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.

Third-party cookies have been integral for digital marketing for over a decade and their reach covers everything from audience targeting to behaviour tracking to re-marketing and more. However, with searches for "online privacy" at an all-time high and this being a key concern for people all over the world, the traditional methods of collecting behavioural data as we browse needs to change, which is why Google is depreciating cookies. As we all know the digital industry ecosystem is extremely dynamic in nature. With the recent developments and changes within the marketing space, one thing always remains constant, Audience. Understanding our audience's behaviour and reaching out to the right set of consumers is the most vital aspect. And for this, marketers require data to pull insights about their user behaviour. Defining Different Types of Data Available Let’s start by looking at the different types of data that marketers use. First-Party data First-party data is data about an enterprise's customers that's collected and owned by the enterprise. Information about customers is compiled through codes and systems that the enterprise itself owns. The enterprise can use this information (digital interactions, purchase history, behaviour, preferences, etc.) to create ads, content, and experiences catering to an individual’s interests. Second-Party data Second-party data is first-party data from a trustworthy source. This data will facilitate an enterprise to achieve greater scale than relying on its own data alone, and since the data isn’t sold openly, it can provide greater value than third-party data, which is available to anyone usually who wants to buy it. Third-Party data Unlike first-party data, third-party data comes not from the direct relationship between a customer/client and an enterprise, but from an outside source that has collected the data. Third-party data often usually comes from a variety of sources online, and this information is then aggregated, segmented, and sold out to companies for their own advertising use. What is 1P data? 1P or First Party Data is the advertiser’s data that they collect directly from its customers and owns. It is an element of the mosaic of data marketers have at their disposal. The data includes information such as email, phone number, demographics, interests, time spent on the website, purchase history, etc. This customer information is collected from both online and offline sources, like the enterprise’s website, app, CRM, social media, or surveys. This data is extremely pertinent to all businesses because it is collected directly from digital or offline properties. In this blog, we’ll uncover why First party data has become a powerful tool for modern marketers. The Value Of First-Party data In this age of consumer empowerment, creating personalised and highly targeted experiences that drive brand loyalty and retention means being able to understand and respond to customer wants, needs and intent with 1:1 contextual relevance. What better way than using the actual information that details each and every customer interaction with your brand? First Party Data is qualitative. It’s free. It’s yours. First-party data is the foundation for understanding your customers as it is the data that an individual entrusts to you, in exchange for your superior product or service. And it’s the only information that provides the types of insights and control you need to recognise, relate and respond to your customers in more meaningful and valuable ways. While the concept of leveraging first-party data to reach more to known customers isn't new, the approach for doing so is. Thanks to the evolution of customer/client intelligence solutions, marketers can now integrate all of a brand’s offline and online first-party data to reach and interact with actual customers wherever they are in their decision journey. As marketers increasingly adopt customer/client intelligence as a strategic discipline, brands expect additional information from their first-party data and are planning on increasing their use of first-party data within the years ahead. Sources of First-Party Data The key to reaping the benefits of first-party data is getting the right data from the right sources. First-party data comes from a variety of sources. Website: A website can offer a wealth of data about on-site visitors, from names and email addresses to visitor behaviour and transactions. Plus, there are additional behaviours that can be tracked (such as once users hover over text or images) for specific retargeting strategies. Mobile Apps: App users are few of the brand’s most interested and loyal supporters — after all, they made the effort to download the app. To ensure useful data is being extracted from a brand app, marketers need to define which user events are significant and be sure to log and measure them. Email and SMS: Email offers data like open rates, click rates and bounce rates that date back to the beginnings of the brand’s digital marketing efforts. Furthermore, marketers may segment audiences and execute particular ads aimed at varying degrees of engagement using the comprehensive data on who is opening emails and whose interest is flagging. Similarly SMS data, text messaging is an intimate form of communication, customers who allow brands to engage with them via SMS show a high level of interest. Challenges of Using First-Party Data ​​While the rationale for employing first-party data may appear to be obvious, marketers who want to make better use of their audience and customer data face a number of challenges: Lack of a Data Strategy You can’t resolve your information issues in a single afternoon. You have to form a strategy first, which means knowing what sources you have got, what you’re collecting, and mapping it across the customer journey as you comprehend it. Your strategy will guide the method & process, and it has to be customised so that it's relevant to your brand. Integration of Data Integration is difficult. A lot of your customer engagement data lives within the fragmented silos of your third-party technology partners. Even though these partners have gathered the data on your behalf, obtaining it all at once in one place can be hard. However it’s yours, and you need it to make things happen. Pulling your data out from these silos and into one place will help you see the big picture of your data points, and the outlines of your customer profiles will start to take shape. Taking Action in Real-Time The value of data decays quickly. A first-party should be able to distribute data and information to your internal and external media execution partners so as to take advantage of what you know about each customer before the window of opportunity closes. First-Party Data Strategy 1. Create a framework for your first-party data. First-party data is the foundation for a bigger, omnichannel marketing strategy that can facilitate brands to achieve lower-funnel objectives, like customer loyalty, retention, and upselling. Outline your marketing and customer experience goals and objectives, the techniques and analytics needed to execute the strategy, and create a roadmap for how your cross-channel marketing capabilities will develop over time. Break down the long-term effort into smaller projects that show incremental returns at each stage. 2. Determine the right data points and sources. Examine and audit your data sources and points to identify what data is being generated and how it is measured. Check your data sources and data points with the data requirements of the marketing and analytics use cases you’re planning to implement and make sure you’re collecting the data that’s critical to your goals. 3. Create a Benchmark and track it over time. Continually evaluate your first-party data capabilities, monitor progress, and integrate what you’ve learned at every step along the way. Establish key success metrics for your answer, both in terms of operational capability and support for cross-channel marketing initiatives. Track information volumes, sources, process speed, profile depth, and which information is activated for analytics and measurement. Conclusion Enterprises will no longer use third-party data to target their audiences in the future. They have started to explore ways to use first-party data as the foundation of their advertising needs. First-party data is increasingly crucial from a measurement standpoint—and businesses may consider utilising their data and analytics for enhanced one-to-one engagement as well as measurement and optimisation. It's time marketers place a strong emphasis on building first-party data as their customers are demanding increased data privacy and deserve the best personalised experience. It’s true that staying on course with today’s consumers is challenging as they hop from one channel or device to the next. However, with the right technology and a customer intelligence strategy rooted in first-party data, you’ll discover the most direct route begins and ends with the first party data that i.e. the data you already own.

When I got my summer internship in January’2021, I was hoping that the Covid-19 situation in India would subside, and I would get to go to Gurgaon and experience an in-office summer internship, since the first year of my MBA was unfortunately in online mode. But these are scary times, and now I am glad to be working safely from my home in Indore. The work keeps me busy and helps me cope better in these chaotic times. Before joining, I was excited but anxious because Com Olho being an Artificial Intelligence-based B2B company, was a completely new domain for me. However, after learning about the business of Ad fraud detection and engaging in regular conversations with the founders, I realised that Ad fraud detection, though very complex, isn’t very hard to understand plus it is more relevant than ever in the digitally driven times we’re living in. The work environment is friendly and nurturing, there’s freedom to share, ask questions & give suggestions. At Com Olho I'm made to feel more like an employee and less like an intern, because of the responsibilities I have been given and how my contributions are taken equally seriously. Apart from Marketing which is my role, I am also learning about the journey and growth of a young startup in India, which I believe is invaluable. I am also observing the importance of empathy and sensitivity, being practiced as core values at Com Olho, as India faces the worst crisis of the century. I am grateful for the learnings, and there is more to come. As a student of the PGDM batch of IMT Ghaziabad 2020-22, I want to say that we might have missed a year of “campus life” but that makes us a unique and resilient batch.

When I was looking for an internship, I was looking for a challenge. A place where I could learn a lot, gain real-life experience in order to prepare myself for the corporate world. I came across Com Olho on LinkedIn and I knew that it’s exactly the place I was looking for. I joined Com Olho as the Technical Intern, where I could get to work on the hottest technologies like Cloud & DevOps. My job responsibilities here are diverse. To put it into perspective, there is always an opportunity to dive deep into things and find a unique solution to the problem and I can say that I have groomed myself a lot during this internship, also, I’ve developed a lot of confidence in my skill set. I’m a Edureka Certified DevOps Engineer. I am passionate about ‘Technology’, because technology has the ability to impact lives at a level and scale that has never been realized in the history of mankind. The idea that something I create can impact someone across the world now, or in the future is what drives my passion for technology. I enjoy nothing more than learning the trends that technology is taking in order to work more efficiently and see progress and success. The internship gave me the opportunity to put into practice a lot of disciplines I had previously only studied conceptually. It really has broadened my horizons and given me a better understanding of why we study certain things and their relevance in the industry. I am thankful for having this wonderful opportunity and would like to express my gratitude towards Com Olho team members for helping me learn every day. I cannot wait to explore even more in this company in the future. This internship has been such an amazing journey of learning, sharing, and presenting my knowledge and skills. Connect with me on LinkedIn : Link

My work experience at Com Olho has been very insightful and eye-opening. Things started well from day one. This company is pretty organised in terms of being ready for new employment. I had my schedule before the day started, and when I reached office, my computer and swags were waiting for me. Once I settled down and met my new employers, it was time for the formal training to begin. I chose to work as a Product Manager to get a better idea of researching, designing, implementing and identifying areas for modification in existing programs. The amount of trust that the company has put in me is honestly unbelievable, they provide the employees with all the resources that would enhance their capabilities and bring the best out of them. Week after week in this organisation, I also built up my capabilities progressively and that resulted in more confident in the tasks that I was assigned. I am honestly beginning to feel a part of the team. Getting to know my workmates daily made me feel that any problems I would be facing with the task that I’m being assigned would be quickly diminished by simply asking for assistance on anything I wasn't sure of. As a 23-year-old, it’s hard to determine exactly what career opportunities might interest me, especially with my focus being largely on achieving good A-Levels leaving little time for exploring what the workplace could be like. However, it’s been a high learning curve for me, which leads me on the journey of discovering myself. This work experience has helped me to better understand what working in an office-based environment is like and I now feel more prepared for, not only work but choosing a career path that better suits me. I know I'm still within the early stages of this job, and things will still change and evolve during my time here. But for the foremost part, things have started off well and I am very proud of my job and therefore the company. Connect with me on Linkedin : Link

Due to the ever-changing needs of the industry, artificial intelligence and data science have become a catalyst for business growth and corporate value. Today, I am proud to be a member of an industry in which artificial intelligence and data science play such a pivotal role in solving business problems. Data, in my opinion, tells us more than just numbers; it helps us understand our users and their needs. I loved numbers from a young age and I knew I would make a career with them. That is why I wanted to be a data scientist, because not only is it a new and untapped field but there is enormous potential for businesses to maximise their value by harnessing the power of data. I've always wanted to do something out of the norm in my life, such as major in mathematics in college and pursue a career in technology. There has always been a dearth of female participation in the tech industry and its leadership roles. I aspire to be one of the top female data scientists and artificial intelligence experts in the Indian tech industry by the age of 30. Com Olho has been a terrific experience for me to work with such a team of incredibly talented people, thriving to make it easier for businesses and industries to detect fraud and tackle it efficiently and effectively. For both consumers and businesses, Com Olho uses state-of-the-art technology, which I extremely admire. It has given me a tremendous head start in my career and I look forward to mutual growth and progress. As a problem solver and analytics person, my career goal is to make data tell its story in an insightful and informative manner. Connect with her on Linkedin : Link

Throughout my professional journey, I have always worked as a content creator and a writer. I love creating valuable content and have always been passionate about presenting my thoughts in a medium that can resonate with the readers. Although I have produced a number of insightful articles for several entities, I often lacked actual engagement with my audience. My previous position confined me to a role where my contribution was limited to content creation with minimal participation in strategic discussion. One can build a successful campaign if and only they can learn how their target audiences feel about their efforts and what they expect from them in the future. In my quest to make a meaningful impact, I set out to look for new responsibilities and challenges. I wish to work in a capability wherein my creativity can be further supported by the flexibility to be at the forefront of crucial projects. I was elated when the team at Com Olho recognised my talent and saw my potential to be an assistant to the marketing team. I joined Com Olho as a Senior Associate of Marketing, with my role focused on ensuring the brand's presence in the industry. At the same time, I was looking forward to working with a young and promising team. Working in a small team meant I was set for a demanding yet rewarding experience. And I can safely state that it was a true start-up experience that I could have imagined. I started with my regular duties, gaining efficiency on the marketing assignments while utilising all the resources provided by the company. I had only been in this position for a few days when I was handed bigger responsibility. I was soon attending client meetings, making proposals for future prospects, and was also given the opportunity to interact with our investors and founding members. They trusted me and included me in important organisational decisions. You know, like which beverage should be on our menu! Very important. All of this made me feel like I belonged to this organisation and that I was an integral part of the team. At Com Olho, I can certainly see my growth accelerating and I am confident that this company is ideally suited for me at this point in my career. Working in a tech firm is all new to me. But in spite of all the challenges ahead, I know that the team at Com Olho will always support me. In addition, the company gives me the platform to bring out the best in me. So far, this journey has been an amazing learning opportunity and I cannot wait to explore more in the future. Connect with me on LinkedIn : Link

To understand how to detect ad fraud, you need to understand how it started. The History of Ad Fraud When online ads were first introduced, they truly transformed the way businesses can market their products. Placing your ad on an online website, attracting visitors with your ad, and successfully completing an online transaction is still a reality in today's world. And this has been a prevalent practice since the first digital ad was placed on the internet. However, spending millions of dollars on various marketing campaigns online will also attract a large number of fraudsters who are looking to make a quick profit. While businesses were celebrating their sales resulting from online ads, at the same time, they were putting huge sums of money in the clutches of fraudsters. Advertisement frauds and cybercrime are plaguing the digital ecosystem at large. Bots account for the majority of clicks in most digital ad campaigns these days, fuelled by a network of bots rather than genuine humans. As a result, businesses are spending their money on clicks that are not genuine. But how did we arrive here? How could a brilliant money-making idea result in losses for businesses? Why are online ads more promising avenues for fraudsters but not marketers? To understand why ad fraud is a growing concern and why marketers must be vigilant in addressing it, you must first understand how it all started. It is critical to examine the history of Ad Fraud and how it cost advertisers throughout its history. Introduction to Online Advertising When digital advertisement started, brands used to place paid banner advertisements and sponsored articles on the internet. In fact, the first even digital banner appeared on the AT&T-owned website HotWired.com in 1994. Those campaigns were based on a CTR model, with extremely effective results in the initial periods. Paid ads created a sensation among prominent internet companies, and Pay per Click became a thing. Goto.com was a search engine that promised to help businesses rank high in search results. Of course, this comes at the price of charging them for the same. Soon after, companies such as Google and Yahoo followed and established their own search engine to enter the digital marketing business. When pay per click was launched, publishers were only charged when a site visitor clicked on their ad. This was groundbreaking at the time, yet it also provided a golden opportunity for fraudsters. The First Impact of Digital Ad Fraud Just when pay-per-click (PPC) was gaining popularity in the dot-com era, the first impact of ad fraud was felt during the same period. There have been numerous reports of sophisticated internet ad fraud attempts. As a result, there were growing concerns about these attacks, which could endanger PPC's sustainability. At that time, there were limited methods to combat the possibility of these frauds, and this has become a lucrative business for fraudsters. The truth is, that marketers and advertisers spend money on advertisements in order to drive visitors to their company. However, ad campaigns can produce the desired traffic and outcome and are yet labelled a failure. Why! Well, it was discovered that most of the visitors that come to their websites aren't real people. They are bots instead. This became a standard procedure for internet scammers to take advantage of the click campaign's feature and make a profit for themselves. Despite various initiatives to fight digital ad fraud and click fraud on the internet, the business continues to lose billions of dollars every year. In fact, recent estimates put the total amount of money lost last year due to ad fraud at $59 billion. And all indicators point to an annual increase in digital frauds. The Evolution of Internet Bots Internet bots are merely software programs that run on computers and mostly cyberattack has something to do with bots at its core. Internet bots can perform automated tasks and cybercriminals frequently use these bots to perform illegal actions such as stealing data, hacking accounts, etc. While the first generation of bots mostly behaved like bots, we can see modern bots often hiding themselves pretending to mimic actual human beings. This, as a result, makes it difficult to track them, and at the same time, equally important to combat them at the earliest. Businesses need to learn how to spot fake traffic. Let's look at some of the major fraud attacks that disrupt the digital marketing channels on the internet, and the role of bots in committing those ad frauds. Attack of the bots Bots are developed such that they can mimic an actual user and could thus befool anyone, giving the impression of an actual visitor. The usage of bots has definitely become an issue on the internet and they accounted for around half of all web traffic. Bots started to appear in all types of internet advertising platforms and campaigns, resultantly draining money from valid sources, and putting it in the pocket of fraudsters. Methbot (2015-2017) Methbot was dubbed one of the largest ad fraud schemes ever formed, costing businesses half a million dollars each day. It is believed that the attack was active between 2015 and 2017. The bot was delivering 3-5 billion false bids and clicks each day. In this, fraudsters produced fake copies of popular websites with URLs that looked identical and placed video advertising on these fake websites. This was followed by a network of bots visiting these websites, and clicking on ads to inflate the prices. Resultantly, this fooled the advertisers by displaying exceptional reports, which in reality were irrelevant. At its peak, Methbot was paying its operators between three and five million dollars per day for losses to the ad business. Advertisers lost an estimate of $16.4 billion to digital ad fraud in 2017. Industry response to rising ad fraud This acted as a wake-up call for advertisers to tackle the issue seriously. Many organisations and top executives have expressed their concerns while laying out their agenda on how to combat those. Companies like Procter & Gamble announced in 2017, that they will be cutting their ad spending by $200 in order to minimise the impact due to fraud. Moreover, other major organisations including Unilever stated their intention to combat these frauds. In 2017, search engine giant, Google officially recognised the issue of ad fraud and started processing refunds to advertisers, who had been victims of malicious practices on their platform. Furthermore, Google has started issuing guidelines to limit the reach of bots. However, these are only the first steps in a conflict against scammers, who are always developing new tools and strategies to defraud businesses. Fight against Modern Sophisticated Bots Recent technological advancements have also resulted in more sophisticated programs and intelligent bots capable of imitating real-life human behaviour. For fraudsters, this is becoming a much easier operation, leaving little room for detection. Because of advanced bots, detection methods based on traditional methodology are basically obsolete. As a result, new techniques and methodologies are required to overcome the increased threat to cybersecurity. What’s Next? Since its origin, several organisations and networks, including major players in marketing have been at the center of the ad fraud debate. Advertisers are still processing methods to fight the issue, which is unlikely to be fixed anytime soon. Furthermore, ad fraud costs genuine businesses billions of dollars each year. There has been increasing ad fraud in sponsored search and paid social, mobile apps, affiliate marketing, and so on. Brands and marketers are now competing in a digital field that is vastly inflated because of the presence of these malevolent variables on the internet. Thus, they need to be extremely cautious when deciding their digital advertising budget. It is critical to examine your data thoroughly; and ensure that your efforts are yielding genuine results, not simply vanity numbers.

When it comes to brand campaigns aka CPM's or top of the funnel campaigns, marketers are least concerned on how much such campaigns would add to the bottom of the funnel, we often hear if we have 2-5% CTR then we must keep spending. Marketers are confident too that such brand campaigns would add a lot to the brand visibility and name assuming they are being shown across all channels of digital engagement. We recently analysed more than 100 mobile applications engaging in generating impressions through their inventory leveraging ad exchanges, and the results are shocking and revealing on how much dirty business is going inside advertising technology right now. Understanding Good CPM Traffic The healthy traffic and to be examined traffic is visualised over a 2d scatter plot to understand data behaviour of the impressions (CPM) acquired for the brand by the networks, affiliates and other sources. Conclusion: Once visualised we can clearly see a strong relevance of the “To be Examined Impressions” with our Healthy Vector. The inventory of such network/affiliate can be highly effective for the brand as it seen by real humans. Result: Good Impression Traffic Source Understanding Bad CPM Traffic – Type 1 The healthy traffic and to be examined traffic is visualised over a 2d scatter plot to understand data behaviour of the impressions (CPM) acquired for the brand by the networks, affiliates and other sources. Conclusion: Once visualised we can clearly see a puny relevance of the “To be Examined Impressions” with our Healthy Vector. The inventory of such network/affiliate cannot be highly effective for the brand as it is not seen by real humans. Result: Bad Impression Traffic Source Understanding Bad CPM Traffic – Type 2 The healthy traffic and to be examined traffic is visualised over a 2d scatter plot to understand data behaviour of the impressions (CPM) acquired for the brand by the networks, affiliates and other sources. Conclusion: Once visualised we can clearly see a puny relevance of the “To be Examined Impressions” with our Healthy Vector. The inventory of such network/affiliate cannot be highly effective for the brand as it is not seen by real humans. Result: Worse Impression Traffic Source You cannot buy engagement, you would have to build it-Nelson