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Ad Traffic Validation

Ad Fraud Detection

Do You Think Ad Fraud Detection on Mobile Attribution Platforms is Enough?

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Mobile attribution platforms are present to report performance measurement, attribution, and analytics on your campaigns. These platforms are essential to get relevant business insights and efficiently analyze the App performance campaigns. If these platforms are not present, the advertisers will be unaware of the whereabouts of their payouts made to their networks. However, the advertiser must also ensure that they are not paying for fraudulent transactions. Most of the attribution platforms claim to provide fraud detection tools which are often bundled with their attribution services. However, the question is whether the fraud detected on mobile attribution platforms is enough. Though the attribution platforms are providing fraud detection solutions, there is often a gap between the fraud detected and the actual ad fraud. In this blog, learn how attribution platforms fail in detecting actual fraud and why your brand needs an expert to prevent the consequences of ad fraud. 1. Bundled Package Schemes The biggest attribution platforms or the MMP run on a revenue model where the billing is done on the attributed data. However, some attribution platforms also offer additional services of ad fraud detection and prevention solutions to their consumers. But there is a loophole. The attribution platforms bill the advertisers on the attribution data and due to ad fraud detection, the revenue eventually reduces. To create a balance between the attribution and the ad fraud, they choose to miss the actual fraud traffic coming. This further results in the loss of the advertiser’s money as they are paying for the fraud detection and attribute data to the MMPs along with the fraud traffic coming from SIVT, organic hijacking, and business compliance frauds. 2. Ad Fraud Detection In relevance to the above case, the ad fraud detection solutions provided by the attribution platform often claim to detect fraud up to 20%. However, ad fraud is still present in up to 50-60% of the ad traffic they claim to be clean. In this case, the advertisers are under the impression that the fraud on their ad campaigns has been detected and prevented. But the reality is that they are still paying for the ad traffic coming from bots and click injection. 3. Offering Make Your Rules Benefit Along with providing ad fraud solutions, the attribution platforms also offer one of their best-selling USPs – “customers can customize their rules to detect ad fraud”. This means they can decide under what criteria they want to detect ad fraud. For instance: An ‘X’ customer wants to detect ad fraud location-wise”. However, in this case, there is a major gap between the ad fraud detected and the actual ad fraud happening. However, the advertisers may detect the bot traffic coming from an irrelevant location outside their selected locations where the ad is supposed to serve. However, the advertisers are not ad fraud experts and cannot detect sophisticated bots that are coming every day. This further results in a loss of time and money for the advertiser on the ad traffic which is not benefitting them in any way. How mFilterIt Offers a Solution Full-Funnel Ad Fraud Detection At mFilterIt, we run a full-funnel ad fraud detection on ad campaigns to track sophisticated bot patterns and take immediate measures. This helps prevent the impacts of bot traffic on ad campaigns in the future and saves the waste of advertisers’ money on invalid traffic. Quick Action on New Detected Bots When we detect a new ‘bot’ in an ad campaign of an X customer, our first step is to identify that bot in the campaigns of other customers and flag them on every customer’s ad campaign. Proactive Reporting Some of the attribution platforms provide the ad fraud report on a D-7 basis. This means that if the ad campaign is detected till the 20th of a month, then the advertiser will receive the report on the 28th of that month. During this time, the advertiser is in a constant dilemma to understand the actual ad fraud detected in their ad campaigns. This further delays the possible preventative measures that could have been taken against ad fraud. However, we provide D-1 data, which means that if the ad campaign is analyzed till the 20th of the month, the advertiser gets the report on the 21st of the month. This helps the advertiser to understand the possible impact of ad fraud and take preventative measures immediately without wasting further ad spending on irrelevant traffic. Conclusion MMPs claim to provide ad fraud solutions but for many reasons, they miss a high percentage of fraud. This further impacts the performance of ad campaigns and forces you to keep investing in fraud traffic. On the other hand, an ad fraud prevention and detection solution like mFilterIt not only detects ad fraud at the early stages but also ensures to prevention of its impact on your campaigns in the future. Get in touch to learn more about Ad fraud detection

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Bot-Traffic

5 Clear Signs to Detect Bot Traffic in Your Digital Ad Campaigns

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Advertisers spend millions of dollars every year on digital ads to ensure that they reach the right audience and expand their reach. They get the traffic, and they are happy that their ads are reaching the desired audience. But is this traffic coming from a genuine audience? This question was never thought of until the word “Bot Traffic” came into existence. In the past few years, bot activity has taken a surge and advertisers are unknowingly spending money on views that are coming from Bots instead of real users. Not just the money, irrelevant traffic coming from bots is impacting the effectiveness of the digital campaigns and the advertisers are in a shock. In this blog, we are covering the impacts of bot traffic and how one can detect bots in their ad campaigns. Read along, What is bot traffic? According to recent statistics, 50% of the web traffic constitutes bot traffic. These bots are used for good and bad purposes. While the good bots help the internet to run smoothly, the bad bots are malicious bots that mimic human traffic. In recent times, there has been a rapid rise in bot traffic. These bots do not just compromise the ad campaign data, they can also commit grievous cyber-attacks to steal data and commit DDoS attacks. The bot traffic heavily impacts the advertisers running “pay per click” or “pay per impression” campaigns by disrupting the analytics data and draining their advertising budget. Bot Traffic Drains Not Just Advertising Budget The foremost thing that advertisers have to deal with is the draining of ad budget on bot traffic. Instead, this wasted ad budget can be used to target real humans. But that’s not the only aspect of concern. Apart from money, the advertisers also end up with skewed data due to bot traffic. Some of the consequences of a manipulated data are: 1. Automation Leads to Targeting Wrong Audience Major advertisers use automation to target a large amount of user behavior data and allocate advertising spend on ads without any manual intervention. However, if the targeted audience data is generated by bots instead of genuine customers, then due to automation the ads end up in the wrong place at the wrong time. 2. Heated traffic Due to bot activity, some pages can witness a sudden peak in website traffic boosted by bots. Some posts may seem to work better on social media due to high impressions and engagements. Seeing the high traffic, advertisers fall into the trap and invests more money in the ad campaigns instead of investing time and money on campaigns that can attract a real audience. 3. Wrong Chargebacks In case of a credit card fraud where bot activity is involved, the businesses have to incur the cost of chargebacks. However, this money goes to the fraudster instead of the legitimate owner of the credit card. Moreover, this cost is not considered in the revenue figures when analyzing the campaign’s effectiveness. Ways to Identify Bot Traffic 1. Unusual Spike in Traffic If you see an unusual spike in your ad traffic, this is a clear sign of bot activity in your ad campaign. Below is an example of an unusual flow of traffic due to bots. 2. High Impressions An impression is a metric that measures the number of times an advertisement is displayed on a user’s screen. When running a CPM campaign, if you see a spike in impressions at a consistent rate then it can be assumed as a bot activity. Below is an example of a case of an IP bot pattern where repetitive impressions are served to a specific IP at a specific hour during the day. 3. Click To Conversion rate is low If you witness a spike in the number of clicks in your ad campaign, and the number of conversions is not relative then it is a case of bot fraud. As the bots cannot convert, they just visit the website and leave. This results in high traffic whereas the conversion rate remains low. 4. Traffic from Unusual Location If you are receiving traffic from a location outside your targeted area, it could be a sign of bot traffic. For example, if you’re targeting an audience from Chicago and you’re receiving traffic from California, Iowa, and even France then it might be the bot interacting with your ads. Below is an example of the geo fraud committed by bots. 5. Analyse Suspicious IP Addresses If your campaign is getting heavy traffic in a short period from a single IP, it is a clear sign of bot activity. The best way to protect your ad campaigns from IP bot attacks is to block them. Why your brand needs an ad-fraud expert to combat bot traffic? The above-mentioned ways can help you track basic bot activities. However, over time some sophisticated bots have also emerged which are hard to trace without an expert eye. To protect your ad campaigns from sophisticated bots, it is important to partner with an ad fraud detection and prevention solution provider like mFilterIt to ensure full-funnel coverage from fraud. Along with detecting the usual bot patterns, our Ad traffic validation suite ensures that your ad campaigns are not impacted by a new bot. Every day there is a new bot emerging, thus whenever we detect a new ‘bot’ in an ad campaign of an X customer, our first step is to identify that bot in the campaigns of other customers and flag them on every customer’s ad campaign. So, if you’re still thinking about acting against bot traffic, do it now. Save your ad spends to go in the drain on irrelevant traffic and focus on investing it to attract real customers. If not now, then when?

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Click-Injection-Fraud

Click Injection Fraud Costs More Than Just Money for A Brand

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With the growing trends of mobile advertising, fraudsters are finding new ways to sneak into the digital ad ecosystem and loot the advertiser’s money. One of the known frauds in the mobile advertising segment is Click Injection. According to Statista, followed by SDK spoofing, the click injection cases have increased up to 27% worldwide in 2018. And with the increasing cases, fraudsters are making money while the advertisers are losing their ad spending on ineffective campaigns. Apart from the revenue loss, the click injection fraud also leaves a big impact on the brand in terms of credibility. But before we move forward, the foremost thing is to understand the meaning of click injection. What is Click Injection? This is a sophisticated form of click-spamming that is majorly related to Android devices. According to Statista, in 2021 the install fraud rate was found up to 12% in Android devices whereas in Apple IOS it was 7%. Click injection is like a hidden spy camera installed by fraudsters. When a user downloads an app that is affected by the “install broadcasts”, fraudsters can detect when any other app is downloaded. Further, it triggers a click before the installation process completes. As a result, the fraudster receives the credit for the completed app installs. Along with this, the act also results in poaching of organic installs that were driven by genuine advertising. This fraud impacts both the revenue and efficiency of the campaign run by the advertiser. Here are a few instances of how click injection impacts a brand. Impact of Click Injection on Brands Draining Advertising Budget Though the ad engagement is fake, the advertiser remains under the impression that the received “ad click” is genuine and eventually leads to the payout at CPI to the affiliate network or the publisher. This leads to a loss in the advertising budget which can be instead used to reach genuine users. Stealing Real Conversions Beyond the loss of the advertising budget, the click injection also costs the advertiser the conversions expected from the campaign. When a user clicks on an injected ad, the fake action on the ad will be attributed. This further leads to poaching of organic conversion and unknowingly the advertisers continue to invest in an ineffective campaign. Manipulated Analytics If we look at the bigger picture, apart from the revenue loss, the brand has compromised data due to click-injection fraud. For instance, when an advertiser sees that their paid campaign is attracting traffic, they will most likely spend more to optimize the ROI. However, due to the manipulated results, the damage becomes two-fold. First, the advertiser is investing more in ads, and secondly, they are ignoring the possible channels which will bring real traffic. How To Protect Your Brand from Click Injection Fraud Data Analysis The Average Click Install Time (CTIT) is an important factor to understand and detect click injection fraud in ad campaigns. If the installs are fraud-proof, then the data will be most likely be in the range of an average CTIT. On the other hand, if the installs are fraudulent then there will be a visible peak in the number of installations during the time range of CTIT. However, there is a loophole in this process. Some of the apps are also capable to manipulate the data pattern by setting a time range after which the app opens. Choose A Reliable Marketing Partner When choosing a marketing partner ensure to do a deep analysis of their previous work and expertise. If anyone claims to provide an ‘n’ number of app installs at a surprisingly low price, then it is highly likely to be fraudulent installs. Even though the rates may differ for different industries, the delivery of genuine installs by ethical methods comes at a high price. Fraud Detection Solution Instead of beating around the bush, it is better to focus and eliminate the bug first. In this case, despite taking all the precautions it is hard to say that your campaign will be protected from click injection ad fraud. Thus, it is better to switch to a holistic ad-fraud solution like mFilterIt. Our ad-fraud elimination suite helps advertisers run digital campaigns and avoid becoming a victim of app fraud. With the advanced solutions provided throughout the customer journey, the advertisers can rest be assured to get engagement from real humans and eliminate bots from their ad campaigns. With the help of high-tech and future-driven AI and ML techniques, we ensure to provide the best solutions for the fraud-free growth of your business. Conclusion Even though the click injection fraud generates manipulated install numbers, the CPI and other associated events are real. This makes it very hard for the advertiser to differentiate between a real and fraudulent lead. The earlier the advertiser decides to take the right action to prevent and eliminate ad fraud from their campaigns, the sooner they will be able to divert their revenue spend on effective campaigns. And to take quick action, the mFilterIt ad traffic validation solution will be your helping hand to eliminate click injection fraud from your mobile advertising campaigns.

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OEM-Myths

Busting the OEM Myths

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During the first quarter of 2021, OEM app stores acquired nearly 42% of the global market share. OEM refers to original equipment manufacturers, and in mobile terminology, it caters to brands like LG, Redmi, Realme, etc. Such companies offer personalized app stores, and brands can obtain premium leads through OEM advertisements. Moreover, unlike Google Play Store, OEM apps are perceived as relatively safer and fraud-free. The cost of advertising on OEM stores varies on the type of placement. OEM advertising has two broad categories: pre-installed apps and app store promotion. Pre-installed apps are a gateway to new users as they are visible on the screen upon first-time phone usage. App store promotion is an icon & browser-based promotion, hot downloads, and recommended apps on an OEM app. In mobile terminology, OEM stores are even referred to as alternate Play stores, as they are pre-installed in addition to Google Play Store. OEM advertisements have opened doors to an untapped market, wherein brands can directly connect with the targeted traffic. Moreover, advertisers believe that they can generate higher ROAS and not worry about fraud, as the mobile manufacturer ensures exclusivity. OEM stores are mainly used for app installation. According to sources, OEM stores can boost app installs by 5x higher than the standard advertising methods. Does the App You are Promoting Require OEM Type Traffic? OEM app stores offer high-quality users and increase the visibility of the app. Moreover, it is an optimum platform for boosting installations. Apps removed from the Google Play Store can use the alternate app store to increase their market growth. The third-party app stores receive security certification and clearance from the manufacturer. Unfortunately, they may not take measures like Google Play Store apps when they encounter potentially harmful apps (PHA). Therefore, it is necessary to decide whether putting the app on an alternate store with lower protection levels against ad fraud can cause more harm than benefit. Look at the Data Points When receiving installs, carefully look at the app versions used. Many times, fraudsters may display fake installs using an archived app version. Moreover, sudden spikes in conversion levels should also match the click levels. If you find discrepancies, it is most likely due to ad fraud. Closely monitor and question the type of traffic. For example, is the correct targeting happening, or a plain install campaign? For, what is the percentage of the handsets traffic in installs vs. reality? Are the installs happening on older handsets? Besides this, do a simple click-to-conversion analysis and see what the graph looks like, and does that make any sense? Then, check your backend/KPI’s are they getting met or not. Issues with OEM Advertising Merely Runs on Faith Advertisers believe that OEM app stores offer brand-safe environments because they trust the OEM mobile manufacturing brand. The two-way communication between the advertiser and the brand ensures transparency in this relationship. Building a two-way trust helps in increasing the app installs, but how does it prove that they are legit? Do you have to leave that on trust too? Moreover, does it eliminate the possibility of duplicate/fake apps? So, are alternate app stores offering a brand-safe environment, or is it an illusion? Moreover, the recent malware release through the Netflix duplicate app on an alternate store is sufficient proof that “yes” is a questionable answer to any of these questions. If it were true, ad fraud elimination companies wouldn’t be working hard and fast to detect data anomalies. Nobody Goes Behind and Checks What is the Actual Source? Is the Actual Source and Claimed Source to be Same or Different? The transparency between the OEM and advertisers often leads to the belief that the actual and claimed source would remain the same. However, if advertisers go in-depth and review, they would find many discrepancies. For example, fraudsters display fake installs by cloning the SDK of an app and using different means of installation. Sources state that 13-18% of third-party app installations happen majorly through fake devices and other ad frauds. At times, users are unaware of the app install. Fraudsters also use cloned installs to display the “x” installation of the advertiser and achieve monetary gain. Moreover, cybercriminals even add malicious codes to these apps and conduct more ad fraud in the background. By default, these Sources are Whitelisted on MMPs. Commonly, an MMP receives click and impression attribution after a user clicks on an ad. The “install” attribution happens whenever a user opens an app for the first time. Such in-app OEM installs, impressions, and clicks are commonly whitelisted by MMPs. However, fraudsters register fake impressions and clicks with the MMP. Moreover, they even use spoofed SDKs for faking “install” attribution on the real device and report the same to the MMP. Another common method of stealing attributions for organic and inorganic installations on MMP is through click spamming, wherein fraudsters fire clicks until they claim the last click attribution. When analyzed, the install-to-attribution ratio goes beyond the 1:8 ratio. Therefore, the default misattributions by MMPs are causing analytic and reporting discrepancies. How did they Get Themselves Whitelisted and Start Mixing Traffic and Fooling Everyone? At present, the decision to recognize sources to include in the whitelist lies with the MMPs and includes numerous fraudulent attributions. Moreover, the whitelists are created by default, and the advertiser has no say in the whitelisting decision, even though the advertiser is making the payments. As such, the advertiser believes that the MMP is doing its due diligence and providing accurate attribution results. Moreover, the results provided by the MMP motivate the advertiser to increase the advertising budget and the payout to the fraudster. Similarly, outdated app or SDK version installation is typical fake installs used by fraudsters. Moreover, the fraudulent ad network may make the fake attributions appear organic to boost the installation’s legitimacy. Furthermore, cybercriminals may even use the older version of the SDK for displaying purchase rates. In reality, there is no purchase from the fraud ad network, and neither does

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Click-Injection

Click Injection: Why Should Brands/Advertisers Worry About It?

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During the first install session, fraudsters hijack ‘install broadcasts’ using bots/malware, and inject clicks for misattribution with the MMP. This fraud is commonly called click injection and is the most hated fraud by brands/advertisers. It diminishes click integrity and derails the efforts of providing a safe experience to the user, the backbone of an organization. In addition, it forces brands/advertisers to pay for their ‘own’ traffic from the advertising budget to the fraudster The reliability of campaign analytics for building marketing strategies is further hampered, and the scary part is that fraudsters build ‘relationships’ with the brands by sharing false performance reports. If we want to add fuel to the fire, cybercriminals also take over user accounts and steal identities and financial details through malware/bots. 6 Ways Click Injection Endangers Brands/Advertisers Organic Stealing Organic traffic is an intent-based audience targeted using many marketing practices. They are vital to advertisers as they help diminish advertising budgets, increase app installs, generate higher revenue, etc. Brands often advertise their apps on their websites, and social media handles to increase organic installs. The users click on such ads and install the app after redirection to the Google Play Store, Apple Store, or a third-party store. Such users have organically installed the app, but unfortunately, the credit for it often goes to the fraudster because he/she injected the last click, and it got registered with the MMP. As a result, cybercriminals are stealing organic users of the app owner. Attribution Theft Attributions are important for advertisers because they help understand the highest/lowest-performing sources/channels, drive campaign goals, and structure investment decisions. Unfortunately, advertisers become victims of attribution theft through click injection. It is the basic principle of this ad fraud. The cybercriminal can report a high install conversion rate (CVR) by manipulating the advertiser’s attribution and acquiring financial gain. However, the user could have organically installed the apps from any store or the brand’s website. Bad Analytics Brands often measure the click-to-install (CTI) ratio to determine the CVR of an ad install campaign. Unfortunately, attribution theft caused by click injection leads to reporting falsified high CVR of the fraudster. As a result, advertisers instill confidence in the campaign’s performance. In reality, the conversion rate of install campaigns lies between 1-1.5%. Therefore, a high percentage of CVR, which in most cases is a result of click injection, is 100% and drives the marketers in the wrong direction. Furthermore, the estimated Click-to-Install Time (CTIT) becomes extremely short through click injection. As a result, brands misinterpret the performance of campaigns/affiliates and make wrongful investments. Builds Trust on ‘Fraudsters’ – Scary! Fraud affiliates share high-performance reports with the advertiser and gain the advertiser’s trust. However, they are in the game for making money and don’t care about them. So, they continue with their click-injection fraud. Moreover, brands/advertisers would seek alternative options if they don’t receive the ongoing performance. Additionally, brands/advertisers don’t recognize the attribution misrepresentation by cybercriminals because the real CVR is hidden through spiked traffic. Their irresponsibility of not using an ad traffic validation solution makes them vulnerable to fraudsters. Meanwhile, brands/advertisers disassociate with an underperforming affiliate displaying the real campaign performance. Furthermore, affiliates rely on ‘word-of-mouth’ for brand associations, and their distrust drives away other affiliates from the brand/advertiser. However, this doesn’t last long as the latter has the option of switching affiliates. Loss of Advertising Budget Brands/advertisers lose millions of dollars every year from their advertising budget to fraudsters by not eliminating click injection. The misattribution caused by it diminishes the profits/commissions of legitimate publishers and advertisers. Moreover, most businesses run CPI campaigns on different ad networks. Additionally, global CPI rates for many countries are much higher than in India. Therefore, brands/advertisers constantly expand budgets for increasing networks for running CPI campaigns on such networks. Our research suggests that networks with higher CPI costs often witness higher click injection because the fraudsters can make more money and find this an ad campaign vulnerability. Therefore, brands/advertisers begin paying even more than before to cyber criminals due to network expansion or placements in costlier networks. Creates Brand Distrust Due to Malicious Device Activities Users installing brand apps and becoming victims of click-injection fraud also experience malicious device activities. Besides stealing unconsented “install broadcast” notifications from the user’s device, fraudsters also use bots/malicious codes to read messages and take over accounts. User messages often consist of OTPs and financial details. Fraudsters steal this information and conduct identity/financial theft. As a result, the malicious activities through the app make the user disinterested in the brand and uninstall the app. Brands experience high drop-offs as the users have lost trust in it. Furthermore, the CTIT ratio of the install campaign substantially diminishes. Therefore, click injection directly hampers the brand’s reputation. A Single Solution for App and Web Ad Frauds mFilterIt’s Ad fraud solution uses AI, ML, and data science to reveal the actual traffic sources and eliminate ad fraud on the web and app. In addition, the solution reports activities of click injection to the brand/advertisers and helps prevent association with fraudsters. Moreover, mFilterIt’s solution tracks sudden spikes in traffic, attribution hijacking, organic stealing, and other fraudulent activities on brand and performance campaigns. Therefore, a single solution is enacted as a safeguard against ad fraud. Diminishing ad fraud through click injection restores the user’s faith in a brand, optimizes analytics, and avoids wrongful investments. Conclusion Mitigating ad fraud has become a primary objective for advertisers across the globe because it reaps multiple advantages. In addition, however, it has become crucial to fight against click frauds, especially click injection, because marketers rely on user engagement and assess it through click-to-visit conversion as a measuring metric. mFilterIt’s Ad Traffic Solution solidifies consumer trust in the brand/advertiser by avoiding the dangers associated with ad fraud. Brands seeking accurate analytical results, higher human ad engagement, and reliable CVR must use this solution. Get in touch to know more about Click Injection.

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Click-Injection-Affect

How Does Click Injection Affect a Brand’s Users?

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“You have been locked out of your account/You have zero balance” is a message no user ever wants to see. Can you believe this could happen to a brand’s user through the same source of click injection? – a copycat app or pirated APK. Users behold brands as the responsible party for their asset duplication. The repercussions for the brand become dire in this process. On the other hand, fraudsters committing identity and financial theft, besides click injection, make the user’s life a living hell. Here is what happens to them: 4 Direct Implications of Click Injection Attacks on a Brand’s Users ● Device Access/OTP Fraud/Financial Fraud Click injection is often found in pirated apps downloaded from app stores or APKs. Users are tempted to download such apps because they offer free access to the content/features and remain immune to the click-firing activity in the background. Moreover, fraudsters use malicious codes or bots within the app or APK to acquire access to a user’s device, messages and hacking financial details. Unfortunately, the user also blames the brand for the financial and OTP fraud. Therefore, the apps/APKs responsible for click injection fraud also drive users away from a brand and switch to next-in-line alternatives. ● Decreases Trust and Loyalty Click injection generates unconsented ‘clicks’ on behalf of the real user. Unfortunately, the MMP doesn’t see such ill-actions, so the advertiser/brand remains unaware & unworried. Unfortunately, the sources of this ad fraud are also responsible for plaguing other attacks through them on the user’s device. Such activities make the user concerned and hardwire distrust in the brand, which becomes nearly impossible to repair. Furthermore, the brand’s inaction to fight back against the sources of fraud makes the user backlash through negative reviews, app store reports, and participation in social media trolling. The bad publicity causes a dent in loyal users and increases the real app’s drop-off rate. Moreover, the users become tempted to find other shortcomings and cripple the brand’s reputation through the ongoing repercussions. ● Creates Widespread Panic and Anxiety Pirated apps or APKs causing click injection and identity/financial theft create widespread panic and anxiety in the minds of the brand’s users. The users become more concerned about the thefts and want payback. At this point, they can’t sue anyone other than the brand. On the other hand, the brand doesn’t take responsibility for the thefts because the user was never on its app. But unfortunately, when a large number of users use a brand, new users are less likely to create accounts, and the old users won’t want to stay associated with the brand. Anxious app users also believe any fake news and share it across social media, causing widespread anger, panic, and irritation against the brand. Moreover, the user’s actions diminish the potential reach of organic traffic, and competitor visibility significantly increases. ● Cannibalizes Revenue from Existing Users Bad reputation caused by click injection and other frauds certainly cannibalize business aspirations; however, a positive notion makes a brand rise: “Time heals all wounds.” – the Greek poet Menander. But until the right time arises and the brand has somehow restored faith in the existing users, the company witnesses diminished revenue through in-app and web ads. Moreover, the brand also has users who haven’t been victimized. Moreover, the existing users still have faith in the brand and believe it will repair its reputation. Furthermore, the existing users are scared of making profiles and purchases. So, they are less likely to make large transactions. A Solution to Avoid Ad Traffic Violations mFilterIt’s Ad Traffic Solution safeguards brands against web and app ad fraud. Moreover, it is driven by AI, ML, and data science and generates real-time alerts. Therefore, brands can detect analytical anomalies caused by ad fraud instantly. Moreover, mFilterIt’s solution uses technology to eliminate ad fraud and safeguards digital advertising and customer data systems. Additionally, it systematically showcases the types of ad fraud and their sources. Some of the biggest advantages of using the solution include avoiding attribution & organic stealing, better ad engagement rates, no wastage of advertising spending, etc. Conclusion Click injection seems like an advertiser-centric problem, but it is also a brand and user issue. Moreover, fraudsters commonly use the source of this ad fraud for identity and financial theft and cause widespread panic, disinterest, and disengagement with the brand. As a result, fighting back against click injection has become essential for safeguarding a brand’s reputation, revenue, and users. mFilterIt’s Ad Traffic Validation monitors and eliminates ad fraud on the internet and contributes to the brand’s faith restoration in the users’ minds. Get in touch to learn more about the Click Injection.

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Organic-Stealing

How Bad is Organic Stealing for Your Brand?

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Unpaid/Organic traffic signifies that a brand has obtained a market reputation and trust of its consumers. The traffic growth happens over time and is a collaborative result of the product, marketing, promotion, and other teams. Organic traffic is beneficial for brands for many reasons such as visibility, garnering consumer trust, free engagement with qualified prospects, etc. Meanwhile, inorganic traffic boosts reachability/visibility to the target audience, influences brand searches, acquiring leads, and more. On average, 16-20% of conversions happen through organic users. The term ‘organic stealing’ often stirs up emotions like fear, anger, frustration, etc. “By doing organic theft, fraudsters deprive brands of new user acquisition and steal attributions of existing loyal users.” For any given brand, a user base is quantified by the revenue. The purpose of doing advertisements is to increase this very base. But what if your ads are not bringing in over and above the revenues that it is expected to increase the current traffic base? You might be a victim of organic stealing. What essentially happened is that you are paying for customers who are already engaged with your brand, and no new addition has happened. Your ad budgets went inlining the cybercriminal’s pocket. Stealing organic traffic also causes other repercussions for a brand. For example, a fraud affiliate may continuously inject clicks and register attributions with the Mobile Measurement Partner (MMP). Besides money, the brand receives falsified campaign analytics because the user never clicked on the ad. Additionally, misattribution results are used to develop marketing strategies, and an additional budget is used to boost the fraud affiliate’s activities. App optimization efforts also get scrutinized due to organic traffic theft. A team working on app optimization would use the behavioral data to check organic downloads/installs. The team would use the exact data for optimizing features, functionality, and user experience (UX). Unfortunately, the data visible to the analysts is falsified or doesn’t display its full potential. 2 Ways to Combat Organic Stealing ● Continuously Review CTRs on Every Campaign Paid digital ads witness meager conversion rates whenever organic stealing comes into the picture. Your click-through rate (CTR) substantially plummets for every campaign and demands reviewing the analytics. Upon review, you would notice high impressions or views but drastically low clicks or visits. As such, paid ads should increase users because the brand has enhanced visibility. Unfortunately, the reverse impact is happening and draining the advertising budget faster than before. ● Ad Traffic Validation The best method of staying away from fraud affiliates and avoiding organic stealing is by using mFilterIt’s Ad Traffic Validation. The solution works 24×7 and alerts about analytical anomalies in real time. Therefore, brands can eliminate ad fraud and retain their organic traffic. Furthermore, detecting authentic inorganic sources helps brands identify the actual top performers of their affiliate marketing campaigns and build marketing strategies using accurate analytics. Besides this, the solution also validates traffic sources on the URLs shared by the brand. So, brands can eliminate ad fraud and keep their customer data systems/remarketing lists clean. Conclusion Cannibalizing organic traffic drains the marketing budget and straightforwardly showcases that ad fraud is prevalent. Moreover, it dramatically threatens analytics concerning marketing strategies and compromises asset optimization. Therefore, brands need to mandate an Ad Traffic Validation solution. mFilterIt is a pioneer in ad fraud detection and elimination. The company’s solution is safeguarding brands across six continents from advertising fraud. Get in touch to learn more about Organic Stealing.

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digital-marketing-budget

Are You Using Your Digital Marketing Budgets for Paying Your Offline Orders?

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Yes, this is one of the digital ad frauds that the affiliate networks are doing, and the advertisers end up paying for orders that are not online orders. As a result, offline orders get cannibalized into online orders, and marketing budgets are drained. Apart from the loss of digital marketing budgets, the advertiser pays online offers/discounts for these offline orders. How is this Fraud Happening? In the below graph, a fraud affiliate has used a Bot to send spiked traffic during a specific hour of the day to control the conversion ratio. However, orders are placed during the whole day from two devices only. As a result, the flat line conversion rate is at 26%, in which orders are coming from two devices (offline cannibalizing). However, the spiked traffic conversion rate is 2%, in which orders are all coming from the same two devices. This clarifies that this traffic is purposely spiked in this hour to control the overall conversion ratio. Actual repetitive events are coming from visits. Moreover, these visits are from the same desktop and IP, which indicates that the visits are coming from the exact location, and offline orders are getting punched in. These orders can be cash on deliveries and canceled at any time or a meager value that adds nothing to the bottom line. What Does the Network Achieve? ● Advertisers Make Payouts Affiliates team up with the retailer to earn commission from advertisers by completing the KPIs of a campaign by unethical means, which are other than digital sources. This happens when a retailer places orders using affiliate and referral links. The affiliate receives a monetary benefit from the advertiser for delivering high conversion rates or confirmed orders. Moreover, most affiliates receive a fixed payout from the advertiser for delivering confirmed purchases. But, on the other hand, the “order value” is not often set. Therefore, the affiliate could receive a payout of Rs 20,000 or Rs 200/100 order, whereas the order value could be as low as Rs 50/order or Rs 5,000 for 100 orders. Assuming the affiliate pays a fixed amount to the retailer for placing the order, let’s say Rs 5,000, the fraudulent affiliate still makes Rs 15,000. Moreover, the retailer can place CODs and reject or cancel online orders. So, the advertiser might not even receive money but must make payouts to the fraud affiliate. Therefore, the advertiser loses money for non-online orders. ● Loss of Commission/Offer/Discount on Online Orders The retailer partnered up with the affiliates to get a better-discounted value on their sale. They also can resell the products to their offline customers at the MRP. As a result, the retailer is making money by reselling products and even receives money from the fraud affiliate for placing the orders. mFilterIt & Ad Fraud Solution checks for retailers creating multiple fake profiles on e-commerce apps by detecting their location and device as it remains constant. By detecting such anomalies, brands can avoid cannibalizing their online orders and making commission payouts for offline orders to fraudulent retailers. What Losses Do Advertisers Incur? ● Offline Orders Get Cannibalized The retailer orders for multiple customers by creating various profiles with a single delivery location. Therefore, the retailer cannibalizes online orders offline and makes additional money by reselling at MRP to offline customers after availing of online discounts/offers. On the other hand, the brand suffers a loss as it doesn’t expand its customer base. Moreover, the advertiser fails to explore the scope of areas with the demand, as the existing customer base lies with the retailer. Furthermore, the advertiser only receives a signal that a single location has high demand when the reality is different. ● Digital Marketing Budgets Incur Offline Order Payments Through their digital marketing budget, brands make payouts to affiliates and retailers. As mentioned earlier, the retailer places the order using the fraud affiliate and resources, and the fraud affiliate shares a portion of the earned commission with the retailer. Moreover, the retailer will likely resell these orders at MRP to offline customers and earn more money from the sale. There were no payouts required for these offline orders as the affiliate is incentivizing retailers for placing orders, a.k.a., incentive fraud. Furthermore, the affiliate hides the peaking conversion rate by using bots to deliver high traffic within certain time intervals. For example, an affiliate spikes 1000 visits using bots and displays a 100% conversion rate. As such, CVR can never achieve its full scale. On the other hand, legit affiliates have a 1-1.5% CVR. Therefore, such a high CVR indicates ad fraud and is only done by fraud affiliates to hide their fraud CVR. In reality, the fraud affiliate might be using 100 visits to deliver 100 purchases. Therefore, advertisers are losing the marketing budgets by paying commissions to fraud affiliates and retailers. ● Derails Reachability to Potential New Customers The fraud affiliate uses a retailer to create multiple profiles and place orders at the exact location. As a result, the advertiser fails to build a new customer base. Moreover, the customer base created by the advertiser is also displaying falsified information, as the same retailer creates the profile. Additionally, we can say that fake users also avail of discounts/ offers. Moreover, the advertiser pays a commission to the fraud affiliate for delivering bot traffic and not a single customer. Such partnerships between affiliates and retailers drain the marketing budget to attract legitimate customers from different locations. Furthermore, the advertiser may attract zero customers if the retailer cancels the orders. Takeaway Partnerships between affiliates and retailers are cannibalizing offline orders as online. As a result, brands and advertisers lose their marketing budgets to commission payouts. Also, it leads to warped marketing analytics and polluted business numbers. Putting an end to this is possible by detecting ad fraud, especially incent fraud in marketing campaigns. mFilterIt ad fraud solution detects any sudden spike in online traffic and displays the source credentials to advertisers. As a result, advertisers can recognize the fraud affiliate and attract a new

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Ad Fraud in Performance Vs. Brand Campaigns

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Digital Marketing spending is growing at a 9% CAGR globally, and digital media today has become a non-negotiable medium to reach out to consumers/audiences. For a marketer, the 2 obvious choices are to run either performance or brand campaigns to reach, act, convert, and engage with their target audience. While Performance campaigns are directly associated with results achieved, Brand campaigns’ focus is to ensure visibility and recall. Brand campaigns rely largely on viewability (impressions), while performance campaigns focus on down-the-funnel metrics. Performance marketing focuses on CPI, CPV, cost per sale, conversion rate, etc. on the other hand, the share of voice through mentions, sentiments, tags, etc., measures brand campaigns. Marketers and advertisers spend a large portion (>50%) of their digital advertising budget on these two campaigns. Our research suggests that it takes 6 to 8 impressions for someone to build a recall value of your brand. The regular reappearance of the brand ensures higher recognition of the solutions it offers. Viewability, according to IAB is, 50% of the ad’s pixels are visible in the browser window for a continuous 1 second. For larger ads (those greater than 242,000 pixels), 30% of the ad’s pixels are visible in the browser window. The same applies to video ads but for a minimum of two seconds. Ad viewability is the topmost layer of an ad metric. Fraudsters use fake impressions, bot impressions, ad stacking, and pixel stuffing for impression fraud. Meanwhile, performance campaigns work down the funnel and measure clicks, visits, events, and conversions. Clicks are important because they define the website traffic from online advertising. Visits account for the number of people who viewed the URL associated with the ad. Similarly, events could include installs, add-to carts, registrations, signups, conversions, etc. A close look at click-to-visit ratios and a visit-to-conversion ratio will give you the efficacy of your performance campaign. Cybercriminals impact these through click fraud, lead generation fraud, CPA fraud, influencer marketing fraud, cookie stuffing, click farms, and domain spoofing. The impact of ad fraud also influences programmatic, affiliate, and retargeting campaigns. The result of ad fraud is higher ad budgets, lower ROIs, diminished brand safety, fraudulent analytics, and infiltration of cybercriminals in customer data systems and ad servers. Ad Fraud in Brand Campaigns Impressions are the measure of brand recognition through online ad campaigns. Most digital brand advertisements are based on cost-per-mille (CPM), a.k.a., cost per thousand impressions. Total impressions determine the campaign cost in a CPM advert. The impressions also determine the reach of the advertising channel and total ad viewers in a specific channel. Ad fraud in impression-based campaigns happens when a fraudster opens a fake website, joins an ad exchange, loads ads on a fake website uses bots for page loading & impressions, and sells the impression inventory to the ad exchange. The common methods of impression fraud include the following: Pixel Stuffing: Loading a 1×1 pixel ad on a page counts as an ad served but is not visible to the human eye. Ad Stacking: Piling one ad on top of the other and keeping the original ad at the top. The impression counts for all ads, even when the top ad blocks ads below it. Fake Websites: Using bad bots to generate impressions on fake websites created solely to sell inventory that does not have human visitations. Bot Inventory on Genuine Websites: Fraudsters use bots to fulfill the “most required inventory” needs of the advertisers for acquiring credit and financial gain. Auto Impressions: Running in-app ads (even on inactive apps) on mobile devices to auto-generate impressions. Determining ad fraud in impression-based campaigns is challenging because the analytics reveal more data than performance-oriented ads. You only have the option of comparing CTR with impressions. High impressions mean an advertisement has significant exposure. Typically, campaigns with high impressions experience a high click-through rate (CTR). Under the unlikely circumstance that you have low CTR and high impressions, the ad is possibly incurring fraudulent activity in the background. Businesses thinking that programmatic or retargeting can resolve issues about brand campaigns should know that it’s not true. Fraudsters have spoofed domains, penetrated customer data systems, and used bots to act as a target for remarketing lists. So, ad fraud is prevalent in brand campaigns. Furthermore, brands should optimize programmatic campaigns by incorporating inclusion lists consisting of URLs where the ads should be placed. This fear of programmatic ads landing on sites built for ad fraud has become a common affair. Fake websites distort the analytics of brand campaigns. The unexplainable ad impressions can only account for invalid traffic as only 36% of the online traffic is human. Moreover, sometimes programmatic campaigns declare results higher than the population of a location. So, ensuring that ads are delivered to humans is a serious concern. Ad Fraud in Performance Campaigns All marketers and advertisers rely on analytics for creating brand strategies. Infiltration of ad fraud into the data falsifies the results, gives false hopes, increases the marketing budget, and doesn’t reach a large proportion of the human audience. Popular researchers quote that ad fraud would exceed $50 billion by 2023. Moreover, nearly 40% of advertisers think that ad fraud is a significant downside of programmatic ads. For example, fake clicks display that the campaign achieved higher performance than expected, but in reality, engagements with bots will not bring home any business. Ad fraud is still happening even after optimizing the campaign with geolocation, remarketing lists, and pre-bid programmatic placements. Fraudsters use the following methods to target performance campaigns of brands: Click Spamming: Executing clicks on behalf of real users without their consent in the background and claiming credit for obtaining financial gain from advertisers. Click Injection: Using malware in apps to stay alert about “install broadcasts” and obtaining the last-click attribution through click firing before the new app installation. SDK Spoofing: Tricking advertisers to believe that their ad will appear on premium apps, whereas it appears on fraudulent apps through SDK spoofing. Lead Generation Fraud: Filling lead forms using real or fake user information with the assistance of bots. Eliminating Ad Fraud in

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The Rise of Fraud in Retargeting Campaigns

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Brands enhance awareness, conversions, and ROIs through retargeting campaigns. Our research suggests that engagement rates go up by 2X through retargeting ads. Pixel, dynamic, and list-based retargeting are three of the most common methods used by brands to reach their potential buyers (through retargeting campaigns). Companies invest a large portion of their advertising budgets in such ads. Our research suggests that most brands invest 30-40% of their ad budget on approaching prospects through retargeting campaigns. The retargeting campaigns have been an attractive proposition for fraudsters to commit ad fraud. Retargeting fraud happens through bots, click injection, autoloading, install fraud, automatic redirects, inappropriate ads, and crypto miners. Furthermore, optimizing reach through programmatic retargeting ads increases fraud percentages because of the increase in programmatic ad frauds. The Most Commonly Used Methods in Retargeting Fraud ● Fake Impressions and Cookie Bombing Remarketing campaigns often involve view-through conversions. Fraudsters bombard them with fake cookies and impressions. Our research suggests that almost 40-50% of the time, the display ads are not visible to the users. Cybercriminals engage in pixel stacking or hidden iframes to record views on the remarketing cookie. The fraudster takes attribution for purchases on a legitimate website and receives payment for the same. Advertisers often spend more on websites delivering higher conversions on their ads. Fraudsters engage in cookie bombing to maximize conversions by delivering cookies to unique users. In reality, the fraudulent ad impressions are not visible to the users on these websites. These are generated by ads commonly stacked above each other or resized to 1×1 pixels. Fraudsters target unique users for poaching conversion attributions through the cookies—the view-through conversions of fraudulent advertisers skyrocket. Most ad platforms state that view-through conversions are nearly 9-10x higher than click-through conversions. ● Auto-generated Fake Clicks Users who visit a website add products/services to the cart and leave without purchasing are often considered prospects. Brands add their data to the remarketing list using cookies, pixels, lists, etc., and retarget through ads. Now, the user visits another website wherein a fraudster serves invisible ads and clicks automatically to the original publisher’s website. So, the click displays customer visits to the website. Now, the remarketing cookie of the customer displays that the customer viewed an ad, clicked on it, and visited the website. The credit goes to the ad whenever the customer purchases on the website. This practice is referred to as attribution hijacking. Under such an instance, advertisers think that their remarketing platform is performing better than expected and tend to increase their budget. However, in reality, a fraudulent click gets the attribution and even receives the payment for it. ● Hijacking with Remarketing Pixels Prospects visiting another website and not making any clicks may still record a view on the remarketing cookie. Whenever the customer revisits your website, the pixel script detects an ad view and loads an invisible iFrame. The iFrame generates an automatic click and visits after loading the original ad. The remarketing cookie of the legit customer now has a view, click, and visit from the ad. Moreover, the analytics support that the customer came through ad clicks instead of an organic source. The credit for the conversion goes to the ad whenever the customer makes a purchase. Furthermore, the remarketing platform of the analytics would display jacked-up visitors and conversions. However, the reality is that a fraudster hijacked the remarketing pixels and displayed the organic visitors as customers. Takeaway Retargeting campaigns help brands boost awareness, incur higher ROIs, and generate more sales. However, retargeting fraud causes a serious loss of advertiser revenue and should not be taken lightly. Fake impressions, cookie bombing, auto-generated fake clicks, and hijacked remarketing pixels obstruct real analytics, market reach, and conversions. Eliminating retargeting fraud can enrich these data points. However, sophisticated invalid traffic is not commonly detected easily. Ad fraud solution providers can even help to optimize ad spending on walled gardens (Google and Facebook). Driving impactful results through such a solution requires data trust and transparency between service providers and brands. Get in touch to learn more about the rise of fraud in retargeting campaigns.

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