Think your password is safe? It might be easier to crack than you think
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Brand Safety & Suitability: You Might Be Unknowingly Showing Ads to Kids – Know How
Yes, you read it right. Your ads often get placed next to kids’ content. And the concerning part? Your brand safety filters don’t identify these placements as unsafe, because technically they aren’t. What they are, however, are brand-unsuitable placements. It is a systemic gap in how traditional brand safety tools classify content and demographic targeting that affects more campaigns than most advertisers realize. In this blog, we break down exactly how this happens through real examples, why your current filters and targeting settings may not be enough, and what it actually takes to ensure your ads are brand safe and brand suitable, in every sense of the word. Brand Safety & Brand Suitability: They Are Not The Same Thing Before we get into how this happens, it’s important to understand two terms that are often used interchangeably but mean very different. Brand Safety Brand safety is about making sure your ad doesn’t appear next to content that is harmful, offensive, or controversial — violence, hate speech, adult content, or extremist material. Most advertisers today are aware of brand safety and have some level of filtering in place for it. Brand Suitability This goes one level deeper. Brand suitability is not just about avoiding inappropriate placements. It’s about making sure the content environment your ad appears in actually fits in the environment, context, and sentiment of your brand, your product, and the audience you’re trying to reach. Here is a simple example. A children’s cartoon is not unsafe content. It carries no violence, no hate speech, nothing harmful. But if you are a premium financial brand targeting urban professionals between 30 and 50, running your ad before that cartoon is a suitability failure, not a safety failure. The content is perfectly fine. The contextual ad targeting is completely wrong. This is the gap most advertisers are not solving for. Why Do Basic Brand Safety Tools Fail to Identify the Brand Suitability Issues? Here are the two major reasons why your ads keep appearing besides irrelevant content ad placements. The Content Identification Problem Platforms and traditional brand safety tool do their classification work by reading what is written about a video – the title, the description, the tags, and other metadata. They do not actually watch the video. What’s written about a piece of content and what’s actually inside it can be two entirely different things. A video can be tagged as a cartoon and correctly land in a kids’ content category, but still carry themes, visuals, or emotional tones that are completely at odds with what that label suggests. The Audience Targeting Problem When an advertiser sets up a campaign targeting adults, say, 25 to 45 year olds, the platform uses data signals like age registered in Gmail accounts, browsing behavior, and declared gender to identifyand reach that profile. The platform then delivers the ad to that account. Technically, it has done exactly what it was asked to do. But here is what no one identifies; the platform has absolutely no way of knowing who is physically sitting in front of the screen at that moment. The account belongs to an adult; however, the viewer watching the screen at that moment could be a child. And this can only be prevented if the content is identified not just based on title and tags, but based on content, context, sentiment, as well as frame-level video analysis. How mFilterIt’s Brand Safety Solution Solves Brand Suitability Issues? mFilterIt’s brand suitability and brand safety solution, PACE, addresses both the content gap and the visibility gap that traditional tools leave behind. Here’s how it works and what it delivers for advertisers. Analyses videos frame by frame including visuals, audio, on-screen text, sentiment, and scene context to understand what a video actually contains, not just what it is labelled as. Classifies placements against GARM brand safety categories with risk levels as high, medium, and low, so exclusions are precise and not over-blocking safe inventory. Operates in real time, detecting and blocking unsuitable placements before your ad impression is served, not after the budget is already spent. Builds a curated whitelist of videos that are not just safe but genuinely suitable for your specific brand, audience, and campaign sentiment. Identifies regional and vernacular content with language-specific ML models built for the diverse market, where over a billion hours of regional content is consumed every month. The result: Your ad runs in the right context, in front of the right audience, every time. Conclusion Brand safety keeps your ad out of harmful environments. On the other hand, brand suitability makes sure it lands in the right one. Both matter. And right now, most advertisers are only solving either one or none. So, before you take another campaign live, ask this: Is the content my ad is running next to reinforcing my brand or quietly working against it? The brands that get this right aren’t just the ones with genuine results. They’re the ones who know, with precision and confidence, exactly where their ads are landing. To learn more about how we can help, Get in touch with our experts today. FAQ,s What is the difference between brand safety and brand suitability? Brand safety avoids harmful or inappropriate content, while brand suitability aligns ad placements with a brand’s values, tone, and target audience for better contextual relevance. Why is brand suitability important for branding campaigns? Brand suitability ensures ads appear in relevant environments that match brand values, improving audience perception, engagement, and overall campaign effectiveness. How can brands ensure safe and suitable ad placements? Brands can use content filters, whitelist/blacklist strategies, and verification tools to control where ads appear and ensure alignment with brand guidelines. What tools help monitor brand safety in digital advertising? Brand safety tools analyze content, detect risks, and provide real-time insights. They help advertisers avoid unsafe placements and maintain control over ad environments. How do contextual targeting strategies support brand suitability? Contextual targeting places ads based on content relevance, ensuring alignment with brand messaging and improving engagement without relying on user data.
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$14.8B at Stake: Will You Let Cookie Hijacking Slip Through?
The U.S. affiliate marketing industry is entering a new phase of scale. It is crossing the $10 billion mark for the first time, up from $9.1 billion in 2023, and projected to reach $14.8 billion by 2028. With giants like Amazon, Walmart, and Target running large, complex affiliate programs, the stakes have never been higher. But as the channel grows, so does the race to claim commissions (sometimes wrongfully) which can also look like this-imagine a shopper comes directly to your website, ready to buy but yet somehow, a third-party partner ends up taking creadit for that sale. Many brands are already trying to tackle it, but the growing sophistication of the tactic makes it increasingly difficult to control. In this blog, we dive into a sophisticated tactic known as cookie hijacking where affiliate cookies are secretly inserted into a user’s browser to claim credit for organic traffic, ultimately stealing conversions that rightfully belong to the brand. Behind the Scenes of Cookie Hijacking: 3 Tactics You Might Be Missing Here are three common ways affiliates cause cookie stealing to hijack organic traffic: Extensions Injecting Cookie Affiliates driving sales by influencing real customers is ideal but them stealing is not. One common way an affiliate program experiences this issue is through cookie hijacking. While analyzing a leading global e-commerce platform, we found that many users were directly visiting the site to make purchases. However, some had browser extensions installed (like coupon or deal tools) that silently triggered affiliate links in the background, without any click or user consent. As a result, when the purchase was completed, the system attributed it to an affiliate. Since most tracking follows a “last click wins” model, the affiliate whose cookie was dropped last received the credit, despite having no real influence on the sale. Auto-redirect with Affiliate Tag Another way of cookie hijacking that we noticed in the same brand’s use case was, the page as when users were redirected to brand’s website. If a user is browsing normally and visits a random page (this could be a shady site, popup, or even hidden script). The page quickly redirected them to brand’s site and in a split-second redirect, an affiliate cookie is dropped silently. When that user makes purchase, the credit is given to the affiliate as system sees the cookie. Forced cookie from an external site A user visits a completely unrelated website, not your brand’s. In the background, that site quietly drops an affiliate cookie without the user clicking anything or showing any intent. Sometimes, the user is even redirected to your website, making it look like a normal visit. Later, when they make a purchase, the affiliate gets credit, simply because their cookie was already placed earlier. How Can You Safeguard Your Brand From Cookie Hijacking Cookie manipulation is a growing risk for U.S. brands, especially those running large-scale affiliate programs. As partner ecosystems expand, having clearer visibility becomes essential to avoid affiliate fraud and protect genuine performance. Legacy, surface-level tools can highlight obvious issues, but the real question is whether they can keep up with increasingly sophisticated fraud tactics. In most cases, they fall short. And for U.S. brands running high-stakes affiliate programs , uncertainty isn’t something they can afford. With a more advanced, third-party approach like mFilterIt’s, renowned brand are already bringing more transparency to their affiliate marketing programs. Here’s how it empowers brands- Launch instantly, stay in control – No integrations needed, just immediate visibility into your affiliate ecosystem Gain complete transparency – Always-on scanning ensures you see every leakage, not just the obvious ones Expand your risk coverage – Protect your brand from both known partners and unknown bad actors Make decisions with confidence – Accurate, low-noise insights you can actually act on Hold the right partners accountable – Clear attribution helps you take precise, effective action Understand your true customer journey – See exactly how users reach and convert on your platform Protect revenue in real time – Identify and stop fraud before it impacts your bottom line Conclusion The key to a smooth affiliate program is visibility to understand real user journeys and know where attribution is coming from. Brands that focus on transparency and proactive monitoring through holistic ad fraud solution can prevent revenue leakage and build stronger, more reliable affiliate programs. FAQs What is cookie theft? Cookie theft is when someone steals a user’s cookie or places their own cookie in the user’s browser to wrongly take credit for a purchase they didn’t influence at the first place. How to prevent cookie hijacking? Monitor affiliate traffic and user journeys closely Block suspicious extensions, redirects, and unknown sources Validate partners and enforce strict program rules Use advanced tracking/monitoring tools for better visibility Why is cookie hijacking difficult to identify? Cookie hijacking is difficult to identify because it often happens silently in the background. Since the user still completes a genuine purchase, the fraud appears legitimate in standard attribution systems, making it harder for legacy tools to flag. What are the common signs of cookie hijacking in affiliate programs? Common signs include sudden spikes in conversions, abnormal click patterns, high traffic from unknown sources, and mismatched user journeys that indicate unauthorized tracking activity What impact does cookie hijacking have on attribution and commissions? Cookie hijacking manipulates attribution by assigning credit to fraudulent affiliates, leading to incorrect commission payouts and reduced returns for genuine marketing efforts. What compliance measures help prevent affiliate fraud in the US? US advertisers can enforce strict affiliate policies, conduct regular audits, use fraud detection tools, and follow FTC guidelines to ensure transparency and prevent fraudulent activities.
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