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Decoding complex digital challenges like ad fraud, brand safety, brand protection, and ecommerce intelligence for brands to help them advertise fearlessly.

ecommerce pricing intelligence

The Hidden Cost of Instinct: Ecommerce Pricing Intelligence Insights

Blog, Digital Shelf Analytics /

Most brands are still pricing based on instinct, internal costs, or outdated competitor scans. And it’s costing them, sometimes without them knowing. A 5 percent gap in your average selling price compared to the market can quietly bleed revenue week after week. Miss a category-wide discounting trend by even a few days, and you’re left reacting while others are gaining share.  Winning on price today isn’t about dropping rates. It’s about knowing exactly where you stand—by SKU, by platform, by geography—and acting before competitors force your hand. Without that visibility, pricing becomes reactive, inconsistent, and risky.  This article breaks down what marketers miss without doing an in-depth pricing analysis and how to fix it with real-time data.  The Hidden Risks of Operating with Pricing Blind Spots Here are the risks that arise when you don’t have full visibility into their pricing environment and competitors’ moves: 1. Limited Visibility into Average Selling Prices (ASPs) Without tracking ASPs across marketplaces, brands risk flying blind. A price that seems competitive internally can be completely off when placed next to real-time market dynamics.  Take this example. Your brand launches a product at $50, feeling confident in its positioning. However, the ASP for similar products across key platforms has quietly dropped to $42. Without that visibility, your brand unknowingly overpriced itself, losing both traffic and conversions. Pricing too low can hurt just as much, eroding margins without gaining meaningful volume. 2. Discounting Trends That Quietly Erode Margins Competitor discounts don’t always show up in obvious ways. Flash sales, time-limited offers, and bundle pricing often fly under the radar, but their impact adds up. If you’re only tracking list prices, you’re missing the real picture.  Say a competitor has been quietly running 10% discounts every weekend. On paper, their list price matches yours. But their actual selling price is lower, and you’re unknowingly losing share—or worse, matching that price later and cutting into your own margins just to keep up. 3. Missed Opportunities in Competitive Categories High-growth categories move fast. If you’re not actively watching how competitors price within them, you risk losing share without even realizing it. Electronics, seasonal products, trending gadgets—these are the battlegrounds where pricing decisions directly shape who wins the sale.  Picture this. A competitor drops prices on wireless earbuds just as demand spikes. Their volume surges. Your product sits at the same price, losing visibility, conversions, and momentum. By the time you react, the wave has already passed. 4. Non-Compliance with MAP (Minimum Advertised Price) Guidelines MAP violations usually don’t scream for attention. They slip in quietly. And if you’re not actively monitoring them, the damage creeps in just as quietly—until retail partners start picking up the phone.  Think about it. An unauthorized seller lists your product below MAP on Amazon. Most buyers won’t question it. They just assume that’s the new normal. Your retail partners? They see it too—and they’re not happy about being undercut while playing by the rules.  It’s not just a pricing issue, it’s a trust issue.  Building a Data-Driven Pricing Strategy Here’s what a modern, proactive pricing strategy should include: 1. Benchmarking Using Real-Time ASP and Discount Data Imagine this. Your flagship product sits at $120. Competitors? They are all clustering around $105. You notice it only after weeks of slower sales and rising cart abandonment rates.  At that point, it is not just about lowering prices. It is about regaining lost ground.  This is where real-time benchmarking changes the game. Tracking ASPs and discounting trends live—not after a quarter closes—helps brands stay responsive, not reactive. If you are serious about staying competitive, set up monthly reviews where your prices and discount patterns are directly compared against your top 5 category rivals. No guesswork, just clear gaps you can act on.  Without this discipline, even the best pricing strategies fall behind market movements that happen faster than internal processes can catch up. 2. Comparing Pricing Against Industry and Category Averages You are confident in your pricing—until the numbers tell a different story.  In the fashion category, your dresses are priced 20% higher than the industry average, while your footwear is underpriced compared to competitors. Neither situation is ideal. One segment risks losing volume due to sticker shock, the other leaves margin on the table.  Category-level pricing analytics show patterns that product-level thinking often misses. They reveal whether your brand’s pricing feels premium, fair, or inconsistent to shoppers browsing multiple options at once.  Smart brands tackle this by setting up category-specific dashboards. These dashboards track where your pricing stands against both the industry and direct competitors, allowing you to course-correct without guessing. It is not about matching everyone else—it is about knowing when you should stand out and when you should realign.  Without this layer of visibility, your pricing strategy is flying blind at the category level 3. Monitoring MAP Compliance Using OEM Codes You can’t fix what you don’t see—and MAP violations are a classic example.  Most brands only catch them when a retailer complains or when brand value takes a hit. By then, damage is already done. That’s why tracking MAP compliance with OEM codes or unique identifiers isn’t just useful, it’s non-negotiable.  Let’s say a SKU slips below MAP on a niche marketplace. With OEM-coded tracking, the violation is flagged immediately. No manual checks. No delays. You now have the leverage to take it down or reach out before your other retail partners even notice.  This level of automation only works when MAP monitoring is baked into your pricing system. Alerts should be real-time, platform-wide, and specific to each product variant. That’s how you stay ahead, not just informed. 4. Analyzing Pricing Across Geographies and Platforms What works in Europe might fall flat in North America. And the same product can demand two very different prices depending on where—and how—it’s being sold.  In European marketplaces, brands often have higher prices. Less competition, stronger demand, and fewer discount-driven shoppers make that viable. In contrast, North America moves fast and fights hard on price. Aggressive

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programmatic ad fraud

Programmatic Ad Risks & Brand Safety Solutions for MENA Advertiser

Blog, Ad Fraud Blog - Valid8 /

Programmatic advertising is seeing a massive growth in the Middle East and Africa region. According to the statistics, the demand of programmatic advertising market will see a splendid growth of 7.89% between the period of 2022-2027.   This increasing demand generates from the region’s growing adoption of digital advertising. Where the demand increases, the challenges emerge as well. As more brands invest in programmatic channels, the challenges increase too. Despite its advanced and automated system of ad delivery, these channels are prone to some fundamental challenges like programmatic ad fraud, brand safety and transparency gaps.   In this blog, we will break down the challenges in programmatic advertising, its impact on advertiser’s campaigns and how marketers can solve it and make their programmatic campaigns effective and brand safe.   An Overview of Challenges in Programmatic Ads in MENA region   Advertisers are often drawn to this due to its promise of scalability, automation and precision targeting. However, these platforms pose several structural and operational challenges that limit the growth for the advertisers and give a picture they didn’t expect. Here are a few key challenges in programmatic that the advertisers in MENA region face today:   – Lack of Transparency  What is not visible cannot be trusted.   Yet, advertisers have to spend trusting the platforms, based on metrics shared, without knowing where their ads are showing up. One of the most persistent issues in programmatic advertising is the limited visibility into where budgets are being spent, who is watching their ads, where their ads are placed.   The supply chain often involves multiple intermediaries — DSPs, SSPs, trading desks, and more — each adding layers of complexity. As a result, advertisers frequently struggle to track where their ads are running, how much is being spent at each step, and whether the impressions served are real or just bot driven.  – Rising Threat of Programmatic Ad Fraud  MENA’s digital ecosystem, while growing, remains vulnerable to various forms of programmatic ad fraud — from invalid traffic (IVT) and fake clicks to domain spoofing and impression laundering. Without robust ad fraud detection and prevention measures, a significant portion of programmatic budgets risks being wasted on non-human or low-quality traffic, diminishing campaign performance and brand trust.  – Limited Access to Quality Inventory  Access to high-quality, premium inventory is still a challenge across many MENA markets. While larger markets like the UAE and Saudi Arabia offer better options, advertisers targeting wider regional audiences often end up buying lower-tier inventory. This affects not just campaign reach but also engagement, conversion rates, and brand perception. And adding to this is the problem of ads appearing beside any unsafe content. This leads to a brand reputation issue for advertisers.  – Measurement and Attribution Gaps   Many advertisers in the region continue to rely on basic performance metrics like clicks and impressions. However, these surface-level KPIs do not paint a full picture of campaign effectiveness. Advanced measurement models like multi-touch attribution (MTA) are still not widely adopted, making it difficult to connect programmatic spend to actual business outcomes like customer acquisition and revenue growth.  – Fragmented Technology Infrastructure  The level of programmatic maturity varies significantly across different MENA countries. What works in the UAE or Saudi Arabia might not scale effectively in Egypt, Kuwait, or Morocco due to differences in publisher ecosystems, audience behavior, and available technology. This fragmentation complicates regional planning and demands a more localized, agile approach to media buying.  – Dependency on Platform-Driven Metrics   Programmatic advertising demands specialized expertise across campaign setup, optimization, fraud detection, and analytics. In the MENA region, there is still a noticeable gap in skilled programmatic talent, leading brands to depend heavily on platform-driven metrics. This dependency often results in less control, reduced transparency, and missed opportunities for optimization.  Emerging Demand of Programmatic Video Advertising in MENA   In the last few years, video content has also become a major medium to drive engagement. Therefore, programmatic video advertising is also seeing a rise in the MENA region. However, this medium also experiences challenges like Frequency Capping Breach, where ads are shown more than the times it is required leading to overexposure and causing ad fatigue for viewers.    How to Solve Programmatic Advertising Challenges — and Where mFilterIt Supports  As programmatic ads expand across the MENA region, brands need more than just automation — they need clarity, credibility, and control. Here’s what an effective programmatic approach looks like — and how mFilterIt supports advertisers along the journey: – Gaining True Transparency into Ad Traffic and Placements  Without knowing where ads appear and who is engaging with them, optimization becomes guesswork. Valid8, our ad fraud detection solution integrates directly with Demand Side Platforms (DSPs) and other sources to provide advertisers with independent visibility into traffic sources, ad placements, and ad inventory quality across the programmatic ecosystem. With this transparency, brands can make smarter, evidence-based decisions for campaign planning and media buying.  – Validating Traffic and Detecting Fraud Early  MENA’s growing digital market also faces complex threats like invalid traffic (IVT) and domain spoofing. Our ad traffic validation solution applies behavioral analysis, heuristic checks, deterministic models, and frequency validation to verify ad interactions. This enables advertisers to distinguish real users from bots and invalid sources — safeguarding campaign data and ensuring budgets reach intended audiences.  For advertisers spending on programmatic video advertising can curb the impact of frequency capping breach by leveraging the frequency cap monitoring solution. This enables advertisers to keep track of how many times their ads are shown to the users, and if they exceed the frequency cap limit. Proactive monitoring reduces the chances of overexposure of ads to the users and helps the advertisers to genuinely reach their targeted audience.    – Identifying Safer and Higher-Quality Inventory  Ad misplacement can quickly damage brand trust. Valid8 flags suspicious, inappropriate, and Made-for-Advertising (MFA) sites, providing advertisers with placement-level insights. Brands can then proactively blacklist unsafe environments and prioritize premium, brand-safe inventory for better engagement and reputation management. – Enabling Better Campaign Optimization By delivering deep, independent insights — such

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digital-commerce-intelligence

Why QSRs Need Digital Commerce Intelligence & Key Features to Know

Blog, Digital Shelf Analytics /

The global Quick Service Restaurant industry, as of 2024, was valued at $971 billion. By the end of this year, the industry is expected to grow to $1055.48 billion. In the near future, the industry is expected to continue growing at a CAGR of 9.01%, being valued at $1930.14 billion by 2032. Clearly, these aren’t small numbers. The Quick Service Restaurant model is quickly emerging as a lucrative business and naturally will attract a lot of new players in the coming years.   This growth is being powered by a number of factors. The most obvious one is the growing affinity of users towards digital ordering. Similarly, the fantastic growth of third-party food aggregators like Uber Eats, Zomato, Swiggy etc. has added some truly potent fuel to the fire.  When the barrier to entry in the industry has become so low, differentiating your business from the rest can be difficult. Thankfully, there’s a proven way to succeed in such a dynamically growing economy- to make data driven decisions by implementing digital commerce intelligence. Let’s see how this intelligence works and how it is obtained in the following sections.   The Need for Digital Commerce Intelligence in QSRs To say that in the last decade, consumers have changed the way they make purchases would be an understatement. Thanks to trends and technologies like online food delivery, mobile ordering, and digital loyalty programs, modern consumers are driven by very different motivations as compared to a decade ago. For instance, the abundant availability of options has diminished the brand recall value of even the most memorable businesses and shortened the attention spans of prospects.   Getting in front of the right audiences may have become easier in theory, since aggregator platforms and search engines can potentially direct interested audiences towards modern QSRs. However, these platforms have become overcrowded and even with access to targeted audiences and that’s why, getting visibility has become a battle for most QSRs.  Here, getting access to and acting upon real-time insights can prove incredibly advantageous. Such insights, usually delivered by data intelligence platforms, can help QSRs improve operational efficiency by enabling better management of demand forecasting, stock levels, and using these metrics to further devise better pricing strategies and menu audits. This is just one aspect of using digital commerce intelligence.   With all that said, all the advantages associated with digital commerce intelligence depend on choosing the right tool. How do you do that? Let’s find out in the next section.  Key Aspects to Look for in a Digital Commerce Intelligence Solution Specific features that may be important to individual businesses may vary when it comes to picking a digital commerce intelligence solution. However, there are some common features that may be relevant to most QSR business. These include:  – Market & Competitive Insights: One of the most important functions of a digital commerce intelligence tool is to enable QSR businesses to make better business decisions. The smart way to do that is to track category trends, pricing, and competitor strategies and hence, the ability to track these metrics is a non-negotiable when picking a digital commerce intelligence tool.  – Customer Sentiment Analysis: Choosing a tool that can help you understand consumer feedback from different sources can prove incredibly advantageous. When picking a tool, make sure it has the ability to pull and analyse customer feedback from sources like third-party review websites, search engine listings, and social media platforms.   – Actionable Data for Decision Making: Finally, when picking a digital commerce intelligence tool, you are looking for one with an easy-to-understand and user-friendly dashboard. This is important because all the data collected and analysis done by the tool will be presented to you in the dashboard. Here, it should be available in a manner that allows business owners or brand managers to derive actionable insights from the data and use it to inform quick optimization actions and long-term strategies. The best tools in the market will even derive the insights for you, using AI-enabled suggestions.  The Impact of Digital Commerce Intelligence on QSR Growth So what kind of a difference can a digital commerce intelligence tool make? Here are some advantages any QSR business can start experiencing almost immediately upon implementing a solution:  – Better Menu and Pricing Decisions: Using insights from marketing and competitive analysis and combining them with insights from consumer sentiment analysis can help QSR businesses make better pricing and menu-related decisions. This cannot just potentially improve sales figures but can also optimize menu items for demand and better inventory management.   – Improved Customer Retention: With consumer sentiment analysis and insights from performance of campaigns and promotional offers, QSRs can inform better consumer retention strategies. The same data can also be used to create personalised experiences for consumers and incentivise consumer loyalty in a meaningful and impactful way.  – Maximized Revenue Opportunities: Analysing the data derived from a digital commerce intelligence tool can help QSRs identify the conditions and times for demand surges. Similarly, analysis of historical data can also help QSRs identify ideal delivery zones and determine which upselling strategies work the best with specific customer personas.   Conclusion In a digital economy, access to and the intelligent use of intelligence can put any brand ahead of their competitors. On the flipside, not using the vast amount of data available online to their advantage can prove to be a huge lost opportunity cost for QSR brands.   Choosing and implementing the right tool can pay off exponentially in terms of more rapid and sustainable growth, improved operational efficiency, and heightened brand trust. In other words, implementing a data-driven strategy is not optional for QSR brands that are serious about their growth.  Have a Quick service restaurant? – Connect with mFilterIt experts to learn how we can help.  

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full funnel validation

Reclaiming Digital Transparency: 1000Farmacie’s Full-Funnel Approach

Blog, Ad Traffic Validation /

The dashboard says ROAS is up. Conversions are climbing. The team’s celebrating. But beneath the surface, something’s off. Traffic looks strong—but isn’t converting. Budgets are growing—but impact isn’t. That’s the trap of affiliate fraud and misattribution—they inflate performance on paper while draining real results. From cookie stuffing and click spamming to bot traffic masked as human behavior, invisible threats distort the numbers marketers rely on most. The missing layer? Full-funnel validation. This blog breaks down how misattribution quietly sabotages performance, why validation is no longer optional, and how 1000Farmacie uncovered the gap—and fixed it. The Hidden Cost of Misattribution Affiliate marketing promises performance-based growth—but what happens when the performance you’re measuring isn’t real? Misattribution is one of the most under-recognized threats to marketing efficiency. It occurs when credit for a conversion is incorrectly assigned to the wrong source—often due to deceptive practices designed to exploit attribution models. In affiliate campaigns, where commissions and payouts depend on tracking performance, this opens the door for fraud. Fraudsters use several tactics to hijack attribution and artificially inflate results: Cookie Stuffing: This involves secretly placing multiple affiliate cookies on a user’s browser without their knowledge or action. If the user later makes a purchase—regardless of the actual channel that influenced it—the fraudulent affiliate still gets credit. Click Spamming: Also known as “click flooding,” this technique sends a high volume of low-quality or automated clicks hoping to match a legitimate conversion through sheer volume. It’s a numbers game that can distort your attribution data and create phantom performance. Bot Traffic: Sophisticated bots mimic human behavior—browsing products, clicking links, even triggering conversion pixels. These non-human visitors can seriously inflate your traffic numbers, conversion rates, and ROAS, all while draining budget. The impact isn’t just technical—it’s strategic. When misattribution is baked into your performance metrics: Budgets get misallocated to underperforming or fraudulent affiliates. Reports tell a distorted story, masking the real sources of growth. Optimization decisions become flawed, leading marketers to double down on what isn’t working and overlook what is. Worse, it creates a false sense of success—campaigns that seem to be thriving on the surface may actually be leaking value underneath. So here’s the question: How much of your affiliate “performance” is actually performance—and how much is fraud disguised as success? Why Full-Funnel Validation is the New Must-Have If misattribution is the invisible leak in your performance marketing, full-funnel validation is the essential tool to detect—and seal—it. At its core, full-funnel validation involves verifying every stage of a user’s journey, from the initial click on an ad or affiliate link to the final conversion. This comprehensive approach delves deeper than surface-level metrics to assess whether the traffic, clicks, and conversions are legitimate, human, and incremental. Here’s how it operates: Traffic Quality Checks at the top of the funnel detect suspicious patterns—such as bots, data center IPs, or abnormally high click rates. Engagement Validation in the middle of the funnel monitors behavioral cues: is there genuine user interaction, or just empty clicks? Conversion-Level Analysis at the bottom ensures that attributed sales are backed by authentic user journeys—not automated scripts or cookie drops. This layered approach provides marketers with comprehensive visibility into the authenticity of their traffic. The necessity of full-funnel validation becomes even more evident when considering the current landscape: Bot Traffic: In 2023, bots accounted for nearly half (49.6%) of all internet traffic globally, with “bad bots” responsible for a third of this figure.   Affiliate Fraud: In 2022, fraudulent clicks constituted 17% of all affiliate traffic, leading to an estimated $3.4 billion in losses.   Ad Fraud Growth: Ad fraud is projected to cost advertisers $84 billion in 2023, accounting for 22% of all online ad spend, with expectations of this figure rising to $170 billion by 2028.   The benefits of implementing full-funnel validation are substantial:  Improved Attribution: Accurately identify which partners and platforms genuinely drive value—and which ones are manipulating the system.  Smarter Budget Allocation: Redirect spending toward high-performing channels and eliminate wasteful or fraudulent ones.  Real-Time Insights: Detects and addresses fraud as it happens, preventing damage before it escalates. Without full-funnel validation, many marketers are operating in the dark—especially in affiliate-heavy campaigns, where performance-based payouts create strong incentives for manipulation. Modern marketing demands more than just tracking conversions; it demands proof of authenticity. Full-funnel validation is the safeguard that ensures your data, decisions, and dollars are grounded in reality. Case in Point: 1000Farmacie’s Affiliate Campaign Was Underperforming—But Looked Great on Paper 1000Farmacie, a leading digital pharmacy marketplace in Italy, serves over 1 million retail customers with more than 800,000 orders annually. As part of its performance marketing strategy, the company relied heavily on affiliate partnerships to drive conversions and grow reach. On the surface, the numbers looked strong. But beneath that surface, there were serious issues affecting efficiency and accuracy. When mFilterIt stepped in, their full-funnel fraud detection and validation uncovered critical insights:  28% of affiliate traffic showed signs of invalid activity—including tactics like click spamming and cookie stuffing. A significant portion of traffic displayed non-human behavior patterns, such as:  Visits originating from data center hubs.  No mouse movement, scroll, or swipe behavior. Misattribution at the order level accounted for a large share of the problem, distorting ROI and misguiding budget allocation. To address these issues, 1000Farmacie deployed mFilterIt’s full-funnel validation and real-time fraud prevention stack, which included: Automated blacklisting APIs integrated directly with ad managers to block fraudulent sources in real time. Traffic quality validation from visit to conversion, identifying anomalies and flagging suspicious sessions. Omnichannel monitoring dashboards that offered transparency across paid and affiliate channels. Ongoing campaign optimization with a focus on reducing invalid traffic and correcting attribution errors. By validating 5.7 million visits and 60+ paid channel orders, and reducing incorrect attribution by 20% on affiliates, mFilterIt helped expose the disconnect between reported and real performance—proving that what looked like success was, in fact, driven by inefficiencies and fraud. The Outcome: Real Efficiency, Better Attribution, Higher ROI With full-funnel validation in place, 1000Farmacie was able to move from reactive to

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IPL 2025 Ads: Smart Brand Tips for Monitoring, Frequency & Fraud

Leave a Comment / Blog, Ad Fraud /

The Indian Premier League (IPL) continues to shatter records, not just on the field but also in the advertising arena. The 2025 season has witnessed a remarkable 29% increase in the number of advertisers compared to the previous year, with over 55 brands vying for attention during the first five matches alone.  However, with this vast opportunity comes significant risk. The surge in advertising can lead to overspending, ad fatigue among viewers, and an uptick in fraudulent activities targeting high-profile events like the IPL.   This blog explores how strategic implementation of ad monitoring, frequency capping, and fraud detection can be the difference between a successful IPL campaign and a costly misstep.   What will your brand get out of IPL advertising?   Here are the benefits your brand will get out of IPL advertising:  Fast Massive Reach   The Indian Premier League (IPL) isn’t just a cricket tournament—it’s a nationwide spectacle with a global fanbase. In the 2024 season, the IPL reached a cumulative audience of 546 million viewers on television alone, with digital platforms like JioCinema attracting an additional 620 million viewers.  This unparalleled reach offers brands instant national visibility.   For brands, this means instant national visibility. Doesn’t matter if you’re launching a new product or driving top-of-funnel awareness, IPL advertising is your opening batsman—aggressive, high-impact, and out to make a statement from ball one.   In most media environments, building this kind of reach would take weeks, even months. With IPL, it can happen in a matter of days, sometimes even overnight. You’re not just reaching people—you’re entering living rooms, conversations, and social media feeds in real time.   Hyper-Engaged Audience  IPL viewers are not just numerous; they are deeply engaged. During the 2024 season, JioCinema reported that viewers spent an average of 75 minutes per session, up from over 60 minutes in the previous season.  This substantial time spent indicates a highly captivated audience, providing brands with extended exposure and increased opportunities for message retention.   A neuroscience study revealed that during IPL 2024, viewers exhibited 1.2 times higher attention to ads on connected TVs compared to linear TV, and brand equity increased by 1.5 times on connected TVs.  This heightened engagement translates to more effective advertising, as audiences are more receptive and responsive to brand messages during the tournament.   Better Brand Recall  Repeated exposure during the IPL significantly enhances brand recall. The tournament’s high-frequency matches and extensive viewership provide multiple touchpoints for audiences to internalize brand messages.   Integrating advertisements with specific in-game moments, such as boundaries or wickets, further amplifies recall. For instance, Cadbury Dairy Milk’s #ThankYouFirstCoach campaign during IPL 2024, which featured heartfelt tributes to cricketers’ first coaches, resonated deeply with audiences and reinforced brand association.  By now you’ve understood the massive opportunity IPL advertising is. But over the years, there’s been a marked increase in programmatic ad buys and real-time bidding (RTB). Platforms like JioCinema have enabled precise audience targeting, allowing brands to bid dynamically for premium ad slots in real time. While this opens up opportunities for better efficiency and control, it also intensifies competition.   With thousands of brands vying for the same inventory, standing out without overspending becomes a strategic challenge. The very speed and scale of programmatic — if not managed carefully — can lead to frequency spikes, wasted impressions, or audience fatigue. For smart advertisers, this creates an opportunity: those who can balance agility with optimization can win both attention and efficiency.  Ad Monitoring  With millions of impressions served in real time across multiple platforms, devices, and geographies, this is not the kind of campaign you can set and forget. Without active monitoring, you risk losing both visibility and impact.  Performance dips, under-delivery, missed geographies, or even incorrect creatives can all quietly eat into your campaign effectiveness. These aren’t just technical glitches — they’re lost opportunities in a media moment that’s all about timing and precision.  This is where our Ad Detection & Analysis on OTT solution comes in. Built for high-velocity environments like IPL, it enables brands to monitor every single impression with precision — across CTV, mobile, and OTT platforms.  The ad monitoring solution provides comprehensive ad tracking, detecting when, where, and how your ads appear. Whether it’s during a top-billed match or a weekday double-header, you get complete visibility into ad delivery across regions, languages, and content types.  It also offers Peak Viewership Heatmaps, helping brands align their ad placements with moments of maximum audience engagement — ensuring not just delivery, but visibility when it matters most.  Performance is benchmarked category-wise, allowing you to understand how your brand stacks up against others in your industry. Plus, with regional and language-based analysis, you’ll know exactly how your ads performed in key cities like Mumbai, Delhi, Bengaluru, and across language feeds including Hindi, Tamil, Telugu, and Kannada.  In short, this isn’t just monitoring — it’s effective campaign intelligence, tailor-made for IPL-scale advertising.  Frequency Capping  With matches happening nearly every day and audiences tuning in across screens, the risk of overexposing your audience to the same ad grows rapidly. Too many impressions in a short span can lead to ad fatigue, reduced attention, and even negative brand perception.  This is where our Frequency Capping Management solution steps in. Built with IPL-scale dynamics in mind, it provides real-time control over how many times an ad is shown — per user, per device, per region, and even per campaign.  The platform checks every ad request against the cap limit before serving. If a device has already reached the cap, the ad is withheld — ensuring no overserving occurs. This allows for real-time protection against over-frequency, reducing media wastage and boosting campaign efficiency.  Brands can configure caps using multiple parameters:  Publisher-based: Set distinct limits per publisher or apply a uniform cap across all.  Geolocation-based: Adjust capping for different cities or regions.  Campaign-based: Apply caps tailored to specific initiatives or objectives.  Time-based: Control exposure over days, weeks, or months.  The system integrates seamlessly with ad servers and wraps creatives with a smart VAST tag that enforces these rules automatically

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pay-per-call

The Hidden Cost of Lead Generation Fraud in Pay-Per-Call Campaigns & How to Stop It

Blog, Ad Fraud /

If you are selling products or services online in the US, there’s a good chance that you have dabbled with performance marketing or pay-per-call (PPC) campaigns, as they are commonly called. In fact, these days, in order to drive any kind of business online at scale, PPC campaigns have emerged as a necessity, and for good reason. In a perfect world, PPC campaigns have the potential to provide businesses with high-intent leads that can easily be converted into paying customers. Many brands have deployed significantly large teams of sales experts to handle the leads generated by PPC campaigns and drive conversions. Unfortunately, the world isn’t perfect, and modern PPC campaigns are plagued with lead generation fraud. Fraudsters use a variety of simple and sophisticated techniques to defraud advertisers and waste their ad spending while making a quick buck in the process. The worst part is that the wasted ad spend has just a short-term impact on such fraudulent activities. In the longer run, scammers can skew the metrics that advertisers use to plan their campaigns. As a result, lead generation fraud can have lasting effects on any brand’s PPC performance. Let us look at this problem in more detail. The Problem: How Lead Generation Fraud is Hurting Pay-Per-Call Campaigns Lead generation fraud is a huge problem, especially for advertisers operating at a large scale. This problem can be made easy to understand by breaking it down into its components: 1. Fake and Invalid Leads The most noticeable impact of fake campaigns is the fake lead generation with the use of bots and duplicates. Fraud publishers employ bots and in some cases, real people to click on ads and generate calls. However, since these calls are generated with the sole purpose of defrauding the advertisers and securing unethical monetary gains for the fraudsters, they have no real intent behind them and never convert into paying customers. The only losing party in this mix is the advertiser who ends up paying for calls that have no chance of converting, no matter how well a sales team works on them. 2. High Volume Of Fake Engagements Fake and invalid leads generated with the use of bots of poorly paid employees of fraud publishers generate a lot of engagement but drive no real value. In fact, they drain ad budgets that could otherwise drive engagements that boost the business’ bottom line. Similarly, the fake calls generated also engage call center resources that could be otherwise used to engage with genuinely interested prospects. This reduces the operational efficiency of the call centers. 3. Lack Of Pre-Call Filtering Mechanisms Most businesses don’t have a mechanism for lead validation designed for filtering out bad and fake leads before their call gets connected to their call center. This results in increased cost-per-acquisition (CPC) for the advertiser. Impact of Lead Generation Fraud on Brands The impact of lead generation fraud on a brand’s campaigns may not always be obvious. However, knowing where to look can work to the advantage of advertisers trying to make the most out of their PPC efforts: 1. Revenue Drain If a brand has fallen victim to lead generation fraud, it means that they are spending a portion of their ad spend on fake leads. Depending on the severity of the problem, this wasted budget can make up a significant portion of the advertiser’s total ad budget. 2. Call Center Inefficiencies Fake leads, after an advertiser has unwittingly paid for them, land as calls to their sales team. As a part of their responsibilities, sales teams have to take these calls and spend valuable time attending to them. Since they never even have a chance of resulting in a sale, the entire ordeal ends up wasting the time of valuable sales resources. 3. Brand Safety and Compliance Risks If a brand is struggling with lead generation fraud, it usually means that its ads are being published by fraudulent publishers. The brand is also usually never aware of the kind of content hosted by such fraudulent websites. As a result of association with such publishers, the brand risks damaging their reputation and in extreme cases, failing compliance checks. 4. Distorted Marking Analytics Finally, such instances of fraud have the potential to skew the very advertising metrics that advertisers use to inform their campaign strategies. If, for instance, an advertiser notices that ads with a particular set of publishers are generating good engagement, they may be inclined to direct more of their budget towards these publishers. However, if the publisher is not generating genuine leads, it leads to the advertiser wasting more of their budget with them. Besides the cost of the wasted ad budget, the brand also ends up paying the opportunity cost of not directing their budget towards genuine publishers that could have enabled them to access genuinely interested prospects. Real Case This problem is exemplified by the case study of one of our clients operating in the banking sector. Our client was struggling with poor lead quality, with some campaigns registering as many as 98% of generated leads as fake. Besides the fake leads being sent their way from bad affiliates, the other challenge our client was facing was to improve the efficiency of their quickly growing call center, something that was being plagued by the menace of fake leads. Let’s look at how we helped our client overcome these issues with our tool’s state-of-the-art validation features. How mFilterIt Solves the Problem Leveraging its advanced AI-enabled technology, mFilterIt helps advertisers gain transparency in their lead funnel. Here are a few ways it solves the lead gen fraud issue for advertisers: 1. AI-Powered Click-To-Call Validation Mechanism Our AI-powered validation mechanism is designed to detect bot-driven call interaction. This is made possible with behavioral and network analysis to identify patterns and detect bot activity. Leveraging this feature, the mFilterIt tool is able to execute reliable lead validation before the call is ever initiated. This, in turn, improves call center efficiency by eliminating fake call connections.

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How a Real Estate Player Secured Its Digital Identity with OSINT-Powered Solution?

Blog, Brand Safety & Suitability /

Imagine this- a consumer goes online to find a real estate project where they can purchase a home. They start their search on a well-known search engine and come across results from some of the most reputed names in the real estate game in the country. They click on one of the sponsored results, look through the website, and shortlist a project that aligns with their needs. This prospect then fills out a contact form which subsequently leads to a call with the builder’s sales team. The salesperson informs the prospect that they will have to pay a small fee as an expression of interest in the project, to reserve their property. To incentivize the prospect, the sales rep even promises to offer them a competitive price that almost seems too good to be true. Considering the opportunity cost of not acting immediately, the prospect makes the expression of interest payment. However, they never receive any confirmation from the builder’s side and are never able to reach the sales rep again. This unsuspecting prospect has just fallen victim to a scam. While this scenario may seem far-fetched to some, it is an unfortunately frequent occurrence in the realm of digital ads and real estate. While the plight of the victim of the scam, the consumer is evident, the builders whose names are used to execute such scams stand to lose a lot more. For the builders, such instances translate into lost revenue, legal issues, and broken customer trust. To further cement the notion that this isn’t a made-up scenario, here’s a case study about one of our clients who was facing a similar predicament, and was able to get out of it with the help of Brand Protection Tool. Let’s find out more about this case: The Challenge: Why Real Estate Brands Are at High Risk Big real estate firms face an enormous yet hidden risk in the online realm. Scammers can employ a number of methods to dupe unwitting consumers while also tarnishing the name of the builder. Some of the most common ways scammers do this are: Fake Property Listings This is perhaps the most common and the easiest way for scammers to steal money from potential customers of real estate firms. Scammers create fake property listings on popular listing websites and use them to lure potential buyers. From this point, depending on how much they are able to influence individual buyers, scammers take money from them in the form of visitation charges to booking amounts for reserving a property for purchase at a later date. Impersonation & Brand Misuse This method is quite similar to the previous one, except with this, scammers are not limited to property listing websites. They may go one step further by creating fake social media profiles or even fake websites under the name of reputable real estate players. Using these, they can once again attract potential buyers and scam them. Intellectual Property Violations Real estate businesses have to publish a variety of documents when advertising a project. Since most such documents, such as floor plans and certificates are available in the public domain, they can be used by scammers to appear authentic in front of potential customers. Besides causing distress to buyers and potential customers, such practices cause a lot of damage to authentic and well-meaning real estate players. Consumers who fall victim to these scams often form the impression that the actual real estate business has tried to outsmart them. While clarification on the subject can change this notion, providing such clarifications to tens of customers every day can prove impractical. In fact, a similar reason is behind the widespread proliferation of such scams. Since it is impossible to manually track every instance of a brand’s name being used by a third party, especially in the case of big brand names, scammers take advantage of volume to outsmart vigilance. The Solution: AI-Powered Brand Protection for Real Estate While manual tracking cannot solve this problem, overcoming this issue is possible. With the Brand monitoring tool, such as the mFilterIt solution, real estate businesses can track and monitor instances of fraud and protect their prospects, customers, and most importantly, their brand image. At mFilterIt, we used the following brand protection features to help our client overcome the dangers of online scams: · Automated Digital Scanning: This feature is designed to detect fake listings, impersonations, and other forms of unauthorized brand usage. The AI-enabled feature does the tracking across platforms, including property listing websites, social media platforms, ad platforms, and even search engine result pages. · ML-Based Categorization: In severe cases, automated digital scanning can uncover hundreds, even thousands of instances of brand impersonation. Dealing with so many cases one by one can take a long time. With Machine Learning (ML) based categorization, mFilterIt helped by identifying and prioritizing high-risk cases for quick takedowns and bulletproof protection. · Confidence Scoring: Confidence Scoring is a feature that assigns a severity score to violations, based on the amount of risk they pose against the brand and its customers and prospects. · Data-Driven Enforcement: All of the data points collected using the previously mentioned features are presented in an easily digestible format on a central dashboard. This dashboard enables smart and quick decision-making, enabling brand managers to monitor their brand protection in real-time. The Results: Real Impact So what did we achieve by helping our client? How big was the problem? Did we manage to solve it? Here are the numbers: Our solution detected 1,177 cases of brand impersonation in the span of just six months. With this data, we took down 905 fake listings and fake social media accounts spread across five different platforms. New fake pages and listings that would pop up on our radar were being removed in an average of 1-2 days. As a result of this exercise, the brand experienced an improvement in its brand reputation and enjoyed enhanced customer trust. Evaluating a Brand Protection Solution for Real Estate Real estate

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Is Your Brand Safe? A Step-by-Step Guide to Auditing Your Ad Placements

Blog, Brand Safety & Suitability /

Digital advertising has grown into a vast industry. Thousands of advertisers use advertising networks to publish their ads through millions of publishers. This scale in the ability to reach consumers is nothing short of a miracle, especially for smaller businesses trying to cut through the noise created by their larger competitors. However, thanks to the same scale, there are grave issues concerning all advertisers, regardless of the size of their business or advertising budget.   In this article, we are focusing on one of the most pressing issues faced by digital advertisers- tracking where their ads appear in the digital ecosystem. Why does it matter? Just as a good placement will drive more sales, a bad placement may result in a wasted ad budget or worse, it may end up harming your brand’s image.   This flaw in the way the digital ad industry operates has been exposed by a recent report published by Adalytics. According to the report, ads representing some of the biggest, most well-known brands across the globe were found to be hosted on websites that publish and host child sexual abuse material (CSAM).  The irreparable damage to brand reputation in such a case is not difficult to imagine. Thankfully, there’s a lot that advertisers can do to prevent their ads from being published with harmful or illegal content. This guide will walk you through all the steps you can take to protect your brand against such threats.  Let’s start at the beginning:  Step 1: Gain Visibility – Understanding Your Ad Placements  The first step to safeguarding your brand against problematic ad placements is to understand how ad placements are decided. One of the most common ways to publish ads at scale is to use programmatic ad platforms. These platforms, in theory, allow advertisers to precisely target specific audiences at scale, in real-time.   However, since programmatic platforms operate using a complex ecosystem of algorithms, supply-side platforms, and delivery-side platforms, advertisers have extremely limited visibility into their ad placements.   This was evident in the Adalytics report that highlighted big brand names like Amazon, Arizona State University, and even US Government Departments like the Office Of Texas Governor were found to be unaware of their ads appearing on a website that would also host CSAM content.   This lack of transparency on programmatic campaigns can be counteracted with the right tool.   One of the best ways to ensure that your ads are placed in a safe environment is by implementing a brand safety monitoring solution . mFilterIt’s brand safety tool makes use of real-time monitoring to help advertisers get transparency on their ad placements, where it is getting placed to ensure that their brand name is not associated with appraising advertisers about all the brand safety issues that they may be facing, presented through an actionable data points dashboard. The dashboard offers a categorized view of all unsafe content categories, along with risk levels and a detailed list of placements on which advertisers can take proactive action to safeguard their interests.  Step 2: Conduct Content Safety Analysis Once it is clear how ad placements are decided and you have set up the tracking for the same, it is time to ensure your ads are appearing next to contextually relevant content. While programmatic advertising promises the same, the CSAM case has made it clear that the content verification methods of ad networks are incredibly lacking.  Once again, a reliable brand safety tool can prove extremely handy in such a situation. The tool features a Content Safety Analysis feature that is designed to detect harmful content environments that may not be suited to hosting a specific advertiser’s ads. The tool should not just consider safe ad placements but monitor and flag content based on contextuality and relevancy.   Step 3: Check the Website’s Safety Parameters  Next, brands and advertisers must conduct individual website audits to determine whether a publisher is suited to host their ads. These checks are important because in many cases, a website may seem like a safe bet at a glance but may be holding questionable content within its deep pages. The website exposed in the Adalytics report is a good example of the same. At a glance, it seems like a safe image-hosting website. However, by monitoring the specific URLs one can identify harmful or illicit content websites like the CSAM content.  To make sure none of your ads appear on a questionable website, analyze the list of websites associated with an advertising platform on the following metrics: Website Basics: These include the URLs, titles, meta descriptions, and tags associated with the pages where the ads may appear. While these may seem like rudimentary aspects of website analysis, one may find themselves surprised at how much information these tidbits of a website contain.  Website History: This one may be familiar to many business owners. Checking the history of the website for instances of blacklisting from an advertising platform is a great way to ensure that the ads are appearing in a reputed publication. To be thorough, it is a good idea to also check for historical instances of policy violations.  Domain Safety: Advertisers must also give the domain of the publishers a second look to scan for terms that may not align with their brand safety standards.  Whois Information: The Whois Database is a superb resource for checking any website’s hosting details, credibility indicators, and the name(s) of the owner(s). This information can be used in conjunction with the website’s history and basics to make sure that the website in question truly fits within the brand’s safety guidelines.  These checks, when done thoroughly, can do wonders for ensuring your brand’s safety in the ad ecosystem. However, a typical ad network may have thousands of publishers suited to an advertiser’s targeting needs. Analyzing thousands of websites can prove to be cumbersome, to say the least. For such cases, a tool like PACE can be beneficial. It helps advertisers build an exclusion list and ensure that any of

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How Fraudsters Manipulate App Installs and What Marketers Can Do About It?

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Mobile apps are big business and the same is apparent through the significant advertising budgets dedicated to increasing app installs. In 2022 alone, advertisers spent more than $18 billion on advertising their apps to drive more installs. This makes the app install advertising business lucrative.   Unfortunately, this lure also attracts bad actors and frauds. That’s perhaps why, today, app install fraud is one of the most common forms of ad fraud in the online realm. According to our analysis, we have found that on IOS, the average fraud at the install level is 57% which rapidly increases to 70% on Android devices.   Fraudsters use fake app installs to steal from advertising budgets. The financial impact of this, while significant, is only a small part of all the trouble caused for the advertisers as a result of these activities. What’s more troublesome is that fraudsters are evolving their methods and employing sophisticated methods to carry out their fraudulent activities.    In times like these, advertisers need to start ahead of the curve to protect their ad budgets. To do this, one must first understand how app install fraud works and that’s exactly what the next section describes. Read on.  The Hidden Tactics Behind Install Fraud While it may seem like app install fraud is a single threat, the reality is much more complex. Fraudsters utilize several simple and complex methods to fake installs and steal from advertisers’ budgets. Here’s a quick overview of the most common methods employed by app install fraudsters:  – Click Injection: This is one of the most sophisticated forms of app install fraud. To execute this, fraudsters publish an app that “listens” for app download broadcasts. Using this information, they can “inject” a click right before an app install is completed. This allows fraudsters to claim the credit for the app install despite not contributing anything to make it happen.  – Click Spamming: Click spamming is usually employed to target campaigns where advertisers are paying for clicks on their ads. As the name suggests, fraudsters generate a large number of fake clicks, usually using bots, and claim the rewards. However, the advertiser unfortunately ends up paying for clicks that will not result in any genuine interest or installs of their application.  – Organic Hijacking: Another sophisticated form of app install fraud; organic hijacking works by stealing the credit of organic installs. Fraudsters employ malware or other methods to send a fake click right before an app download is completed, claiming the credit for the app installs, along with the associated reward.   – Incent traffic: This type of app install fraud is one of the most difficult to detect, as it uses real users to scam advertisers. In this type of fraud, fraudsters place ads on incent walls and incentivize real users to download an application and in some cases, complete an action that claims the reward. In many cases, fraudsters straight out share a part of their affiliate payout with the user. While there are real users involved and the app download is also authentic, since the user is only interested in the reward, the entire activity doesn’t drive any value for the advertiser.   – SDK Spoofing: With SDK Spoofing, fraudsters usually use a malware-laced app of their own to infect user devices. This app then manipulates the SDK communication of the advertisers’ apps to generate fake installs and register other actions that may be rewarded by the advertiser. Alarmingly, such an activity is extremely difficult to track and can be conducted indefinitely, effectively draining entire ad budgets without delivering any real value.   But Aren’t Fraud Checks by MMPs Enough?   Impression campaigns are often the first leg of a successful, larger ad campaign that may target app installs. As a first step, getting authentic impressions is important to make informed decisions to drive more app installs. To make sure their impression campaign data is authentic, many advertisers depend on Mobile Measurement Platforms or MMPs.  Unfortunately, MMPs are not as capable or dependable as many advertisers have been led to believe. One of the biggest problems with MMPs is that they are paid for impression attribution and not validation. To that end, if they start reporting all the fraudulent impressions, it may affect their revenue associated with attribution.   Moreover, in cases where MMPs can detect and report impression fraud, the standard timeline is simply too slow to make any real impact. Most MMPs follow a D+7 reporting schedule, creating a significant delay between the moment a fraudulent activity is detected and the time when an advertiser finds out about it. Finally, most MMPs employ basic checks to detect fraud which are largely ineffective against sophisticated ad fraud techniques.  The Cost of Fake Installs: Why It’s More Than Just Wasted Budget  No doubt, the wasted ad budget is perhaps the most obviously painful effect of ad fraud experienced by advertisers. However, impact of ad fraud goes much deeper than draining your budget and can have a long-term impact on the business.   Fraudulent activities, when undetected, can also skew the ad performance data that advertisers depend on to make optimization decisions. These distorted key performance indicators (KPIs) can further lead to advertisers making optimization decisions that waste even more of their marketing budget.  Not to forget, skewed metrics also impact other decisions related to user acquisition and experience. The wrong decisions, especially in the case of user experience, can lead businesses to decisions that worsen the experience of installing and using their apps, negatively impacting long-term user retention and organic App Store/Play Store rankings.   In other words, a wasted ad budget is just the tip of the iceberg. App install fraud can impact user data analytics which can, in turn, impact long-term marketing ROI. Red Flags Valid8 has Detected  Fighting fraud starts with detecting fraud. Advertisers must stay vigilant and look for the following signs to catch instances of fraud and deal with the fraudsters before they can cause significant harm:  Abnormally Low Conversion Rate– An

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