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Top 5 Brand Strategies to Boost Black Friday Sales 2025

Leave a Comment / Blog, Digital Shelf Analytics / Noopur Mathur

Black Friday is the Super Bowl for marketers! Prepare well off-season to score big during the season. Oh! You didn’t get that reference. Let’s lay it down in Indian terms, it’s like an IPL, a once-in-a-year where your brand talent meets sale opportunity. It’s a massive occasion for sellers to cash in on the global sale phenomenon. However, to ace the race brand need digital commerce intelligence, to make sure they on the top of the digital shelf monitoring discoverability share, pricing, stock availability, customer feedback etc. Brands on black friday day offer exclusive offers and massive discounts ranging from apparel, and fashion, to trendy electronic items. It’s time for sellers to entice the shoppers with attractive offers and push their products on an eCommerce marketplace targeting Millennials and Gen Zs that are well aware of the day and prep their wish lists in advance. But, just rolling out exciting offers and deals is not enough! To swiftly attract the customer brands needs to move up the ladder, increase online traffic and visibility with a well-thought of strategies needed to make the most of this occasion. Brand Strategies for Black Friday & Cyber Monday? To capitalize on Black Friday sale, brands need to cover every aspect across e-commerce marketplaces and quick commerce platforms with digital shelf analytics. Here are some strategies that could help your brand do so. Promote Shoppable Content – Boost Brand Visibility Over the years, Shopping as an idea and practice has gone through transitions, intending to make shopping more exciting, engaging, and seamless for the shoppers. One such transit is the promotion of shoppable content. Focus on Product visibility with organic and sponsored listing. It plays a key role in brand strategies brand need efficient and automated processes for keyword bidding to make sure their product achieves max visibility on organic and strategic budget allocation on sponsored. Create a Pre-Sale Brand Curiosity with Dynamic Pricing – Beyond Electronics Category Black Friday and Cyber Monday are not just limited to Electronics or tech devices categoy. All product categories on e-commerce platforms, Quick commerce platforms D2C website are explore possibilities of massive sales boost during Black Friday Sale. As the sale is now not limited to Friday it extends over the weekend till Cyber Monday. Pricing and discount strategies are always a key factor in purchase decision. New Trend in shopping has emerged that promote bank offers to offer massive discount on credit card, combined with platform offers and brand offer on ASP. It prompts shoppers to get involved in the sale as the timer beside the product provokes the customer to stimulate and magnetize your customers towards the Friday sale. Limited time offers. Pre-Black Friday Sale fosters the customer’s interest to plan their purchase even before the sale starts. Also keep track of your stock to ensure the hassle-free purchase and avoid the risk of going out-of-stock during sale season. Keep track of pricing with real time pricing tracker and alerts. Every hour surprise shoppers with attractive and interesting Black Friday deals and offers. Cheer them up and encourage them and match competitions at different times across different platforms and geographies. Be the Top choice with Quality Content to attract shoppers A quality product at attractive prices is nothing without quality content, title, description and high-quality product images. Pricing alone is not enough to attract shoppers! It needs discoverability and content that entice shoppers. Stay free from chaotic and hectic promotions and stay organized this weekend. Attract shoppers make them feel the product is worth shopping during the sale season with details on specifications and what they get in the product with A+ content images and videos. These activities should not end with the long Black Friday weekend content consistency and monitoring keyword share can keep you well ahead in the game even during the regular days. It is an effective way to gain your customer reach and amplify the number of loyal customers. Personalized Black Friday – Listen to what customer has to say The best way to engage customers is personalization, adding a touch of personalization to your Black Friday marketing campaigns. Monitor customer sentiments theme with feedback analysis. Product reviews are the most sought-after element in purchase decisions. What other shoppers have experienced drives good responses from new new shoppers. The Brand must be aware of their customer sentiment and identify gaps before they lose out during sale season. It also boost brand visibility, thereby monitoring feedback becomes key part of brand strategy during the Black Friday sale and for non-sale days, to keep the brand consistency and main brand reputation Frictionless Customer’s Journey with Quick Commerce Analytics One of the biggest problems for an online retailer is abandoned products in shopping carts. Creating a frictionless shopper’s journey is crucial during big sales days like Black Friday. Shoppers often traverse through adding products to their carts but abandon them due to complex purchase barriers like hefty shipping charges, additional charges, or taxes. Customers have proved their interest in the brands by adding products to their carts. Most of these customers are your potential customers from the past. Brands need to create a smooth pathway to make a purchase and offer free shipping or reduced additional charges to convert interest into purchase. This is the perfect time to remarket products with exciting offers to those customers, who looked for products earlier but did not buy. Entice them with attractive & valuable discounts and try to influence their purchase decision. Also, remember to add a buffer period to your Black Friday marketing strategies to capture early birds or late-wakers. Black Friday Expectations – How mFilterIt can help? The future holds great prospects for eCommerce business across platforms and categories. The result-driven marketing strategies play a crucial role in cashing in on this exponential market growth. Black Friday deals help acquire new customers as first-time buyers make up for a big portion of Black Friday shoppers. This online shopping carnival is the key to the sustainable

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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 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. 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. 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. 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. Fraudsters also exploit software development kits (SDKs) within legitimate apps to load ads in the background without the user’s knowledge. 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. 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. 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 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. Brand Safety Issues: Next is combating brand safety issues with safe and relevant placement, protecting brand reputation. 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. 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. MMPs typically focus on tracking clicks and conversions but have minimal protection against impression fraud. 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. 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% were deemed fraudulent. The breakdown of these fraudulent clicks included 2.13% from Click Injection and

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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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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-to-save-ad-budget with-bot -detection

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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Misleading Ads and Offers on WhatsApp and Telegram

Blog, Ad Traffic Validation / Jagmeet Singh

Misleading ads on popular messaging platforms like WhatsApp and Telegram have opened the door for fraud to swiftly take place. The infringement and impersonation of trusted brands lure people into believing in the misinformation. These misleading ads often generate high traffic, but the conversion is not a long-term prospect as all clicks and app installation are there in the lure of getting incent rewards. These types of frauds are prevalent on messaging platforms like Telegram and WhatsApp due to their broad reach and ease of communication. Misleading ads or offers generate incentivized traffic Affiliates promote offers in Telegram groups or WhatsApp chats and offer users small rewards such as cashback, points, gift cards, etc. for completing tasks such as clicks, app installs, or sign-ups. Users are incentivized by the affiliate to complete the tasks not out of genuine interest but to receive the reward. This leads to a high volume of low-quality traffic, installs, or sign-ups that do not translate into actual engagement or revenue for the advertiser. Such ads or offers directly impact the advertisers, leading to financial losses and reputation damage. Advertisers pay for traffic that does not convert into meaningful user engagement or sales. It also results in Market Distortion as low-quality traffic distorts performance metrics and analytics. It becomes challenging for advertisers to assess the true effectiveness of their campaigns and make informed decisions. Brands associated with fraudulent activities can suffer reputational damage. When users do not get incentives as promised in misleading or fake ads, they lose trust in the brand whose name is being used in such ads. Enhance tracking and monitoring with advanced AI-ML powered tools to identify too good to be true click to install or install to a registration issue. Down the funnel event quality degrades with low-quality users coming from misleading ads. Case of Misleading Offers or Ads The misleading ads include offers, incentives, investments lure, or links to install apps. For instance, let’s consider a scenario where a misleading ad offers to win a jackpot-sharing app with the circle to win ₹1000. But when you or the people install the ad it does not get a reward. Sample Misleading Ad Such scenarios can erode trust and damage a brand’s credibility, even if the brand isn’t directly involved. Users, lured by ads promising rewards or discounts, often generate high traffic and numerous installs. However, when these promises aren’t fulfilled, users feel betrayed and uninstall or stop using the app. This leaves the brand with no benefits and a pool of low-quality users In hard KPI events, the quality of users varies significantly when comparing organic or walled garden sources to affiliates promoting misleading ads. Affiliates tend to drive more low-ticket value events, often compromising user quality. For instance, in arbitrage cases, publishers pay users an amount less than what they earn from the brand. 40% of events from affiliates had ticket values between ₹50 – ₹100, while in the case of Organic and Walled Gardens, only 2% of events with such low-ticket values occurred. However, for ticket values above ₹300, the percentage of contribution from affiliates drops drastically to 1%, with organic sources contributing 23% and walled gardens 29%. This clearly shows that higher-quality users are more prevalent in organic and walled garden sources compared to affiliates. The average order value for these cases is lesser as compared to other sources. How to Combat Misleading Ads Combating misleading ads by affiliates on Telegram and WhatsApp requires a multi-faceted approach involving monitoring, reporting, and educating both affiliates and consumers. Monitoring and Detection with Automated Tools – Deploy AI, ML, and OSINT-powered tools to automatically scan and detect misleading ads based on keywords, phrases, and image recognition. Utilize data analytics to gain insights into affiliate performance and identify patterns of misleading behavior. Combine technological solutions with strict monitoring. Regular Audits are Must – Conduct periodic audits of affiliates to ensure compliance with your advertising policies. Implement a rigorous vetting process for new affiliates to ensure they adhere to your advertising standards. Reporting and Enforcement – Establish clear Reporting Channels to report misleading ads on social media channels, messaging platforms, etc. Develop a protocol for the immediate takedown of misleading ads once detected or reported. Penalties for Affiliates – Enforce strict penalties for affiliates who repeatedly share misleading ads, including suspension or termination of their affiliate status. Ensure traceability and accountability in affiliate marketing. This can help in tracking the source of misleading ads and enforce compliance with advertising standards. Set Clear Guidelines – Provide clear and comprehensive advertising guidelines to affiliates, emphasizing the importance of honesty and transparency. Stay informed about the latest regulations regarding online advertising and ensure your policies are compliant. Be prepared to take legal action against affiliates who engage in deceptive practices. Conclusion Misleading Ads or Offers on various platforms have major repercussions on brand reputation along with the final losses. Brands can even end up being penalized for such activities that tarnish brand image. Monitoring across platforms including messaging apps such as Telegram and WhatsApp can help proactively identify such activities before, leading to trust erosion and customer end up losing faith. mFilterIt Affiliate Monitoring Solution leverages advanced AI, ML, and OSINT Tech to detect misleading ads more effectively with prompt reporting to safeguard brand repute. This ensures you get sustainable engagement. Get in touch to learn more about the Misleading Offers on WhatsApp and Telegram.

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The Menace of Mule Accounts and Fake Gateways offering ‘Money Mule as service’

Blog, Brand Safety & Protection / Dhiraj Gupta

It’s time to peel back the curtain on Mule accounts, drawing off Indian monies to offshore fraudsters. But why are they a big deal? ‘Mule’ better known as ‘Money Mule’ are regular bank accounts, used for collecting payment or to hide the money trail by fraudsters. The BFSI ecosystem is stepping up the security measures, running awareness campaigns but accurately identifying these accounts remains a challenge for banks. Fake gateways offering ‘Mule as service’ have heated up the situation. Prevent the leakage before it breaks down the floodgates drowning the reputation. Let’s explore the threat they pose and how Mule Account monitoring can help. Combatting the Threat of Mule Accounts Mule accounts are bank accounts used to transfer illegal funds, often linked to money laundering schemes, illegal betting gambling sites, Forex trading sites etc. converted to crypto and taken offshore. They pose a significant risk, slipping through the cracks of traditional monitoring systems and enabling cybercriminals to exploit financial operations. Use of Mule accounts is violation of Indian tax laws and GST fraud. For instance, betting sites use mule accounts to take bets associated with Indian payment instruments, bank accounts, UPIs, and mobile wallets. This leads to massive tax evasion as this money gets transferred to offshore accounts from these mule accounts of individuals or companies. As per regulations of the National Payments Corporation of India (NPCI) and Reserve Bank of India (RBI), the Indian payment systems should not be used for blacklisted or banned website categories like gambling, pornographic sites, Forex trading sites, Chinese laundering/loan apps or on other restricted sites. ‘Mule’ as service offered by Fake Payment Gateways Another pressing issue with mule account generating high concerns is Fake Payment Gateways offering mule as service or offshore websites. Yes, Shocking right? These gateways provide such mule, manage them and rotate them frequently to avoid any spike in transaction to come in notice of banks. “Mule as a Service” (MaaS) involves using fake payment gateways in various scams, such as e-commerce, task scams, loan scams, gaming apps, pig butchering scams, and betting sites. For instance, Fake e-commerce sites trick buyers into paying for non-existent products, while task scams lure individuals with promises of high returns for simple jobs. Loan scams often require upfront fees paid through these fake gateways. In gaming and betting scams, in-app purchases and bets are redirected through fraudulent channels. These gateways create and manage a network of mule accounts using link sellers for resetting free invite, sell invites to agents, mule groups that source money mule and rotate them, making the money trail hard to trace. Ways to Identify Mule Accounts Money Mules are a major brand reputation threat to financial institutions as they often use reputed bank accounts, either P2P accounts with a lower threshold or Merchant accounts for high-amount transactions. But there’s a way to turn the tide and protect from these hidden threats. Transaction Monitoring using Bank Data: This method is used by banks to monitor transaction data patterns that highlight any suspected transaction. As fraudsters use hundreds of accounts and keep rotating then it gets to detect patterns in transactions. A prediction score is given to probable mule accounts. This solution requires complex data modelling, transaction analysis and training, which may not always be possible. It also requires a long setup and investment over time. Also with Mule-as-a-Service, since transactions are rotated across hundreds of accounts, this can easily be bypassed. Simply for fraudsters to make small tweaks to their rotation can make them evade detection easily. Detection from Mule Source: This method identifies websites that use mule accounts and detects the mule accounts by DIRECTLY going to those websites and tracking all mules being present there. This method helps identify guaranteed mule accounts without using any bank data and is quick to scale. Since this method goes DIRECTLY to websites where mules are present, it doesnt need complex integrations, doesnt need model training and evading detection is not possible. While both options have their pros and cons, “Detection from Mule Source” is the game-changer in this fight. Detecting mule accounts from source websites such as gambling and betting sites identifies accurate finding with guaranteed mule. At scale. Detection at source also provides proof point to validate findings, help in taking swift action. This data also can be used to train AI-ML based transaction monitoring system to identify mule accounts more accurately at a later stage. A public sector bank consolidated and strengthened its rule engine system to more accurately identify the mule accounts by taking data from “Detection from Mule Source” and feeding to its model training. mFilterIt mule account monitoring tool leveraging advanced algorithms and tech for swift identification of guaranteed mule accounts. No data is required from banks, we detected mules used by the source itself. Identification of suspicious websites using mule accounts with proof points that guarantee mule accounts. This proactive approach ensures banks stay one step ahead of fraudsters, safeguarding financial integrity, but can also take swift action with proof point and strengthening their data model at scale. Currently mFilterIt is monitoring almost 25,000 websites EVERY HOUR at scale by automated browsing and access. This ensures that even payment gateways offering Mule-as-a-Service are getting caught in large volumes, and their ENTIRE load of mule accounts get blocked IMMEDIATELY! Proactive Action on Mule Accounts We detect 18 to 20 thousand mule cases every single day for Banks. These mule accounts are usually owned by regular people, who are either tricked into opening these accounts or knowingly use these accounts at the behest of some monetary incentives. We are also working in collaboration with national banks regulatory bodies, payment apps, and other major platforms in India to spot and safeguard from Mule Accounts frauds. Our role is to track these platforms leveraging OSINT (Open-source Intelligence) and our transaction laundering detection solution as we crawl across a pool of more than 25000 sites for fraudulent activities for various stakeholders. Eg Casino and gambling sites, betting sites, pornographic sites, FOREX

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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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Click Tracker: Measurement and Validation of Clicks to prevent ad fraud and click-fraud prevention

Blog, Ad Fraud / mFilterIt Experts

Ensuring the legitimacy of clicks is a key performance measurement metric for marketers and businesses. Verification backed with accurate measures leads to optimized performance. Click Tracking ensures all invalid traffic is identified before it drains the ad budget and skews ad campaign performance data. Let’s delve deeper to understand the need for click tracking and how it can help in campaign optimization. Click Measurement and Validation Consider a scenario where an ad gets a massive number of clicks, generating a good number of impressions but ending up with a low conversion rate. This is a clear waste of spending. Advertisers need to identify gaps across the funnel that start with first and foremost wider end with a flurry of clicks. What does the advertiser need? Advertisers need to optimize their ad campaigns with click fraud detection software, that can bring transparency to the ad campaigns. Weed out invalid traffic starting with clicks Invalid traffic from clicks on Google ads and Meta Ads need to be identified in real-time, ensuring no damage to your ad budget. Identify genuine clicks vs Bots clicks Genuine clicks usually show varied patterns, high engagement, and diverse geolocations. While Bot clicks exhibit rapid, consistent patterns, low engagement, and suspicious IP addresses. Identifying Bot patterns and accurate measurement is the key to protecting wastage of ad spend. Detect Fake clicks Driving genuine traffic led to getting conversions. Detecting fake clicks generated via click spamming in real time improves your quality of traffic and can get you more conversions. Click farms Are large-scale dedicated click fraud operations generating invalid clicks? Are you able to track that? Usually, click farms are hired to inflate the click volume on ads leading to inflated and skewed metrics. Accuracy of Measurement can prevent hefty payout on invalid clicks and bring transparency into the ad campaign across app, web, or programmatic advertising platforms. How can Click Tracker help advertisers? The size of the online click campaign market is growing. This is evidenced by the Google Ad revenue (US) to the tune of $237 billion (2023) and Meta’s ad revenue stands at $131billion (2023). This has grown 6% and 16% respectively in the last year. With the size of the click market growing, it is estimated that digital advertising fraud costs will increase from $88 billion to $172 billion within the next five years. That figure will grow 14% annually and nearly double, as per a Statista Report. This impacts all advertisers’ spending on clicks across platforms as click fraud is a multifaced threat that can take many forms, from sophisticated bots and malicious software to organized human operations like click farms. Advertisers need to understand the need for accuracy and transparency in click measures and validation to protect their investments and ensure that their marketing efforts reach genuine and interested audiences. Ensure Accuracy in Data Collection with real-time tracking and detailed analysis Real-time data on user interactions ensures that marketers have up-to-date information on campaign performance, while analysis and insights into click-through rates (CTR), user behavior, and engagement metrics, help in the precise measurement of campaign success. Fraud Prevention with Click Fraud Detection and Verification Identify and filter out invalid clicks, such as those from bots or repeated clicks from the same user, thereby reducing click fraud. along with verifying source to ensure clicks are coming from targeted geographies, the authenticity of traffic sources is validated ensuring that clicks are coming from legitimate users. Enhanced Campaign Performance with Click to Conversion tracking Monitoring and validation are needed across the funnel. By tracking which clicks lead to conversions, marketers can optimize their strategies for better ROI. Full-funnel protection with ad traffic validation and ad fraud detection can enhance campaign performance. Clear and concise information on campaign performance, making it easier for stakeholders to understand results. Using third-party click trackers such as mFilterIt Valid8, adds an additional layer of trust. Customizable and Tailored Metrics for efficient measurement: Trackers can be customized to measure specific metrics relevant to your campaign goals. With advanced AI, Machine learning tech, and algorithms, campaign performance measurement and optimization. Integration with ad managers also helps automate and provide a holistic view of campaign performance. Final Thought mFilterIt, ad traffic validation, click tracker and ad fraud prevention tools can play a vital role in building trust and transparency in digital marketing by providing accurate data, preventing fraud, ensure click integrity, enhancing campaign performance, ensuring transparency in measurement, and offering customizable solutions. By leveraging mFilterIt Valid8 marketers can gain valuable insights, optimize their strategies, and foster trust with their audience and stakeholders. Get in touch to learn more about click tracker.

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