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

Programmatic Advertising

How Top Brands Are Winning with Programmatic Advertising

Blog, Programmatic /

In this competitive digital environment, brand messaging reaching the right audience at the right place has become imperative. To boost the brand’s success rate, programmatic advertising is the best way to ensure high accuracy and high turnover in depth. In 2023, programmatic advertisements accounted for 90% of the total ad spending. However, the big question is how brands and businesses are leveling it up to remain relevant in the market. Let’s discuss how programmatic advertising can be used the right way by implementing the right strategies.   Why Brands are Embracing Programmatic Advertising? Programmatic advertising has transformed the way brands interact with their target audiences by automating the buying and placement of ads with the help of powerful algorithms that provide precision, efficiency, and scalability.  to increase the success rate which is lacking in traditional advertising.   -Precise Targeting: Using precise targeting in programmatic ad marketers use data to identify target audiences. It allows brands to send modified messages based on demographics, activities, and even real-time intent.   -Real-Time Optimization: Programmatic campaigns help in delivering real-time analytics, allowing brands to monitor performance and adjust the campaign according to their need. This enables marketers to optimize ad creatives, placements, and budgets in real-time, resulting in better results.   -Scalability Across Platforms: Programmatic advertising connects people to a wide range of platforms, including social media and display networks, as well as connected TV and audio streaming services. This enables marketers to maintain the presence across several touchpoints without having any extra burden on managing individual channels separately.   -Cost Efficiency: Traditional processes of buying and placement of ads can be time-consuming as they require negotiations and manual adjustments. With programmatic systems marketers can process millions of transactions in milliseconds, enabling brands to swiftly launch and adjust campaigns to close potential opportunities. Challenges in Programmatic Advertising   Programmatic advertising is used in revolutionizing brand engagement with audiences, yet it brings its own set of challenges.   -Lack of Transparency: Programmatic advertising has enabled advertisers to reach large audiences, but it also poses significant gaps. Transparency of the ad campaigns is one of them. The advertisers are unaware of where their ads are showing. In some cases, this non-transparency can lead to ads appearing on low-quality, spammy websites that produce irrelevant traffic, hampering the brand reputation. The lack of transparency can impact on budget allocation because advertisers cannot judge campaign performance and ad placement.  -Viewability Issues: IAB has defined ad viewability as a standard metric to measure viewable impressions. According to it, an ad is considered viewable if the ad appears at least 50% on screen for more than one second. However, this parameter is not enough to ensure the ads are viewed by the right audience or in most cases even a human. Fraudsters deploy bot traffic to see the ads and even fraudulent publishers use tactics like ad stacking to generate impressions. The advertisers are under the impression that their ads are seen by the right audience, but in reality, they are not.   -Advertising Fraud & Bot Traffic: Ad fraud is one of the rising issues in programmatic advertising, with 37% of ad buyers concerned about abusive suppliers, bots, and invalid traffic. Over time, the fraudulent activities have become sophisticated and difficult to detect. KPIs like impressions and clicks can be easily met by fraudsters, resulting in skewed data and loss of budget  -Impact on Brand Safety: Apart from ad fraud, one of the other challenges that arise with non-transparency is placement of ads beside safe content. In many cases, the brand’s ads appear beside illicit or unsafe content which further impacts the brand’s reputation. Brands need to keep a check on their ad placements in addition to traffic validation.   Winning Strategies by Top Brands   Here are some strategies brands can implement to improve their programmatic campaign performance effectively.   -Ask for Transparency: Transparency should be the cornerstone for advertisers to ensure their optimization strategies are backed by clean data. By deploying an advanced ad fraud detection tool, advertisers can ensure they are getting genuine traffic on their ad campaigns. The right tool will help them with source-level transparency, helping them to understand where the traffic is coming from and take proactive action.   -Go beyond viewability metrics: While viewability is an important metric, it is important for advertisers to opt for a holistic approach. Advertisers should not just focus on “if the ad is visible or not” but also “who is seeing and interacting with the ad”. Using an ad fraud verification tool, advertisers can validate their ad traffic and also ensure quality traffic is engaging with the ads.   -Tackle Ad Fraud: Ad fraud remains a persisting challenge in the digital ecosystem and advertisers need the right guards to protect their ad spending. By deploying a real-time fraud detection solution, advertisers can identify evolving fraud techniques and implement preventative measures without major damage. By regularly auditing the data of their ad campaigns, advertisers can ensure where to invest more thereby improving the ROI and ensuring that their ads reach a genuine audience. -Prioritizing Brand Safety: For advertisers, protecting the brand image is the utmost priority. This includes ensuring that the ads are placed in an appropriate and brand-friendly environment. By continuously monitoring the ad placements using advanced brand monitoring tools, the advertisers can avoid associations with inappropriate and harmful content. A proactive approach to validate the ad placements can help the advertisers establish strict guidelines for partners and platforms where their ads are appearing. By prioritizing brand safety, brands maintain consumer trust, reinforce positive perceptions, and protect long-term relationships with their audiences.   A Real Case: How a global brand tackled low engagement on programmatic campaigns  A global brand in the energy sector faced low conversion rates and limited engagement despite significant investment in audio and display campaigns on platforms like DCM and DV360. The brand realized its ad delivery process was inefficient, leading to wasted resources and poor returns. They partnered with mFilterIt and deployed its

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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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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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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

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ad fraud

Full-Funnel Ad Fraud Protection: Beyond Impressions & Viewability

Blog, Ad Traffic Validation /

Ad Spending in the US market will reach $421 billion in 2024. Out of a market worth $143 billion, TV and video Advertising stands out as the largest market there. Accurately measuring an ad campaign’s effectiveness is essential. It is the marketer’s job to protect against waste and improve campaigns’ ROI. Adopting ad fraud detection tool driven by AI-ML tech can achieve this. According to the Statista Report, by 2029, it has been estimated that 87% of advertising revenue in the United States will be attributable to programmatic advertising. Need for Full Funnel Protection When it comes to combating ad fraud, one must understand that the focus on impressions alone will not work. It is imperative to adopt full-funnel protection, focusing on detecting ad fraud and preventing it within the entire customer journey from the first impression to post-click interactions. Here’s why- Impression Validation is not enough. Full funnel protection is a must as impression validation is not enough. It’s not a foolproof indicator of ad fraud. Here’s why: Bot-generated views and impressions: Bots can be programmed to simulate human behavior, including scrolling and pausing on pages, to ensure ads are “viewed.” These bots can inflate viewability rates without generating any real user engagement. Low-Quality Traffic: Even if a human views an ad, the traffic may come from low-quality sources like click farms or websites with minimal user engagement. These impressions may not lead to conversions or meaningful interactions. Click-Through Rates (CTR): While viewability indicates if an ad was seen, CTR measures if it was clicked on and engaged with. A high viewability rate and a low CTR can be a red flag for low-quality traffic or ad fraud. Low conversion rates: Ultimately, advertising aims to drive conversions, such as sales or sign-ups. A high viewability rate without corresponding conversion increases is always suspicious Data is limited Trackers easily bypassed by using Safe-Frames / iFrames Due to the huge volume of impressions, only sampling is executed but with limited time for analysis (~20ms). Limited data for analysis covering only IPs and user agents. Impressions are the easiest to spoof! Deeper Fraud Checks Fraud is not only inflated impressions. There are several ad techniques used by publishers such as ad pixel stuffing, domain spoofing, fake clicks, etc. A comprehensive validation process needs to be in place covering deterministic, behavioral, and heuristic checks for a multilayer approach to fraud prevention across the funnel. Full-funnel checks address these deeper issues to guarantee that the figures reflected in the campaign metrics translate to valuable interaction from the target audience. Combined Power of Click & Down the Funnel Analysis Embrace the power of click validation and ensure the click turn visits with genuine engagement.  Seek validation beyond those that bypass walled garden restrictions, and ensure a more reliable environment on advertiser’s own pages. For lower volume, allows census analysis and makes sure that more time is available to track user behavior patterns and generate genuine engagement.  Track bot patterns vs huma to detect sophisticated fraud like mouse movements and cover all campaign types with down-the-funnel analysis mFilterIt vs Competition – Pre-Bid Analysis vs Post-Bid Analysis There are several ad verification tools on the market. However, they differ in their effectiveness in providing ad verification services. This will examine the relative advantages for us against its competitors in both pre-bid and post-bid analyses. mFilterIt: A Full-Funnel Approach We detect fraud in post-bid analysis; thus, fraud detection is our strong suit. It employs techniques for the detection of fraud that reach beyond the most basic advertisement viewability measures. Impression Fraud Detection- We detect up to 15-20% fraud in campaigns. When it comes to validation at the impression level, the focus is on both real human impressions, impressions on Made-for-ad sites, and frequency cap violations. Also, viewability scores are measured to counter fraud throughout the life cycle of the campaign. Click Validation- Validate click with visit lead intent to check on campaign performance. Visit Intent Scoring is a must for improved channel management and retargeting campaigns Getting a lead is not enough to ensure a swift automated process in place for lead validation and lead quality assessment for setting priorities. Competition: A Narrow Focus on Viewability & Pre-Bid Validation 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 analysis is a more beneficial method for detecting ad fraud. As viewability is not a measure to detect fraud, most of our competition focuses on advertisers spending 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.   By focusing on robust ad fraud solution 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. Understanding the Scope and Limitations of Industry Accreditations Limited Geography Some accreditations are largely limited to the US Market. However, competitors use these globally as a selling point. These accreditation bodies have recently come out to express their discontent with traffic validation platforms using it globally. Brands and agencies must check the geo-limitations of accreditations before onboarding the platform. Service-Specific Accreditation A part of these accreditations is granted on a service-by-service basis, rather than offering blanket accreditation for entire platforms. Each service or tool must be evaluated separately for its compliance with standards. Exclusion in Major Platforms Notably, brands must do a platform-wise analysis

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