the Pmax campaign algorithm to optimize toward the traffic sources generating them. What the Data Shows: Performance Max Campaigns Have Nearly Double the Fake Traffic of Google Search You don’t just have to take our word for it. We measured it. Based on our analysis of ad fraud and invalid traffic (IVT) across all major Google campaign types revealed a clear pattern – Performance max is the most vulnerable to bot-driven traffic, with the highest IVT% observed among all channels. Google Search, the channel most associated with high-intent, human-driven traffic, recorded 11% invalid traffic rate and an 8% invalid lead fraud. Google Discovery at 17% invalid traffic and Google Display Network at 18%. In the case of Google PMax, a 24% invalid traffic rate and a 14% invalid lead rate were recorded. This means nearly 1 in 4 visits generated by PMax was non-human traffic. And 1 in 7 leads generated by PMax were fraudulent. Despite generating less than half the total visit volume of Google Search (65,204 vs 1,40,875), the performance max campaign produced almost the same absolute volume of invalid visits — 15,871 vs 15,980. This shows the ad fraud density in PMax is nearly double that of Search. It isn’t just the most fraud-vulnerable channel; it is an outsized contributor to total invalid traffic in absolute terms. Where PMax Traffic Actually Comes From & Why It Matters To really understand why performance max campaigns are so vulnerable to ad fraud, you need to look at where its ad traffic is actually coming from. When we analyzed the internal channel distribution within a PMax campaign, here’s what it revealed. A large majority of the traffic didn’t come from high-intent environments like Search. Instead, it came from channels designed for scale. Over 80% of PMax traffic was driven by Google Display Network (GDN) and Discovery. These channels are built for reach. They offer lower CPCs and broader inventory, which makes them attractive for algorithms trying to maximize volume. But they also carry a much higher exposure to low-quality

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FY Closing Checklist: Are You Auditing Ad Fraud Media Waste Before Budget Reset?

Guide, Ad Traffic Validation / mFilterIt Experts

It’s that time of year again. Finance wants numbers. Leadership wants plans. And marketing teams across the country are doing what they do every time during financial year close: reviewing channel spends, comparing ROAS across platforms, and deciding where next year’s budget should go. But here’s what most of those budget conversations skip. Channel-level reporting tells you what you spent. It doesn’t tell you whether any of it actually worked the way you think it did. The uncomfortable reality is that media waste doesn’t happen only in bad channel choices or poorly targeted campaigns. It happens at every stage of the funnel: Impressions served but never seen Clicks generated by bots or non-intent traffic Visits that never engage Conversions that were misattributed or would have happened organically (Source: Statista) This means a vast majority of media advertising budget wastage, and ad fraud is invisible without deliberate, layer-by-layer auditing. As you close the financial year and plan for FY 2026, the most important question is not just where to spend more, but where your budget may already be leaking. The Full-Funnel Media Waste Audit Checklist To ensure your next year’s budget is based on reliable performance data, marketers should audit campaigns across four key stages: Impressions (Reach & visibility) Clicks (Traffic quality) Visits/Installs (Real engagement) Events/Conversions (True business outcomes) Below is a structured financial-year closing audit checklist for each stage. Impressions & Reach Stage You Paid for Reach. But Did Real People See It? Impressions are hardest to tie to outcomes and often get ignored while auditing ad traffic. It is because an ad delivered is often considered to have been viewed. As per IAB viewability standards, if a static ad is visible on the screen for a continuous one second, the impression is counted as served. However, delivered is not the same as seen. And seen is not the same as seen by the right person, in the right place, at the right moment. If you’re not actively auditing where your impressions are going, which placements, which audiences, which environments, you’re not running a branding campaign. You are just running a reach report. What Advertising Budget Waste Looks Like At The Impression Stage Invalid Traffic (IVT): Bot-generated impressions consuming budget and reporting as delivered. Viewability failures: Ads technically served but never actually in-view by humans. Brand safety violations: Impressions delivered in unsafe or irrelevant content environments. Pixel stuffing: Multiple ads hidden within a single placement or tiny pixel, generating impressions that users never actually see. Ad stacking: Multiple ads layered on top of each other in a single placement, with only the top ad visible while all register impressions. Audience mismatch: Impressions served outside your target demographic, geography, or intent band. Frequency breaches: Ads repeatedly served to the same users beyond frequency caps; inflating impression counts without increasing incremental reach. Made-for-Advertising (MFA) sites: Low-quality publisher sites designed primarily togenerate ad impressions rather than genuine user engagement. Know why brands need to go beyond viewability in details here. Here’s what we saw in one of the campaign audits for a FMCG brand A full-funnel audit conducted on an FMCG brand campaign running across placements over a four-week period, revealed something that the campaign dashboard simply wasn’t showing. At first, the numbers looked fine. Impressions in the millions, a 1.43% CTR, and IVT at 3.4%. But the real signal was buried in the visit-to-click ratio: of every 100 clicks recorded, fewer than 48 resulted in an actual website visit. More than half the clicks were going nowhere. Digging deeper into placement-level data made the picture significantly worse. Out of 4,859 total placements generating impressions, 92.98% of placements generated zero clicks further. Placement-Wise Breakdown Total Placements Active 4,859 across the campaign Placements with ZERO clicks 4,518 placements — 92.98% of all placements Impressions on zero-click placements 2,55,808 impressions completely wasted Good placements (11 only) Delivered 1,25,15,646 impressions (1.69% CTR) Placements with low VTC ratio 169 placements with only 17.88% visit conversion Moreover, some of these were structurally incapable of generating visits, screensaver apps and set-top-box interfaces where a user has no ability to click through to a website. What a programmatic campaign audit revealed for an energy sector brand A near-identical pattern emerged in a programmatic campaign run by a global energy sector brand across two major programmatic advertising platforms. The brand was running audio and display campaigns to boost visibility and audience reach. Reach and engagement metrics were low, but nothing on either platform dashboard was flagging why. After ad traffic analysis at the placement level across both platforms, here’s what the gap between the two platforms revealed. On Platform A, 11% of all traffic was invalid, with invalid geo as the dominant ad fraud type at 8.06%, meaning a significant portion of clicks was being attributed to the wrong geographies entirely. On Platform B, 38% overall IVT, led by IP Bot Repeat at 22.90%. More than a third of all programmatic budget on that platform was generating zero genuine human engagement. Furthermore, impression fraud didn’t stop at traffic quality. Brand safety violations compounded the financial waste with reputational risk. Ads were actively serving beside arms & ammunition content, generating 16% of impressions, and in a four-ad-stacked placement, absorbing 38% of impressions in a single cluttered slot where no user could meaningfully engage with any of the four ads. Neither violation was visible on the platform’s own reporting. The audit trigger questions advertisers must ask before the financial year closes ✓ Do you have a third-party verified viewability rate and attention metrics of each campaign, not just what the platform reports? ✓ What was your IVT % on programmatic inventory, and was it measured post-bid? ✓ Have you pulled a placement-level report showing click and visit performance by placement? ✓ Do you know which placements are structurally incapable of delivering website traffic? ✓ Were brand safety inclusion/exclusion lists active from campaign launch — not added mid-flight? Click Stage Your CTR Looks Fine. But Who’s Actually Clicking? Advertising budget wastage and ad

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The Most Defrauded and Exposed: Ad Fraud and Brand Safety Risks for BFSI Brands in MENA

Ad Traffic Validation, Guide / mFilterIt Experts

Of the $114 billion projected to be lost to ad fraud globally in 2025, financial services bear a disproportionate burden. In the GCC alone, the sector carries an invalid traffic rate of 11.34%, the second highest of any industry. And that’s a conservative estimate. For most industries, that’s an efficiency problem. For BFSI, it’s a threat to the integrity of financial decision-making. A fraudulent lead isn’t just wasted spend; it’s a corrupted data point that can skew risk models, influence credit decisions, and trigger compliance exposure. In MENA, the risk compounds further. Digital ads spend is scaling faster than measurement and transparency standards, making it easier for fraud to go undetected and harder for brands to trust their own numbers. The question isn’t whether ad fraud exists in your campaigns. It’s whether your growth is built on verified performance or inflated figures. This guide covers: Ad fraud in branding and performance marketing: How it infiltrates your funnel The impact of ad fraud on BFSI campaigns: Why the stakes are higher here than anywhere else Why full-funnel protection is no longer optional in 2026 Ad Fraud in Branding and Performance Marketing: How It Infiltrates Your Funnel Brands believing that ad fraud can be controlled with the surface level checks are still stuck in the loop of myths that are standing on the face of their branding and performance campaigns. As soon as these myths exists, the campaign performance will keep on suffering the most and the real threat will skip every single time. So, to keep your marketing efforts intact, the first thing to do is to bust the myths and face the reality – Myth 1 – Walled Gardens Automatically Deliver Clean Traffic What marketers believe: Closed ecosystems mean better fraud control. Platform signals handle quality checks, so traffic is assumed to be safer even with limited transparency. What actually happens: Traffic quality is largely reported by the platform itself. Invalid traffic often blends into aggregated data, and limited visibility makes fraud harder to detect early. The graph above has visit counts on y-axis and 7 days dates on x-axis. The visit counts from 13/12/2020 to 16/12/2020 reached to 600+. This also symbols identical hourly patterns (28-30 visits every hour), indicating that bot traffic has entered in your campaigns. What this can lead to: This can lead to invalid or bot traffic going unnoticed, inflating clicks and engagement metrics. As a result, marketers may make decisions based on misleading performance data and end up spending budgets on low-quality traffic. Myth 2 – Pmax Guarantees Performance And Brand-Safe Placements What marketers believe: PMax is a powerful, automated campaign type that finds the best placements across Google’s inventory while maintaining performance and brand safety. What actually happens: PMax operates like a black box. Marketers have limited visibility into: Which placements are driving real clicks The actual sources of leads (Search, Display, YouTube, etc.) How much traffic comes from brand searches you already own What this can lead to: Cheaper clicks, heavy reliance on brand queries, and returning users you may have acquired anyway. It can also pollute remarketing audiences. This can also give a false idea of strong ROAS but when dived deeper, traffic could be recycled or of low-quality. Myth 3 – Premium Publishers Mean Lower Fraud What marketers believe: Higher CPMs and premium inventory mean better filtering and more genuine users. What actually happens: With advanced bots and AI-driven traffic, fraudulent activity can closely mimic real user behavior even on premium sites. High CPMs don’t always guarantee high-quality traffic. What this can lead to: Apart from monetary losses including wasted marketing budgets, it also builds a false confidence in “premium” inventories. Myth 4 – Bots Are Easy To Detect What marketers believe: Fraud or invalid traffic shows clear, abnormal patterns in the funnel, making it easy to identify and filter out. What actually happens: Sophisticated bots are designed to ditch the advanced solutions with complex behavioral patterns including clicking ads and even moving through parts of the funnel. What this can lead to: Inflated clicks and engagement metrics and optimization of wrong channels that give an illusion of “fine campaign performance.” Myth 5 – High Time On Site Means High User Intent What marketers believe: Longer sessions indicate stronger interest. More time on the website is often treated as a clear signal of user quality and intent. What actually happens: Session duration alone doesn’t always reflect genuine engagement. Automated scripts or passive browsing can artificially increase time on site. What this can lead to: Overestimation of user interest and engagement. This also makes segregation between genuine user and bot traffic, harder than ever. Myth 6 – If I Pay For Verified Leads, My Campaign Is Safe What marketers believe: Verified leads mean clean leads. OTP verification is often seen as enough to confirm authenticity and quality. What actually happens: Lead verification only confirms that a form was submitted, it doesn’t guarantee genuine user intent or relevance. What this can lead to: Punched Leads – Lead forms are filled forcefully using repeated or irrelevant data to quickly meet targets. In this graph, we can see lead punching where lead concentration rises abnormally during specific hours of the day. Fake Leads – Entirely fabricated data is filled in lead forms that includes false, non-existent, or stolen information. Non-prioritized Leads – Low-quality or irrelevant leads that do not match the brand’s target audience or intent. Myth 7 – Paying For Down-The-Funnel Events Eliminates Fraud What marketers believe: Fraud usually happens at the install stage. Once users complete actions after install, those signals are considered genuine. What actually happens: Post-install events can also be manipulated. Fraudsters can fake events or mimic user activity like fake signups to make traffic look high quality. This type of fraud is also triggered by incentivized users who are paid to perform soft KPIs What this can lead to: Fake users completing scripted actions to look genuine and lower ROAS despite strong numbers. Myth 8 – Brand

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Ecommerce Analytics: How MENA Quick Commerce Brands Can Win On Digital Shelf

Guide, Digital Commerce Intelligence / mFilterIt Experts

Ramadan reshapes daily life in the MENA region, and quick commerce brands feel the impact instantly. It is a period of cultural reset – daily routines change, eating schedules shift, social gatherings become more frequent than usual, and everyone plans their days around Iftar and late-night meals. This further changes how people shop, especially on ecommerce platforms. They expect deliveries in minutes, not hours or days. But speed is not the only thing that matters at this time. During Ramadan, quick commerce platforms become a necessity. Consumers rely on these platforms to solve real, time-sensitive problems such as a forgotten ingredient just before Iftar, get-together needs at home, or a last-minute need that cannot wait until the next day. In these moments, shoppers mostly buy the first product they see. This is where the pressure of being visible and available at the right time starts to build. The demand is high, and the margin for error is very low. So, the real question is – how do you ensure that your brands bags in those last-minute sales? This is where winning or losing the Ramadan sales opportunity actually happens — on the digital shelf, in real time. And that’s exactly what this guide is about: How Ramadan reshapes quick commerce shopping behaviour Operational challenges for brands across pricing, availability, visibility, and shelf performance What it truly takes to win on the digital shelf A practical Ramadan-to-Eid execution roadmap How mFilterIt’s ecommerce analytics tool enables real-time monitoring and action A case study on improving platform presence for a global F&B brand in MENA Consumer Behaviour Trends During Ramadan for Brands in MENA Success during Ramadan is more about how shoppers experience your digital shelf in moments of urgency. Therefore, it is important for quick commerce brands to understand these behavioral shifts to stay visible on the digital shelf. 1. Many shoppers install and engage with apps before Ramadan begins App install and engagement data consistently show a lift in acquisition activity in the weeks leading up to Ramadan as consumers prepare for the month; these pre-season cohorts often convert to higher LTV than users acquired mid-Ramadan. That makes early, targeted user acquisition and retention work a high-leverage play. 2. Consumers shop in short, high-intent bursts During Ramadan, consumers don’t open apps to browse endlessly and discover new brands. They come with a clear purpose and specific immediate needs. These shopping sessions are short, decisive, and highly concentrated around certain hours of the day. Post-iftar and late-night windows see sharp spikes in traffic, but they also come with heightened expectations. Shoppers want to find what they need quickly and confirm availability instantly. Any delay in discovery or confusion on the product page increases the likelihood of abandonment. For quick commerce brands, this means the digital shelf must perform at its best during these narrow windows. Visibility during off-peak hours matters far less than being present and easy to choose when intent is highest. 3. Already familiar brands feel safer During Ramadan or mid-Ramadan, shoppers are generally less inclined to experiment with new brands or unfamiliar products, especially when purchasing food, beverages, or essentials tied to family meals and hosting. On quick commerce platforms, this translates into a stronger pull toward brands that shoppers already recognize and trust. Listings that feel unfamiliar, poorly presented, or inconsistent are more likely to be skipped, even if the price is attractive. This means ecommerce brands need to pay extra attention to maintaining a strong, consistent presence on the digital shelf 4. Trust signals matter to drive conversions Industry studies show delivery performance and up-to-date reviews strongly influence purchase intent. In the Ramadan context, a product that appears slightly more expensive but clearly available, well-rated, and deliverable within the required timeframe often wins over a cheaper option that feels uncertain, because shoppers optimize for certainty. Brands should surface these signals prominently on the product card. They act as shortcuts in decision-making, helping consumers choose quickly without second-guessing. 5. Late-night shopping windows take the lead Ramadan turns nights into the busiest commerce window. Multiple regional analyses show a spike in app sessions and orders after iftar and through the late night (roughly 8 pm – 3 am), with particularly sharp activity around the hour after iftar and the pre-suhoor window. If your dark-store coverage or push-timing isn’t aligned to these hours, you risk missing the moment. 6. Category mix shifts – groceries, gifting and wellness surge Quick commerce demands extend beyond groceries during this time. While essentials like food ingredients and beverages continue to drive volume, there is a noticeable rise in gifting, wellness, and hosting-related purchases. Consumers look for convenient solutions such as curated iftar bundles, premium food items, desserts, dates, beverages, and personal care or wellness products linked to self-care routines during the month. This shift also fuels impulse buying, especially when bundles or ready-to-order packs are easily discoverable on the platform. For quick commerce brands, this means assortment planning cannot focus on staples alone. Pairing high-frequency essentials with gifting-friendly and occasion-led SKUs helps capture incremental demand that peaks throughout Ramadan, not just at mealtimes. Operational Challenges Quick Commerce Brands Face During Ramadan As demand compresses into narrow windows and consumer expectations rise, even small operational gaps surface quickly. Here are some of the operational challenges quick commerce brands face to stay relevant on the digital shelf during peak times like Ramadan: Products go out of stock in specific locations during peak demand periods Availability is the most critical element of quick commerce performance during Ramadan or any high-demand period. 1. Location-level out of stock issues during peak windows Products may be available centrally, but go out of stock at specific dark stores or delivery zones just before iftar or late at night. 2. Delayed visibility into stock gaps Teams often discover availability issues only after sales decline, leaving no time to recover lost demand. 3. Lost sales due to competitors When primary SKUs are unavailable, shoppers immediately switch to substitutes or competing brands, often

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CLICK FRAUD PREVENTION - AI FOR FRAUD DETECTION

Click Fraud: The Complete Guide for Marketers in 2026

Guide, Ad Traffic Validation / mFilterIt Experts

A few years ago, a globally recognised brand cut two-thirds of its annual online advertising budget around $100 million. What happened next revealed a shocking truth about the digital advertising industry. There was little to no drop in performance. Conversions held steady, demand didn’t collapse, and the business continued as usual. The reason wasn’t efficiency; it was ad fraud and the brand that showed the mirror to the world was Uber. Fast forward to 2026, and the problem has only become more complex. If you are investing in paid media in 2026, it’s important to know that your PPC campaigns may already be exposed to highly sophisticated fraud tactics, many of them powered by advancements in AI. What once started as a side effect of digital advertising has now evolved into a deeply embedded part of the ecosystem marketers operate in today. According to the recent Imperva report, automated traffic surpassed human activity for the first time in a decade, accounting for 51% of all web traffic in 2024. This surge has been driven by the rapid adoption of AI and large language models (LLMs), which have made bot creation easier, cheaper, and far more scalable. The challenge is even more pronounced in PPC campaigns within walled gardens, where limited transparency and closed ecosystems make fraud harder to detect. This click fraud guide serves as a practical framework to help you understand how modern click fraud works and how to act against it effectively. What is Click Fraud Click fraud is a fraudulent practice of triggering repeated clicks on online advertisements to give a false idea of performance (augmented number of impressions and clicks), generating unfair revenue for publishers and draining budgets of advertisers allocated to PPC campaigns ad budgets of advertisers. To generate fake clicks, fraudsters put bots in action or hire low-paid workers to click on ads repeatedly. The problem becomes bigger in affiliate campaigns when brands trust their affiliates. but they become the one causing major attribution problem through simpler and sophisticated fraud tactics that we are going to cover further. Types of Click Fraud Click fraud is broadly classified into two main categories, both aimed at creating a false sense of campaign performance. For brands running PPC campaigns across web and app environments, fraud can occur at every level, sometimes in obvious, low-effort forms, and other times through highly sophisticated methods that closely mimic real user behavior. Following are some of the common click fraud types – Click Farms Click farms use large groups of low-paid workers who are instructed to manually click on ads or perform specific actions like visiting a page for a fixed time or installing an app. Since real people carry out these activities, the traffic looks more genuine than bot traffic and can easily slip past basic fraud detection systems. Competitor Clicks In this type of fraud, competitors intentionally click on your ads to drain your advertising budget and reduce your campaign’s effectiveness. These repeated, non-genuine clicks increase costs without any real intent to convert, pushing your ads out of auctions faster and lowering overall ROI. Advanced Click Fraud Fraud used to be easy to spot—repetitive patterns, sudden spikes, and low-quality traffic. But AI has changed the click fraud landscape. Now, bots can mimic real users and generate fake clicks in web and app campaigns. Bots can now mimic real users, triggering fake clicks across paid campaigns in web and app environments. In fact, reports show bot activity has risen for the sixth consecutive year, with 37% of all internet traffic now being bot driven. Following are the tactics through which bots trigger fake clicks – Headless Browser Bots These are advanced bots that operate within real browser environments, allowing them to behave like human users. They can scroll pages, click ads, and spend time on sites, making their activity difficult to distinguish from genuine traffic and harder for basic fraud tools to detect. Click Injection In click injection fraud, advanced bots trigger a fake “last click” on a user’s device just moments before an app is installed. This tactic mainly targets app campaigns, where the fraudster steals the credit for the install, even though they played no real role in driving the user to install the app. Botnets Botnets are large networks of infected devices controlled remotely by fraudsters. These devices generate fake clicks, installs, or impressions from different IP addresses, locations, and devices, making the traffic appear distributed and legitimate. Incent Fraud Here, users are rewarded with points, money, or other benefits for clicking ads, installing apps, or completing tasks, attracting incentivized traffic. While real users are involved, they have no genuine interest in the brand, leading to low-quality traffic and poor conversion outcomes. Read in detail about incent fraud and its impact Domain Spoofing In domain spoofing, bots disguise low-quality or fraudulent websites as well-known, trusted domains. This makes the traffic appear premium, misleading advertisers into paying higher prices for inventory that has little or no real value. Read in detail about how AI enables fraud and yet AI is the only defense How Click Fraud Impacts Advertisers? The impact of click fraud is not limited to merely one aspect of marketing funnel, it extends beyond that impacting the entire funnel. Following are the ways in which it largely impacts advertisers – Ad budget is consumed by fake clicks Money is spent on bots or hired click farms instead of real users. For example, a campaign with a ₹1,000 daily budget may exhaust it by noon due to fraudulent clicks, stopping ads from reaching genuine prospects later in the day. Cost-per-click (CPC) increases artificially Repeated fake clicks raise competition signals in ad auctions, pushing CPCs higher. Advertisers end up paying more for the same keywords without any improvement in conversions. Sales teams chase fake or low-quality leads Click fraud often generates invalid leads or empty form fills. Sales teams spend time calling numbers that don’t connect or emails that never respond, reducing productivity. Geographic and device targeting get distorted Bots often operate from specific locations or devices. Advertisers may mistakenly block or scale down regions or audiences that appear “low quality” but are actually victims of fraud traffic. Reduced ROI and campaign scalability Even high-intent campaigns fail to scale because fraud eats incremental budget. Performance plateaus not due to market saturation, but due to invalid traffic. Bottom of the Funnel Impact of Click Fraud The entire marketing funnels comes under attack when click fraud happens and its bottom of the funnel impact is much more distorted – High CTR,

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Holiday Safety Playbook for Marketers Spending on Affiliates

Guide, Ad Traffic Validation / mFilterIt Experts

The holiday season is the biggest time for the year when campaigns scale fast, budgets expand, and every click counts. Brands prepare months in advance to capture the surge in consumer intent, aiming to convert festive enthusiasm into measurable ROI. Affiliate marketing campaigns play a key role in this strategy, with brands amplifying their reach, boosting app installs, and attracting high-intent shoppers through affiliate partnerships. In fact, the US affiliate market is valued at 11.53 billion in 2025 and is anticipated to grow at CAGR of 11.08%. This explosive growth shows how integral affiliate partnerships have become for digital marketing success, connecting brands with millions of potential customers. But with scale comes risk. As affiliate traffic surges, so does the volume of invalid or fraudulent activity that hides within it. Many brands see higher traffic but unchanged conversions, a clear signal that all that “activity” isn’t coming from real users. That’s where ad traffic validation at all levels becomes essential. In this guide, we will cover – What is affiliate fraud? Impact of affiliate fraud during the holiday season How can full-funnel ad traffic validation safeguard brand this holiday season? Frequently Asked Questions (FAQs) Conclusion What is Affiliate Fraud? Affiliate fraud is when some affiliates perform any illegitimate activity to drive up numbers and generate commission from the inflated metrics. It spoils the campaign metrics and ROAS, especially during the holiday season, when it matters the most. This can occur due to any method of fraud, including fake leads, repeated leads, etc. How Holiday Affiliate Fraud Impacts Performance Affiliate fraud spikes during the holiday season as both customer activity and affiliate partnerships surge, with brands competing to capture maximum attention. Let’s look at how this impacts affiliate marketing campaigns and the common types of fraud that tend to peak during this time. 1. Surge in Budgets and Campaign Volume a. Why fraud rises: During the holidays, brands spend more and launch bigger campaigns. With so much traffic and so many clicks coming in, it becomes easier for fraudsters to hide fake activity. b. Common fraud types: Fake clicks (known as click spamming or click injection), and brand keyword hijacking. c. How it happens: Fraudsters use bots or click farms to generate thousands of fake clicks or inject clicks just before a real app install, stealing credit from genuine affiliates. Some even bid on your brand name in search ads to capture users looking for you. d. Impact: Brands end up paying for fake traffic, face inflated costs per click (CPC), and see misleading data on engagement and conversions, paying more but getting less real performance. 2. Rush to Onboard New Affiliates a. Why fraud rises: As brands try to scale fast, they onboard new affiliates quickly, sometimes without proper checks. Fraudsters use this rush to sneak in as “legit” partners. b. Common fraud types: Coupon misuse, referral fraud, fake conversions, and brand keyword hijacking. c. How it happens: New or unverified affiliates may create multiple fake accounts, share discount codes widely, or run unauthorized ads using your brand name. d. Impact: You end up paying fraudulent commissions, your CPC spikes unexpectedly, and your brand message appears in places you never approved. Read in detail about referral and coupon fraud 3. Incentive-Driven Campaigns Become Fraud Magnets a. Why fraud rises: High cashback offers, discounts, or referral bonuses attract not just customers but also opportunists. b. Common fraud types: Coupon fraud, referral fraud, and fake conversions. c. How it happens: Fraudsters or bots create fake accounts to repeatedly use referral links or coupon codes. Some even set up “install farms” to fake app installs just to earn rewards. d. Impact: You attract a flood of low-quality users who rarely return, damaging long-term retention and skewing your success metrics. 4. Attribution Manipulation Peaks a. Why fraud rises: Holiday campaigns offer higher payouts, so fraudsters compete to take credit for the “last click” that leads to a conversion. b. Common fraud types: Click injection, and click spamming, also organic hijacking c. How it happens: Fraudsters trigger fake clicks right before a user installs your app, making it look like they caused the conversion. d. Impact: Real affiliates lose credit, your optimization decisions become inaccurate, and marketing spend shifts toward bad traffic sources. 5. More Sophisticated Automation Attacks a. Why fraud rises: Fraudsters use advanced bots that can imitate real users during high-traffic seasons. b. Common fraud types: Fake clicks, fake signups, and automated referral abuse. c. How it happens: They use tools like “headless browsers” (bots that act like real browsers without showing a screen) or emulators to mimic user actions like clicking ads or filling forms. d. Impact: Your analytics fill with fake data, increasing payouts to dishonest affiliates and making performance reports unreliable. 6. Masked Fraud in High Volumes a. Why fraud rises: When traffic surges during the holidays, small signs of fraud easily get lost in the mix. b. Common fraud types: All types, especially coupon/referral abuse and click spam. c. How it happens: Fraudsters mix fake traffic with genuine visitors or spread out fake clicks over time to avoid detection tools. d. Impact: Fraud becomes harder to spot manually and slowly eats away at your budget and performance metrics. 7. Limited Time to Validate Data a. Why fraud rises: Fraud is no longer a black-and-white issue, and reviewing every click or conversion isn’t practical. Dishonest affiliates often blend legitimate traffic with incentivized fraud and organic hijacking, which are the real human interactions that show activity but no genuine intent to convert. b. Common fraud types: Incent fraud and organic hijacking c. How it happens: Fraudsters push fake activity in short bursts, ensuring they get paid before the fraud is discovered. d. Impact: You end up getting non-genuine users who lead to wasted ad spend, skewed performance data, and lower overall campaign ROI. How does mFilterIt’s Ad Fraud Detection Tool help Brands during Holiday Season? To fight affiliate fraud effectively, brands need to validate ad traffic across the entire funnel, ensuring

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Marketer’s Guide to Ad Fraud – What it is and How to Solve it

Guide, Ad Traffic Validation / mFilterIt Experts

If your campaigns are costing you more than they’re performing, it’s time to rebuild your strategy, because the issue might be lying in your traffic itself. Ad fraud has become one of the biggest reasons impacting your campaigns and marketing budgets across walled gardens, open networks, affiliate platforms, apps, and programmatic ecosystems. The first half of 2025 recorded an average global ad fraud rate of 39.7%, and fraud peaked at 49% in June, the highest in five years. With AI-driven bots, fake users, and manipulated attribution becoming more advanced, the financial impact is far deeper than most marketers realize. Therefore, to help you get clarity, this guide will help you understand what ad fraud looks like today, where it hides, how it impacts real performance, and what you can do to protect your budgets with the right validation strategies. What is Ad Fraud? Ad fraud is the deliberate manipulation of advertising systems to generate illegitimate revenue by simulating real user interactions, such as clicks, installs, or views, without actual consumer interest. The lost advertising money is not the only obvious impact of fraudulent activities. Since fraudsters manipulate the most important ad performance metrics, they also skew the insights marketers and advertising teams may draw from those metrics. The impact from this, in many cases, leads to a long-term negative impact on the brand’s advertising efforts. The problem is made worse because of the availability of options for fraudsters. Let’s look at some of the most common methods and techniques employed by fraudsters to scam honest advertisers. What are the Different Types of Ad Fraud? [Channel-wise Fraud] Types of Web Ad Fraud Web advertising remains one of the most vulnerable digital channels because of the open networks and automated programmatic advertising ecosystem, that makes it challenging to track and verify the legitimacy of each impression and click. Here are the common types of web ad fraud techniques every advertiser must be aware of: Click Fraud As the name suggests, click fraud involves generating fake clicks on pay-per-click (PPC) campaigns. Many fraudsters use simple bots to generate these fake clicks. However, most ad networks and platforms can now detect fake clicks coming from simple bots. To overcome this, fraudsters have started developing and deploying sophisticated bots that can mimic human-user behavior and fool the algorithms of the ad platforms. In some cases, specifically in less developed countries, fraudsters employ cheap labor on “click farms” to generate fake clicks without attracting suspicion from ad networks. Impression Fraud Impression fraud involves fraudsters creating fake impressions on ads that pay in exchange for those impressions. This type of fraud also often involves bots to create fake traffic that can be used to register impressions on ads. Tech-savvy fraudsters may also use more sophisticated methods such as pixel stuffing or ad stacking. With pixel stuffing, the fraudsters “stuff” the ad into a single pixel on their webpage. This way, when a real user visit said webpage, they don’t see the ad and the fraud publisher still ends up getting paid for that impression. Similarly, ad stacking involves “stacking” multiple ads on top of each other in a single ad space on the webpage. This way, when the user visits the page, they may see just one ad, but the fraud publisher will get paid for all the ads stacked in the ad space. Domain Spoofing Domain spoofing is a type of ad fraud where a fraudster tricks advertisers into thinking their ads are showing on popular, trustworthy websites. However, in reality, the ads run on low-quality MFA (Made for Advertisements) websites or even fake websites. The primary goal is usually to steal sensitive information like login credentials, generate fake leads, and earn money. In digital terms, the fraudsters change the website’s identity by using a spoofed domain name, elements, and visuals (similar to that of a legitimate website like a well-known press release page) during the ad auction process, so it appears to be a premium site. Advertisers end up paying high prices, thinking their ad is being seen by a valuable audience, but it’s actually wasted on irrelevant or fake traffic, hurting performance, ad budgets, and brand safety. Cookie Stuffing Cookie stuffing is one of the common ad fraud tactics used by fraudsters to manipulate affiliate marketing performance. This happens when a fraudulent affiliate secretly “stuffs” or adds multiple affiliate tracking cookies into a user’s browser without their knowledge or action. These cookies are meant to track if the user later makes a purchase on a brand’s site. If they do, the fraudster earns a commission, even though they didn’t contribute to the sale. It’s like someone secretly putting their referral name on your order so they can get credit. This affiliate fraud tactic hurts brands because it inflates affiliate payouts, messes up marketing data, and steals credit from genuine affiliates who actually put real efforts to earn the sale. Geo Masking Geo masking, also known as location fraud, is another type of web ad fraud where the actual location of the user is hidden or faked to make it appear as if they are from a targeted region. Fraudsters use various methods like using proxy servers, or VPNs to route invalid traffic through target locations spoofing GPS data and IP addresses. Fraudsters do this to trick advertisers into paying higher rates for traffic that looks like it’s genuine, when it’s really coming from irrelevant regions, misleading performance metrics and further campaign optimization. Types of Mobile Ad Fraud With the expansive growth in app-based marketing and the complexity of attribution models, mobile apps have become a breeding ground for highly sophisticated ad fraud. These fraud types manipulate app installs, in-app engagements, and user attribution at each stage of the funnel using following techniques: Install Fraud Install fraud is a type of mobile ad fraud and involves faking app installs to scam advertisers that operate on cost-per-install (CPI) campaigns. Fraudsters may employ simple or sophisticated techniques to execute this type of fraud. Simpler techniques

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