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Digital Shelf Monitoring for E-Commerce: Cover Every Store & Pin Code

Blog, Digital Shelf Analytics / mFilterIt Experts

The Indian e-commerce sector is in a state of rapid transformation, with experts projecting it to hit an astonishing $400 billion+ by 2030, powered by a 19% annual growth rate, according to Inc 42 report. With this kind of momentum and each one vying for prominence on the digital shelf in a market as sprawling and diverse as India brands must dig deeper, focusing not only on top-tier cities but extending their reach into every dark store and at the pin code level to get the true picture. The major challenge faced by brands is scaling, covering multiple platforms and categories. This requires a solution such as mFilterIt that covers more than 150 platforms globally with all pin-codes. Brands aiming for success need to look beyond traditional ways, integrated multi-platform intelligence is needed. Competition is fierce, digital intelligence is the key to unlock brand success across platforms. Trends Shaping Indian E-commerce Expansion Across Tier-2 and Tier-3 Cities: The growth of e-commerce extends beyond large cities, with consumers in Tier-2 and Tier-3 cities embracing digital shopping. Brands aiming to grow in these areas must tailor their strategies to local preferences region-specific marketing, opening new channels for growth through personalization. Also, with over 526 dark stores across India, Blinkit plans to double the number to 1,000 in the next one year. On the other hand, Zepto, at present, already has a network of over 340 dark stores across seven cities in India. Market Intelligence for Real-Time Data Insights: Brands are leveraging advanced tools such as mScanIt, Digital Commerce Intelligence for real-time actionable insights. This enables dynamic pricing, hyper-targeted marketing, and timely inventory management, all of which require brands to pivot from broad strategies to tailored experiences for each consumer journey. The Quick Commerce Boom: Quick commerce has redefined consumer expectations around delivery speed, particularly for essentials. For brands in Q-commerce, optimizing inventory and logistics down to the dark store level is crucial, ensuring products are available precisely when and where consumers need them. Blinkit, over the years, has expanded into multiple categories including electronics, home décor and cosmetics, increasing the cart value. It delivers more than 4 lakh orders daily. Zepto, which does 5.5 lakh orders is set to raise $650 million at $3.5-billion valuation. The Game-Changer: Digital Shelf Intelligence. Why Digital Commerce Intelligence Matters? Real-Time Pricing and Insights: Pricing directly influences purchase decisions. By accessing real-time data, brands can adjust prices in response to competitor moves and market trends, ensuring they stay attractive to customers without compromising profit margins. Availability Checks: Ensuring product availability down to the pin code level is critical. Digital shelf intelligence enables brands to verify stock at a granular level, preventing missed sales opportunities due to out-of-stock items. Competitor Analysis at Every Touchpoint: Brands must have a 360-degree view of their rivals. By monitoring competitor promotions, product launches, and consumer feedback, brands can spot gaps and respond proactively to market shifts. Product Detail Page (PDP) Optimization and Feedback Analysis: Optimizing PDPs means more than adding keywords; it’s about creating engaging, relevant content that resonates with the audience. Insightful feedback analysis allows brands to refine their messaging and offerings based on real consumer behavior. Share of Shelf Monitoring vis-a-vis competition across platforms: Monitor keyword share and brand presence on multiple marketplaces and Quick commerce platforms. Identify gaps along with opportunity to boost brand performance. Pricing & Promotions Trend monitoring with pricing intelligence: Track pricing and promotion across platforms, along with keeping tab on MAP violations and price intelligence with real-time insights. Case Study – How a Beverage Giant Optimized Product Availability Across Q-Com Platforms A global leader in the beverage industry, in optimizing their performance across platforms and geographies with the digital shelf tracker to monitor their products. Product availability on platforms two major e-commerce platforms 57%, and 86%, respectively. However, after comprehensive real-time of monitoring stock availability, they were able to identify the gaps and by the end of November, it improved significantly across platforms, soaring to 100%, and 94%, respectively within a couple of months with mScanIt digital shelf tracking, which enhanced their presence across platforms and bolstered their brand reputation. It mainly focused on enhancing its market presence by monitoring availability which includes. Brand Availability Trends 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 Sellers performance Maintaining Out-of-Stock product lists & real-time alerts The Success Formula for Indian E-commerce Brands To thrive in India’s evolving e-commerce landscape, brands should prioritize: Investment in Intelligence and Real-Time Monitoring: Market intelligence tools are essential for keeping a pulse on what’s working and addressing issues before they become major setbacks. Product Listing Optimization: High-quality images, accurate descriptions, and competitive pricing are vital. Think of each product listing as a virtual salesperson that needs to capture attention, build trust, and drive conversions. Brand Safety and Protection: Beyond counterfeit prevention, brand safety involves protecting intellectual property, monitoring potential infringements, and maintaining a positive brand reputation across digital channels. The Final Thought The future of Indian e-commerce is fast, competitive, and brimming with potential. Brands that adapt to these trends and invest in robust e-commerce intelligence will be well-positioned for success. However, succeeding in this market demands attention to detail at every level, from digital shelves to pin codes. Brands ready to go the extra mile in visibility, pricing, and availability will lead in this dynamic, high-stakes landscape. The future is here. Are you ready? Get in touch to know more about digital self monitoring.

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Festive Season 2025: Digital Analytics & Brand Protection for Brands

Blog, Digital Shelf Analytics / mFilterIt Experts

It’s almost September, and the sale season is on! The users are eagerly waiting to buy from their favorite brands. And the brand increases their spends to ensure they are visible to their relevant set of audience. And amidst this excitement, there are fraudsters too who are excited to see the ad spends increasing and ready to make the most out of it. However, there are some roadblocks brands face while trying to navigate the digital landscape seamlessly. Because running an ecommerce business is not just about running sales during festivals and tracking your buy box position, it’s also about protecting your brand from any kind of potential digital threats like ad fraud, brand infringements, unsafe ad placements, and more. All these factors, when taken care of, together contribute to a brand’s financial growth. That is why, to build trust and transparency across the funnel, every brand needs third-party ad fraud detection and analytics tools offering festive season market intelligence to enable real-time monitoring and flag off suspicious activities harming ad campaigns during the festive season. Let’s explore what challenges this festive season holds for brands and what they can do to safeguard their brand and optimize performance during the season and beyond. Challenges for E-commerce Brands During Festive Season While the festive season brings unmatched opportunities for sales, it also amplifies the challenges for e-commerce brands. Brands are supposed to navigate multiple hurdles to truly make high profits during the festive season. Here are some major challenges brands face: 1. Protecting Your Brand from Ad Fraud Advertising campaigns peak during festive times, and ad fraud is one of the critical threats to brands. While on one side, performance marketers are all ready to utilize their budgets to the optimum, on the other end, fraudsters are also all set to siphon off budgets using manipulative web and mobile ad fraud techniques. They use sophisticated ad fraud techniques like click injection, ad stacking, impression fraud, domain spoofing, ad stacking, etc. that go unnoticed to the human eye. According to a report by ANA, 56.1% of ad spends do not reach the intended consumers and could be wasted due to ad fraud and other pipeline issues in terms of media purchases. Some major consequences of ad fraud include: Wastage of budget due to invalid traffic – Bots, click farms, and fake install activities consume ad spends, inflating metrics without adding any real value to the campaign performance. Low quality leads in case of web campaigns – Fraudsters deploy bots to fill lead forms in bulk using fake details only to manipulate the overall campaign metrics, leading marketers to make further decisions based on irrelevant data. Low retention rate in case of mobile campaigns – When most of the downloads are fake or incentivized, it directly impacts lifetime customer value, as users are not interested in the app, and only came in for incentives. High competition for placements – Rise in CPCs and CPMs during the festive season makes it even harder for brands to maintain visibility without overspending, resulting in significant wastage of budget. Lack of data-driven optimization – Campaigns that aren’t continuously monitored and optimized often miss quick-win opportunities. In a high-stakes festive environment, a few hours of inefficiency can mean thousands lost. 2. Monitoring the Digital Shelf Across Ecommerce Landscape Winning the digital shelf is as important as keeping a check on fraudulent activities. This requires actionable data points,ecommerce competitive analytics, and ecommerce intelligence across platforms. However, with a range of products distributed across geographies, and the continuous growth of ecommerce businesses and new competitors emerging at a scale, brands face some major challenges like: Discoverability on digital shelf – With hundreds of brands bidding on the same keywords, being discoverable and visible on the digital shelf is tougher. If your products don’t rank in the first few scrolls, you risk being invisible to festive shoppers. Out of stock issues – If your product goes out of stock today and you realize it after two days, you not only lose immediate sales, but also divert customers directly to competitors offering similar alternatives. Mismatched content across platforms – Poorly optimized product titles, descriptions, or images reduce discoverability in searches. Even if customers find your products, inconsistent content can hurt trust and conversions. Price Undercutting and Discount Violations – Unauthorized sellers slash prices or violate MAP policies, hurting brand value and disrupting pricing strategies. If left unchecked, this not only confuses customers but also impacts ongoing campaigns. Moreover, you also risk falling behind, losing share of shelf without monitoring competitor pricing strategies. 3. Ensuring Brand Safety with Contextual Relevancy Festive campaigns are often run on a massive scale to gain as much visibility and reach as possible. However, when campaigns run across various platforms, publishers, and networks, brands often risk being vulnerable to unsafe or irrelevant ad placements that harm credibility and form negative perceptions among the audience. Some challenges include: Ads get placed beside harmful content – Festive ads appearing alongside controversial, sensitive, or inappropriate content result in damaged brand reputation and distrust among customers. Lack of visibility – Ads that don’t match the surrounding content appear irrelevant, leading to wasted impressions and poor user engagement. Brands are most of the time unaware of these situations, leading to poor decision-making. Association with fraudulent publishers – Partnerships with shady or fraudulent publishers during peak season can harm both performance and brand trust. Regional Sensitivity Issues – A message that works in one region might backfire in another if not aligned with cultural or religious sensitivities. 4. Ensuring Brand Protection Across Open Platforms Festive seasons aren’t just attractive to shoppers; they’re also the best time for fraudsters to set up fake websites or fake social media channels, using trademark assets of known brands to sell counterfeit products. This not only impacts sales of a brand but also creates confusion among consumers, harming brand integrity and reputation. Major challenges are: Fake Websites and apps – Fraudsters create lookalike domains or

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Full-Funnel Ad Fraud Protection: Beyond Impressions & Viewability

Blog, Ad Traffic Validation / mFilterIt Experts

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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Is your CTV Ads Budget ROI Optimized with Ad Fraud Detection?

Blog, Ad Traffic Validation / mFilterIt Experts

Connected TV (CTV) ads have emerged as a powerful digital advertising medium for brands looking to engage in a more targeted and interactive manner. As CTV viewing time has doubled over the last four years, CTV ad spending is also projected to reach $27.47 billion. Some of the popular CTV platforms for advertising are Roku, Amazon Fire TV, Apple TV, etc. The radical shift in viewership from traditional TV to streaming TV has opened this great opportunity. However, the opportunity is coupled with threats and challenges to ensure the integrity of ad traffic. Advertisers spending on CTV ads risk wasting precious ad budgets on illegitimate views and impressions, ultimately diminishing their return on investment (ROI). According to a recent study, in the second quarter of 2024, 19.4% of programmatic ad traffic to CTVs was invalid worldwide. To protect CTV ad campaigns, automation with advanced processes and AI ML-powered solutions is necessary. Let’s dwell deeper and explore why validating ad traffic is essential for CTV campaigns and how it can significantly enhance your advertising effectiveness and profitability. What is CTV ad fraud? Approximately, $1.14 billion in global CTV open programmatic ad spend was lost to invalid traffic in Q2 2024. This highlights the gravity of ad fraud in the CTV ecosystem. CTV ad fraud causes inflation in ad campaign metrics of CTV ads due to invalid traffic, bot-driven engagement, and app spoofing. Some of the most common CTV ad fraud include: Invalid or Bot Traffic: That does not come from a genuine user, including traffic generated by data centers (DCH), automated clicks, and other non-human sources. Bots generate fake ad views or clicks, making it appear as though there is legitimate engagement from real users. Device Spoofing via: Creating fake CTV devices or apps to mimic real ones. It often tricks advertisers into buying ads on non-existent or fraudulent platforms. VPN/DCH: Traffic coming from Virtual Private Networks (VPNs) or data centers, is often used to hide the true location of the user and generate fake engagement from non-targeted regions. CTV ad fraud also includes device spoofing, running ads through secondary devices while the TV is off, and invalid server-side ad insertion (SSAI). Campaign Optimization for Frequency Cap Violations: Improve performance while preventing frequency capping violations, which occur when an ad is shown to the same user too often. By monitoring and managing frequency, advertisers can enhance engagement and reduce ad fatigue, ultimately maximizing return on investment (ROI). Viewability Attention Metrics: The issues occur when advertisements are assessed for their visibility without adequately measuring user engagement. This leads to a mismatch between the visibility of ads and genuine interactions, resulting in distorted performance metrics. Impact of CTV Traffic Fraud Addressing CTV ad traffic fraud is essential to protect advertising investments and ensure accurate performance measurement. Implementing advanced fraud detection solution can mitigate these impacts, leading to more effective and efficient CTV advertising campaigns. Wasted Ad Spend: A significant portion of the advertising budget is lost to fraudulent traffic. CTV fraud detection and ad Traffic validation can identify any ineffective allocation of marketing resources. Distorted Performance Metrics: Inaccurate data on ad impressions and engagement due to skewed metrics leading to misguided strategic decisions. Reduced ROI: Lower return on investment due to non-human interactions or invalid traffic, which makes it difficult to achieve campaign objectives. Damage to Brand Reputation: Ads potentially appearing in inappropriate or non-existent placements lead to a loss of consumer trust and brand credibility. Inaccurate Audience Targeting: Ineffective targeting and personalization efforts due to misleading information about audience demographics and behavior. Compromised Strategic Planning: Inability to accurately measure campaign success and challenges in optimizing future campaigns based on flawed data. Competitive Disadvantage: Brands without robust fraud detection may fall behind competitors and reduce the effectiveness of marketing strategies compared to competitors using advanced fraud prevention. Case Study Improving CTV Ad Campaign Performance for a Global Energy Player A leading global player in the energy sector was running CTV audio and display campaigns on Roku TV to boost visibility and audience reach. Challenge: Despite substantial digital spending, the brand was experiencing low reach and engagement metrics (impression & viewability, completion rate, VTRs, reach and frequency metrics) which did not align with its investment. The primary challenge was the discrepancy between the digital spending and the actual reach and engagement metrics. The brand suspected that a significant portion of their ad traffic might be fraudulent, negatively impacting their campaign performance and ROI. Solution: mFilterIt was brought in to validate the traffic for the CTV campaigns, ensuring that the brand’s ads were only shown to legitimate viewers. The process involved identifying B.A.V (Brand Safety, Ad Fraud & Viewability) & F-Cap over-exposure prevention to ensure the impression gets served within the frequency defined by the advertiser, brand safe, and non-IVT only. Results: The mFilterIt analysis for the video campaign showed, that the average fraud was around 16% invalid traffic including 6.11% from invalid geographies, and the rest was from repeated IP bots, device repetition, and low-intent users. Reach and frequency metrics were also analyzed to streamline budget performances. For the banner campaign, the average fraud was around 17% invalid traffic with a major chunk coming from repeated IP bots 14.49%, and the rest of the invalid traffic was from invalid geographies, DCH, and low intent users. After implementing mFilterIt CTV ad traffic validation, the brand saw a significant improvement in its campaign performance. This led to a 4% increase in conversion rate and an 11% lift in ROI. Impact of CTV Traffic Fraud Addressing CTV ad traffic fraud is essential to protect advertising investments and ensure accurate performance measurement. Implementing advanced fraud detection solutions can mitigate these impacts, leading to more effective and efficient CTV advertising campaigns. Wasted Ad Spend: A significant portion of the advertising budget is lost to fraudulent traffic. CTV fraud detection and ad Traffic validation can identify any ineffective allocation of marketing resources. Distorted Performance Metrics: Inaccurate data on ad impressions and engagement due to skewed metrics leading

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Ad Fraud in Programmatic Ads: Why Impression-Level Protection Matters

Blog, Programmatic / mFilterIt Experts

Performance Programmatic Platforms follow the same rules as traditional programmatic platforms, but the focus on performance campaigns is to optimize ad placements through real-time bidding and enable data-driven decision-making. These platforms buy and place ads for advertisers with targeting functionalities, dynamic creative optimization, and performance analysis. As they market themselves, the entire process is ML and algorithm-driven. However, there is a prevailing myth that these platforms are fraud-free. Even MMPs are failing to do anything to curb these frauds because they have no protection at the impression level and minimum protection at clicks. Let’s delve deeper to burst the myth and highlight what advertisers need to do to optimize campaigns on performance programmatic platforms. The Myth of Fraud-Free Performance Programmatic Platforms With the sophisticated technology behind performance programmatic advertising, these platforms are propagated to be fraud-free. This misconception arises from the belief that advanced algorithms and data-driven strategies can fully protect against fraudulent activities. However, fraudulent activities such as click fraud, impression fraud, and fake installs continue to plague the programmatic advertising ecosystem. Fraudsters constantly evolve their tactics to exploit system vulnerabilities. Many programmatic platforms claim to have robust ad fraud detection solution mechanisms, but these measures often fall short in practice. That’s where a third-party independent validator is needed. The sheer volume of transactions and the complexity create numerous opportunities for invalid traffic to slip through the cracks. Type of Fraud on Performance Programmatic Platforms 1. Impression Fraud: Impression injection artificially inflates the number of ad impressions, executed by generating fake impressions in the background, later if the user downloads and installs an application organically or inorganically, the attribution gets stolen. This technique manipulates the ad delivery system to make it appear as though ads are being viewed more frequently than they are. 2. Click Fraud: Fraudsters generate fake ad requests that make it appear as though legitimate users are viewing ads. These can be triggered by bots or automated scripts. 3. Imperceptible Window: Ads may be loaded in ways that are invisible to the user, such as in a background process or in a 1×1 pixel iframe, ensuring they are not seen by actual humans. 4. Ad Stacking: Sometimes multiple ads are stacked on top of each other, but only one is visible. Each ad in the stack registers an impression, leading to inflated impression counts. 5. Fraudsters also exploit software development kits (SDKs) within legitimate apps to load ads in the background without the user’s knowledge. 6. Fake Devices: non-genuine or simulated devices to generate fraudulent ad activity or BOT-based impressions that are totally junk. Fraudsters use device emulators or simulators to mimic the behavior of multiple real devices. This allows them to generate fake traffic at a scale. 7. Device Farms: collections of physical devices, often managed by automated systems, that repeatedly engage with ads to create the illusion of genuine user activity. Fraudsters also manipulate device identifiers, such as Android Device IDs, to create fake device profiles. 8. IP Fraud: Fraudsters also use Invalid IP (use of VPNs) and get impressions from regions not targeted which results in high impressions but low ROI. Challenges in Optimizing Ad Campaigns 1. Myth of No Ad Fraud: The first thing is busting the bubble and countering the myth that there is no fraud on impressions, programmatic-based partners, or programmatic performance. Once advertisers accept the fact then proactive measures for full-funnel protection can be put in place to tackle ad fraud at every level and elevate campaign performance. 2. Brand Safety Issues: Next is combating brand safety issues with safe and relevant placement, protecting brand reputation. 3. Frequency Cap Violations: The most common and often neglected issue is FCAP violations along with bots spamming impressions for payouts. 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. 4. Down-the-funnel KPIs are ignored: Aggregators also mix traffic and sell it by the name of premium inventory. In case of fraud, the clean publisher gets a bad reputation. Since the organic is stolen, down the funnel, is going to be met. Limitations of Mobile Measurement Partners (MMPs) MMPs provide insights into user behavior, campaign effectiveness, and ROI. However, their ability to curb fraud is limited. 1. MMPs typically focus on tracking clicks and conversions but have minimal protection against impression fraud. 2. Impression fraud involves generating fake ad impressions to inflate metrics, which can mislead advertisers about the reach and effectiveness of their campaigns. While MMPs do have mechanisms to identify and filter out invalid clicks, these protections are often not comprehensive enough to detect all fraudulent clicks. 3. Another key issue with MMPs is attribution challenges as fraudsters often use tactics like click injection and click spamming to manipulate attribution models. MMPs, despite their advanced analytics, can struggle to differentiate between legitimate user actions and fraudulent activities, leading to incorrect attribution and wasted ad spending. Let’s get a better understanding of the challenges and how mFilterIt helped resolve them Case 1: How A Popular Gaming Brand Optimizes Performance in USA – App Campaign For instance, Let’s take the case of a trusted and most popular gaming platform in the US. The app offers a variety of games across a range of categories, such as card games, casual games, etc. Fraud at Impression Level: On Android, the fraud at the impression level was as high as 33% among over 56 million impressions generated, while on the iOS platform, 14% fraudulent impressions were detected among 4.8 million impressions. The major chunk of fraudulent impression was due to impression Injection, and the rest came from Invalid IP addresses, or sophisticated invalid traffic (SIVT). Fraud At Click Level: Among million and above clicks 11% were fraudulent on the Android platform. 6.13% of clicks were generated via click Injection and 3.69% came from fake devices while on the iOS platform, among 98, 800 plus clicks, 6%

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Validating Leads via Pixel: A Smart Way to Ensure Quality

Blog, Ad Traffic Validation / mFilterIt Experts

In the world of digital marketing, getting leads is just one part of the puzzle. Ensuring those leads are high-quality is what truly matters. One of the most effective ways to validate leads is by using a conversion pixel. A conversion pixel is a small piece of code that you add to your website to track and measure specific user actions. When used correctly, it helps you to filter out the irrelevant bots traffic and focus on genuine human filled leads that are more likely to convert. How you can validate leads with a pixel: Set Up Your Pixel: The first step is to install the pixel on your website or landing page. Whether you’re using Facebook Ads, Google Ads, or any other platform, most of them provides an easy guides to integrate their conversion pixel code on your website landing and thank you page. You can also choose any third party pixel to do the same, mFilterIt Visit and Conversion pixels are similar to any of these advertising platforms pixel. Pixels allow you to track user interaction in real-time, from filling out a contact form to clicking on a product page. Track Specific Actions: With the right pixel in place, you can start tracking specific actions that indicate lead quality. For example, you can track form submissions, page visits, or time spent on a particular page. Users who engage more deeply with your content are likely more interested, and therefore, their actions are better indicators of a qualified lead. mFilterIt’s event pixel does the same and provides you tons of data points and KPIs to compare and make insightful decisions from the incoming traffic’s data. Monitor Behavior Patterns: By tracking behavior, you can gain valuable insights on the leads, being which have most engaged with your business and filled by a genuine user. For instance, a user who visits your pricing page and spends time reading your product details is probably more likely to convert than someone who merely clicks through to homepage. Refine Your Lead Generation Efforts: Once you validate leads through pixel tracking, you can optimize your ad campaigns, tailor your content, and refine your targeting to focus on high-quality converting traffic and can weed out the incoming bots traffic whose goal is to simply drain out your campaign budgets. This helps you make better decisions on where to allocate your resources and ultimately boost your conversion rates. Validating leads through mFilterIt’s Ad Fraud Solution, Visit and Conversion pixels is a smart way to ensure you’re focusing on the right prospects, increasing your chances of engaging genuine user with your ads.

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Brand Bidding: Do not allow your Affiliates and Competitors to steal Your Spotlight

Blog, Ad Traffic Validation / mFilterIt Experts

Have you ever wondered why your brand name is showing in the sponsored search when you are not paying for advertising? Because of brand bidding. A magical, quick, and powerful covenant process that can turn into a deadly curse when affiliates aggressively bid on your brand keywords, purely for traffic or competition bidding on your brand keyword to rob you of the spotlight your brand deserves. What is brand bidding? Why is it a problem for Advertisers? 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. Simply put, it’s the practice of bidding on your own brand keywords to pop up on the top. Exploring The Dark Side of Brand Bidding: Affiliates and Competitors bid on Brand keywords There is no questioning the effectiveness of brand bidding in increasing visibility and guarding the brand, but it too has its own problems. One of its major drawbacks is the situation whereby there’s excessive bidding from affiliates and rival brands. Revenue Hijacking: Affiliates may bid on your brand keywords with the intention of capturing traffic and driving sales through their own affiliate programs, potentially diverting revenue away from your website. Brand Hijacking: Competitors may bid on your brand keywords to confuse consumers and potentially drive traffic to their own websites. Market Share Erosion: This can lead to a loss of market share and brand reputation if customers are misled or confused. The impact of brand bidding by Affiliate and Competiton Aggressive bidding from affiliates and competitors can drive up the cost per click (CPC) for your brand keywords, leading to higher advertising expenses. This lead to Loss of Revenue: If affiliates or competitors successfully capture traffic through their ads, it can result in lost revenue for your brand. Damaged Brand Reputation: Confusion and frustration caused by misleading ads can tarnish your brand’s image and reputation. It is important to identify who is bidding on your brand keywords. Are they authorized to bid on brand keyword or not? Continuously monitor your brand’s search performance and report any instances of affiliate or competitor misconduct to the relevant advertising platforms. By proactively addressing these challenges, you can protect your brand, maintain control over your online presence, and ensure that the benefits of brand bidding outweigh the potential drawbacks. A Case Study: Brand Bidding for a Popular Shoe Brand 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. Keyword Tracking: 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. Search Volume: The brand garnered a significant search volume across time slots. This indicated strong interest in and demand for the brand. Google Ads Activity: 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. Competitor Analysis: 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. Affiliate Activity: 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. 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 buit within the marketing approach. Beyond Bidding: Value-Based Optimization for Competiton Bidding on Brand Keywords Location-Based Campaign Optimization Combine actionable insights and location-based campaign optimization, you can create more targeted and effective brand bidding campaigns. This approach can help you improve your return on investment, enhance customer engagement, and drive business growth. Target specific regions enable tailoring your campaigns to different geographic locations based on factors like demographics, search volume, and competitive landscape. Optimize bids to adjust bids for specific locations to maximize performance and ROI. Leverage geo-targeting features to target ads to users within specific geographic areas. LOCOKS (Location-Based Campaign Optimization Keyword Strategy) with mFilterIt Effectively implement LOCOKS, mFilterIt offers valuable tools for tracking and optimizing keyword usage. By monitoring how competitor keywords are used in different cities and at various times of the day, mFilterIt provides actionable insights that can be used to tailor campaigns for improved relevance and efficiency. This data-driven approach ensures that your brand bidding efforts are aligned with local search trends and maximize their impact. Expanding the Scope of Brand Bidding While traditional brand bidding focuses on protecting your brand and improving visibility, it’s essential to consider the broader implications of this strategy. Customer Experience: Brand bidding can significantly enhance the user experience by ensuring that customers are directed to your website seamlessly. This can lead to increased conversions and brand loyalty. Competitive Advantage: By effectively implementing brand bidding, you can gain a competitive edge over rivals who may not be as proactive in protecting their brand. Brand Protection: Preventing competitors from hijacking your brand can safeguard your reputation and prevent potential confusion among consumers. Best Practices for Brand Bidding Competitors or affiliates may bid on your brand keywords,

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Affiliate Fraud: Detect, Defend & Protect your Brand

Blog, Brand Safety & Suitability / mFilterIt Experts

Affiliate marketing has emerged as one of the most viable sales promotion strategies that brands employ today. However, the rapid rise in affiliate marketing fraud has become a significant concern, as businesses can lose hundreds of billions every year with fraudulent activities. Affiliate marketing campaign are not excluded from these schemes, and mFilterIt reports indicate that affiliate fraud may result in the potential loss of up to 30-35%. For most businesses, affiliate advertising fraud wastes promotional, and marketing spends, which would be recovered with smart monitoring tools. What is Affiliate Fraud? Affiliate ad fraud refers to the fraudulent acts of malicious affiliates that exploit the system to wrongly earn commissions. They go through marketing procedures in the wrong manner and are making false conversions, clicks, or leads, which inflates the marketing metrics and ad spends for a brand without giving a good ROI on the campaign. According to Influencer Marketing Hub, affiliate marketing is expected to grow at a CAGR of 10.1%. Hence, the need for efficient tools to detect and prevent ad fraud is more important to optimize spending, minimize losses, and protect brand integrity. Why is affiliate fraud so serious? It is a very significant reason to distinguish why affiliate fraud should not be taken lightly because it usually leads to severe financial losses and damage to the reputation of the brands. The issues range from ad fraud, both general and sophisticated, to matters such as brand infringements and fake brand communication by affiliates, in which the unethical affiliates misuse the brand resources for personal gain. Ad Fraud Impact Affiliate ad fraud undermines ad effectiveness because it artificially inflates conversion metrics. Ad fraud issues like lead punching, ad stacking where several ads are layered to get impressions, and fake clicks impact brands. Over time, these acts prove counterproductive to marketing efficiency, present misleading data, and tremendous brand loss. In an environment where ad budgets are significantly constricted, failure to focus on these types of fraud will be detrimental to the long-term success of the campaign. Concerns with Brand Infringements with Affiliates Affiliate infringements are far more prevalent than traditional ad fraud. That is a set of practices that are unethical and could damage the reputation of a brand. This includes a practice known as brand bidding, in which the trademark of a brand is used to drive traffic to their sites, or the use of influencer coupon codes to inflate sales metrics artificially. Very often, affiliates would also make IP violations such as typo-squatting, a method that uses small misspell of the brand’s URL to route traffic to harmful websites. Such violations not only compromise the overall effectiveness of the affiliate campaign but also erode the trust created between the brand and its legitimate affiliates. Types of Affiliate Ad Campaigns Brand must Track for Full-Funnel Protection There are different types of affiliate fraud contingent upon the commission structure of the campaign, and they may be classified as follows: Cost-Per-Click (CPC) In this, for every click on an ad, the affiliate would make money. It is prone to click fraud wherein bots and click farms inflate the number of clicks but engage no real customer. Cost-Per-Leads (CPL) The affiliates are paid according to customer actions such as the form submissions and signing up on emails. In this aspect, the most common tactic fraudsters would use is fake leads or invalid customer actions. Cost-Per-Sale (CPS) Affiliates get paid according to commissions on sales that are completed. Manipulation with this model typically happens through the pushing of fake transactions or exploiting return policies for gaining commissions from sales later reversed. Common Issues in Ad Fraud Of course, ad fraud manifests in many ways, and the most common categories included are listed below: Lead Punching- Bad or low-quality leads are generated to earn a commission. These convert into no sales, and hence marketing dollars go to waste. Organic Poaching- They steal the organic traffic and dupe tracking systems to earn commissions for sales they never help make. Ad Stacking- Here, multiple ads are overlapped on top of one another in unnoticeable ways in which impressions are created that seem to be real but do not engage the user. IP & Proxy – There are certain techniques that are used in affiliate marketing fraud and these fraudulent schemes are carried out by creating malicious locations using IP spoofing and proxy servers to generate fake traffic and clicks that cannot be traced. Imperceptible Window – Techniques used include showing advertisements through small, transparent or overlay ads that are not seen by the user hence resulting in fake impressions or fake clicks without the knowledge of the user. Click Fraud – It occurs when a company’s automated bot or dishonest user simply repeats online advertisements or incurs damages to the clicked ad in order to exhaust most of the company’s resources. Brand Infringement Issues for Affiliates Affiliates’ infringement includes unauthorized uses that compromise a brand’s intellectual property or marketing efforts. Affiliate infringements include the following, though not limited to: Brand Bidding- Affiliates use a brand’s keywords or trademarks while competing with that brand. This type of practice has increased costs to a brand and easily confuses consumers. Duplicate Products- Sometimes, affiliates make duplicate products that dilute brand presence, present various prices at these sub-sites while making others unavailable and bring discrepancies in pricing. Misuse of Influencer Coupon Codes- Some affiliates distribute the influencer coupon codes to people beyond the intended reach. Doing this implies that the sales metrics inflated do not represent genuine consumer intent behind it. Violations with IP and Typo-Squatting- Affiliates open up fake websites that resemble the domain of the brand closely and capture the misdirected traffic thus misleading consumers. Brand Information Misrepresentation- Affiliates often give false information about a brand’s products or services that smear the brand’s reputation and result in revenue loss. How mFilterIt protected a Global FinTech Brand from Affiliate Fraud A leading fintech player collaborated with mFilterIt to fight affiliate fraud on a global scale. mFilterIt affiliate

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How Bot Detection Enhances Marketing Campaign Accuracy and Safeguards Ad Spends

Blog, Ad Traffic Validation / mFilterIt Experts

Bots make up about a third of all web traffic, and shockingly, 65% of those bots are classified as “bad bots”. These malicious bots indiscriminately destroy marketing campaigns by inflating impressions and clicks; thus, they financially devastate marketing campaigns. So, ironically, although companies do not intend to, they spend a percentage of their ad budget on fraudulent traffic, making every campaign less effective than it could have been. Ad fraud is rising; therefore, the detection of invalid traffic across all digital campaigns has become necessary for businesses’ success in the digital space. There is a need for a full-funnel ad fraud detection tool to provide omnichannel protection against general and sophisticated invalid traffic i.e. GIVT & SIVT. An additional brand safety layer of protection helps to boost campaign performance. To guarantee the success of digital marketing efforts, the traffic validation tools should provide coverage across app, web, OTT, and CTV ecosystems. Let’s understand how bot detection works, why it is so important in marketing campaigns, the technologies involved, and how we help organizations overcome the risks of ad fraud in the bot-driven world and enhance marketing analytics accuracy. What Is Bot Detection? Bot detection is the technology and methods used to identify and prevent non-human traffic—specifically bad bots—from serving interaction with a website and other digital destinations. From a digital marketing perspective, “good bots” (search engine crawlers, etc.) assist in increasing visibility for search engines or in monitoring the performance of a site, bad bots are designed to imitate human behavior, falsify clicks, impressions, and other down-the-funnel engagements. Bots skew digital campaign efficiency for businesses if left unchecked since they adversely affect customer acquisition costs and artificially inflate performance reports. Why Is Bot Detection Important for Successful Marketing Campaigns? Here’s why tracking and detecting bots in marketing campaigns are important- Protection of Ad Spend Bots generate fake clicks, impressions, and visits which means businesses are paying for fake user engagements instead of real ones. Often leads are also filled up by sophisticated bots bypassing OTPs and captchas. A huge portion of the budget spent on advertising goes to waste without proper detection of ad fraud. Real / Effective Analytics Bots taint the quality of the data collected from digital campaigns and yield wrong interpretations. In turn, this may lead to wrong business decision-making as well as inefficient use of resources. Businesses cannot rely on their marketing data unless the bots are detected and blacklisted. Higher ROI Based on the bot-cleansed, accurate metrics, businesses that deploy full-funnel ad traffic validation tools understand how their marketing campaigns are doing. This leads to a channel-wise analysis and therefore can operationally direct more budgets to the most effective channels, which means a higher ROI. Brand Safety Bad bots are often placed by publishers on content that is highly questionable and brand-unsafe. Good fraud detection tools not only end up finding sophisticated invalid traffic but also provide a layer of brand safety from bad inventory and unsafe ad placements. How Do Bots Get Detected? There are many advanced techniques and technologies used in bot detection to identify fraud and block such malicious activities- Device Fingerprinting Device fingerprinting helps track and identify unique devices across the internet. Each time a particular device accesses a website or clicks on an advertisement, a unique “fingerprint” can be created with various signals and device attributes. This technique is driven by AI & ML algorithms to analyze data and identify anomalies that pinpoint bot traffic in real time. Sophisticated bots are largely identified at down-the-funnel (i.e. clicks, visits, leads, or sales) metrics. The General IVTs are identified at the pre-bid impression stage. Behavioral Analysis Human users do not exhibit predictable patterns, but the behaviors are predictable in the case of bots. Behavioral analysis tracks user interactions to detect unusual activities. One of the most common types is mouse movement. Bots tend to have straight-line patterns vis-a-vis a random pattern in the case of real humans. For any traffic validation tool, behavioral checks should feed into the overall ad fraud checks. Heuristic Checks Heuristic checks are a technique to detect bad bots by analyzing the known patterns of fraud on the web. This may include checking for indications that correspond with previously established models of fraudulent activities. Heuristic checks often include monitoring for unusual user-agent strings, changing IP addresses, or clicking patterns. Bot detection tools need to continually upgrade their techniques for detecting bots by keeping heuristics models current and updated to adequately monitor new tactics of fraud. Deterministic Checks Deterministic-based bot detection manifests itself by applying an actual, predefined set of rules in detecting bots. These include data on hard data such as the IP address, session cookies, and other metadata about a user. For example, if the known bad bot’s IP address is giving traffic to a website, the system can deny it on plain identification. Deterministic checks can filter out low-level bot activity quickly and are often used in conjunction with more advanced techniques, such as behavioral analysis. How mFilterIt helped a Global Conglomerate in Bot Detection and Ad Traffic Validation mFilterIt started working with the advertiser to deliver ad fraud detection solutions, which involve a multi-layered approach that can protect digital marketing campaigns from fraudulent traffic. Both branding and performance campaigns across walled gardens (like Google & Facebook), programmatic channels, and affiliates were validated by mFilterIt. The bounce rates on their website were sky-high and YouTube VTRs & CTRs were under suspicion. The mFilterIt solution provided the following to the advertiser: Full-Funnel Protection – Our technology protects your business on a Full-funnel level, ensuring bots can be detected regardless of whether they interact with display ads, video ads, or mobile app ads. Real-Time Monitoring – This solution continually monitors traffic in real-time and detects bad bots before the event can affect performance metrics. It effectively filters out non-human traffic with a combination of behavioral analysis, device fingerprinting, and deterministic checks. Comprehensive Reporting – We provide complete reports on bot traffic

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Content Analyzer – The Game Changer Every E-commerce Brand Needs

Blog, Digital Shelf Analytics / mFilterIt Experts

E-commerce is fueled by customer engagement and purchasing decisions that revolve around content such as product descriptions, images, customer reviews, and even FAQs-composing every piece of it into a buyer’s journey. In this stream of data from a digital platform, how will e-commerce businesses know if their content is doing its job correctly? Here, the Content Analyzer becomes the tool to track, evaluate, and optimize the content across digital platforms. A Content Analyzer ensures that the content is attractive and converts into buyers. It’s a performance measure for knowing which parts of the content work, which part needs improvement, and what is going well with the target audience. For optimizing performance on digital commerce platforms, strong customer interaction and purchase intent, content tracking and analysis are much more significant. Most of them do not realize the importance of e-commerce content marketing until it happens too late: little engagement, lost sales, inefficiency- the list goes on. Metrics of Content Analyzer which brands must track Analyze content based on perfect page scores and unique product code counts. It provides insights into own vs competition with the image analysis which tells various parameters like pixel threshold, DPI threshold, white background, etc. It gives insights about brand-wise organic discoverability shared on a monthly and weekly basis. It provides perfect page analysis with the overall score, content, title, and review score. It provides recommendations for PDP for its brands. There are parameters like traffic keywords used by competition but not own, high traffic keywords used by none, and poorly Q&A content themes. It provides a word cloud based on the title and description. Downsides of Not Monitoring and Analyzing Contents Missing Chances to Optimize Without tracking and content analysis, organizations do not get key insights. Perhaps this means that the content is non-performing, but there is no data-driven feedback to let companies know what needs change. Keywords, metadata, product descriptions, and visuals may not be driving organic traffic or converting site visitors into buyers. Customers have inconsistent experiences E-commerce platforms thrive in seamless, cohesive customer experiences. Without appropriate analysis, your product descriptions are inconsistent, prices are wrong, or images are misaligned, creating confusion. A user who sees many different pieces of information on separate product pages becomes frustrated and leaves the site. No Alignment with Content Strategy Most companies operate based on intuition and are not data-driven when it comes to strategy. Lacking the analysis of content performance, brands cannot align their content with consumer intent or industry trends. Marketing campaigns can prove ineffective when resources are being wasted on the wrong content that does not represent the brand’s objectives or the expectations of the consumer. For e-commerce, trends change rapidly, so not analyzing the content means lagging behind competitors. Unable to Identify Spam or Malicious Contents User-generated content, such as reviews and ratings, influence buyer behavior in e-commerce. The absence of analysis of this kind of data therefore opens the way to spam content or possibly malicious comments. It can therefore damage the reputation of a brand and mislead its customers, which leads to foregone sales. Significance of Content Tracking and Analysis Enhanced Customer Experience Content analyzers help brands grasp how customers interact with their website; which particular kind of content is preferred by customers; and where improvement is needed. Such in-depth analysis helps businesses personalize by channeling the content as per the interest of customers. Increased Conversion Rates Analyzing content helps businesses get a precise idea of what types of content produce conversion. It might be in the style of a product description, an image, or even a tone in customer reviews that influences buying behavior. Content analyzers give the information a business needs to drive improvement in every phase of the buyer journey to ensure they’re serving the right content, at the right time, to maximize conversion. Better Amazon Rankings and Visibility Uninteresting pages are pointed out by content analytics, which act as weaknesses in the ranking perspective. With keyword monitoring, metadata, and content engagement, businesses will be able to optimize their strategy to come out with higher rankings in the Amazon rankings. Decision-Making Using Data The most important advantage of content analysis is helping to make data-driven decisions. It offers in-depth insights about what works and what does not, hence allowing a business to pivot its strategies and put resources in the right places. E-commerce firms are no longer required to make guesses about what can be corrected with content. Improved ROI on Content Investments E-commerce companies are investing heavily in content generation – from professional product photos to comprehensive blogs, videos, and posts on social media. What matters most, however, is not the generation of this content, but rather monitoring and measuring it – so that such investments can produce the maximum return possible. Case Study For instance, one of the largest multinational food, snack, and beverage corporations faced the challenge of optimizing Product Page Content. The brand needed a comprehensive integrated solution to monitor product page cont. Our ecommerce competitive analysis conducted image analysis and keyword analysis for our brand vs competition across platforms and geographies to identify gaps in PDP content. Fig 1: Image Analysis The mFilterIt content analysis checks primary content and secondary content on product pages. The primary content analysis checks the product page on various parameters which include title length as per defined threshold by the brand, brand mention in title product description requirements, analysis of images used, and compliance with platform-specific guidelines. It also checks the presence of the primary image and ASP presence. For secondary parameters, it monitors additional information if applicable on the platform like supporting images, mention of the brand in the description, ingredients, nutrient facts, or how to use as part of the description. The content analyses provide insights and measure product content in terms of score vis-a-vis competition. Quarterly Perfect Page Analysis (Category – Beverage) mFilterIt Impact: The ratio of ‘traffic to page’ to ‘add to cart’ has gone up by 25%. It helped

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