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Shiraz Noor

With 15+ years in Digital and Telecom, Shiraz Noor combines expertise in technology, strategy, and innovation. A strong advocate for digital transformation, he simplifies complex trends into actionable insights, sparking conversations that help professionals stay ahead.

Attention Metrics

What Real Campaign Data Analysis by mFilterIt Reveals About Viewability and Attention Metrics

Blog, Viewability /

Many advertisers still believe ‘if an ad is viewable, it means the user actually saw it.’  But that’s not the case anymore. Impressions and viewability still dominate reporting, but they don’t reflect whether audiences actually watched or engaged with an ad. That is why the digital marketing industry and advertisers have now started shifted their focus towards a more reliable metric – attention measurement.  The recent campaign analysis conducted by our experts shows this major shift: attention metrics reveal intent and creative effectiveness in a way traditional KPIs simply can’t.  How Are Attention Metrics Better than Viewability?  Unlike viewability, attention is measured based on multiple signals and human behaviour patterns, not one parameter. The parameters include time-in-view analysis, completion rate, drop-offs, mute rate, picture-in-picture behaviour, etc. These signals are processed using an ML-driven model to estimate likelihood of genuine attention given by a user to an ad.  This multi-signal view creates a far more accurate representation of user intent. It uncovers whether the audience accepted the experience, tolerated it, or tried to avoid it. And as seen in our recent campaign, these behavioral indicators can completely change how creative formats are evaluated.  Two formats. Same brand. Yet drastically different attention outcomes. Here’s what the data really revealed.  What We Observed in Format-Level Analysis: Understanding Audience Engagement Behaviour with Attention Metrics  We analyzed audience interactions across two non-skippable video formats – 15 seconds and 25 seconds, to understand how runtime influences attention quality. Both formats were served to similar targeting sets across comparable inventory, ensuring the behavioural differences were meaningful.  Completion Rate Revealed Early Fatigue 15s format: 95.05% completion  25s format: 84.31% completion  The longer format triggered noticeably higher drop-offs, suggesting that even a small increase in duration can introduce friction.  Mute & PIP Exposed Active Disengagement Mute rates:  15s format → 3.38%  25s format → 4.52%  PIP rates:  15s format → 4.14%  25s format → 5.46%  Both indicators rose significantly for the 25-second version. These behaviours aren’t accidental; they are user choices to reduce exposure, showing clear discomfort with the longer ad runtime.  Final Analysis 15s format attention score: 90.15%   25s format attention score: 79.65%  When all signals were combined, the 15-second creative clearly showed stronger intent, lower disruption, and higher-quality engagement. Know more about how mFilterIt attention metrics tool differs from competitors.  What This Means: How Advertisers Can Improve Ad Engagement Using Attention Metrics The behavioural signals from this campaign clearly show what audiences accept and avoid. By focusing on attention metrics, brands can shape smarter creative decisions and optimize media planning for real engagement, ensuring every rupee spent earns genuine consumer attention. Here’s how:   Creative Video Strategy: Build Ad Campaigns People Stay With  The campaign highlights clearly demonstrate that audience attention is not guaranteed; it must be earned through thoughtful creative choices.  Key implications:  Shorter formats respect user choices and reduce cognitive ad fatigue.  Creative storytelling should prioritise clarity and impact within tighter runtime limits.  Low mute/PIP levels indicate the ad was accepted rather than avoided.  Attention metrics data replaces guesswork with evidence, helping brands choose formats that not only convey their message but keep viewers engaged.  Media Efficiency: Focus on Attention Metrics, Not Just Viewability Ad engagement is no longer determined by cost per impression but by cost per high-attention impression. The campaign findings suggest:  High viewability doesn’t guarantee valuable ad exposure.  Formats with higher attention scores should receive higher budget allocation.  Advertisers should prioritise placements that reduce disruptive behaviours (mute, PIP).  Optimizing campaigns based on attention metrics allows brands to maximize real engagement and improve overall campaign performance, not just reported visibility.  How Attention Ad Measurement Enhances Fraud Detection Signals Attention metrics offer value beyond creative and planning insights; they strengthen ad fraud detection. Fraudulent traffic can mimic traditional metrics like impressions and viewability, but it cannot replicate the natural variability of human attention. Bots do not:  Display inconsistent completion patterns  Trigger realistic mute or PIP behaviour  Show behavioural fluctuations across formats  When attention signals appear unnaturally uniform or abnormally perfect, they help identify suspicious activity that standard fraud filters may not catch.  This creates a powerful layer of quality assurance by merging traffic validation with engagement behaviour, ensuring advertisers pay only for impressions that reach real, attentive users.  Also know why attention metrics matter for marketers to eliminate MFA sites.  Conclusion: Drive Ad Effectiveness with Attention Metrics We go beyond viewability to offer a detailed analysis of behavioural signals that reveal how audiences truly interact with your ads. Attention metrics uncover the difference between an impression that’s merely delivered and one that’s genuinely absorbed. By understanding real user behaviour using ad fraud detection tool, brands can optimize creative choices, refine media planning, and eliminate wasted spend with far greater precision.  When attention becomes the foundation of measurement, campaigns become sharper, more efficient, and more aligned with what today’s audiences actually respond to.  Want to ensure that your ads are only seen by humans and not bots? Connect with our mFilterIt experts to create a high-performing campaign by evaluating your impressions quality and ensure that your ads are only seen by humans.  

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Device Spoofing

Device Spoofing at the Impression Level: How User-Agent Anomalies Impact Campaign Data

Blog, Mobile Ad Fraud /

Detecting fake devices isn’t as easy as it used to be.  There was a time when the red flags used to be clearly visible – random clicks at odd hours or sudden traffic spikes from unfamiliar regions. Those patterns made it simple to tell when bots were at play.  But fraudsters have now become smarter. Instead of relying on easily traceable bot behavior, they now use sophisticated techniques to spoof impressions and pretend to be real users on real devices. This next-level masking of fake devices as real is known as device spoofing, and it’s quietly reshaping how ad fraud hides in today’s campaigns.  Unlike traditional bot traffic, spoofed devices mimic genuine user behavior so well that standard validation platforms struggle to tell them apart. The result? Campaign dashboards that look real but are actually filled with fake interactions. What is Device Spoofing? Techniques Used for Device Spoofing Device spoofing is a sophisticated ad fraud technique where fraudsters disguise fake, old, or low-quality devices to appear as genuine, tricking marketers into counting them as real users. Common device spoofing techniques include:  Geo-Location Manipulation Fraudsters spoof GPS coordinates or use proxies/VPNs to mimic users from premium regions. This helps them access high-value audiences and inflate campaign reach in targeted geographies without using real devices.  Simulated or Fake Devices Fraudsters alter device IDs, OS versions, screen resolutions, or hardware profiles to make outdated or non-existent devices appear new, authentic, and high performing.  Browser Spoofing They alter browser fingerprints, including headers, plugins, versions, and configurations, enabling fake environments to perfectly mimic real browsers and bypass platform-level verification or anomaly detection systems.  User Agent String Manipulation Fraudsters manipulate technical details like device IDs, operating system details, user-agent strings, browser information, etc., making it difficult for ad platforms to detect them as fake devices.   This means, while you believe your ads are reaching real people, a portion of that ‘audience’ might actually be nonexistent, generating fake impressions.   In a recent case, our tool detected a surge of ad impressions coming from devices supposedly running on Android OS 6. On the surface, that seemed fine until our system cross-checked the actual device model metadata.  It turned out that these devices were originally released with Android 9, supporting upgrades to Android 10 or 11.  This technical mismatch, an outdated OS appearing on a newer model, was a clear red flag. It revealed that fraudsters had manipulated the device identity to make fake traffic appear genuine, hoping to slip past standard detection systems.  Why Marketers Need to Validate Device IDs in Their Campaigns? Device IDs and user-agent strings are two of the earliest signals that define “who” your ads are actually reaching. Device spoofing doesn’t just manipulate campaign data because when these signals are manipulated, everything built on top of them becomes unreliable. Here’s how:  Device IDs are the backbone of attribution, frequency & measurement Device IDs determine how platforms track reach, frequency, and conversions. When fraudsters spoof or rotate them, one device appears as hundreds of unique users. As a result, frequency caps stop working, and attribution becomes inaccurate. Marketers unknowingly pay more to reach fewer real users because the foundational identity signal is corrupted from the start.  User-agent strings validate whether a device ID is plausible A device ID is easy to fabricate, but a user-agent string provides context about OS, browser, and device type. When these don’t match, like a new device running an outdated OS or many IDs sharing the same UA, it signals synthetic traffic. UA validation helps separate real devices from scripted environments.  Unchecked device IDs pollute media optimization & audience models Fake device IDs contaminate remarketing pools, distort lookalike audiences, and push automated bidding systems toward non-human traffic. Over time, targeting becomes less accurate and more expensive, even if campaign metrics appear stable. The performance engine quietly drifts away from real customers because its learning data comes from manipulated or spoofed identities.  Device & user-agent inconsistencies reveal impression-level fraud early Device and UA metadata are available from the first impression, making them valuable for early fraud detection. Mismatches in OS versions, device lifecycle, browser type, or session stability quickly expose spoofed devices. Identifying these inconsistencies upfront prevents downstream wastage and protects campaign performance before budgets begin to leak.  This helps marketers ask better questions Understanding device IDs and UA signals helps marketers challenge suspicious reach spikes, inconsistent delivery, or unexplained traffic patterns. It encourages smarter conversations with publishers and reduces reliance on surface-level KPIs like CTR. In an ecosystem full of manipulated traffic, signal literacy becomes a strategic advantage for protecting ROI and improving transparency.  Therefore, advertisers need advanced ad fraud detection solutions like Valid8 by mFilterIt to protect their ads from device spoofing. Our tool helps validate device IDs, user-agent strings, and impression-level signals in real time.   This enables the marketer to take investment decisions with confidence and ensure their ads reach the right audience.   For more information, contact our experts.

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brand safety

Why Addressing Regional Nuances is Critical for Effective Media Brand Safety?

Blog, Brand Safety & Suitability /

When we think about brand safety, the first things that often come to mind are avoiding explicit, harmful, or misleading content. But in reality, the risks can be far more nuanced—especially when advertising across regions with diverse languages, cultures, and contexts. What feels neutral in one market might carry sensitive undertones in another. Take culturally diverse regions like India and MENA. In India, where dozens of languages and dialects coexist, a word that seems harmless in Hindi might have a very different, even offensive, meaning in Tamil or Bengali. In MENA, imagery or references that are acceptable in one country may be viewed as inappropriate or insensitive in another due to local religious or cultural norms. A single oversight can unintentionally shift how audiences perceive your brand. This is why regional nuance matters. Brand safety isn’t just about avoiding the obvious—it’s about ensuring your campaigns respect cultural sensitivities and linguistic differences. Without this lens, even the most well-crafted campaigns can end up in the wrong context, putting brand trust at risk. So, here’s the critical question every advertiser and marketer must ask: Are you confident your ads aren’t being placed next to culturally unsafe, politically charged, or regionally sensitive content? If your answer is “not entirely,” you’re not alone. In this article, we’ll explore: Why addressing regional nuances in brand safety is no longer optional Why markets like India and MENA demand special attention Why generic brand safety solutions fall short How regional intelligence ensures your ads stay relevant, respectful, and truly safe Why Addressing Regional Complexity is the Need of the Hour? India’s digital audience is incredibly diverse, and the demand for vernacular content is growing rapidly. Users are increasingly engaging with videos and posts in Hindi, Tamil, Telugu, Bengali, and many other regional languages across YouTube and other social media platforms. In fact, YouTube recorded a 60% surge in regional language viewership between 2017 and 2020. This isn’t a short-lived spike; it reflects a fundamental shift in how people across India consume and connect with digital content. Moreover, in MENA, Arabic dialect content dominates social platforms, OTT, and digital news consumption. This means brands are exposed to risks that go beyond the usual categories of violence, hate speech, or adult content. Regional complexity includes: Slang and satire that generic filters miss. Cultural references tied to festivals, traditions, or taboos. Political undertones embedded in everyday entertainment content. Religious cues that carry heavy meaning in local communities. Audiences today are hyper-aware. They don’t just notice what you advertise; they notice where you advertise. A misplaced ad next to unsafe local content isn’t seen as an accident, it’s seen as a lack of cultural sensitivity. This is why addressing regional complexity isn’t optional anymore, it’s a foundational need to protect brand trust. Why Regions Like MENA and India Demand Specific Attention Brand safety can never be a one-size-fits-all-strategy. MENA and India represent two distinct digital ecosystems. Both offer ample opportunities for brands, but their complexity makes them uniquely challenging when it comes to ensuring brand safety. Generic designed frameworks fall short because they do not account for the linguistic diversity, cultural nuances, and socio-political sensitivities that define these regions. In India: Languages like Hindi, Tamil, Malayalam, and Punjabi come with their own slang and mixed-language usage like Hinglish, etc. Festivals are frequent and deeply cultural, often tied to religion. Associating with the wrong content during these times can backfire rapidly. Politics and religion influence narratives across states during high-stake or emotional times like elections, tragic events, etc. In MENA: Arabic dialects differ widely. Egyptian Arabic is not the same as Gulf Arabic. Religious sensitivities are paramount; even seemingly neutral symbols can be inappropriate in the wrong context. Political undercurrents often blend with news and entertainment content, making context harder to spot without regional awareness. Therefore, with such complexities, audiences in every region expect brands to demonstrate cultural sensitivity, not appear besides offensive narratives. Know more about how brand safety threats are evolving in culturally diverse regions like India, and MENA. The Consequences of Avoiding Regional Contexts When brands avoid regional nuances, the risks are immediate: 1. Consumer backlash: A single screenshot of an ad next to unsafe content can spread across social media in minutes. 2. Loss of credibility: Cultural insensitivity erodes brand integrity, especially in markets where respect is highly valued. 3. Regulatory violations: In tightly controlled industries like banking, healthcare, or politics, the wrong placement can trigger compliance issues. The Gaps in Generic Brand Safety Solutions Most traditional media brand safety tools use a limited set of predefined categories to identify brand safe or unsafe content such as: Adult or explicit content Violence and graphic imagery Hate speech Political or religious extremism While these categories are essential, they represent only a fraction of the risks brands face in culturally diverse regions. These frameworks fail to capture the regional nuances of local language, culture, and context. And as a result, brands unintentionally end up endorsing unsafe content, damaging trust and ROI. Here’s what generic media brand safety tools often miss: Politically charged regional narratives that are highly sensitive during local election cycles. Culturally inappropriate use of colors, symbols, or metaphors, which may have specific religious or social implications. Localized hate speech or community-specific terms, expressed in vernacular languages or dialects outside the scope of English-only keyword lists. Subtle cues in satire, memes, or slang that convey offensive or divisive undertones but are invisible to global classifiers. This not only exposes brands to reputational harm but also creates the perception that they are indirectly funding harmful narratives. Over time, such misplacements erode customer trust and weaken brand credibility in markets where cultural sensitivity is non-negotiable. This is why the industry needs to shift from generic brand safety to regional intelligence. The Shift Toward Regional Intelligence The digital landscape is evolving fast, and brand safety must evolve with it. The shift is clear – from generic filters to regional intelligence. Regional intelligence in brand safety means embedding cultural, linguistic, and contextual

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mFilterIt's Attention Metrics Tools

How mFilterIt’s Attention Metrics Tools Differs from Competitors?

Blog, Ad Fraud Blog - Valid8 /

Most branding campaigns today are measured by impressions, clicks, and viewability scores. These numbers can confirm that ads were displayed on a screen—but they reveal very little about whether the audience actually paid attention. An ad might be technically viewable, yet ignored, skipped, or scrolled past in a split second.  That’s why marketers are increasingly turning to attention measurement. Unlike traditional metrics that focus on exposure, attention metrics uncover whether ads truly capture consumer focus and influence behavior. In today’s crowded media landscape, it’s not enough to win screen space—you need to win meaningful human attention.  The real challenge, however, is choosing the right solution. While some tools provide only surface-level visibility checks, others go deeper to show how attention translates into engagement and impact. In this blog, we’ll compare these approaches—highlighting how mFilterIt measures attention across the full funnel to help brands optimize campaigns, reduce wastage, and drive ROI.  Why Attention Metrics Matter? Traditional metrics like impression and viewability only measure if the ad was viewed or not based on the standard IAB viewability criteria. According to this, a display ad is considered to be ‘viewable’ if at least 50% of its pixels are visible on the screen for one second, and a video ad is considered to be ‘viewable’ if viewed for two seconds.  However, these criteria might light up the dashboards with green signal metrics but do not answer the real questions.  Was the ad genuinely noticed? Did it capture attention long enough to influence action? Did it contribute to measurable outcomes? This is exactly what attention measurement does.  It captures the right set of insights required to know whether a particular campaign performed well or not. What further steps need to be taken at the optimization level.  But do all attention metrics tools offer the right set of insights you need? Here’s how you can find that out.  Here are four key dimensions that brands need to consider while evaluating attention measurement solutions:  Depth of measurement – Moves beyond basic visibility to capture interaction, dwell time, and attention stickiness.  Funnel coverage – Assesses attention across the journey, from awareness to engagement to conversion.  Optimization readiness – Ensures real-time, actionable insights that can directly help in optimization of media and creative strategies.  Adaptability across channels – Verify that the solution delivers accurate insights across regions, platforms, and emerging environments like OTT/CTV.  How mFilterIt Differentiates from its Competitors? Stage-by-stage Breakdown When evaluating attention metrics tools, it is important to recognize how they measure performance across the campaign funnel – top, middle, and lower stages. To understand the real impact of attention analytics advertising, brands need to move beyond surface-level simple viewability indicators and assess how focus translates into outcomes at every step of the customer journey.  Here’s how we at mFilterIt takes a differentiated approach compared to competitors.  Awareness & Reach Stage – Top Funnel Competitor approach: Focuses on surface-level visibility signals like impressions, audibility, player size, and exposure time. While these confirm the ad was served, they fail to reveal whether the user actually noticed or engaged with it.  mFilterIt approach: Our ad fraud solution, Valid8, goes beyond visibility to assess real view-worthiness, tracking mute percentage, skip percentage, scroll behavior, fullscreen or PiP usage, and contextual relevance. This ensures brands measure whether ads are actually seen and absorbed by users rather than just being displayed.  Consideration & Engagement Stage – Mid Funnel Competitor approach: Relies on proxy metrics like cursor hover or generic data, which provide limited insights into the depth of engagement.  mFilterIt approach: Measures authentic engagement behavior signals, including scroll depth, unmute/mute events, fullscreen adoption, repeated interactions, etc. It also segments engagement by audience type and placement (creative performance, audience segments, and placement quality), enabling marketers to make informed adjustments and design more effective mid-funnel strategies.  Conversion & Action Stage – Lower Funnel Competitor approach: Often stops at the conversion level or requires 3rd party uplift or attribution tools, leaving advertisers with fragmented data that does not connect directly to outcomes.  mFilterIt approach: Maps attention signals to business results, linking behaviors like bounce rate, time on site, OTT/CTV drop-offs, and conversion likelihood. This allows brands to spot underperforming placements, optimize spend, and tie attention directly to return on investment.  Regional Accuracy and OTT/CTV Attention Measurement – A Major Differentiator Most competitors rely on standardized viewability or attention models that overlook the local nuances of user behavior, cultural context, fraud patterns, and brand safety requirements. This often leads to misrepresentation of campaign effectiveness in diverse markets.  On the other hand, mFilterIt’s Attention Measurement Tool embeds regional data intelligence and advanced fraud detection into its measurement framework. It ensures that brands receive contextually accurate and market-relevant reporting.  In addition, mFilterIt brings a distinctive advantage in OTT/CTV ecosystems, where risks of ad overexposure, inflated impressions, and fraudulent traffic are notably high. By combining attention-first measurement with invalid traffic (IVT) checks and brand safety validation, mFilterIt ensures ads reach the right audience segments while controlling costs and maximizing genuine engagement.  This approach enables brands to move beyond surface-level metrics and gain a true view of audience behavior across regions and media platforms.  Therefore, if you operate across diverse regions, multiple platforms, and emerging channels like OTT/CTV, you may need an attention metrics tool that provides deeper, more contextual insights rather than relying solely on contemporary benchmarks.  Final Thoughts The advertising industry has evolved far beyond counting impressions, and if you are still stuck only on those metrics, you are probably lagging behind. To keep up with the competition, brands need to know whether their campaigns are truly resonating with real people and driving meaningful outcomes.  Therefore, it is important to use advanced solutions that connect attention with authentic engagement beyond viewability and drive true business impact.  So, if you’re ready to move beyond surface-level validation and unlock the real value of your advertising, it’s time to explore mFilterIt’s attention metrics intelligence.  Book a demo today and see how attention metrics can transform your advertising strategy. 

How mFilterIt’s Attention Metrics Tools Differs from Competitors? Read More »

How MFA Sites Hurt Ad Performance

How MFA Sites Hurt Ad Performance and Why Attention Metrics Matter for Marketers

Blog, Viewability /

Do you usually find yourself wondering what is the real impact of the branding campaigns that I have run? Where did the audience go? Why isn’t the performance on dashboards not translating into outcomes? Here’s the truth that might hurt a little – An ad ‘seen’ does not mean it is seen by the people who matter. Your programmatic campaigns, specifically planned to maximize reach, visibility, and engagement, might be only getting seen by bots or irrelevant audiences due to it’s automated nature and vulnerability. The ads could be running on MFA (Made-for-Ad) sites, pages designed to game the system, packed with cluttered ads and irrelevant content. These environments drain budgets, distort performance metrics, and leave marketers chasing numbers that mean nothing. According to a report by ANA, brands waste 15% of their ad spend on MFA sites instead of premium inventory, and most marketers don’t even realize it’s happening. So here’s something you need to focus on if you want to move the needle. Because viewability doesn’t equal visibility, and visibility doesn’t equal attention. Therefore, marketers still focusing on just the viewability metrics to measure an ad’s performance, need to move beyond vanity metrics and start looking at what really matters – attention measurement or also called attention metrics. For modern marketers measuring attention is a more reliable and smarter way of understanding whether ads are truly working or not. Let’s understand how it really helps. In this article, we will unpack: What are MFA sites and why marketers need to care? Why is viewability no longer a reliable metric to measure ad performance? Why is it important to measure attention metrics? How to eliminate MFA sites? How does an ad fraud solution like Valid8 by mFilterIt help brands to optimize for real impact? What are MFA (Made-for-Ad) Websites? How These Sites Impact Campaign Performance? MFA (Made-for-Ad) websites, also called arbitrage sites, are not made for efficiency, visibility, impact, or to reach real audience. They are solely designed to steal the ad revenue being spent by marketers. These sites, on the surface, may look like legitimate publishing platforms with articles, images, or even video content; however, are filled with thin or recycled content, clickbait headlines (often fake news), and layouts overloaded with ads, including tactics that encourage accidental clicks. The working model of MFA sites is to exploit programmatic campaigns by doubling impressions and ad spend, while delivering no real user engagement. Here’s a quick breakdown of how MFA sites work and manipulate the whole programmatic ad ecosystem: Auto-refresh: Ads reload every few seconds, inflating impression counts (CPM metrics) without giving users time to process the message. Fake content loops: Articles mimic real stories but lead nowhere, trapping users in an endless cycle of clicks without giving meaningful information. Aggressive layouts: Ads are stacked near navigation buttons or scroll traps, tricking users into accidental clicks and artificially boosting CTRs. Traffic laundering: The automated nature of programmatic campaigns often bundles MFA domains as safe inventory, making them appear legitimate in DSPs and SSPs. All this contributes to budget wastage, as most DSPs and SSPs don’t classify MFA traffic as fraud. The impact on campaigns is significant, with high bounce rates, negligible dwell times, and minimal brand recall. For branding managers running branding campaigns, it dilutes your message, associating your brand with poor-quality environments. Why is viewability no longer a reliable metric to measure ad performance? Viewability has been the industry standard to measure ad performance for years. According to IAB (Interactive Advertising Bureau) guidelines, a display ad is considered “viewable” if at least 50% of its pixels are visible on the screen for one continuous second, and two seconds in case of a video ad. A standard that is now too easy for fraudsters to manipulate, and MFA sites do exactly that. Some common tactics used in MFA sites to inflate CPM campaign models include: 1. Ad stacking Multiple ads are layered on top of each other in a single placement. Only the top ad is visible to the human eye, but every ad in the stack registers as “viewable.” Advertisers end up paying for impressions that never had a chance of being seen. 2. Pixel stuffing Ads are shrunk into tiny 1×1 pixel placements that are invisible to users but still count as “in view.” To reporting systems, the campaign looks like it’s meeting viewability standards, but in reality, no human could ever engage with these ads. 3. Auto-refresh placements Ads are fixed to corners of the screen or reload every few seconds to inflate impressions. They remain technically viewable but rarely capture user attention. These tactics make dashboards look green, but in reality, high viewability doesn’t equal high value. Viewability metrics give marketing teams a false impression that their ads are performing, but do not reveal if users genuinely noticed, processed, or engaged with the ad. This is why relying on viewability alone is no longer enough. It has become a vanity metric, only useful for technical checks, but meaningless when it comes to proving real business outcomes. Today, the focus has shifted to attention metrics, which provide a truer measure of whether an ad actually made an impact or not. Here’s How Attention Measurement Makes a Difference Attention metrics are about measuring the reality of how each programmatic or branding campaign performs. These metrics don’t just confirm if an ad appeared on screen; they measure whether it actually captured user interest. This includes tracking metrics such as: In-view duration: How long the ad stayed visible. Engagement signals: Scroll depth, clicks, dwell time, video played with sound, whether skipped or not, etc. Completion with focus: Whether a video was watched without being muted or minimized, and quartile progression. Contextual relevancy: Whether the surrounding content was contextually relevant to the ad and encouraged the user to stay. Here’s what we consistently observe at mFilterIt when auditing campaigns polluted with MFA inventory: Therefore, unlike viewability, attention metrics reflect real human behavior. It reveals if users scroll past your ad

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attention metrics

What Are Attention Metrics: Why Brands Need To See Beyond Viewability

Blog, Viewability /

Marketers have relied on viewability as a metric for the longest time to measure the success of an ad campaign. Afterall, an ad seen means the ad is working – right? But with the auto-play video ads in the picture and the attention of the users moving to instant scrolling, the ad being just viewable cannot be reliable. The hard truth that modern marketers are realizing – the ad might be technically “seen” but it can be completely being ignored by the audience. Focusing just on viewability metrics is not sufficient to understand whether the user absorbed the ad’s message or not. Therefore, the need for an advanced ad metric to evaluate ad performance was required. This shifted the focus to attention measurement or what the industry now calls attention metrics. In today’s ecosystem, where digital platforms are cluttered, user behavior is fragmented and choose what they really want to pay attention to, being seen is no longer enough. Brands need to understand the real difference between a wasted impression and a meaningful engagement. In this blog, we’ll break down why viewability metrics are no longer enough, what attention metrics actually are, how they differ from traditional viewability, and how ad fraud detection solutions like Valid8 by mFilterIt are helping brands optimize not just for ad impressions, but for real impact. Why Viewability Is No Longer Enough For years, viewability has been the go-to metric to validate ad delivery. According to the IAB (Interactive Advertising Bureau) standard, an ad is considered “viewable” if 50% of its pixels are in view for at least one second (for display) or two seconds (for video). Let’s take an example, think about a banner ad placed in the middle of where the page scroll ends. As per the IAB standard, if it is 50% visible, it will be considered viewed. But in reality, your ad failed to get the attention of your viewers. Or a muted video ad that autoplay’s in the background, technically viewed, but your user never saw it. This is where improvement was really needed from older viewability standards, which didn’t account for whether the user ever saw the ad at all. Viewability is a binary metric. It doesn’t reveal: Whether the user noticed the ad Whether it resonated Whether it drove engagement or action What are Attention Metrics? Attention metrics is a more advanced, holistic way to measure ad engagement. They go beyond visibility and ask: Did the ad actually capture the user’s attention? Rather than relying on a single data point, attention metrics pull together a wide array of proxy measurement signals – behavioral, device context, user intent. Here’s how each signal helps reveal true engagement: 1. Time in View An ad seen for 1 second isn’t equal to one seen for 7 seconds. Example: If a user pauses scrolling and watches your ad for 8 seconds, it signals genuine interest, unlike someone who scrolls past instantly. 2. Scroll Depth How far a user scrolls before encountering your ad can impact its effectiveness. Example: If your display ad is placed lower on a webpage but still gets noticed, it reflects active user engagement, not passive viewability. 3. Position on Screen Ads placed at the top of the page are more likely to be seen but not necessarily remembered. Example: An ad shown at eye-level in the content zone is more likely to draw attention than one placed in the banner blind spot. 4. Audio Status (Mute vs. Unmute) Muted ads play in the background. Unmuted ads demand attention. Example: If a user unmutes a video, it’s a strong indicator they want to hear your message, far more valuable than just a view. 5. Pause/Play Behavior This signal captures active intent to watch rather than passive exposure. Example: If someone pauses your video mid-way and resumes later, they’re engaged. That’s meaningful attention; viewability cannot track that. 6. Skip Rate & Skip Point In skippable ads, when users skip matters more than if they skip. Example: If 80% of users skip at 3 seconds, your hook isn’t working. If most watch for 7-10+ seconds, you’ve captured their attention. 7. Screen Orientation Device orientation changes reflect real-time distraction or focus. Example: A user flipping their phone from portrait to landscape to watch your video indicates commitment. Switching apps mid-ad signals lost attention. 8. Click or Interaction Activity Clicking, swiping, or engaging with ad elements shows active intent. Example: Hovering over a CTA or clicking to expand a product carousel shows curiosity, an attention metric that impressions can’t quantify. 9. Dual-Screen Behavior This detects whether users are actively watching your ad or multitasking on another screen or app. Example: If a user switches to another app mid-ad (like messaging or social media), it signals attention drop-off, even if the ad was technically in view. The Core Differences: Viewability vs Attention Metrics Challenges Brands Face Without Attention Metrics Viewability metrics create blind spots across different ad formats, ultimately affecting how brands measure, optimize, and scale their campaigns. Here how: Display Ads 1. Lack of Depth in User Engagement – Without attention metrics, brands can’t differentiate between a view and actual user interest or interaction. 2. No Insight into On-Screen Placement Performance – Ads may be technically viewable but shown in low-engagement zones, leading to misjudged campaign effectiveness. 3. Inability to Identify and Prioritize High-Intent Ad Impressions – Without behavioral data like time-in-view or interaction rates, valuable signals for retargeting and optimization are lost. 4. Exposure to Display Ad Frauds like Ad Stacking – Without attention validation, fraudulent tactics such as ad stacking, where multiple ads are layered on top of one another, inflate viewability numbers while delivering zero real attention. Skippable Video Ads 1. Misleading Viewability and Completion Metrics – Videos may be counted as viewed even when skipped early, hiding poor creative ad performance. 2. No Visibility into Drop-Off Trends – Without skip point tracking, brands cannot identify where audience interest fades or how to refine the first few seconds. 3. Missing

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