Ad Traffic Validation

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.

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

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.

Digital advertising, being a relatively new channel, is still evolving. As digital ads become more and more popular, new concerns are being identified. One such concern that has been in the limelight recently is data transparency. Users are becoming increasingly concerned about their privacy. They want to (rightfully) control who obtains their information, how they obtain it, and how they use said information. In other words, digital users expect brands to build trust through transparency. However, such concerns are not limited to users. Transparency matters also concern advertisers. As third-party cookies are being phased out and the focus on privacy becomes sharper, brands must also demand transparency from advertising platforms and providers. Recent privacy regulations and concerns surrounding consumer trust have made things more difficult for brands. In such times, access to reliable data and transparency have become critical to success. Still wondering why? Here are three solid reasons: Reasons Brands Need Data Transparency to Thrive in 2024 1. Mitigate The Risks Bad data negatively impacts digital efficiency. This means that bad data prevents brands from making the most of their advertising and marketing efforts. This is because bad data usually stems from invalid traffic or anomalies found in ad traffic reporting. Such instances can impact the marketing of brands in a variety of ways. The most obvious impact is the wasted ad spend. If you are paying for a click or an impression, and if it doesn’t come from a real user, then your ad budget for said click or impression is wasted. Fraudsters may use bots or click farms to direct invalid traffic to an advertiser’s website and steal their advertising dollars. A less obvious impact of invalid traffic is on organic rankings and traffic of websites. Too much invalid traffic may lead to a website losing precious rankings and traffic on search engines. On the contrary, if brands have access to reliable data, they can effectively mitigate these risks. Access to accurate data will enable brands to accurately pinpoint their most valuable traffic sources and nurture them. It will also give them clarity on their effective channels and best-performing campaigns in which they can invest for greater returns. 2. Targeted Reach One area of digital advertising where there is a serious lack of transparency is ad placements. Advertising networks and platforms let brands exercise some control over who sees their ads. By targeting the right audience, brands can ensure that their ads are being displayed on websites frequented by their target audience. However, this is usually only true in theory. In most cases, brands have little control over or information about the websites that publish their advertisements. As a result, many brands remain unaware that their ads are being displayed next to irrelevant content or on completely irrelevant websites. The obvious impact of this is, once again, wasted ad spend. If the ads are being served to users who may not find them relevant, the conversion rates suffer, diminishing the returns for the brand. The less obvious impact of the same can be observed in extreme cases. In such cases, brands become victims of unsafe ad placements. This means that without the knowledge of the brand/advertisers, their ads are displayed next to questionable or extremist content. It isn’t difficult to imagine the impact on a brand if its ad is displayed next to, say, homophobic content. While the brands have little control over this, most users who view these ads are unaware of the same. As a result, when such unfortunate ad placements come to light, the advertising brand’s image suffers the most damage. If, however, brands have the power to verify and control where their ads are displayed, they get access to targeted reach. This means that brands can target users who are most likely to respond to their offer and convert into paying customers. 3. Improve Efficiency One of the biggest yet most overlooked effects of bad data on advertising is skewed metrics. The most lucrative aspect of digital advertising is the access to ad reporting data that enables optimization decisions. However, due to the lack of transparency, bad actors in the advertising supply chain may tamper with their traffic reports in the hopes of making a quick buck. Similarly, invalid traffic can make campaign reports inaccurate. It may compel advertisers to give credit to bot traffic sources and overlook legitimate ones. Alarmingly, this effect isn’t limited to traffic sources. Bad data may lead advertisers to invest in the wrong ad variations, audience variations, and even ad platforms. In the long run, this can have a compounding effect on wasted ad spending. On the flip side, if brands can validate their traffic, execute data optimization, and get access to accurate reporting, optimization decisions will be easier and more accurate. This can result in substantial improvements in the ROI a brand can expect from its digital advertising efforts. Your Partner for Trust and Transparency The good news is that brands and advertisers are not powerless about transparency. By validating traffic and publishers and carefully selecting advertising platforms and vendors, advertisers can ensure access to transparent and reliable data. Manually validating traffic and its sources can prove to be inefficient. It is time-consuming, and there exists a margin for human error. This is where a solution like mFilterIt becomes relevant. Using AI and ML algorithms, mFilterIt’s ad fraud solution and brand safety tools validate traffic and publishers in real-time along with tracking the unsafe ad placements. Our solution ensures continuous monitoring of traffic and traffic sources, eliminating all margins of error or overlooked incidents. It also enables brands to stay clear of objectionable ad placements and reduces the risk of brand risks. It is designed to enable informed business decisions based on reliable, verified data. Way forward A transparent internet is better for users and brands alike. As we progress toward a more privacy-focused future for the web, advertisers’ reliance on transparent data will only become more prominent. It will enable advertisers to continue being productive contributors to a better internet and