ad traffic validation

VAS Ecosystem

Roadmap to Drive Efficiency in VAS Ecosystem

Creating a cleaner ecosystem necessitates addressing complex challenges like VAS subscription validation and lack of transparency. The evolving digital ecosystem is driving innovation, technology, and enhanced efficiency across the digital ecosystem. But the challenges that plague the digital ecosystem are evolving as well, invalid traffic, bots driving clicks and impressions, replicating human behavior, and opening doors for sophisticated fraud across app, web, and digital transactions. Safeguarding your ad campaigns, placements, and digital subscriptions has become a priority for enterprises and advertisers. Why Validation and monitoring of Value-Added Service (VAS) subscriptions are essential? Protect Your Consumers Ensuring that VAS subscriptions are validated helps protect consumers from unauthorized or fraudulent subscriptions. It prevents users from being charged for services they did not knowingly or unwillingly subscribe to, reducing the risk of financial loss and enhancing consumer trust. Follow the Regulatory Compliance Every country’s regulatory body has defined guidelines and procedures to protect consumers from unfair practices related to telecommunications services, including VAS. Subscription validation and monitoring help service providers comply with these regulations and avoid legal issues or penalties. Enhance Customer Experience Monitoring VAS subscriptions contributes to a positive customer experience. It helps prevent the occurrence of unexpected charges, reduces the likelihood of customer complaints, prevents fraud from affecting the subscription flow, enhances overall customer satisfaction, and makes it easy for the user to activate the services. Stringent Fraud Detection and Prevention. Subscription validation is crucial in preventing fraudulent activities related to VAS. Unauthorized subscriptions can be identified and addressed promptly, protecting both consumers and service providers. Build Subscriber Trust and Ensure Retention A transparent and well-monitored VAS subscription process builds trust with subscribers. When users feel confident that they are in control of their subscriptions and are not being subjected to unfair practices, they are more likely to remain loyal customers and it will lead to more activation of services. Fraud prevention in VAS ecosystem VAS services in the digital ecosystem require protection from fraudulent activities to boost revenue with clean traffic and validated subscriptions. Prevention from duplicate IPs or Proxies Reduce the risk of fraudulent activities by preventing multiple activations or transactions from the same IP address or proxy. Also, safeguard from iFraming/Overlay on the subscription button or page and use of server or device farms for fraudulent activations. Use of BOT devices or fake activations. Bots are automated programs that can simulate human behavior. Fraudsters may use Sophisticated bots to generate fake activations or interactions with VAS services. Implementing measures to detect and prevent Bot activities is crucial for maintaining the integrity of the system. Automated clicks by bots for activation Bots may generate automated clicks to activate VAS services, leading to false transactions. Implementing anti-bot measures, such as Enforcement Challenges, Behavioral analytics, and Heuristic checks working in tandem can help in distinguishing between genuine user interactions and automated bot clicks. Transactions from non-targeted regions Fraudsters may attempt to make transactions from regions that are not part of the targeted audience for the VAS services. Implementing geolocation checks as one of the parameters would help in differentiating between genuine and fake requests. It can also help in identifying and preventing transactions from unauthorized or unexpected regions. Device Signature Mismatch Each device has a unique signature based on its characteristics and configurations. Fraudulent activities may involve manipulating or mimicking device signatures. Monitoring and validating device signatures can help in detecting and preventing transactions with mismatched or suspicious device information. Fig. 1: Frauds plaguing the digital ecosystem Creating a cleaner ecosystem necessitates addressing the complex challenges associated with monitoring both Media Spends and VAS Subscriptions comprehensively. Validating the VAS Subscriptionsin real-time is one of the major challenges in the digital landscape. Another key issue is the Lack of transparency. Thus, ad traffic validation across the VAS ecosystem is crucial along with monitoring spending. The Blueprint for a Cleaner VAS Ecosystem Embark on a journey into a comprehensive solution that not only bridges the existing gaps but transforms the monitoring VAS Subscriptions into boost efficiency: The adoption of integrated analytics platforms that seamlessly amalgamate data from Media Spends and VAS Subscriptions paves the way for a unified, comprehensive analysis, dissolving the barriers between siloed data. Transparency and security stand as a formidable deterrent against fraud and discrepancies. Decentralizing transactions ensures accountability and traceability. Infusing artificial intelligence (AI) and machine learning (ML) Identify patterns that might otherwise remain obscured. Predictive analytics, and AI/ML tech will empower and enhance automated validation processes and checks. Final Thought Validating, Optimizing, and Protecting subscriptions of Value-Added Services (VAS) over the Carrier Billing platform reflects a commitment to building an Effective, Secure, Seamless, and Transparent ecosystem. Building a clean DCB VAS ecosystem suggests a focus on ethical and transparent practices that contribute to Positive Adoption, Reduce Churn, Enhance User Experience, and a Cleaner and more reliable channel for enabling services to esteemed users. Taking a transformative path, envisioning a forward-looking perspective, and adopting innovative technologies and strategies will not only enhance revenue but also contribute to sustainability and growth in the long term. Get in touch with our experts for deeper insights. Reach out to learn more!

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data-clean-rooms

Data Clean Rooms: The Key to Ethical and Efficient Advertising

Third-party cookies have been the key for marketers to track individuals online and understand their preferences. This enabled the advertisers to run personalized ads and do accurate targeting. However, things are going to drastically change in the digital ecosystem by the end of 2023. Apple’s browser Safari and Mozilla’s Firefox have already done away with third-party cookies. Google has now announced its final decision to shut the doors for third-party cookies. Marketers are looking at alternatives to overcome this problem, and one of the prominent solutions that have emerged happens to be data clean rooms. What are Data Clean Rooms? Data clean rooms are software pieces that facilitate brands to run targeted digital advertising campaigns, cap the frequencies, measure campaign performances, and generate reports in a secure and user-friendly manner. This is done by uploading the brand’s first-party data and comparing it to the aggregated data in the data clean room. This includes data added by other companies. Users can access data in a data clean room, but none of the first-party or user-level information is shared with anyone outside the data clean room. Data clean rooms provide various services such as audience segmentation and overlap analysis, and they can facilitate measurement and attribution research of the campaigns without sharing any individually identifiable data. With data clean rooms, brands can access data for a wide range of tasks wherein the privacy rules are defined and implemented by the clean room provider. The data uploaded to a clean room is fully encrypted and anonymized throughout onboarding and audience building. With cookies going out, we are witnessing the rise of various data clean room providers. However, just like any other emerging technology, data clean rooms also have certain pros, cons, and risks associated with them. Let’s take a look: Pros of using data clean rooms Data clean rooms are privacy-friendly, and companies can use them to analyze their target audiences, ad targeting, and evaluation of campaign performance. Despite the user-level data being added to the data clean room, it is protected from exposure to other companies. Companies can get complete visibility of the campaign performance across different channels on some clean data rooms. The data that collaborating businesses add to a data clean room remains completely under their control, and not shared with any other users. Cons of using data clean rooms The data is not ID-based but aggregated. Hence it affects the precision of ad targeting. Before uploading the data to any data clean room, users need to standardize it in a single format to get visibility of the same. First-party and transactional data is gold for businesses and many enterprises might be reluctant to share it. Thus, it would adversely affect the outcomes and the functions that companies seek from a data clean room. There are data clean rooms specific to large platforms such as Google and Facebook. This would make advertisers manually compile and collate data from the different data clean rooms to get the complete picture. The data clean rooms don’t yet have any global standards or operational uniformity as they are only an evolving technology. Risks of using data clean rooms The first-party data is uploaded to the data clean rooms, and in the eventuality of a data breach, companies can face fines, loss of reputation, and clients. Manual management of data clean rooms can make them prone to errors, and accidentally granting access to people who are not authorized can’t be ruled out. There can also be incorrect queries and the exchange of data in an unsecured environment. There can be variations in the type and quality of data uploaded to a data clean room. For instance, one company might not share all of its customer data, and the other might share all of it. This would lead to unfair and inaccurate data exchange and analysis. Having looked at the pros, cons, and risks, we can still say that data clean rooms are one of the most promising solutions to the challenges faced by digital advertisers especially in a programmatic ad scenario in the absence of cookies. However, there are other safer and more convenient options as well. Alternatives to Conventional Data Clean rooms Contextual advertising is one of the most prominent alternatives to data clean rooms. Conventionally, cookies have been used to track and analyze user behavior and target advertising accordingly. However, with the GDPR and other privacy laws and concerns leading to a cookie-free digital world, contextual advertising can help marketers by working as a privacy-friendly source of data collection that is accurate, but non-invasive. It allows targeting of the audience through the context of a web page. For instance, a user visiting a fashion and lifestyle website would be shown products in those categories, and another browsing book will get ads related to books. This contextual approach to advertising ensures that the ad budget is spent more accurately as only the relevant people will be targeted. Unlike cookie-based behavioral targeting, businesses require fewer data and tools or technology for execution. AI systems can make trend and insights-based predictions that help in choosing the right channels and web platforms to advertise on. Contextual advertising also leads to greater personalization as consumers are likely to see ads relevant only to what they are currently looking for. 64% of the customers value the relevance of advertising, and it can lead to greater customer engagement and loyalty. Moreover, contextual advertising is more real-time as it is based on the current actions of a user, and not on the documented habits. For instance, someone might have been buying a lot of books and playing games during remote working or lockdowns, but with offices reopening the current preferences might be more about eating out or shopping from physical stores instead of online stores. Contextual advertising can help out with such information. Towards Transparency & Data Sanity Whether the advertisers go ahead with data clean room or contextual advertising, the key to digital growth in 2023 will be gaining efficiency with data

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ad-fraud

8 Things to Stop Believing In 2023: A Marketer’s Checklist

2023 is coming with a storm of changes in the digital advertising world. Meanwhile, the bots are also ready to upgrade themselves to steal the advertiser’s money. According to the Statista report, the global cost of loss in ad budgets is going to reach $100 bn. in 2023. To ensure the advertisers are also ready with their armor to protect their ad campaigns next year, it is important to let go of a few beliefs that might have led to some mistakes in 2022. We are here with an exclusive marketer’s checklist to help digital advertising to stop believing in things that are pulling back their digital growth. By letting go of these thoughts’ advertisers can be prepared to “Advertise Fearlessly” in 2023. 1. Stop Believing That Programmatic Publisher’s Reports Are 100% One of the biggest disadvantages of programmatic ad is the lack of transparency. In this case, to give a clear picture the publishers provide a report including the ad placements and where the brand’s budget was spent. However, in most cases, the fraudulent publishers provide a skewed report to receive their payments. It is important to not trust the publisher’s report because they don’t know if the placement, they are claiming is true or not. For example, they claim that the ads are running on BBC. But there is still a glimmer of doubt about whether it actually running on BBC or not. Therefore, it is essential for advertisers to resort to validating their ad traffic and not trusting the publisher’s report. By understanding the amount of invalid traffic coming they can make payments based on the clean traffic and partner with confidence. 2. Stop Believing OEM Platforms Are Fraud Free OEM app stores are believed to provide high-quality users and significantly increase the visibility of an app. It also results in being an optimum platform to attract high installs. Due to fewer restrictions, these platforms can also be used by apps removed from Google Play Store to increase their market growth. The OEM app stores receive a security certification and clearance from the mobile manufacturer. However, it doesn’t have the required safety provided by Google Play store apps against potentially harmful apps. The publishers claim OEM traffic is fraud-free, however in reality they provide mixed traffic. When a person purchases a device, the OEM apps are pre-installed in them. In the pre-installed/pre-burned app case, the digital advertiser is paying the handset for those pre-burns. So they have incurred a cost here, and then when the affiliate/OEM partners get those apps opened, the advertiser again pays for the same install. This way, the digital advertising is under the impression that they are getting unique traffic. But the reality is that they are actually paying the customer acquisition cost for the same person twice. Therefore, it is essential for app advertisers to deploy third-party ad traffic validation solutions to safeguard their apps on third-party app stores. With an ad traffic validation suite, the digital advertising can verify the quality of installs and the devices from which it has been installed to ensure the traffic is genuine. 3. Stop Believing That Performance campaigns are fraud free One of the many misconceptions that digital advertising and agencies have is that no fraud happens on performance campaigns as they are targeted campaigns. It is believed that even though media campaigns are prone to ad fraud, performance campaigns cannot be skewed by publishers with invalid traffic. This is because they are paying for performance, and they are getting performance However, over time the bots have become sophisticated and can easily imitate human behavior. The advancement of the bots has reached a level where the events like filling a lead form, making a purchase and other events can also be spoofed. According to our findings, performance campaigns (CPC/CPV/CPL/CPS) attract up to 30-35% of invalid traffic across the industry. Therefore, it is important to do a full-funnel check of the performance campaigns to ensure they are not hampered by invalid traffic. 4. Stop Believing MMP Fraud Protection Is Enough There are a number of MMPs or attribution platforms that claim to detect invalid traffic on ad campaigns. However, this is a conflict of interest. MMPs revenue is generated from the number of attributions. And when the more numbers of fraud they detect on attributed sources, their revenue decreases. This causes a conflict of interest and therefore the real fraud is left undetected. According to mFilterIt findings, we have detected 50-60% fraud on the same ad traffic in which MMP has detected 20% fraud. In this case, the digital advertising is in the shadow that the fraud on their ad campaigns has been detected and prevented. But the reality is that they are still paying for the ad traffic coming from bots. On top of that, the MMPs have limitations in detecting invalid traffic at the impression level and have minimal checks that often miss out on sophisticated fraud patterns. Therefore, it is essential for marketers to partner with an ad traffic validation suite to ensure their ad campaigns are getting clean traffic. Moreover, the marketers must also ensure that their traffic verification partner’s solution is not limited to just detecting invalid sources at the impression level but also at the click stage, re-engagement and referral. 5. Stop Believing keyword blacklisting is enough for brand safety Brand safety is no more a choice, rather it has become a necessity for brands to stay protected in the digital landscape. One of the key reasons brands need a brand safety suite is to ensure their ads are not placed beside violence, hate speech, morbidity, and other derogatory content. Blacklisting certain keywords to ensure the ads are not displayed next to illicit content is one of the common ways to deal with such issues. However, it is not enough to ensure the safety of ads. One of the loopholes of keyword blacklisting is that it assumes that the platform knows the context of the content. It can be relevant for English-focused content,

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ad-traffic-solution

Know The Unknown Cause Behind Your Abnormally High Installs

The shift towards digital advertising brought many major changes in the way of advertising. In comparison to traditional advertising methods, digital intrusion introduced marketers to a transparent way of digital advertising with more control. Attribution platforms are also known to ease the task for app publishers and advertisers. They enable them to track every impression, click, install, and in-app event. The attribution platforms attribute each install to a corresponding click based on this acquired information. However, there is a catch. The advertisers cannot solely rely on the attribution data to take business decisions. With the evolution of digital media, fraudsters have also evolved with time and have been able to create a more advanced level of fraud which requires advanced techniques to detect mobile ad fraud. Types of Advanced Mobile Ad Frauds Fake Attribution While attribution platforms give a clear picture to the advertisers about the incoming traffic on their ad campaigns, there is still a loophole that cannot be ignored – Mobile Ad Fraud. This can lead to rendering inaccurate or misleading attribution data. Fraudsters have become very advanced to match the ever-evolving digital ecosystem. They can inject bots that have human-like behavior and are hard to detect. In the case of app campaigns, fraudulent affiliates are adept at manipulating the attribution process and can hack the last-click attribution and claim it to be provided by them. Whereas the reality is that they played no part in driving that app install or event. These “affiliate fraud are aware of the attribution mechanism and can easily fool the attribution platforms into crediting them with the install. SDK Spoofing This is another form of sophisticated fraud where legitimate-looking installs are created by the method of SDK spoofing. This is used to show a high number of installs using the data of real devices without any actual installs happening. Fraudsters compromise a legitimate device to punch installs that look real to drain the advertiser’s budget. This method is also called traffic spoofing and replay attacks. To commit fraud, fraudsters hack the SSL encryption that is placed between the tracking SDK and the backend servers. With the “man-in-the-middle-attack”, the fraudster creates a series of test installs for their targeted app. Once they identify the URL that controls specific actions within the app, they look for the dynamic URL to create fake installs. This can be done repeatedly and appear like a genuine activity to the advertiser. Why MMPs are not enough? Fraudulent techniques like fake attribution and SDK spoofing are advanced-level frauds that are hard to detect by average fraud detection methods. They require some advanced technology that can analyze the behavior of the traffic to differentiate between a bot and a human. The biggest drawback of MMP fraud detection is they have limited rule checks. And as their billing happens on the attributed data, they often claim less fraud to increase their revenue. Thus, it results in a conflict of interest. Therefore, marketers need a holistic ad traffic validation partner like mFilterIt to ensure that their app campaigns are protected from sophisticated fraud. We use AI, ML, and data science capabilities to detect invalid sources in real time across the funnel to ensure the sophisticated bots don’t penetrate further into the sales funnel and skew the data. To protect the app campaigns from advanced-level mobile fraud techniques like SDK spoofing, we implement our own SDK to fetch the data and validate the quality of the traffic. Real Case We have found a recent case of misattribution where affiliates have not given any purchase and passing the invalid order ID for all the orders placed. Given below is a pictorial view of the case which happened by spoofing the data from Affiliates. We detected anomalies by implementing our SDK and pointed out the discrepancies in the attributed data based on behavior and device checks. The Way Ahead The advertisers must be more vigilant, smart, and technologically armed to counter the attacks of sophisticated bots. Incorporating an ad fraud tool can help advertisers identify the traffic coming from non-humans and eliminate them in real-time and work confidently with media partners. Get in touch with our experts for deeper insights. Reach out to learn more!

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