Ever wondered why Ad Tech companies with no real inventories and most questioned for ad fraud are able to deliver on KPI's that matter the most? Have you been running an eCommerce mobile application and frequently supply limited & heavy discounted ad creatives to your ad tech vendors? The eCommerce landscape is so competitive, every performance marketer goal is to have maximum end of the funnel conversions keeping the user experience as the top priority. But do humans really scale? Next Generation Bots : In App Bot Fraud Those days are gone when cyber criminals used to target mobile app's marketing budgets for soft KPI conversions such as fake impressions, fake clicks and fake installs. While the marketers became aware of such a organized crime siphoning off there precious budgets, usage of preventive tools and measurements became a part of budgets. The New Age bots are programmed to act like a human and carry out specific in-app events, often tailor made for single mobile application. These bots are so sophisticated, they evade all fraud templates and are becoming a new headache for advertisers and policy makers globally. At this year’s Mobile World Congress conference, James Hilton, global CEO at M&C Saatchi Performance, urged the industry to work together to get the problem under control, observing that cyber criminals “use devious ways to keep pushing and maximizing revenue” through bots and “by spotting them through AI we can be a step ahead.” How is In App Fraud fueling retail black market? 1. Reselling Products: In App Bots often mimic human behavior to buy out high demand and low priced products on the e-commerce mobile applications. This forces legitimate users to purchase these items at a higher marked up resale prices, creating a bad user experience and deincentivizing loyal customers. These bots not only help siphoning off advertiser's budgets for a valid purchase and qualifying for all KPI's, but also help black-market supply chain gain momentum by supplying below cost price products into the market due to promotional heavy discounting done by e-vendors. 2. Fake Log-ins : Bots have dreams and they are highly ambitious, one of most easiest way to siphon of advertiser budgets is to gain access to real user and trigger product purchases or skim credit cards/UPI's which later lead to much bigger thread, financial fraud. 3. Deliberate Data Fudging : Since data has the ability to recognize and capture potential fraud and their endorsers, today cyber criminals are trying to deliberately skew this data to evade detection. This is triggering a much bigger problem for eCommerce players since these data decision fuels feedback loops and re-targeting algorithms. Solutions: 1. Deploy AI to uncover systematic Fraud : No matter how big and difficult the ad fraud fraud problem is, it is solvable. Cyber criminals like scale, and real humans don't scale. We need to deploy AI algorithms that follow the principals of behavior & scale. 2. Creating new verification events now and then : Bots have not reached a level of self learning, any new event in between would crack the bot up, advertisers should keep on adding random checks between in-app events to systemically break down any bot operation. 3. Taking Legal Measures against Culprits : Just like Uber took the media agencies, ad networks and ad tech players to court to question them on their data practices, more players should follow. Until the industry doesn't take a strong stand that fake traffic is non acceptable, this menace won't stop.

Let us take you back to the 3rd year engineering lecture on control systems. "If either the output or some part of the output is returned to the input side and utilised as part of the system input, then it is called feedback. Feedback plays an important role in order to improve the performance of the control system". Before we break the current Ad Tech system into one such control system, we would like to you understand how fake apps are used to acquire audience inventory from the market either by running campaigns through them with leading publishers/networks or installing a behaviour bot script onto these apps to generate traffic. If you haven't read this understanding from our previous blog post, read here. Understanding Feedback Loop 1 : The sole purpose of feedback loop 1 is to fuel the second feedback loop for increasing the overall performance of the system. In Ad Tech, the feedback loop 1 can be fuelled in 2 ways, 1. Fuelled by Ad Detection Vendor : Several times, in order to to prove the traffic is invalid and doesn't stand for payment, fraud detection vendors have to share reports and validations on why a particular set of attributes qualify for invalid traffic. This feedback in terms of reports and validations makes today's invalid traffic valid tomorrow as merely few attributes have to be changed to over throw the current algorithms of the fraud detection vendor in place. And then you would often see ad tech vendors say, Oh look, your campaign is optimized, it's fraud free now. 2. Fuelled by Re-targeting Campaigns/CRM :A better of way of building the first feedback loop for the Ad-Tech Vendor is to either acquire an advertiser's re-targeting planning or capture post acquisition data in name of optimization. In both the cases, the idea is to understand what qualifies for the good traffic. Acquiring CRM of advertisers is often used to fuel the acquisition DMP's of ad tech vendors. Understanding Feedback Loop 2 : Once the feedback loop 1 is complete, the information is passed onto the feedback loop 2 to empower the entire semi owned network of sub publishers often dummy mobile applications. And this is how, your traffic gets optimised. Where does the buck stop? The cycle of digital advertisement fraud is vicious one, highly unorganised in the front but organised behind and morally disengaged. The red arrow depicts the flow of funds, and it definitely stops at the Ad Tech vendors. No wonder, the market is highly inflated. What should the investors/advertisers look at? 1. FPPA (First Purchase per Acquisition) : No matter how sophisticated the invalid traffic creators get, the financial gain per acquisition for the advertisers will remain clean. A very easy KPI for investor/advertiser to understand the quality of user acquisition is to measure the performance of ad tech vendors over a ratio of total first purchases/total acquisitions over a period of 30 days. 2. Making the internal supply chain Independent : As the old Russian proverb, Trust but Verify. Advertisers should make sure, each of their systems are independent of each other i.e vendor for UA, vendor for Re-targeting and vendor for fraud detection. Instead of supplying each of the systems with feedback loops, the advertisers should stick to blocking the fraud publishers for further damage because invalid traffic can't be turned valid by mere optimization. 3. Say No to Network Effect : Ad Tech vendors are often heard saying the phrase "network effect". It sounds like the magic wand, which comes into play when the advertiser realises the need of continuous investment into user acquisitions until an effect is created by which scale happens automatically. But in reality, user acquisition's don't scale. Brand and organic growth is build only by continuous effort in content building, noise and customer service. Not everything that counts can be counted, and not everything that can be counted counts.

Data isn't just the source for anomalies detection for advertisers today when it comes to fraud, but it is also the source of reverse engineering for fraudsters to bend the rules and mimic bot traffic as real traffic. If you have been sharing ad fraud data with your partners, you are fueling a much bigger problem than it was at the first place. Every time a type of invalid traffic reason tags are shared within partner network, the clown in the same partner network works to find the way around so that the invalid traffic today becomes valid tomorrow. Basically, invalid traffic is any activity that doesn't come from real user with genuine interest. We are working round the clock to break this systematic type of fraud chain and make sure people who cause it don't profit from it. We are working towards an compliance with Interactive Advertising Bureau , Media Rating Council, Trustworthy Accountability Group to build world's first bait-caught model, where certain traffic changes are create deliberately to understand who is plaguing the supply chain. If you are committing to any of the 4 mistakes below, you need to probably rethink again. 1. Real publishers/networks never ask for attribution data for optimization. If you are being asked for post acquisition/attribution data from your trusted partner network in the name of optimization of your campaigns, you are probably being fooled around. The fraudster would eventually look into how does real traffic for your application looks like in terms of attributed data and mimic all it's sources to fudge all your matrices. This would be the death of performance which would impact your business certainly in 2-3 business quarters. 2. Never let an acquisition partner run your re-targeting campaigns. If you are already doing this, you might have to rethink this particular strategy. Your re-targeting audience is actually your loyal customers that is your brand's real food, you would never want a competitor's promotional creative to reach their eyes which can actually slip this particular customer into your competitors pocket. You might risk your CRM to be used for your competitors acquisition campaign. Set a neat line of legal understanding with your partners on usage of this data only for re targeting and not fuel any acquisition DMP whatsoever. 3. Keep changing your fraud detection algorithms. The fraudster's intention is to understand what logical filters or algorithms you are deploying to understand invalid traffic in your campaigns. Once this understanding is developed, it takes seconds to deploy invalid traffic mimic real user traffic. You would need to collate bunch of algorithms at your place and keep using them in mix-match fashion. 4. Not storing partners past mischief's. Every organization and network in the world today is plagued with ad fraud. It's alright to understand your partner's stand to improve over time, but it is foolish to not store the invalid traffic that you had caught before under partner's name/sub ID name table. Over the time, this data would help you understand the systematic name change of Sub-IDs but same fraud behavior in the subsets. Without facts and principles, data is useless.” – Bob Hoffman

Years have gone by and the Ad Tech industry has seen a whooping sense of consolidation and obliteration. According to Sloan Gaon, CEO of PulsePoint, ad tech leaders should double down efforts and embrace differentiation, specialization and verticalization if they would want to succeed. Analyst's forecast less than 250 net operating companies in ad tech in 2020 from over 1500+ companies in 2013. The domino effect of bad debt, ad fraud, technology upheaval and overheated evaluations within the industry has strong armed Ad Tech companies into the ultimatum, differentiate or die on the vine. Leading brands are moving more into the traditional way of advertising, McDonald's acquisition of Dynamic Yield to create more store walk-ins and drive-thru, trending menu items by geo-fencing or Walmart's acquisition of Polymorph to innovate it's digital advertising and draw more customers to the brand. While the list is endless, Sojern acquiring Adphorus, AirBnB purchased AdBasis. The industry is thrown back to the clear intent of brands looking to adopt, apply and integrate technology with data to effectively create real and transformative changes instead of driving fake acqusitions, MAU's and DAU's over unethically acquired inventories which has created an non transparent and non trust worthy ad tech market. As Jack Welch says, "Change before you have to". To successfully weather the storm, players should be wise to play a long term way keeping customer deliverable an utmost priority. The compound effect of poor profitability in an overcrowded market has left players to scout for working capitals from various sources by window dressing the balance sheets. Advertising needs to take into account the diversity of individuals in a generation to avoid being archaic and ineffective. - Dave Asch

For Every $3 Spent on Digital Ads, Ad Fraud Takes $1 The above figure has been cited so frequently that it has undoubtedly affected the perception of digital advertising. Unfortunately, this is also true, as cybercriminals have been snatching considerable sums of money from major businesses' advertising budgets throughout the years. One of the most poignant instances of fraud in any industry is certainly ad fraud. Digital ad fraud, mobile ad fraud, bot fraud, and other forms of practices that were once believed to be insignificant, are now costing the industry more than $68 billion in losses each year. Publishers and advertisers lose money as a result of the organised cybercrime activities that have grown out of ad fraud. But as a marketer, how should you respond to such sort of malicious activity? To answer that query, you first need to understand what ad fraud exactly is and how does it influence your advertising efforts? In this article, we will be discussing advertising fraud in the digital ecosystem. Ad fraud: What is it? Ad fraud constitutes efforts made by cybercriminals and fraudsters to deceive online networks in order to make financial gains. More specifically, ad frauds prevent adverts from reaching the real target audience and redirect them to non-human traffic. Digital ad fraud can function on several levels. Scammers employ bots to commit ad fraud, and they also have the ability to control traffic as well as elements like impressions, conversions, and imitating user behaviour. In marketing campaigns over the world, metrics such as traffic, bounce rates, impressions, conversions, etc. are used to determine its efficacy. However, it is relatively simple for cybercriminals to skew such data and figures. As a result, they have been duping big brands and businesses all over the world and stealing a good portion of their marketing budget. How does Ad Fraud function? There are many ways fraudsters can get advertisers and ad networks to pay them. In most cases, fraudsters send fake impressions, clicks, and traffic on digital ads. And not only bots, but fraudsters also rely on human-controlled traffic to engage in ad fraud. Bot traffic, often known as non-human traffic, refers to fraudulent ad impressions made by bots. Bots are typically programmed and trained to carry out automated processes. This way, they can perform suspicious activities such as clicking on adverts, visiting websites, and so on under the instruction of a fraudulent programmer. Their robotic behaviour and conduct make them easier to detect. On the other hand, incentivised fraud carried out by actual human beings is slightly difficult to assess. Impressions resulting from click farms will appear genuine (since they are from real beings), but those clicking on adverts are not the real targeted users for the ads. In addition, there is also mobile ad fraud, wherein malware is injected onto mobile devices. It not only compromises the mobile apps and ad campaigns running on the device but also puts the users’ private data at risk. What types of fraud exist in online advertising? Cybercriminals can commit ad fraud in a number of different ways. Sometimes the fraud targets ad networks for views, and on occasion, they may also impersonate clicks or impressions. Let us now look at some of the most popular and damaging ad fraud techniques that exist. Click Spam Click spamming, which is also referred to as click flooding, involves sending a lot of clicks to a digital advert. It is very common in mobile ad fraud, where fraudsters send a huge number of fake clicks in an effort to claim credit for app installations. The commission intended for the advertisers is given to the fraudster after the app is installed. Although the consequences vary, click spamming fraud affects almost every player in the advertising industry. It has a minor impact on users, but it has a significant financial impact if you are a network, publisher, or advertiser. Domain Spoofing Domain spoofing is a type of phishing in which an attacker impersonates a well-known publisher’s domain, and then trick advertisers and people into trusting them. Many websites reserve space on their platform for advertisements and charge advertisers to promote their business. Scammers use a publisher’s website and create a fake domain, fooling advertisers into thinking it is a real website. As a result, they charge a premium to place the advertisements there. Moreover, advertisers receive good impressions, traffic, and clicks, but most of these interactions are fake. (since the website is fake) Click Injection Click Injection is another common technique used largely for mobile ad fraud that steals legitimate, organic traffic from other sources. Using an app (suspicious app with malware) that is already installed on the user's device, Click Injection will trigger a click even before a new app is fully installed, allowing fraudsters to claim credit for the install. Click Injection exploits the existing drawbacks of the last-click attribution model and injects a click before the lead is submitted or an install is completed. Fraudsters can click on numerous adverts simultaneously by using bots or bot networks. Ad Stacking In ad stacking, numerous ads are stacked one on top of one another. In the single ad placement, fraudsters stacks multiple ads, but only the top ad is displayed to the user..In general, all of the ads below the top ad count as impressions but are not really seen by the user. The user only sees the top ad. Consequently, marketers are charged for all of the ad impressions and clicks obtained from the adverts underneath, even though the user only sees the top ad. Advertisers are paying for unseen or un-clicked ads since they still load properly and comply with the rule that at least one pixel must be visible for at least 0.5 seconds (a common metric in the digital advertising industry). The objective of ad stacking is to bill publishers and advertisers for each impression and click on each stacked ad. ​Click Farms It is one such ad fraud where the actual human beings were engaging in the crime. Click farms involve a large number of low-paid individuals recruited to particularly engage in target paid advertisements in order to "fake" impressions, clicks, and overall engagement of ads. Since it features real human traffic, it is also very hard to stop and avoid. Geomasking Geo Masking is a technique that can trick marketers into believing low-quality traffic ad high-quality. It is very easy for fraudsters to spoof or conceal the genuine location or address of a website, resultantly, also presenting fake users as a real ones. Some regions invest more in advertising and see higher conversion rates than others while running marketing initiatives. Thus scammers geomask their genuine identities using a VPN or RDP and thus get paid for irrelevant traffic, which is not the intended audience for the ad. How does Ad Fraud affect online advertising? While the primary motivation for ad fraud is money, in the context of ad tech, it is not exactly the end result. Decisions that are crucial to the campaign's operations are impacted by incomplete information. In addition to costing money, skewed statistics and misrepresented campaign outcomes can force marketers to implement more questionable decisions. The effect of the their method is overshadowed by the existence of malicious sources, even though it might be advantageous in a typical setting. How is Com Olho combating Ad Fraud? Monitoring anomalies in your ad campaigns can help determine the source of fraudulent or suspicious traffic. The anomaly-based strategy examines ad spaces for suspicious activity, such as unusually high traffic, unusual placements, and others. Ad fraud is becoming increasingly difficult to identify, particularly without the usage of anti-fraud technologies designed expressly to protect your campaigns and ad spending from such frauds. Com Olho's technology can assist organisations in preventing different types of ad fraud before they have the opportunity to steamroll their ads and drain their budgets. Schedule a free demo to learn more about how Com Olho may help secure your advertising initiatives.

Mobile penetration is at an all-time high, and hence enterprises have had to go online to stay afloat. People’s perceptions and attitudes towards digital media shifted in the wake of pandemic. App and mobile advertising providers currently own the majority of the digital advertising space. Today the majority of the digital advertising market is dominated by app and mobile advertising providers. Digital media consumption evolved in the wake of the COVID-19 pandemic. As consumers lead increasingly hybrid lifestyles, mobile is the top-ranked priority at 77%, followed by social media platforms and videos. Mobile penetration is higher than ever, and businesses have had to move online to survive. Such times make people more vulnerable, which provides new opportunities to the fraudsters. This year, mobile internet users in India are expected to surpass 600 Million. Mobile ad fraud is plaguing mobile-based performance campaigns like never before, as fraudsters are getting smarter and using innovative and more sophisticated techniques to steal money. Click Injection Evasion is one such sophisticated tactic syphoning off enterprise ad spend dollars. What is Click Injection Evasion? To understand click injection evasion, we first need to understand Click Injection Fraud. Click Injection is a sophisticated form of click spamming and a commonly used mobile ad fraud method that steals organic and quality traffic from other sources. Click Injection exploits the existing drawbacks of last click attribution model, and injects click before the lead is submitted or an install is completed. (To understand how click injection works in detail , read this blog.) Click Injection detection using CTIT (click to install time) anomaly has been widely used by mobile advertisers in India since 2016. Evading this detection, a more sophisticated form of this fraud is click manipulation, a type of ad fraud where fraudsters, while injecting a click, backtime the click time to make sure it evades the existing click to install time algorithms present with existing ad fraud detection companies. Com Olho calls this methodology “Click Injection Evasion”. How does Click Injection Evasion work? Click Injection Evasion, a sophisticated form of click injection fraud, is a type of mobile ad fraud that is advancing as the whole world turned digital and mobile. Fraudsters work with programmatic ad networks or pre-purn applications i.e the mobile applications that are pre-installed on devices by manufacturer, and lace them with behavioural trackers and adwares. This allows fraudsters to hijack organic mobile conversions and also steal traffic from social networks reattributing them as theirs. When more than 70-80% of acquisitions are done using social networks, stealing conversion traffic from these sources makes sense for fraudulent publishers. Com Olho using deterministic and admissible in court data algorithms, has not only been able to detect click injection fraud but also as detected fraudsters attempt to reverse existing fraud detection technology. Using our patented technology, our algorithms in real time can measure any kind of click data manipulation for financial gains. Who is affected by Click Injection Evasion fraud? Click Injection Evasion fraud affects almost every player in the advertising industry, even if the consequences vary. Networks and Publishers: Click Injection Evasion fraud will take away the credit from the worthy and deserving network and publisher, depriving you to make money even if you get an install as a result of your genuine efforts. Advertiser: Even if the campaign was influenced by click injection evasion fraud, it may look that the advertiser eventually received the desired outcome that is app installation. However, it impacts them in multiple ways. To begin with, advertisers might end up paying to the network or publisher even if they earned the installation with the organic efforts. Moreover, such frauds manipulate the campaigns performance and view-ability. This can also lead to a negative impact on advertiser’s decision making as they may keep spending more on fraudulent sources while downsizing the real and true performers. Needless to mention, that was not an ideal scenario to be in. What are the threats that Click Injection Evasion pose? Click injection evasion mostly affects the publishers who run digital ads across several platforms with the goal of driving app installations. CPI campaigns are usually run on multiple different ad networks, meaning that enterprises need to protect them across each such platform. The main threats are: Exhausted Budgets: Click Injection Evasion results in fake app engagements and clicks, wasting advertiser’s hard earned money that could have been spent on reaching real and genuine people.Many fraudsters also employ bad bots to increase ad views or clicks, which speeds up the depletion of budgets even more. Skewed campaign data: One of the most damaging effects of click injection evasion is the skewed campaign data that results from it. Marketer’s future campaigns and ad spending decisions depend on the data that they get from campaigns. Since any data affected by click injection evasion will be skewed, marketers will not be able to accurately identify which channels are most effective, perhaps, resulting in investing money into invaluable campaigns. What can you do to prevent Click Injection Evasion? Using Com Olho’s patented technology, enterprises can detect click injection evasion, a sophisticated type of click ad fraud, which is spoofing more than 4 Crore devices per day an affecting at least 10% of advertising spend siphoning off INR 250 Crore a month by digitally stalking over 10 Crore devices daily. As the fraudster was able to evade click injection, it is clear that our digital ecosystem cannot be protected from this type of fraud using the existing traditional methods for identifying such click anomalies. We ensure at least 20% Month-on-Month savings on mobile ad spends using their deterministic and patented algorithms. We also published a report that deep dives into a live case of a fraudulent publisher/ ad-network manipulating the click to install time and how using our patented technology, the company identified and detected fraudsters attempted to evade such click injection detection. In Conclusion The fraudsters’s ability to evade click injection indicates that the traditional methods for detecting click anomalies are insufficient in detecting and removing such fraud from our digital ecosystems. There’s a need for innovation at the enterprise level. Fraudsters are getting smarter day by day and are siphoning advertiser’s money by sophisticating their tactics.

"Someone once told me growth and comfort do not co-exist. And I think it's a really good thing to remember." - Ginni Rometty A year ago, I started my corporate career as a Data Lead with a start-up. And looking back now, it has been the best decision I could have made as I’m learning and growing every day in my career with Com Olho. The journey as a woman in a tech start-up is seen to be a tough and rocky one, but taking it positively as a challenge, I aspire to overcome all the social misconceptions and hurdles in my way. Com Olho gave me the chance to work together with a very young and highly motivated group of individuals to define and shape the team and the goals of the company. While focusing on learning all about data and tech, and continuously refining my data & tech skills, I often found myself taking on other responsibilities as well - the best way of gaining experience in new areas. It's difficult to summarise my journey so far in a few key moments, but here we go. The team Working with like-minded, driven, and inspiring people on a daily basis is gold. Everyone who joins the company is welcomed into this expanding family. It's all fun and jokes one minute, and then we're all brainstorming and working as a team on a product release the next. Responsibilities & recognition Having a flair for coding and aggressively toying with data, developing it in the most desirable way, and obtaining positive feedback from both management and co-workers gave me the feeling that I could make a difference. This is the place I'd like to be. 'Are you sure you're not a BTech graduate?' It's the nicest feeling in the world to get recognised for what you actually believe in, and what you enjoy doing. The shining moment Acknowledging and discovering my interest in data and technology was not an easy decision in my career, but being associated with a group of people that encourage you at every step helped me feel exactly at home in the moments when I needed it the most. Being a member of Com Olho and witnessing the shift of raising the first fund round - Seed Round - as well as all of the good improvements and recognitions that followed was a wow-moment. It feels amazing to watch our company and team evolve into something so powerful. Connect with me on LinkedIn : Link

Following the COVID-19 outbreak, the industry saw an increase in mobile advertising. According to a recent report, the total ad spend in India is estimated to cross INR 1 Lakh Crore mark in 2022. With a 45 percent share of the entire ad pie, digital is destined to overtake TV as the most popular advertising medium. The total estimated mobile ad spends from the total share of digital ad spend is projected to be greater than 60% in 2022, valuing it at INR 29,000 Crore. Digital spending is only going to increase. As a result, passionate marketers have the perfect opportunity to innovate and deliver the best ROI. However, they got to overcome a significant challenge in the process – Mobile Ad Fraud. Mobile Ad Fraud is a subset of ad fraud plaguing mobile based performance campaigns. It is a collective term used to describe a combination of tactics used to stop digital ads from being delivered to the audiences or spaces for which they were intended. One such tactic syphoning off enterprise ad spend dollars is Click Injection. What is Click Injection? As a marketer who is handling user acquisition, click injection is perhaps the most common fraud that you experience, regardless of if you have figured it out yet or not. Click Injection, a sophisticated form of click spamming, is a commonly used ad fraud method that steals organic and good traffic from other sources. Click Injection will use an app located on the user’s device which informs the fraudsters when a new app is installed, triggering a click before installation is completed, enabling fraudsters to take credit for the install. As a result, the attributes are manipulated and you will be paying the wrong media source instead of the actual (and deserving) source. Click Injection exploits the existing drawbacks of last click attribution model, and injects click just before the lead is submitted or an install is completed. How Does Click Injection Work? Click injection is a type of ad fraud technique that aims to win the last-click attribution in CPI campaigns affecting millions of devices. Fraudsters inject a click when an app is downloaded by a user on their device just before the install is completed. Publishers are usually charged a fixed fee when an app is installed, but when click injection is performed, fraudsters receive the financial credit for the app install. Fraudsters also utilise bots or bot networks to click on multiple ads at the same time. Here is how click injection works: Users may unintentionally install the malicious app that performs non-suspicious activities, like auto-changing wallpapers, flashlight, cat-voicing, etc., and it appears harmless to them. They can even make their way to mobile devices without the user’s knowledge. These apps have the ability to inject a click to run another application. The malicious app installed in the phone keeps performing its unsuspicious action until the user begins to download a new app, and the first malicious app contains code that alerts it of this new installation. Fraudsters inject a fake click to represent as the source of app install, as well as also inject the click to run the application. In the advertising industry that works on last click attribution, advertisers pay mostly to the last source that got the successful installation. In this model, the malicious app is able to claim the credit for getting your app installed. Hence, the advertiser attributes the credit to the fraudster and pays them a percentage of the revenue. Who Is Affected By Click Injection Fraud? Click Injection fraud affects almost every player in the advertising industry, even if the consequences vary. It marginally affects the user experience of the customers, but has a significant financial and reputational impact if you are a network, publisher, or advertising. Networks and Publishers: Click injection fraud will take away the credit from the worthy and deserving network and publisher, depriving you to make money even if you get an install as a result of your genuine efforts. Advertiser: Even if the campaign was influenced by click injection fraud, it may look that the advertiser eventually received the desired outcome that is app installation. However, it impacts them in multiple ways. To begin with, advertisers might end up paying to the network or publisher even if they earned the installation with the organic efforts. Moreover, such ad frauds manipulate the campaigns performance and viewability. This can also lead to a negative impact on advertiser’s decision making as they may keep spending more on fraudulent sources while downsizing the real and true performers. Needless to mention, that as not an ideal scenario to be in. What are the threats that click injection pose? Click injection affects mostly the publishers who run digital ads across several platforms with the goal of driving app installations. CPI campaigns are usually run on multiple different ad networks, meaning that enterprises need to protect them across each such platforms. The main threats are: Advertising budget losses Click injection result in fake ad engagements, wasting advertiser’s hard earned money that could have been spent on reaching real people. Compromised analytics Marketer’s future campaigns and ad spending are influenced by the data that they get from campaigns. Since any data affected by click injection will be skewed, marketers will not be able to accurately identify which channels are most effective, perhaps resulting in investing money into invaluable campaigns. What can you do to prevent click injection? Click injection, even though it is a simple sort of ad fraud for fraudsters to carry out, it is a malicious form of ad fraud because it infects devices directly. Keeping up with all of a fraudster's tricks is difficult. Without proactive anti-fraud solutions that automate the detection of bad actors and their methods, click injection fraudsters will continue to use low-quality apps to hijack devices. Protect your CPI campaigns against click injection Ad fraud prevention often feels like a cat and mouse game. As soon as you block one incident, another ten pop up in its place. Unfortunately, fraudsters are only getting smarter. Ad fraud is becoming more difficult to detect, especially without the use of anti-fraud solutions that are specifically engineered to prevent your campaigns and ad spending from such frauds. Com Olho’s solution can help enterprises prevent multiple forms of ad fraud before they have the chance to steamroll your campaigns and bleed your budgets dry. Find out more about how Com Olho can help protect your advertising campaigns by scheduling a free demo.

To put it simply, Ad Stacking means stacking up adverts on top of each other. Ad Stacking is a very common mobile ad fraud practice wherein, multiple ads are stacked beneath one another in a single ad placement on mobile apps or websites for generating fake impressions. Only the top ad is displayed to the user/visitor. However, every ad in the stack receives a click or impression, because of its placement. As a result, advertisers are forced to pay for fraudulent impressions or clicks which are not intently clicked by the visitor. Ad stacking is among the most widespread types of ad fraud. Moreover, Ad stacking is most commonly associated with mobile ads. It accounts for 20% of global ad spending, stealing hard earned money of marketers and businesses of all kinds. That is because it is more prevalent in click-based campaigns and businesses spend a huge section of their budgets on Cost per Click (CPC) or Cost per Thousand (CPM) campaigns. But how does this work exactly? How can fraudsters defraud big corporations or fool regular internet users? Let's find out How Does Ad Stacking Work? Ad stacking is just what it sounds like, stacking ads on top of each other. On a normal course of action, it would look like a pile of sheets. However, digital marketing and the internet work differently. Herein, by stacking, fraudsters actually hide several ads beneath the main ad, and the users can only see the advert at the top. When a user clicks or watches the top ad, the other stacked ads also get clicks or impressions and are thus recorded for the same. Ultimately, advertisers are paying for clicks and impressions which was not intended by the user, but somehow have a record of click or impression. This way fraudsters steal ad budgets from advertisers and marketers and increase ad revenue for publishers who are also engaged in the scheme by stacking advertising. On a website or any fraudulent platform, the publisher will summons ads and stacks them into a single ad space instead of displaying one ad per ad unit. Only one ad will be shown to the user, with the remaining ads loaded at zero or near-zero opacity, leaving them invisible to the user. A click on one ad unit resulted in a click on all of them. These adverts are never seen by the user, yet advertisers pay for these fake impressions or clicks since they trigger an ad impression. This way, fraudsters make money from multiple channels by generating just one click. With additional ad stacks, clicks, and impressions, the threat escalates tenfold. The impact of Ad Stacking As previously stated, Ad Stacking is a cause of great concern for marketers. Moreover, according to research from 2018, Ad Stacking, together with Click Spam, amounts to 27% of total ad fraud, trailing only App Install Farms (42%) and Click Injection (30%). And just like other forms of mobile ad fraud, Ad stacking also lead to wasted ad spending and biased campaign statistics for marketers. Advertisers and Marketers might get the desired traffic and impression from their ad campaigns. But in reality, most of those data would be untrustworthy and the amount spent on such would be a waste. Ad stacking is mostly used when advertising is paid on an impression-based or click-based model. Brands often pay ad networks on a cost-per-thousand (CPM) or cost-per-click (CPC) basis, but their budgets are depleted because of fake clicks and impressions. By layering ads on top of each other, advertisers waste money, resulting in a low return on ad spend (ROAS). In addition, this will also have adverse effects on a company's marketing strategies. Any marketer who isn't aware of such malicious practices will believe in the misleading reports and poor performance results. Ultimately, this will push firms to increase their advertising spending, resulting in more money for scammers and fraudsters. Not only marketers, but publishers can also fall victim to Ad stacking. It can potentially harm the reputation and credibility of publishers who are unaware of the false ads they are displaying. Finally, the user or the visitor might not suffer any monetary losses, but they are nevertheless flooded with multiple ads on their browser. How to prevent Ad Stacking? Every day, fraudsters are billing multiple advertisers for single clicks and are simply draining large amounts of advertisers' money. But this functionality can also aid in the detection of fraudulent activities. Publishers can detect numerous impressions or clicks from a single user at the same timestamp, indicating that many ads were piled on top of each other. It is the publisher’s obligation to report these malicious practices on their platform From an advertiser’s perspective, brands must regularly check their campaign performance and identify if the same user or device is clicking on several adverts with the same timestamp. Monitoring the conversion rates of campaigns on a regular basis will help detect anomalies. A high number of impressions combined with a low conversion rate is usually a sign of ad stacking. Further, there are also cybersecurity software and tools that employs advanced algorithms to detect and prevent fraudulent behaviour. These were a few techniques to figure out if you are targeted by ad stacking. When Ad stacking occurs, these can help identify it. In Conclusion The digital ad space has become a playground for cybercriminals. Even capable mobile gadgets are also subjected to cyberattacks. Fraudsters are defrauding marketers, networks, and even users, all at once. They constantly find a way to steal money when marketers increase their investments in digital advertising. Thus it is the responsibility of brands to take proactive and preventative measures to ensure that mobile ad fraud does not impact their operations.

In recent years, mobile phones have come a long way. Smartphones have become a companion of our daily lives, with most of our activities centered on them. The widespread usage of mobile devices has had an impact on the advertising industry, with businesses spending money to reach out to mobile phone users. Mobile search results account for 65 percent of clicks on paid search results. While marketers keep pumping money into mobile advertising, there is a negative aspect to it. There are cyber criminals who engage in mobile ad fraud to benefit from this market. Advertisers and marketers work hard to generate clicks and impressions, and they often get the desired results through various campaigns. However, in a majority of cases, these clicks and impressions do not translate into actual conversions. Well, this is because mobile ad fraud, and click spamming in particular, is impacting their marketing efforts and business. Click spamming has long been a source of concern for mobile app advertisers, and this type of click fraud can be incredibly costly for advertisers. It can go unnoticed by ad networks for extended periods of time. Let's understand what is Click Spamming and how it works. What is Click Spamming? Click spamming, also known as click flooding, is a type of mobile ad fraud in which fraudsters can produce fake clicks through infected mobile apps or websites. Here, the mobile user, or the owner is unaware that a malicious app has been installed on their device. The app would then spam clicks on advertisements on the smartphone, giving the impression that the ad has had a lot of traffic. The click generated by click spam is non-human traffic, more specifically, BOT traffic, and thus would not result in any real transaction. Simply a waste of money on fake bot clicks. Click flooding is used to generate fake clicks on advertisements, installs or downloads, or even impressions, visits, or views on websites. These clicks can operate when a program is operating in the background and often imitate actual human behaviour to trick marketers. Advertisers may see clicks or impressions as beneficial, but in reality, they are distorted statistics. How does click spamming work? The initial stage of this operation starts with the user when he or she might download suspicious software. These infected apps are typically downloaded outside of the Google Play Store or the iOS App Store. It is understandable when users download these since the app does not look suspicious, and more importantly, its fraudulent activity operates in the background. The app contains a code that generates a large number of clicks (spam clicking) on adverts. All ad clicks are allocated to the click spammer, and if there is an ad click, an unrelated app store download, or an in-app purchase, the spammer gets paid. As a result, it makes a platform appear more effective than they are and it defrauds marketers of their ad spend. Spammers invest in click spamming operations because it is a lucrative business, with the fraudster receiving their cut on ad clicks or in-app purchases. The higher the number of undetected spam clicks, the greater the prize money. However, for the advertiser, it might imply that there is a lot of activity on their ads, but there isn’t. Their ads are filled with a large number of fake clicks before any form of conversion. In long term, it not only affects their ad spending but their marketing campaigns and strategies as well. Who Is Affected By Click Spamming Fraud? Click Spamming fraud affects almost every player in the advertising industry, even if the consequences vary. It marginally affects the users but has a significant financial impact if you are a network, publisher, or advertising. Marketers and Advertisers Click spamming can have a significant impact on the marketing spending of any business. Advertisers are paying for clicks and spammers are doing their bit to flood their ads with clicks, well fake clicks. Many advertisers use the pay-per-click (PPC) model, and each false ad click is stealing their money, thus affecting their company's revenue. In addition, this will also have a negative impact on their future marketing efforts. The inaccurate results, the inability to distinguish between real or fake clicks, and the dependence on fraudulent reports mean poor decision-making by the marketers. Networks and Publishers Publishers on the other hand are the one who places adverts on different platforms, including mobile devices, for advertisers. And thus, they are the ones who should get paid for any activity on the ads, be it click, installs, or visits. It is their money that is being stolen from them because a code takes the credit from them, and the money into the pocket of the fraudsters. Users The mobile phone user might not face any monetary losses, however, they are also affected by this mobile ad fraud. A malicious app is secretly operating on their mobile devices, and this always poses a threat to their confidential files. They can also experience performance issues on their devices due to these malicious apps. How To Detect and Prevent Click Spamming Mobile Ad Fraud? Examine your traffic and conversions Keeping a close watch on your traffic source can assist you in identifying click spamming. These invalid traffic are frequently caused by a large volume of traffic in a short period of time. However, they never result in any real conversions. Sudden increases in traffic, but only a few conversions can indicate fraudulent click activity. Going deeper into the source of poor traffic can help in eliminating click spamming attacks. Validation of Apps As discussed, malicious code can enter into a user's device through malicious apps only. It is thus the responsibility of the publishers as well as the marketers not to associate with such applications. Always look out for the validity of the app on app stores and it is also possible to ensure if the code within an app is not harmful or not. Combat Mobile Ad Fraud by Being Proactive Ad Fraud detection requires special expertise. Fraudsters are only getting smarter and bots are progressing to the point where they can imitate a real human user. Thus it becomes imperative to switch to anti-fraud solutions that are specifically engineered to prevent your campaigns and ad spending from such frauds. Com Olho’s solution can help enterprises prevent multiple forms of ad fraud before they have the chance to steamroll their campaigns and bleed their budgets dry. Find out more about how Com Olho can help protect your advertising campaigns by scheduling a free demo. In Conclusion Digitalisation has taken over the advertisement sector. Resultantly, marketers rely on digital marketing to reach out to their audiences in cyberspace. A platform that is filled with scammers. When marketers boost their investments in digital advertising, scammers always find a way to profit. As a digital advertiser or publisher, you should be aware of these mobile ad fraud practices and their impact on your marketing efforts. Take proactive and preventative actions to ensure that click fraud like click spamming is recognised and stopped as soon as possible.

The COVID-19 outbreak has caused significant changes in the way businesses identify themselves with different types of content. There is a drastic shift, or I might say, an increase in the number of users who consume information through online means. People are hooked on social media and websites for updates, resulting in more screen time. Brands are thus focused on establishing their online presence. However, the internet is also a haven for dangerous content, with fake news, unsuitable content, conspiracy theories, and other stuff blooming everywhere. As a result, they put a lot of emphasis on brand safety. Brand Safety solutions are intended to safeguard a brand's online reputation by prohibiting it from associating with harmful or inappropriate content. What is Brand Safety? Brand Safety is the measures taken by a brand to prevent itself from appearing next to questionable content online and safeguarding its reputation. With the present state of digital marketing, businesses are aggressively running adverts on prominent websites and social media platforms. Sites with more audiences or visitors will result in brand promotion. But that does not necessarily mean that businesses should blindly go after numbers. It would require appropriate measures to ensure that the brand uses the right step to protect itself from digital ad frauds. In this blog we will discuss brand safety solutions or measures to safeguard your business. But first, we need to understand why brand safety is important. The importance of Brand Safety in the digital world Brand safety ensures a customer's trust in a brand. Revenue, brand equity, and consumer impressions will suffer when there is no trust. As a result, Brand Safety will always be critical for marketers and enterprises. Customers may be alienated and lost as a result of poor brand alignment. Customers may now share positive and negative experiences with more people than ever before because of the advent of digital platforms. As a result, brands must resolve concerns quickly or risk losing customers and money. Brand suitability is the approach adopted by brands to find the right balance of reach and protection for their specific needs. Advertisers must understand that the brand safety strategy used for their digital advertising initiatives works at the speed of culture, and can also create new problems as they emerge. Moreover, Brand safety measures are subjective, and it will depend on what is appropriate for the brand. One strategy might work for you but not necessarily for others. For instance, a car manufacturer would not want to place an advertisement right next to a report on a car accident. However, an insurance company will be interested in ad positioning there. Brand Safety Solutions Keyword blacklisting: It is a strategy wherein the advertisers will suspend the bid if the content page contains dangerous keywords. This has been a very common route for advertisers, but it frequently results in income loss for publishers. Publishers want to be truthful, and marketers want to safeguard their brands. However, more advanced blacklisting of keywords that do not comprehend the context and simply block brands from appearing on websites would cost both advertisers and publishers in the long term. In addition to keyword blacklisting, marketers can also run Site Inspections. This includes an assessment of the website's domain authority, viewability score, fill rate, and historical bid price. The sites that meet the advertiser's expectations in terms of brand placement can help them appear next to the right content with assurance. Moreover, it is advised to keep a watch on these figures in order to prevent being penalised by brand safety authorities. Furthermore, to avoid the complexities of programmatic deals, advertisers opt for a safer option: Direct Transactions. This benefits publishers because direct deals can generate a higher revenue than programmatic auctions for the same amount of impressions. The evolution of Brand Safety and why it is becoming more difficult? While guaranteeing brand safety was once as simple as ensuring your business's ad appeared on the appropriate TV show, the shift to online and the saturation of content has made it more difficult than ever for brands. COVID has generated new hurdles for brand safety by dominating the content consumption cycle. More and more users and targeted audiences are now consuming information via online channels. Thus it now requires more attention towards surfacing authoritative and relevant content and providing critical placement for it, banning fraudulent publishers, and collaborating with partners who assure safety. It is vital today to go beyond brand safety. A good brand suitability strategy to ensure that your brand is aligned with positive settings while avoiding damaging content. However, Keyword blacklisting and URL blocking, which are the most widely used brand safety methods, do not assist in every condition. Many brand safety errors or blunders can be traced back to strategies that haven't been updated to reflect today's content and news cycles. Context is important in determining the underlying meaning of a page and accounting for subtleties in language and interpretation. Professional assistance for Brand Safety Companies Com Olho’s Brand Safety APIs prevent your advertising from being displayed on irrelevant and hazardous websites and mobile applications in real-time. It not only allows your company to show adverts to humans, but it also protects your brand equity. Because digital ads are likely to be seen by more humans, every proactive effort taken to limit the impact of ads being shown in irrelevant and non-human ad slots will multiply your ROAS. The patented technology helps in the assessment of campaigns’ several points, which include ownership, content kind, reviews, engagement, and other factors. After retrieving the data, the platform automatically divides it into categories, ranging from the worst to the best publishers. In Conclusion It is crucial to note that publishers are brands too, are connected with damaging content and can have serious reputational and financial damages. When a platform is accused of displaying harmful content, both the publisher and advertisers suffer. Advertisers are more aware of the benefits of having control over where their brand is placed. Advertisers will constantly strive to have their brand featured on content that reflects their values and messaging. And thus it is important to adopt a policy that maximises brand safety while minimising risk, especially in this fast-changing digital landscape.

Artificial Intelligence (AI) and Machine Learning (ML) are believed to be revolutionary breakthroughs in science and technology. Not only that but they are intended to help humanity to solve serious issues on multiple avenues. Considering Artificial Intelligence is a tool, it is currently used for automating key operations, limiting human intervention, and accelerating major technical processes. However, the application of Artificial Intelligence depends on the individual in charge of it. The technology is intended to aid human beings with their objectives, but whether it is used for the right or bad motives remains to be seen. As a result, Artificial Intelligence is often categorised as either good or bad. Ad Fraud is plaguing the online advertisement business Ever since we got our hands on the internet, every entity wants to be a part of this universe. Whether it is the general public or major businesses, even pet animals have their social account with followers more than any ordinary individual. We have progressed to the point where we can currently discover information about almost everything on the internet, with the exception of a few bad elements (more on that later). As a result, businesses, since the onset of the internet, have tried their best to reach out to the online community, spending millions to market their brand. They engage in digital marketing practices and many businesses have made a fortune serving their audiences. At the same time, over the last two decades, they have been subjected to multiple cyber attacks and ad fraud, which have caused serious disruptions in their operations. Ad Fraud is an ever-growing concern for Marketers worldwide, and the much-discussed Artificial Intelligence, Bad AI to be more specific, is at the bottom of it. “Good AI” is possible but “good human” is still unsound. How do Cybercriminals use Artificial Intelligence to scam marketers? As discussed earlier, Artificial intelligence is used to automate a technical process on its own, without the need for human inputs. Thus, fraudsters use AI for malicious purposes and this has been reported in terms of hacking, stealing confidential information, or distorting the marketing budgets of brands. Cybercriminals, fraudsters, and others engaging in illicit activity frequently create bad bots and use them to harm businesses. A malicious bot is programmed to carry out harmful activities and thus constitutes a bad AI. However, to get in-depth into why AI is bad for marketers, we first need to understand good AI and bad AI, and what makes them different. Artificial Intelligence: The Good Aspect Popular movies and television media have presented a very debatable description of Artificial Intelligence. To some extent, they might be true, while in most instances, they are simply exaggerated versions of AI. There have been several initiatives to use AI in multiple domains, with an objective to assist in the better functioning of crucial projects. AI-assisted solutions are only going to make things simpler for us. It is worth noting that Artificial Intelligence has progressed significantly in the right direction and in this section, we will discuss some of its positive influences. Presented with a large set of data, AI can perform predictive analysis and help in decision making. Recently, we have seen in healthcare, Machine Learning and Image Recognition are used for cancer detection. This has been critical in forecasting severe diseases and contributed to saving human lives. Moreover, they have also been designed to carry out automated tasks, based on user behaviour and data. In online marketing itself, advertisers and publishers employ the technology for their marketing goals. AI is frequently used in marketing campaigns where speed is critical. Understanding the demographic, user behaviour, and preferences, it makes automated decisions that drastically benefit the campaigns. Needless to say, Artificial Intelligence is making its way and is making headlines for all the right reasons. We are yet to see the full potential of a man-made brain, and it will be in everyone's best interest if it becomes the ideal companion for humanity. The Bad AI Coming to the section which pop culture believes is the true nature of Artificial Intelligence. The Bad AI. Yes, it exists. But the question is, who is to be labelled as bad? Does the AI make the decision, or the person controlling it? Artificial intelligence (AI) is programmed to think and act like humans, giving them human-like characteristics like learning and problem-solving. A bad AI will perform all sorts of malicious actions, just like any fraudsters would do. And that is because it is the fraudster who wants them to. They might have been trained to perform questionable actions, but at the end of the day, they are coded by an instructor to do so. Ad Fraud has been on the rise and when we examined the problem more closely, we discovered that it is the result of bad AI doing the dirty work for cybercriminals. Online Ad Fraud like click spamming, click framing, domain spoofing, ad injection, and so on, have been a result of bad bots. Bots in themselves are just code instructed to perform any simple task such as repetitive operations or complex tasks like identifying and imitating human behaviour. But it is their intent that makes them good or bad. Bots are engineered to flood ad campaigns, act like real audiences, produce clicks, hijack real clicks, and whatnot. As a result, this creates an impression that bot traffic is real. Their actions are real. Ultimately, just fooling the marketers before they even realise it. It is expected that digital ad fraud will cost brands $44 billion in 2022. Unfortunately, malicious bots are becoming more sophisticated and thus making it difficult for businesses to combat this issue. With the advancements in Machine Learning, a rising number of bots are imitating human behaviour and fooling the most advanced fraud detection technology. “Unless we learn how to prepare for, and avoid the potential risks, AI could be the worst event in the history of our civilisation” - Stephen Hawking In Conclusion The industry, very recently, has started to address the impact of ad fraud. The potential for irreparable damage to a company's finances and reputation resulting from fraudulent attacks. Therefore, we have seen crucial steps toward the fight against fraudulent practices. It is now the responsibility of a good AI to counter the effects of a bad AI. Machine Learning has emerged as a potential solution, already making significant progress in combating ad fraud. It can be useful in detecting potential fraudulent trends and helping reject bad traffic. However, there is a long way to go. But witnessing such steps in this direction suggests that we can soon lessen the impact of these bad elements in such a promising technology.