app

foxtale

Foxtale’s 21% CPC Drop: Leveraging mFilterIt’s Expertise to Combat Brand Bidding by Ad Networks

Foxtale, a dynamic skincare brand, invests heavily in TOF and video campaigns to boost search volumes and drive high-intent users to their website. However, ad networks were bidding on the same branded keywords, capitalizing on Foxtale’s brand popularity to generate revenue easily. This competitive bidding drove up their CPC by 25-30%, further, impacting return on ad spend (ROAS), and hindered scalability. Download the case study to know how our solution helped the brand identify the ad networks bidding on their brand keywords and helped them optimize their campaigns. Download Submit

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kuku-fm

From Fake Installs to Quality Engagement: Know How Kuku FM Improved their App Traffic and Optimized Spending

Kuku FM, a leading audio content platform runs a user acquisition campaign to bring new users to their app. However, they notice a high volume of app installs with no conversion (in this case, paid subscription). To solve this, Kuku FM partnered with mFilterIt to validate their ad traffic and filter it to optimize their campaigns better. Download our case study to learn how our solution helped the brand identify suspicious traffic sources and fraudulent techniques used to drain their ad budget and block them to protect their campaigns and attract genuine traffic. Download Submit

From Fake Installs to Quality Engagement: Know How Kuku FM Improved their App Traffic and Optimized Spending Read More »

MMP- fraud

Enhancing Transparency in Ad Fraud Detection: Moving Beyond Mobile Measurement Partners (MMPs)

In this compelling case study, learn how a leading bank tackled the growing challenge of ad fraud by uncovering significant discrepancies between transaction data reported by its Mobile Measurement Partner (MMP) and its internal backend system. With MMP-reported transactions consistently exceeding the bank’s backend figures by over 50%, it became clear that traditional fraud detection methods were no longer enough to prevent costly inaccuracies and misallocated ad spend.   What you’ll discover in this case study: The limitations of MMP fraud detection and why relying solely on these systems can leave your data vulnerable. How sophisticated bot patterns and event spoofing techniques are evading detection, resulting in inflated metrics. Insights from the bank’s internal audit that revealed key red flags, leading to a broader strategy for improving fraud detection and enhancing transparency. How mFilterIt ad fraud detection addressed these issues to safeguard ad spend and drive more accurate marketing decisions. Download the full case study to see how this financial institution improved its ad fraud detection and regained control over its campaign metrics, paving the way for better-informed decisions and optimized ad spend. Download Submit

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devil-behind-the-beauty

How a popular beauty & personal care brand identified fake app installs in the MENA region

69% of Beauty & Personal Care installs in the MENA region are fraudulent. 86% Fake events post app installation: sign-ups, transactions, any other in-app activity. mFilterIt deterministically validates digital engagement by fine-tuning the return on digital spends within a brand-safe environment. Create true engagements within a trustworthy brand environment. Identifies and reports BOT-driven frauds hampering digital advertising performance along with issues adversely impacting the brand reputation and trust. Download Submit

How a popular beauty & personal care brand identified fake app installs in the MENA region Read More »

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