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Bot Detection

What Should Marketers Look for in a Bot Protection Tool?

Blog, Ad Traffic Validation /

In today’s digital marketing landscape, bots impacting your campaigns, website analytics, and overall performance is becoming an enormous issue with all the organizations running any kind of advertising campaign. To put a stop on the ad fraud that is caused by bots, having bot detection tools is vital.  After all, how can you put a stop to bots if you can’t detect.   Unfortunately, many firms struggle to detect bot traffic, and the methods they employ are not all created equal. Choosing the right bot detection tool is essential for safeguarding your marketing efforts. Here’s a comprehensive guide to help you select the best tool for your needs. What Is Invalid Traffic and How Does It Relate to Bots?  Bot fraud in digital advertising generally falls in the category of invalid traffic by the marketers no matter good or bad since the bots are not the target audience and cannot be converted into a protentional lead.   Types of Invalid Traffic:    -General Invalid Traffic (GIVT) : It is one of the simplest bots that can be detected easily, and a lot of good bots traffic comes under GIVT as they are not meant to fool the bot detection tool. But some fraudsters may also deploy GIVT as they are easy to make and work against some of their targets.   -Sophisticated Invalid Traffic (SIVT) :  SIVT detection is the bots that one should look out for as these are more capable and are often designed to target to bypass cybersecurity and ad fraud prevention tool. For Example – sophisticated bots might imitate how a human would use a website so it would be difficult to identify between a human and bot. SIVT is common in ad fraud schemes. How Bots Impact Your Marketing Campaigns  Bots can have a negative impact on your digital marketing campaigns in several ways:  -Wasted ad spend: Bots can boost your impressions and clicks, resulting in ad spend burn. For example, if you bid on a brand term that costs $1 per click and a click bots on your ad 1000 times, you would have wasted $1000.  -Inaccurate reporting: These bots can alter your reporting data, making it nearly impossible to track the actual performance of your campaigns. For Example, if a bot is boosting your impressions by 50%, your CTR will appear to be much higher than it is.   -Damage to your brand: So, if your brands are revealed to internet bots, it might damage your brand reputation. For example, if a bot clicks on your ad for a product the customer is not interested in, the user will consider your ad spam.  How to Detect Bots?  Bots often use IP addresses that are associated with known botnets. Here some of the most common methods include  -IP address analysis: Bots often use IP addresses that are associated with known botnets so by analyzing the traffic by these IP addresses you can easily identify the bot traffic. -Behavioral analysis: Bots frequently engage in unusual behavior, such as rapidly clicking on adverts or viewing several pages in a short amount of time. So, by examining the behavior of your traffic, you may detect bot traffic. -Traditional Bot detection tools: They can only detect basic bot patterns and don’t have the capability to identify sophisticated bot patterns like click spamming or lead punching.  Limitations in traditional bot detection tools However, there are some limitations of using traditional bot detection tools.  Over time, bot patterns have become increasingly sophisticated, enabling them to mimic human behavior and carry out complex tasks such as completing sign-up forms or generating leads. Traditional bot detection tools often fall short in identifying these advanced bot activities due to their limited capabilities. Some key limitations include:  -Only Impression-level detection: Many tools rely on impression-level analysis, which may not be sufficient to identify advanced bots. This approach often overlooks nuanced behaviors that occur across multiple impressions or sessions.  -Limited to Pre-bid monitoring: Many fraud detectors focus on pre-bid detection because it is easier to conduct checks because they only need to consider two factors: geolocation and browser, and the success rate is only 2%.   Key Features to Look for in a Bot Detection Tool  -Utilization of the Latest Technology: One of the key features to look out for in a bot detection tool is whether it is using the latest technology to detect ad fraud. When looking for a bot detection tool, evaluate their technology. Many traditional ad fraud solution depend on outdated methods like 1×1 pixel tracking, offering limited visibility. In contrast, to identify sophisticated bot patterns the bot detection must use the latest technology. We use cutting-edge technologies like VAST and JavaScript to assess over 70 parameters of bot traffic for effective identification.  -Deeper and Comprehensive Checks: The bot detection tool will be able to provide deeper insights with a post-bid analysis. With a comprehensive full-funnel check the success rates are boosted by 30%-40%. This approach is reliable and eliminates blind spots in detecting bot activity or ad fraud.  -Omnichannel Coverage: An advanced ad validation solution provides robust protection across multiple platforms, including programmatic advertising, Connected TV (CTV), Over-The-Top (OTT) platforms, and Made for Advertising (MFA) websites. This comprehensive coverage effectively addresses all potential avenues for fraudulent activities.  -Real-Time Insights: The platform detects and assesses fraudulent behavior in real-time, allowing advertisers to take proactive measures to minimize losses and protect their advertising budget.  -100% Transparency: A critical feature of an advanced fraud detection tool is source-level transparency, this provision of detailed, source-level data enables advertisers to trace fraudulent activities back to their origins, ensuring accountability and enabling more targeted counter measures.  How mFilterIt help to detect sophisticated bots?   mFilterIt is known for its effective bot detection and ad fraud prevention capabilities. Ad fraud detection (Valid8) by mFilterIt offers real-time detection, granular insights, and comprehensive protection across the entire campaign lifecycle. By utilizing machine learning, behavioral, and heuristic checks, it ensures the detection of advanced-level bots leading to fraud-free campaigns, making it ideal for advertisers seeking

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impression-validation

Why Impression Validation Matters and Why MMP’s Solutions Fall Short?

Blog, Ad Fraud /

Ad fraud has become the most talked about thing in the digital ecosystem in the last one decade. Over the years it has become sophisticated and led to huge losses for the advertisers. According to the last measured stats, the potential loss due to ad fraud in 2024 will be around $100 billion.   And if marketers who are running impression campaigns are thinking that ad fraud is not impacting their ad campaigns, take a look at your campaign data.   If you see unusual traffic from sources outside your targeted area, there is one red flag for you to check. And like this, there are many more.   Impression validation is as crucial as validation of other hard key performance metrics. It helps advertisers get transparency at the beginning stage of the ad campaign and help them stop it at the root before it impacts the entire campaign, especially metrics like installs and events (like subscription, or first transaction) where the cost is higher.   Let’s understand in detail how impression fraud validation is essential for app marketers and how MMP’s are hiding the actual impact of fraudulent impressions.   MMP’s are hiding the full picture from you   Mobile Measurement platforms or MMPs often play a significant role in app marketing. They help the advertisers track the last click attribution of their ad campaigns and track app performance. There are a few MMPs who also provide ad fraud detection tool bundled with their attribution services. However, ad verification by MMPs have their own limitations.   -Focus on Attribution, Not Validation: Their core services are limited to attribution and not validation. MMPs get paid on the number of attributions made and when they detect fraud on these attributed sources, it directly impacts their revenue creating a conflict of interest. Therefore, they detect only 10-12% of the fraud and the rest of the fraudulent traffic remains undetected.  -Limited Scope of Fraud detection: The MMP’s don’t have the capability of doing deeper checks. They can detect fraudulent traffic based on basic checks and they often miss sophisticated fraud techniques.   -Lack of Real-Time Fraud Insights: The attribution platforms cannot provide real-time fraud insights to advertisers. Their usual timeline for generating ad fraud reports is D+7, where if the fraud is detected by the 20th, the advertisers will receive the report by 28th of the month. This further delays the preventative measures which the advertiser could have taken against these fraudulent sources.   Why App Advertisers Need to Look for an Advanced Ad Fraud Solution?   In comparison to the fraud detection done by MMPs, mFilterIt’s Valid8 solution uses a more holistic approach against the sophisticated fraud techniques. Some of the differentiating factors which will help you realize the difference:   -Transparency on real % of fraud: When MMPs detect less % of ad fraud, the advertisers are not aware of the actual number of fraudulent traffic sources. This further impacts the efficiency of the ad campaigns, and the advertisers end up losing money twice. First, on the invalid traffic interacting with their ads before validation, and second when the actual number is not reported by MMPs. With mFilterIt, brands can transparency at the source-level and identify which traffic sources are skewing the metrics.  -Provides real-time analytics and blocking: Using mFilterIt’s ad fraud detection solution, the advertisers can get real-time analysis of the fraudulent traffic and block them in real-time. This helps advertisers to save money on both invalid traffic on ads and attribution cost for these traffic sources to MMPs.   -Give full funnel protection: Unlike the MMPs, our ad fraud verification tool protects the campaign holistically. Our full-funnel coverage not just validates traffic at impression-level, but also at the install and event level to reduce the impact of fraud. This ensures that cleaner traffic reaches the end-of-the-funnel, resulting in a better conversion rate.   A Real Case  Here is a real case of a brand which was running an install campaign. By partnering with mFilterIt the brand was able to identify the impact of invalid traffic at the impression level. Upon further analysis we found two specific reasons for invalid traffic – impression spamming and traffic coming from incorrect region. We identified the cause and started blocking invalid traffic which resulted in an increase in organic traffic at the install level.    Takeaway  Ad fraud is evolving, and it can easily bypass the basic checks by MMPs. For advanced fraud techniques, you need an advanced ad fraud detection tool in your tech stack. While looking for an ad fraud verification vendor for your app campaigns, don’t believe the surface level reports and checks. It is time to ask for transparency and ensure that your entire ad campaign is protected, thereby your ads are seen by a genuine audience resulting in better conversions.   To get details on how we do it, get in touch with our experts  

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tracking

Pixel Tracking Guide: How to Track Conversions Easily

Blog, Ad Traffic Validation /

Tracking conversions is essential for measuring the effectiveness of your marketing efforts, and one of the most reliable ways to do this is through a conversion pixel. A conversion pixel is a small piece of code embedded in your website or landing pages, which tracks specific actions users take, like making a purchase or subscribing to a newsletter. This helps you evaluate your ads’ performance and refine future campaigns. How to track conversions using a pixel: 1. Install the Pixel: The first step is setting up a pixel on the platform you’re using, such as Meta Ads, Google Ads or mFilterIt Visit Pixel. These platforms typically provide easy-to-follow instructions for adding the pixel to your website. You’ll either add the pixel code directly to your site’s header or use a tag manager to simplify the process. 2. Define Your Conversion Goals: After adding the pixel, you need to define what actions you want to track as conversions. This could include activities like making a purchase, submitting a lead form, or completing a registration. Most platforms let you set up multiple conversion events to capture various types of user actions. 3. Test the Pixel: Once the pixel is installed, it’s important to test it to ensure it’s working correctly. Tools offered by platforms like Meta allow you to check if the pixel is firing as expected. If you find any problems, double-check your website’s code or try reinstalling the pixel. 4. Analyze and Optimize: When users complete the defined conversion actions, the pixel sends the data back to the platform, giving you valuable insights into your conversion rates. Use this information to see which ads or traffic sources are performing best and adjust your campaigns to optimize results. Tracking conversions with a pixel is a powerful way to evaluate return on investment (ROI), refine targeting strategies, and ultimately enhance the success of your marketing campaigns. Connect with us, to start your conversion tracking.

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Brand Bidding

Protection from Brand Bidding with AI and Automations for Brands and Ad Networks

Blog, Affiliate /

Competitors or affiliates may bid on your brand keywords, potentially driving up costs and diluting your brand’s presence. A comprehensive affiliate monitoring tool needs to be in place to safeguard your affiliate marketing spend and protect your brand reputation.  Identify affiliate and competition bidding on your brand keywords along with whitespaces across locations for own and competition keywords.    Brand bidding fraud costs approx. $1.3 billion each year as competitors bid on branded keywords. Over 60% of brand terms are targeted by competitors, inflating cost-per-click (CPC) by up to 30% and reducing conversion rates by 5-10%. This not only drives up advertising costs but also dilutes brand recognition, as 50% of users may click on a competitor’s ad when searching for a brand name. This leads to confusion and lost customers.   Businesses must actively monitor and optimize their paid search campaigns while implementing robust brand safety solutions to mitigate these risks.  What is Brand Bidding? Brand bidding refers to a practice that falls under paid search marketing. It’s a digital marketing strategy where brands bid on their own brand keywords in search engine advertising platforms like Google Ads and when someone searches for your brand name, your company’s sponsored listing is more likely to appear at the top of the search results page.   But this turns into a brand reputation threat and leads when aggressive affiliate bids, potentially aiming to capture traffic and drive sales through affiliate programs or competition bids on your brand keywords.    Why is affiliate monitoring needed for Advertisers? Affiliate monitoring ensures the integrity of campaigns, protects brand reputation, and optimizes performance.   Concerns in Brand Bidding:   – Campaign Integrity: Monitoring affiliate activities ensures that campaigns are running as intended. It helps to identify if affiliates are engaging in practices like brand bidding, misleading advertising, or promoting the brand inappropriately.  – Protecting Brand Reputation: When affiliates are bidding on brand-specific keywords (e.g., your company’s name or a competitor’s), it can confuse customers or misdirect them to other sites. Without monitoring, there’s a risk that your brand reputation could be damaged if affiliates don’t align with your brand values or make misleading claims.  – Optimizing Performance: By closely tracking affiliate performance, advertisers can identify high-performing affiliates and cut out low-performing ones. This ensures that advertising spend is allocated effectively, improving overall return on investment (ROI).  – Organic poaching: A major concern that brands should be careful about. It occurs when affiliates or competitors bid on a brand’s keywords, capturing traffic that would have naturally come to the brand’s website. This misappropriates organic leads and increases costs as the brand must pay commissions to affiliates for traffic that would have come organically.  Ensures unauthorized affiliates are not bidding on brand keywords or misdirecting customers. Prevent unnecessary commissions and preserve your organic search efforts.  Prevent affiliates from hijacking brand visibility, ensuring the brand stays front and center for potential customers without competitors benefiting from organic traffic.  Stopping organic poaching ensures that their customers are consistently directed to the brand, which enhances trust and customer loyalty.  Case Study 1: Brand Bidding for a Popular Shoe Brand Problem statement: Brand was facing challenges in ensuring effectiveness of keyword the brand bidding on across multiple geographies and wants to identify competitor bidding on their brand keyword.   mFilterIt Solution: mFilterIt analysis and insights into the effectiveness of brand bidding, we conducted a comprehensive analysis of a well-known shoe brand across major Indian cities.   We meticulously monitored 35 keywords related to the brand, including brand keyword variations across 35 cities. This allowed us to understand the search queries users were employing to find the brand.   The brand garnered a significant search volume across time slots. This indicated strong interest in and demand for the brand.   A substantial 50% of the total searches were Google Ads for the brand’s keywords. This demonstrated the competitive landscape and the efforts of various entities to capture search traffic.   We identified 28% were competitors count which were actively bidding on the brand’s keywords. This highlighted the intense competition for visibility and market share.    22% of the total came from affiliates and coupon websites who were also bidding on the bidding keywords. This revealed that affiliates were also using brand keywords and running ads.   mFilterIt Impact Here are some key observation and Findings:   – Organic Poaching by aggressive Affiliate Bidding: Affiliates & coupon websites were particularly active in bidding on brand keywords, potentially aiming to capture traffic and drive sales. They were capturing organic users. This is called organic poaching. The brand was having to pay commissions to affiliates where the customer would have come organically.   – Competition on Brand Keywords: Competitors were actively bidding on the brand’s keywords, which meant that competition keyword strategies needed to be built within the marketing approach.  AI based Optimization in Brand Bidding with mFilterIt LOCOKS LOCOKS (Location & Campaign Optimization Keyword Strategy) with AI-ML powered automation of brand bidding process can make identifying and bidding on brand keyword more efficient and controlled. It also prevents overspending on keyword bidding and can schedule when to start or stop the bidding and limit the budget spent for a particular time slot.   – Geo Based Tracking: Our tracker runs in different cities and analyses the different sources of traffic related to a set of keywords coming from various sources  – Intelligent Reporting: Identify when competitors invest more or less and on which keyword. Discover key periods when keyword competition increases or decreases and take action on the findings   – Time Based Tracking: Tracks on-the-basis of day – parting, hourly tracking, ad scheduling strategies of competitors and affiliates   – Seasonal Sales/ Discounts: As most frauds occur during the flash sales such as Black Friday, Prime day etc., we track the user journey to check the source.   Case Study 2: mFilterIt LOCOKS Solution for Optimizing Competition Keywords and Brand Visibility Problem Statement: An advertiser was struggling with white spaces in their campaign where both competition keywords and brand keywords were not targeted. They wanted to identify such whitespaces and explore

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Ad Fraud Verification

Is Your Ad Fraud Verification Partner Using the Latest Technology?

Blog, Ad Fraud, Leadership Voice /

Ad fraud is not any more a storm that comes and goes, it has become the reality in the digital ecosystem. The techniques have become sophisticated, and it is going to become difficult for advertisers to differentiate between a bot and a human. To protect the ad spends, the marketers need to adopt an advanced technique to combat the impact of ad fraud. For validating the ad traffic and helping advertisers get transparency of their traffic quality, there are ad verification solution providers. These verification partners play a crucial role in combatting ad fraud. They help advertisers understand whether their ads are seen by bots or humans. Advertisers, this question is for you: Is your ad fraud verification partner doing enough to protect your ads from ad fraud? More specifically, is your ad verification partner keeping up with the latest technology to protect your ad spends and ensure transparency in your campaigns? Let us help you decode this. Why Advertiser’s Need to Question Their Verification Partner? Imagine this, you’re investing money in your digital campaigns, with the trust that their ad verification partners are ensuring that their ads reach real humans and not bots. However, you realize that even after validating the digital ads, your ads are exposed to ad fraud.  You keep seeing weird patterns, high CTRs, low visit/click rations, fake leads, junk websites etc and you keep trying to work with your agency to optimize. But shouldn’t your Ad Verification partner take the burden of keeping your campaign from fraud? The question the advertisers need to ask their verification partner is not “what they are doing” but “how they are doing it”. Are they still using traditional methods to validate your ad traffic that leaves your campaigns vulnerable? Limitations of Traditional Ad Fraud Detection Technology Many traditional ad traffic validation vendors use the 1×1 image tags, which are essentially small, invisible traffic hits embedded in ads to track impressions. While these tags are easy to integrate and cost-effective (for the verification partner), they are inefficient in identifying fraud. It can only track impression hits and fails to validate sophisticated fraud patterns and doesn’t provide substantial insights to advertisers. It can easily be spoofed, the number of parameters it picks are only marginal, which does not allow any sophisticated fraud detection to be done. Parameters which 1×1 can pick: IP Address: This is now getting anonymized (courtesy apple, relay etc) which means it is a low confidence signal. User Agent: Most browsers now reduce the data sent in the user-agent and only put an indication of the device, stripping it from everything. Referral URL: Where did the user come from. It can also be spoofed and again is a low confidence signal. That’s it. Infact 1×1 is so weak that you can trigger it from your laptop repeatedly and all of those will get tracked. Its value is limited to counting impressions (and limited to that as well) rather than detecting fraud. It was more suitable for ad-servers like Sizmek etc. and not IVT vendors like DV/IAS etc. Even worse, some partners claim they’re using advanced technology while still deploying 1×1 tags in the background. Here’s why 1×1 tags are not enough to combat ad fraud: They only count impressions: These tags cannot give deep insights into whether the impressions were generated by bots or humans. No fraud detection: They lack the ability to identify patterns that signal fraudulent activity. Limited campaign insights: Critical metrics such as viewability, engagement, and location cannot be tracked. Easily spoofed: The metrics can be easily spoofed as there is no transparency of where the traffic came from. Why, then, do some traditional ad verification partners still use them? Because they’re simple to implement and allow verification providers to check the box without delivering real value to advertisers. Convenience over value Imagine you as an advertiser ask an IVT vendor to support publisher A. Publisher A is excited for the campaign you are providing and works with IVT vendor to be onboarded. Publisher A and the IVT vendor BOTH want to get this started asap, since there is money from the campaign to be made. They will take the easy route of integrating a 1×1 which is basically the simplest to plug in. Both will proudly declare to you how they are now “certified” partners and advertisers can now go ahead with 100% confidence that their campaigns are safe. Compounded with the fact that processing a 1×1 is generally 10x cheaper than a tag like VPAID or VAST. And the IVT vendor makes the same money from you across either tag (generally they charge on %age of media which is agnostic to the tag being used) But what if I told you that there are much better tech tags available. But your IVT vendor has lazily chosen the cheapest and fastest to plug in tag rather than consider your best interest in their mind? Advertisers, It’s Time to Clear the Smoke The technology used by these traditional ad fraud detection vendors is not enough to combat evolving ad fraud techniques. Their schemes are becoming more sophisticated and harder to detect. To detect these sophisticated frauds, advertisers need a solution that can go beyond the basic checks. Countering the 1×1 tags, there are JavaScript Tags and VAST tags, which help give a holistic coverage, providing deeper insights into traffic quality, user behavior, and potential red flags. Here’s what sets them apart: Comprehensive fraud detection: They can evaluate up to 70-80 parameters, including location, device type, session patterns, and viewability metrics. JS tags are a piece of code which runs on the client website / video player picking up many data points to detect how the ad is being served, visible, obstructions to it, content on the page, browser parameters, mouse parameters, screen size etc. which is very powerful in detecting the fraud. Real-time insights: These technologies can detect and act on fraud indicators in real-time, reducing wasted ad spend. Better campaign performance: By identifying

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Programmatic Advertising

Ai in Programmatic Advertising Fraud Detection to Deliver Performance and Sustainability

Blog, Programmatic /

The rise of programmatic advertising has shifted the focus towards accuracy and automation. It surged from $9.75 billion in 2023 to $12.46 billion in 2024, an annual growth rate of 27.8% and is expected to continue expanding, reaching $28.12 billion by 2028 at a compound annual growth rate (CAGR) of 22.6%. However, with AI coming into the picture, performance programmatic platforms are prone to ad fraud even more. The need for optimization of programmatic media buying with comprehensive ad fraud solution  across the advertising funnel is the necessity to yield results.   More and more advertisers are pushing for a stronger and harder success KPIs in programmatic advertising. The shift from visibility only to performance-first is underway. With new and upcoming programmatic platforms selling inventory on impressions, it is today evident that impression fraud is 10-15% of campaign spends in the MENA region, as per mFilterIt reports. There is a ROI uplift of 7-10% when advertisers identify and block for Made-For-Ad sites and Ad Frequency cap violations.  For advertisers, an ad traffic validation tool is the need of the hour to weed out fraud, optimise programmatic traffic and improve the hard KPIs of their campaigns. Also, programmatic platforms & ad networks have started providing ‘Certificate of Verification’ to advertisers to ensure their ad inventories are validated.    Let’s dig deeper into the explore how programmatic ad fraud detection can help elevate performance of ad campaigns and what are the key challenges.   Why Programmatic Ad fraud prevention? Protect your brand with programmatic ad fraud prevention. Ensuring the invalid traffic is blocked from malicious sources not only safeguards advertising budget but also protect brand reputation.   Safeguard Your Programmatic Ad Campaigns from Fraud-Explore Our Expert Solutions. Here’s how mFilterIt guides with trust and transparency in programmatic advertising:  Impression fraud Impression Fraud analysis is better at the post-bid stage than pre-bid, measuring performance beyond viewability metrics. In pre-bid analysis, i.e. before the ad is served, fraud can be identified based on only two parameters, IP and User Agents. Also, the time for analysis is limited to 10 milliseconds. This results in a meager 2% fraud identification.      This is where a post-bid analysis trumps a pre-bid impression validation. Now that we have several more parameters fraud detection is done on deterministic and heuristic measures as well. This results in the detection of higher invalid impressions of 15-20%.  This results in improved ROI on Ad spending. Post-bid impression analysis is a more beneficial method for detecting ad fraud.  Made for Ad sites Advertisers spend an average of 15% of their programmatic budget on MFA sites, but some may spend as much as 42%. While 35% of programmatic spending is wasted on low-value environments like MFA sites, according to a recent study by ANA (Association of National Advertisers).  By focusing on robust ad fraud detection advertisers can combat the various forms of fraud that undermine their campaigns across digital advertising platforms. Prioritizing impression validation is essential for maximizing return on investment and maintaining trust in the advertising ecosystem.    MFA Sites not only drain budgets but also pose a challenge to a brand’s safety. Limited reach and exposure, no real user engagement misleading clicks,  click fraud, artificially inflated metrics, poor conversion rates, low-quality/intent traffic and brand un-safe content tarnished brand image and lead to budget drainage.   mFilterIt identify ad placement on MFA sites with   Deep Content Analytics: A multi-faceted analysis using NLP & image & video analysis to identify brand unsafe content. Advanced AI-ML Sophisticated Algos: AI –ML driven analytics for extraction of meaningful insights, patterns, and information.  Regional & Contextual Understanding: Local language, cultural nuances and domestic norms lead to overall risk assessments. Extensive MFA Repository A collection of websites & metric measurement is gathered with regular updates & feedback loop  Fig. 1: The site has multiple ad-stacked ads with high refresh rates. It’s also brand-unsafe promoting gambling.   Ad Frequency Cap Violations The most common and often neglected issue is Frequency Capping  (F-Cap) violations along with bots spamming impressions for burning media budget. Brands need to be vigilant and identify F-cap violations to make sure their ad reaches the broader and relevant audience and is not seen by similar sets multiple times to generate impressions leading to ad fatigue, not conversions.  A quick succession of impressions generated from the same google advertising ID. Distribution for a genuine user could be distributed throughout the day.  These impressions were not only coming so excessively but were also being shown quickly. Multiple Impressions in a Short Period.  A single GAID generates multiple impressions quickly.  Impression Injection from subnets which reflect that the usage of device farm to fire multiple impressions. Subnets divide a larger network into smaller, more manageable sections. IP Repetition with Same IP, different users. It reflects high chances of fake impressions being injected with different GAIDs.  Same IP, Different Impressions. This issue is not limited to IP repetition, but it extends further with the same IP generating multiple unique GAIDs and different impressions.    Viewability & Attention metrics Instead of focusing on a single data signal, check on attention metrics along with viewability encompassing a range of data points. These are processed by a machine-learning model to estimate the probability that a specific media environment and ad creative will capture the attention of a hypothetical audience member.  However, Viewability only itself does not help in taking decisions when it comes to effectiveness or attention. Multiple factors need to be measured, monitored and acted upon swiftly. The Viewability and Attention Model encompasses several key factors that determine the effectiveness of an ad in capturing audience attention. Viewability refers to the percentage of an ad that is actually visible to users and the duration it remains in view.   It must also include:  Viewability Metrices % of ad viewability and number of second viewed based on IAB standards   Display ads should be at least 50% of the ad’s pixels are visible in the browser window for at least one second   Video ads must be at least 50% of the ad unit

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Mobile Ad Fraud

Mobile Ad Fraud: Challenges for Advertisers in the USA

USA, Blog, Mobile Ad Fraud /

As mobile app ads have become more pervasive, advertisers are facing growing concerns around app installation fraud and the complexity of detecting fraudulent activity, especially in markets like the USA, where the stakes are high. The U.S. market mobile ad fraud, with estimated losses of around $1.2 billion. The focus is on safeguarding the organic traffic stolen, preventing APK fraud and referral fraud along with full-stack fraud prevention that can help optimize ad campaigns and build trust and transparency across the digital advertising ecosystem.  Let’s dive deeper the unveil the various aspects of mobile ad fraud and how to combat them.  Challenges of Mobile Ad Fraud in the USA The mobile app ecosystem is growing and evolving and expanding across the global especially in the BFSI industries, the rise of Fintech apps and lending apps has also raised the stake of fraud prevention in app ecosystem.  Most app fraud prevention apps don’t cover the sophisticated and dynamic nature of ad frauds that lead to fake installs and thereby low return on investment.   Here are some of the major challenges:   Organic hijacking via Click Spam: Theft of organic traffic is one of the biggest hurdles in mobile app advertising. Deceptive techniques to mimic legitimate installs and generate traffic that appears organic, resulting in inflated numbers that distort performance metrics. It leads to skewed insights for advertisers who rely on authentic user data and affects the return on investment (ROI).    Click Fraud: Validating traffic with comprehensive click fraud prevention is a must for advertisers to excel in the competitive landscape and ensure that budget is spent on valid clicks only. The deterministic, heuristic and behavioral checks with google approved mFilterIt click tracker can help combat fraud like no other.   APK installs: Fraudulent mobile app ads are created to mislead users into downloading fake apps or counterfeit APK files. This compromises devices or artificially boosts install metrics. Detecting APK fraud is essential for ensuring that advertising budget is spent effectively and that users are protected from malicious content and bring true performance to their campaigns.  Referral fraud: Fake referrals or incentivized clicks driving traffic inflate numbers that affect campaign efficiency. Fraudulent end users use the coupons codes multiple times either by cloning the app or by using VPN/Proxies etc. creating multiple device environments in the same device.  By exploiting referral programs, fraudsters generate fake installs and impressions, tricking advertisers into paying for traffic that doesn’t convert. Implementing mobile ad fraud detection systems can protect advertisers who rely on mobile app ads to drive real user engagement.  How can advertisers combat mobile ad fraud? Make Payout for validated traffic and work with Trusted Publishers Validate traffic and pay for only genuine engagement. Identify the publishers the bring in influx of invalid or fraudulent traffic to your campaign and work with only trusted published to protect integrity of your ad campaign.   Encourage Good practice by Ad Networks to give a ‘Certificate of Validity’ Ad traffic validation could also support ad networks to authenticate and validate based on the performance to safeguard the interest of advertiser and builds clean and transparent digital advertising ecosystem.   Ask MMPs the right questions Do not trust the MMPs blindly, a third-party validation removes the suspicion around traffic validation as fraudsters bypass MMP fraud detection. Mobile Measurement Partners (MMPs) have become pivotal for marketers and businesses, especially in tracking app installs, user engagement, and campaign performance. However, recent developments highlight the limitations of solely depending on MMPs for ad fraud detection.  How deploying independent Third-Party validators build transparency? The most effective way for advertisers to combat mobile ad fraud is by using independent third-party validators—an unbiased, external layer of protection. Validate the fake traffic and interactions associated with an ad campaign. mFilterIt offers a comprehensive ad fraud detection system powered by advanced artificial intelligence and machine learning algorithms. It can identify suspicious patterns with deterministic, heuristic, and behavioral checks.   It enables advertisers to identify and block fraudulent activities before they drain their budgets and ensure that only genuine traffic is counted, reducing the risk of fraudulent interactions, like click fraud, bots, and fake impressions. As an essential step in the fight against ad fraud and invalid traffic, it is important to validate before advertisers, ad networks and agencies collaborate with publishers.  Monitor and verify each install or click with Mobile ad fraud detection solutions. It helps in identifying APK fraud, referral fraud, and protects organic traffic from being stolen. Proactive fraud prevention using data-driven strategies preserves the integrity of mobile advertising campaigns and ensures it delivers true value.  Impression Integrity: Start with checking up impression integrity with Impressions validation, ad visibility and post-bid validation.   Click Integrity: Weed out invalid or fraudulent traffic and bots with click fraud prevention.   Install Validation: Check if the installs are by genuine customers or bots also follows up tracking soft KPIs and events triggered such as registration, logins or signups.   Re-engagement & Post-back Blocking: Hard KPIs such purchases, deposits, and transactions also need to be validated for efficient re-engagement and post-back blocking.  Advertisers and developers need to adopt robust ad fraud detection systems with advanced algorithms and machine learning tools to identify suspicious patterns and block fraudulent activities. As an essential step in the fight against fraud, validate before collaborating. Trusted ad networks and ensured transparency in mobile ad transactions.  Here are some benefits of proactive mobile app fraud prevention:  Weed out fraud to improve ad campaign efficiencies  Enabling brands to take better-quality business decisions  Show funnel visibility & transparency basis performance  Optimizing the publisher ecosystem  Case Study: How FinTech App identified high volume of Fake Installs Problem Statement Fake app installs were significantly inflating the user acquisition costs and reducing the efficiency of marketing campaigns. They needed to identify sources of such fake installs and block them. High volume of fake install adversely affects the overall return on investment (ROI).   The Challenges Inability to accurately measure genuine user engagement and conversion rates. Due to a lack

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Stock Availability

Is lack of Accurate Stock Availability Metrics Impacting your Ecommerce Revenue?

Blog, Digital Shelf Analytics /

Product availability is the key issue for brands looking to expand their presence across the fast-paced E-Commerce landscape. With the expansion of new categories that cater to shoppers’ last-minute needs, quick commerce platforms are expanding their horizons. There is a need to measure and monitor stock availability performance across platforms and geographies. Customer loyalty is affected by availability issues as the industry figures suggest that 20-30% of customers may switch to competitors permanently after encountering product unavailability. Also, Tier 2 and 3 cities may face upto 20% more disruptions due to logistical challenges caused by lack of accurate and high-quality availability metrics.  Let’s dive deeper and assess the core issues that brands face on ecommerce and quick commerce platforms. It is important that digital first customer-facing product-oriented brands today understand that reducing out-of-stock occurrences can lead to a lift of revenue by 5-8% with real-time business intelligence and insights.   Are you getting the right numbers on e-commerce and quick commerce platforms?   Every quick commerce and e-commerce platform has its own set of challenges, but getting out-of-stock poses a major challenge for brands looking to strike hard at the moment customers is looking for them. This not only puts them out of the race but also lose a loyal customer looking for your brand.   What should brands do to maintain stock availability? Keep track of every SKUs in real-time, drill deeper to find out which product is out-of-stock or about to be out-of-stock on which platforms and at which dark store under a pin-code. In-depth analysis and actionable insights are the only way to keep you ahead in this fast-paced race on online shopping platforms.   A brand stock-out or going out of stock (OOS) can occur due to various reasons like supply shortage, poor inventory management, inaccurate forecasting of demand or unexpected demand surge, etc. The key is digital commerce intelligence on stock availability and real-time alerts on Out-of-stock status.  The availability monitoring should not be limited, it should be a more granular update such as on certain pin codes where is your product available? Where they stand vs competition? On which platform brand need to stock it up?  For instance, a shopper looking for a specific product of the brand might search on multiple platforms as well.   This means brands must monitor their presence across platforms at the pin-code level and on the platform’s dark stores. Here are some key metrics that brands must track within the stock availability monitoring:   Brand availability trends versus competition   Availability share versus competition  City-wise availability trends – monthly, weekly, daily, and hourly  Platform-wise & geography-wise analysis  Heat map to identify new geography to target  Tracking Bottlers’ (Sellers) performance  Maintaining Out-of-Stock product lists & real-time alerts  This is where mScanIt, digital commerce intelligence comes in handy as it covers all aspects of product availability monitoring across platforms and geographies. Leading brands from FMCG, electronics, beauty and personal categories trust us as it covers more than 150 e-commerce and quick commerce platforms across the world, drilling deeper within city-level analysis along with global coverage of multiple geographies.   Case study: How a global leader in the beverage industry improved availability across platforms and geographies Problem Statement A global leader in the beverage industry faced challenges in ensuring consistent product availability across digital platforms in key AMESA (Africa, Middle East, and South Asia) markets. In September, product availability in the KSA region on prominent platforms like Quick Market, Carrefour, and Nana was inconsistent, reported at:  Quick Market: 28%  Carrefour: 57%  Nana: 86%.  This lack of availability led to:  Missed sales opportunities  A weakening of consumer trust and brand loyalty  Limited visibility in a competitive digital landscape  The company aimed to bolster its market presence by enhancing availability through real-time monitoring, identifying supply chain inefficiencies, and ensuring sellers maintained optimal stock levels.  How mFilterIt helped the brand boost its brand presence to match the competition across geographies To address these challenges, the company partnered with mFilterIt to implement the Digital Shelf Monitoring, mScanIt a cutting-edge solution designed to monitor product availability across multiple platforms and geographies along with other KPIs such as keyword share, product page content, Feedback analysis of rating & review and product pricing and promotions. Here’s how our capabilities lead the way.   Real-Time Monitoring with Regular updates on product availability and stock levels across Quick Market, Carrefour, and Nana.  Alerts for out-of-stock (OOS) items, enabling immediate corrective actions.  Gap Analysis helps identify bottlenecks in the supply chain impacting stock availability.  Provided detailed insights into seller performance and platform-specific challenges.  Actionable Recommendations helped develop region-specific strategies to enhance stock levels, such as improving coordination with bottlers and distributors.  Prioritized high-demand SKUs to maximize availability during peak shopping periods.  Performance tracking with continuously targeting improvements in availability and visibility.  The results with digital commerce intelligence and shelf monitoring By the end of November, significant improvements were observed across platforms:  Quick Market: Availability rose from 28% to 51% (+82%).  Carrefour: Achieved 100% availability, up from 57% (+75%).  Nana: Improved from 86% to 94% (+9%).  Fig. 1: Product Availability Across Platforms September to November   These improvements translated into:  Enhanced customer trust and satisfaction by ensuring products were consistently available.  Strengthened market share and sales across key platforms, solidifying the brand’s position in the AMESA region.  Through mScanIt, digital commerce intelligence and shelf monitoring – availability analysis, the beverage leader transformed its operational approach, leveraging data-driven insights to achieve exceptional results in a competitive market.  Optimize Customer Journey with Digital Commerce Intelligence Do not limit to just stock availability tracking! It’s essential to consider various analytical metrics to optimize the customer’s journey across e-commerce and quick commerce platforms. Each stage requires a tailored approach to ensure that the brand’s presence is effectively communicated, and customer engagement is maximized across the digital shelf.  This journey can be optimized at three broad levels with digital commerce intelligence:    Awareness and Interest Stage Brands must track visibility and ensure that products are accurately featured throughout the marketplace. This phase boosts awareness and

Is lack of Accurate Stock Availability Metrics Impacting your Ecommerce Revenue? Read More »

Bot Traffic

Google Ads Isn’t Fraud-Proof—Here’s What You Need to Know

Blog, Ad Fraud /

For digital marketers, walled garden is not a foreign word. However, we will take a quick minute to throw light on it.   Walled gardens is a term coined in digital marketing for closed advertising environment where all the operations are controlled by the ecosystem provider. Some of the major players ruling this landscape are Google, Meta, and Amazon. They offer the advertisers access to a large set of audiences and comprehensive data analytics.  Due to the nature of walled gardens, these platforms are often perceived to be a protected space for advertisers. This means that the traffic is assumed to be high quality.   However, reality is not exactly black and white. It is grey.   Let’s find out.   The Myth is – Walled Gardens don’t have bot traffic   When advertising on walled gardens, the advertisers often perceive that their ads are receiving filtered traffic, due to the close nature of the walled garden ecosystem.   The walled gardens claim robust proprietary technologies and algorithms that filter out suspicious or bot-driven activity, leading advertisers to believe these environments are more secure.   However, this “black box” approach also means that advertisers must trust the platform’s own reporting and assurances. Independent verification is limited, so advertisers often accept the platforms’ claims at face value. The perception of reduced bot traffic is partly an outcome of this reliance on self-reported data, alongside platforms’ reputations and massive resources dedicated to tech infrastructure and security. These walled gardens can detect and safeguard from general invalid traffic, however the bots have also become sophisticated over the years. Its ability to mimic human behavior makes it easy to bypass basic rule-based checks. Due to opaque reporting, the advertisers are unaware of the quality of their ad traffic and who is watching their ads. Sophisticated Bots penetrate walled gardens  Sophisticated bots are designed by fraudsters to mimic human behavior in ways that they can mask their movements to evade detection. These bots are capable of taking actions like clicking, scrolling, and even fill forms, which makes it difficult to identify then and differentiate from real users.   These sophisticated bots can even adapt with platform-specific platforms, adjusting their patterns to avoid suspicion. As walled gardens restrict access to third-party ad fraud detection solution, resulting in limited visibility and transparency for advertisers, these bots use this opportunity. Signs of a Sophisticated bot activity   Repetitive visits from a single device  In this case, visits came repeatedly from a single device in a short span of time, indicating abnormal traffic.    Multiple visits in short time span from a single device  In this case, the visits are coming in a short time from the same device fingerprinting, indicating a bot traffic.  Impersonation of a specific device   In this case, the fraudsters impersonate the identity of a specific device. This technique is used by fraudulent affiliates to exhaust the ad budget. Due to this no event (lead/purchases) come from this device. In this case, the visits are coming from a single device, where the user agent at client and server are different, indicating abnormal behaviour.     Partner with an ad fraud validation tool for walled Garden  No platform is immune to bot traffic, including walled gardens. To get full transparency of their ad traffic, advertisers need an advanced solution that can identify sophisticated bots patterns effectively and block them proactively.   The benefit of blocking bot traffic is not limited to clean traffic, but it also helps to improve conversion rate of the ad campaigns. To ensure that the sophisticated bot traffic doesn’t bypass the detection methods, we at mFilterIt use a full-funnel approach along with identifying device signals, behavioral and heuristic checks.   Unlike traditional ad fraud solution vendors, mFilterIt goes beyond the impressions and clicks level to identify sophisticated bot traffic. Our solution detects suspicious traffic at the visit level where more sophisticated patterns can be detected and blocked.   Therefore, protection at just the impression and click level is not enough. Advertisers have to look beyond that to ensure their campaigns on walled gardens are protected from bot traffic.   How did an automobile player improved their conversion rate using Valid8 by mFilterIt?   The major automobile player was running Google search campaigns to bring traffic to their website from various meta platforms. But despite substantial spending, the conversion rate was suspiciously low. Upon identifying suspicious ad traffic patterns, we started the blacklisting process. This resulted in cleaner clicks and lead, improved conversion rate and a savings of $0.47 million for the brand.   Refer to the images below to see the results:   A 13% drop in click fraud and 11% drop in lead fraud rates  A 1.75x increase in conversion ratio  Start Blocking Bot Traffic on Walled Gardens   While walled gardens are trusted for their controlled and secure environment, the reality is that they are not bot-free. To protect ad campaigns from the sophisticated patterns of bot, the advertisers need an additional layer of protection by partnering with ad fraud detection vendor with advanced technology to ensure their ad budgets are consumed to attract genuine audience instead of bots. As bots continue to evolve, advertisers need transparency to evaluate where their ads are shown and who is watching their ads to better assess the quality of their ad traffic and maintain campaign integrity. Get in touch with us today to see how Valid8 by mFilterIt can help you uncover and eliminate hidden fraud in your walled garden campaigns.

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Quick Commerce

Rise of Quick Commerce in UAE: Are You Monitoring Where You Stand vs the Competition?

Blog, Digital Advertising /

The Quick Commerce revolution is reshaping the e-commerce business landscape in the UAE at an unprecedented speed.  Convenience and customer-centric services are at the forefront pushing businesses to embrace a rapid online shopping model. As per recent projections by Statista, the Q-Commerce (quick commerce) market in the UAE is expected to reach a revenue of $3.27 million in 2024, with a compound annual growth rate (CAGR) of 7.71% from 2024 to 2029. This growth could drive the market volume up to $4.74 million by 2029 with 1.2 million users.  In this competitive landscape local players are building hyper-efficient delivery networks to compete alongside international giants. For brands, staying ahead requires market and competitive intelligence across platforms and geographies. Leveraging advanced tech-stack for Quick Commerce analytics to gauge where they stand compared to rivals, identify gaps, and explore new opportunities is the need of the hour. Today, it is not only helping brands to stay ahead of competition but also growing business and making it more profitable.   Quick Commerce in UAE  The Quick Commerce market in the United Arab Emirates is experiencing a surge in demand due to the country’s high population density and fast-paced lifestyle. Understanding the dynamics with quick commerce analytics and preparing brands for a transformative journey into the future.   Q-Commerce companies like Noon, Talabat, Carrefour etc. typically operate their own “dark stores” or cloud stores, where personal shoppers fulfill online orders, offering fast, last-mile delivery. The market is dominated by grocery and essential goods deliveries, often fulfilled within an impressive timeframe. With a densely populated urban environment and a significant population of expatriates, the UAE is becoming a prime environment for Quick Commerce growth.   Local providers are responding by enhancing app-based ordering and expanding their services beyond grocery items to include pharmaceuticals, home essentials, and even fresh foods.   Local special circumstances United Arab Emirates has a large expatriate population, many of whom are time-poor and willing to pay for convenience which has created a strong quick commerce market. Additionally, it is fueled by the hot climate in the region, due to which customers are often reluctant to leave their homes to shop.  Quick Commerce Analytics to Lead the Market  UAE’s competitive Quick Commerce landscape requires brands to prioritize performance monitoring through digital commerce intelligence and analytics. Here are some key areas where Quick Commerce analytics help drive product performance vs competitions: Track global & local competitors’ products performance vs yours across eCommerce platforms  Monitor Search of Search and Visibility Share across platforms & locations  Identify new opportunities -demographics or geographies to target in your market segment  Set market strategies based on insights & analytics  Enhance content to suit the local shoppers’ needs by identifying high-performing keywords  What metrics should brands track in Quick Commerce Analytics in UAE  Quick Commerce focuses on ultra-fast delivery, often within an hour or even less. Analytics helps identify any bottlenecks in the process. Real-time actionable insights allow brands to adapt. Monitoring Key KPIs such as pricing, availability, keyword share – discoverability, product detail page performance, etc. across platforms and geographies helps brand to stay ahead of the competition and leverage data-driven decisions.  – Pricing & Discount Trends  Real-time price tracker and comprehensive competitive analysis can help brand set dynamic pricing to ace the game on quick commerce and e-commerce platforms.   – Availability Monitoring  Keep Track of your stock availability across platforms and geographies at a granular level. Going out-of-stock can push your product into highly competitive marketplaces and platforms and lose brand credibility. – Content Analysis (Perfect page analysis) Keep your product detail page title, description, product images of high quality and optimized can give a massive boost to visibility. On Quick commerce platform, it is mostly about the product title that it should pop up when searched. – Digal Share of Shelf Monitoring Key track of your share of search and presence on the digital shelf. Product discoverability is key to staying ahead of the competitors across the digital marketplaces. – Sponsored Banners Performance  Sponsored listing on e-commerce and quick commerce platforms is critical to reach the right audience. Automate the process of sponsored ad spend and bidding process to ensure your budget gets optimized not wasted.   Case Study: Monitoring Availability across Q-com platforms   Objective & Problem Statement: One of the biggest multinational F&B conglomerates wanted to measure, track and grow platform presence and stock availability in the AMESA region. They were already working with an ecommerce intelligence tool but suffered due to limited scaling capability and platform coverage. Moreover, they were not able to customize data insights for the brand.   mFilterIt Deployment: The F&B conglomerate had deployed mFilterIt e-commerce intelligence stack for its presence on all e-commerce and quick commerce platforms in the region. They monitored the products across multiple KPIs across the Middle East & North Africa region. In the UAE region they mainly focused on enhancing its market presence with monitoring availability and optimizing share of search.  mFilterIt Analysis & Inferences: In the UAE they focused on optimizing availability on key platforms Careem, Carrefour, Noon and Talabat for Beverages, Nutritious Food and Snack category.  Fig. 1: Before and after using mScanIt last year at multiple locations on Q-commerce platforms They identified and acted on performance gaps with global dashboard monitoring availability and other core KPIs. With limited availability and platform presence they were losing out on sales. As they started tracking zip-code wise availabilities, the internal teams could be activated for improved performance in every region. This led them to optimize availability versus competition across platforms and geographies on various categories and sub-categories. With growth of around 41% in availability share across platforms the brand expanded its presence and reached the shoppers.   The first checkpoint on optimizing the customers is staying in the race – prevent stock out. The brand grows availability at the dark store level to make sure the availability doesn’t fall behind the competition. A momentary lapse in availability can lead to losing a potential customer. Frequent stock-outs also affect brand reputation

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