mFilterIt
Contact Us
mfilterit

Expert Opinion

how-to-save-ad-budget with-bot -detection

How Bot Detection Enhances Marketing Campaign Accuracy and Safeguards Ad Spends

Blog, Ad Traffic Validation /

Bots make up about a third of all web traffic, and shockingly, 65% of those bots are classified as “bad bots”. These malicious bots indiscriminately destroy marketing campaigns by inflating impressions and clicks; thus, they financially devastate marketing campaigns. So, ironically, although companies do not intend to, they spend a percentage of their ad budget on fraudulent traffic, making every campaign less effective than it could have been. Ad fraud is rising; therefore, the detection of invalid traffic across all digital campaigns has become necessary for businesses’ success in the digital space.    There is a need for a full-funnel ad fraud detection tool to provide omnichannel protection against general and sophisticated invalid traffic i.e. GIVT & SIVT. An additional brand safety layer of protection helps to boost campaign performance. To guarantee the success of digital marketing efforts, the traffic validation tools should provide coverage across app, web, OTT, and CTV ecosystems.   Let’s understand how bot detection works, why it is so important in marketing campaigns, the technologies involved, and how we help organizations overcome the risks of ad fraud in the bot-driven world and enhance marketing analytics accuracy.   What Is Bot Detection?   Bot detection is the technology and methods used to identify and prevent non-human traffic—specifically bad bots—from serving interaction with a website and other digital destinations.   From a digital marketing perspective, “good bots” (search engine crawlers, etc.) assist in increasing visibility for search engines or in monitoring the performance of a site, bad bots are designed to imitate human behavior, falsify clicks, impressions, and other down-the-funnel engagements. Bots skew digital campaign efficiency for businesses if left unchecked since they adversely affect customer acquisition costs and artificially inflate performance reports. Why Is Bot Detection Important for Successful Marketing Campaigns?  Here’s why tracking and detecting bots in marketing campaigns are important-  Protection of Ad Spend  Bots generate fake clicks, impressions, and visits which means businesses are paying for fake user engagements instead of real ones. Often leads are also filled up by sophisticated bots bypassing OTPs and captchas. A huge portion of the budget spent on advertising goes to waste without proper detection of ad fraud.  Real / Effective Analytics  Bots taint the quality of the data collected from digital campaigns and yield wrong interpretations. In turn, this may lead to wrong business decision-making as well as inefficient use of resources. Businesses cannot rely on their marketing data unless the bots are detected and blacklisted.  Higher ROI  Based on the bot-cleansed, accurate metrics, businesses that deploy full-funnel ad traffic validation tools understand how their marketing campaigns are doing. This leads to a channel-wise analysis and therefore can operationally direct more budgets to the most effective channels, which means a higher ROI.  Brand Safety  Bad bots are often placed by publishers on content that is highly questionable and brand-unsafe. Good fraud detection tools not only end up finding sophisticated invalid traffic but also provide a layer of brand safety from bad inventory and unsafe ad placements.   How Do Bots Get Detected?  There are many advanced techniques and technologies used in bot detection to identify fraud and block such malicious activities-  Device Fingerprinting  Device fingerprinting helps track and identify unique devices across the internet. Each time a particular device accesses a website or clicks on an advertisement, a unique “fingerprint” can be created with various signals and device attributes. This technique is driven by AI & ML algorithms to analyze data and identify anomalies that pinpoint bot traffic in real time. Sophisticated bots are largely identified at down-the-funnel (i.e. clicks, visits, leads, or sales) metrics. The General IVTs are identified at the pre-bid impression stage.  Behavioral Analysis  Human users do not exhibit predictable patterns, but the behaviors are predictable in the case of bots. Behavioral analysis tracks user interactions to detect unusual activities. One of the most common types is mouse movement. Bots tend to have straight-line patterns vis-a-vis a random pattern in the case of real humans. For any traffic validation tool, behavioral checks should feed into the overall ad fraud checks.   Heuristic Checks  Heuristic checks are a technique to detect bad bots by analyzing the known patterns of fraud on the web. This may include checking for indications that correspond with previously established models of fraudulent activities. Heuristic checks often include monitoring for unusual user-agent strings, changing IP addresses, or clicking patterns. Bot detection tools need to continually upgrade their techniques for detecting bots by keeping heuristics models current and updated to adequately monitor new tactics of fraud.  Deterministic Checks  Deterministic-based bot detection manifests itself by applying an actual, predefined set of rules in detecting bots. These include data on hard data such as the IP address, session cookies, and other metadata about a user. For example, if the known bad bot’s IP address is giving traffic to a website, the system can deny it on plain identification. Deterministic checks can filter out low-level bot activity quickly and are often used in conjunction with more advanced techniques, such as behavioral analysis.  How mFilterIt helped a Global Conglomerate in Bot Detection and Ad Traffic Validation  mFilterIt started working with the advertiser to deliver ad fraud detection solutions, which involve a multi-layered approach that can protect digital marketing campaigns from fraudulent traffic. Both branding and performance campaigns across walled gardens (like Google & Facebook), programmatic channels, and affiliates were validated by mFilterIt.   The bounce rates on their website were sky-high and YouTube VTRs & CTRs were under suspicion. The mFilterIt solution provided the following to the advertiser:    Full-Funnel Protection – Our technology protects your business on a Full-funnel level, ensuring bots can be detected regardless of whether they interact with display ads, video ads, or mobile app ads.   Real-Time Monitoring – This solution continually monitors traffic in real-time and detects bad bots before the event can affect performance metrics. It effectively filters out non-human traffic with a combination of behavioral analysis, device fingerprinting, and deterministic checks.  Comprehensive Reporting – We provide complete reports on bot traffic

How Bot Detection Enhances Marketing Campaign Accuracy and Safeguards Ad Spends Read More »

content analyzer

Content Analyzer – The Game Changer Every E-commerce Brand Needs

Blog, Digital Shelf Analytics /

E-commerce is fueled by customer engagement and purchasing decisions that revolve around content such as product descriptions, images, customer reviews, and even FAQs-composing every piece of it into a buyer’s journey. In this stream of data from a digital platform, how will e-commerce businesses know if their content is doing its job correctly? Here, the Content Analyzer becomes the tool to track, evaluate, and optimize the content across digital platforms.  A Content Analyzer ensures that the content is attractive and converts into buyers. It’s a performance measure for knowing which parts of the content work, which part needs improvement, and what is going well with the target audience. For optimizing performance on digital commerce platforms, strong customer interaction and purchase intent, content tracking and analysis are much more significant. Most of them do not realize the importance of e-commerce content marketing until it happens too late: little engagement, lost sales, inefficiency- the list goes on.  Metrics of Content Analyzer which brands must track  Analyze content based on perfect page scores and unique product code counts.  It provides insights into own vs competition with the image analysis which tells various parameters like pixel threshold, DPI threshold, white background, etc.  It gives insights about brand-wise organic discoverability shared on a monthly and weekly basis.  It provides perfect page analysis with the overall score, content, title, and review score.  It provides recommendations for PDP for its brands. There are parameters like traffic keywords used by competition but not own, high traffic keywords used by none, and poorly Q&A content themes.  It provides a word cloud based on the title and description.  Downsides of Not Monitoring and Analyzing Contents  Missing Chances to Optimize  Without tracking and content analysis, organizations do not get key insights. Perhaps this means that the content is non-performing, but there is no data-driven feedback to let companies know what needs change. Keywords, metadata, product descriptions, and visuals may not be driving organic traffic or converting site visitors into buyers.  Customers have inconsistent experiences  E-commerce platforms thrive in seamless, cohesive customer experiences. Without appropriate analysis, your product descriptions are inconsistent, prices are wrong, or images are misaligned, creating confusion. A user who sees many different pieces of information on separate product pages becomes frustrated and leaves the site.   No Alignment with Content Strategy  Most companies operate based on intuition and are not data-driven when it comes to strategy. Lacking the analysis of content performance, brands cannot align their content with consumer intent or industry trends. Marketing campaigns can prove ineffective when resources are being wasted on the wrong content that does not represent the brand’s objectives or the expectations of the consumer. For e-commerce, trends change rapidly, so not analyzing the content means lagging behind competitors.  Unable to Identify Spam or Malicious Contents  User-generated content, such as reviews and ratings, influence buyer behavior in e-commerce. The absence of analysis of this kind of data therefore opens the way to spam content or possibly malicious comments. It can therefore damage the reputation of a brand and mislead its customers, which leads to foregone sales.   Significance of Content Tracking and Analysis  Enhanced Customer Experience  Content analyzers help brands grasp how customers interact with their website; which particular kind of content is preferred by customers; and where improvement is needed. Such in-depth analysis helps businesses personalize by channeling the content as per the interest of customers.   Increased Conversion Rates  Analyzing content helps businesses get a precise idea of what types of content produce conversion. It might be in the style of a product description, an image, or even a tone in customer reviews that influences buying behavior. Content analyzers give the information a business needs to drive improvement in every phase of the buyer journey to ensure they’re serving the right content, at the right time, to maximize conversion.  Better Amazon Rankings and Visibility  Uninteresting pages are pointed out by content analytics, which act as weaknesses in the ranking perspective. With keyword monitoring, metadata, and content engagement, businesses will be able to optimize their strategy to come out with higher rankings in the Amazon rankings.   Decision-Making Using Data  The most important advantage of content analysis is helping to make data-driven decisions. It offers in-depth insights about what works and what does not, hence allowing a business to pivot its strategies and put resources in the right places. E-commerce firms are no longer required to make guesses about what can be corrected with content.   Improved ROI on Content Investments  E-commerce companies are investing heavily in content generation – from professional product photos to comprehensive blogs, videos, and posts on social media. What matters most, however, is not the generation of this content, but rather monitoring and measuring it – so that such investments can produce the maximum return possible.   Case Study  For instance, one of the largest multinational food, snack, and beverage corporations faced the challenge of optimizing Product Page Content. The brand needed a comprehensive integrated solution to monitor product page cont. Our ecommerce competitive analysis conducted image analysis and keyword analysis for our brand vs competition across platforms and geographies to identify gaps in PDP content.    Fig 1: Image Analysis  The mFilterIt content analysis checks primary content and secondary content on product pages. The primary content analysis checks the product page on various parameters which include title length as per defined threshold by the brand, brand mention in title product description requirements, analysis of images used, and compliance with platform-specific guidelines.   It also checks the presence of the primary image and ASP presence. For secondary parameters, it monitors additional information if applicable on the platform like supporting images, mention of the brand in the description, ingredients, nutrient facts, or how to use as part of the description. The content analyses provide insights and measure product content in terms of score vis-a-vis competition.   Quarterly Perfect Page Analysis (Category – Beverage)  mFilterIt Impact: The ratio of ‘traffic to page’ to ‘add to cart’ has gone up by 25%. It helped

Content Analyzer – The Game Changer Every E-commerce Brand Needs Read More »

Click Tracker

Click Tracker: Measurement and Validation of Clicks to prevent ad fraud and click-fraud prevention

Blog, Ad Fraud /

Ensuring the legitimacy of clicks is a key performance measurement metric for marketers and businesses. Verification backed with accurate measures leads to optimized performance. Click Tracking ensures all invalid traffic is identified before it drains the ad budget and skews ad campaign performance data.  Let’s delve deeper to understand the need for click tracking and how it can help in campaign optimization.   Click Measurement and Validation  Consider a scenario where an ad gets a massive number of clicks, generating a good number of impressions but ending up with a low conversion rate. This is a clear waste of spending. Advertisers need to identify gaps across the funnel that start with first and foremost wider end with a flurry of clicks.    What does the advertiser need? Advertisers need to optimize their ad campaigns with click fraud detection software, that can bring transparency to the ad campaigns.   Weed out invalid traffic starting with clicks: Invalid traffic from clicks on Google ads and Meta Ads need to be identified in real-time, ensuring no damage to your ad budget.  Identify genuine clicks vs Bots clicks: Genuine clicks usually show varied patterns, high engagement, and diverse geolocations. While Bot clicks exhibit rapid, consistent patterns, low engagement, and suspicious IP addresses. Identifying Bot patterns and accurate measurement is the key to protecting wastage of ad spend.  Detect Fake clicks: Driving genuine traffic led to getting conversions. Detecting fake clicks generated via click spamming in real time improves your quality of traffic and can get you more conversions.  Click farms: Are large-scale dedicated click fraud operations generating invalid clicks? Are you able to track that? Usually, click farms are hired to inflate the click volume on ads leading to inflated and skewed metrics.   Accuracy of Measurement can prevent hefty payout on invalid clicks and bring transparency into the ad campaign across app, web, or programmatic advertising platforms.   How can Click Tracker help advertisers?   The size of the online click campaign market is growing. This is evidenced by the Google Ad revenue (US) to the tune of $237 billion (2023) and Meta’s ad revenue stands at $131billion (2023). This has grown 6% and 16% respectively in the last year. With the size of the click market growing, it is estimated that digital advertising fraud costs will increase from $88 billion to $172 billion within the next five years. That figure will grow 14% annually and nearly double, as per a Statista Report.   This impacts all advertisers’ spending on clicks across platforms as click fraud is a multifaced threat that can take many forms, from sophisticated bots and malicious software to organized human operations like click farms.   Advertisers need to understand the need for accuracy and transparency in click measures and validation to protect their investments and ensure that their marketing efforts reach genuine and interested audiences.  Ensure Accuracy in Data Collection with real-time tracking and detailed analysis: Real-time data on user interactions ensures that marketers have up-to-date information on campaign performance, while analysis and insights into click-through rates (CTR), user behavior, and engagement metrics, help in the precise measurement of campaign success.   Fraud Prevention with Click Fraud Detection and Verification: Identify and filter out invalid clicks, such as those from bots or repeated clicks from the same user, thereby reducing click fraud. along with verifying source to ensure clicks are coming from targeted geographies, the authenticity of traffic sources is validated ensuring that clicks are coming from legitimate users.  Enhanced Campaign Performance with Click to Conversion tracking: Monitoring and validation are needed across the funnel. By tracking which clicks lead to conversions, marketers can optimize their strategies for better ROI. Full-funnel protection with ad traffic validation and ad fraud prevention can enhance campaign performance. Clear and concise information on campaign performance, making it easier for stakeholders to understand results. Using third-party click trackers such as mFilterIt Valid8, adds an additional layer of trust.   Customizable and Tailored Metrics for efficient measurement: Trackers can be customized to measure specific metrics relevant to your campaign goals. With advanced AI, Machine learning tech, and algorithms, campaign performance measurement and optimization. Integration with ad managers also helps automate and provide a holistic view of campaign performance.  Final Thought  mFilterIt, ad traffic validation, click tracker and ad fraud prevention tools can play a vital role in building trust and transparency in digital marketing by providing accurate data, preventing fraud, ensure click integrity, enhancing campaign performance, ensuring transparency in measurement, and offering customizable solutions. By leveraging mFilterIt Valid8 marketers can gain valuable insights, optimize their strategies, and foster trust with their audience and stakeholders.  Get in touch to learn more about click tracker.

Click Tracker: Measurement and Validation of Clicks to prevent ad fraud and click-fraud prevention Read More »

Brand safety

Protect your Brand Reputation with Safety & Brand Infringement Suite

Blog, Brand Safety & Suitability /

Consider your brand being placed alongside unsuitable content or falling victim to a fraudulent website that affects your image and reputation. Brand reputation is a fragile asset related to its online presence through ad placements across digital platforms.   According to an advertising standards study, about 35% of Indian brand companies faced reputational damage due to misleading advertisements. Digital brand infringement, such as fake websites and social media handles, led to a loss of up to 25% in the market share of various well-known brands.    The irrelevant ad placements and fake websites may quickly harm the reputation of the brand. The damage extends beyond consumer perception. It can lead to diminished sales, loss of customer trust and cost brands long-term financial loss.    Concerns related to brand safety    Brand safety risks develop when ads appear in circumstances that undermine a brand’s image or don’t align with the real values of the brand.    Here is a breakdown of the common concerns related to losing brand reputation:   Irrelevant and unsafe ad placement: Placing ads alongside irrelevant content results in the ineffectiveness of the ad campaign. Issues relating to ads being placed on harmful and unsafe content spoil brand image and do not bring any positive campaign metrics.     Brand Infringement & Safety Issues: It involves risks such as brands visible alongside inappropriate irrelevant material such as hate speech, or violent abusive content.    Issues come due to irrelevant placement of ads    Branding campaign wastage: if ads reach the wrong audience diminishing the desired outcomes efforts and disconnect between the brand and the viewers.    Maximum Ad skips: if the ads appear in irrelevant & unsuitable settings viewers skip them as it is not important to them, or they are more interested in the content   Loss of true views when ads are not delivered to the right audience in appropriate context’ brands lose the chance of gaining genuine connections. Leading to wasted views and ineffective ad spending.    Brand Unsafe placements could include the appearance of an ad alongside explicit content that violates the brand safety guidelines such as those of GARM. Various categories of ad placements cause major reputation damage to the brand.    Unsafe Categories of ad Placements causing major reputation harm    Illegal Drugs Tobacco E-cigarettes Vaping Alcohol   Terrorism   Online Piracy  Adult and explicit content   Arms and ammunition   Spam or Harmful content   Death injury or military conflict   Crime & Harmful acts to individuals and society   Debated sensitive social issues   Hate speech and act of aggression   Solution  Most above-mentioned unsafe categories require an actionable approach that will ensure brands get protected on all fronts and mFilterIt solution carries a comprehensive way to deal with unsafe media advertisement placements.   The key elements of the solution included robust region-specific Content Categories content context analysis, sentiment analysis, video frame recognition, and GARM compliance.       It is done through not only keyword searches and meta tags in the description and title but also AI & ML-driven context analysis and sentiment analysis to ascertain relevancy. Furthermore, the frame recognition strategy involves analyzing individual frames of video content where the ads are placed rather than relying on the metadata only. And lastly the,    enabling active prevention of brand protection with real-time blocking of brand-unsafe videos was undertaken.    Let’s understand this with a case study.  Case study   A large FMCG brand encountered issues with video placements where heavy ad expenditure resulted due to brands content association with explicit content.   To address this issue a brand safety solution was initiated by mFilterIt, and the following results were obtained.     Realtime blocking helped in reduction of brand unsafe percentage   Impact on business: After identifying the brand unsafe placements the solution started blocking them actively and brand unsafe % declined from 10.73% in Sep 2023 to 1.81% by April 2024, it also observed high ad performance on Brand safe videos as compared to explicit videos.  Brand Infringement   Brand Infringement occurs due to violation and unauthorized use of name, logo, trademark, patents or copyrights of the company or brand.   TRA’s Brand Trust Report says that trust decline to negative brand association and brand infringements in sectors like FMCG and Pharms and top brands trusted dips of up to 20%.   A wide range of brand infringement capabilities can be seen that hamper the reputation of the brand.   Intellectual property Infringement   Fake social media handles   APK Copycat Apps   Fake brand’s communication like emails   ATO (Account Takeover)   Logo Misuse   Phishing websites   Solution  mFilterIt proprietary OSINT tech with the use of Open-Source Intelligence, scans the entire digital landscape for identifying possible infringements. AI-Powered automation by which the process of cleaning, tagging, and classification of enormous data gathered through OSINT.    The 3-pillar approach solution can be applied to managing and addressing these brand infringement issues if faced by any brand or company.    Identification of the list of official brand assets such as the official logo, social media handles, and instant messaging handles. Classification based on potential instances of the above-mentioned infringement capabilities Action included takedowns and blacklisting to clean and refurbish the lost trust in the brand. Let’s understand the whole approach with a successful case study of a construction company.   A well-known real estate firm faced various challenges of brand infringement in the form of IPR infringement and fraud occurring on digital and social media platforms. It was challenging to track and monitor violations manually.    mFilterIt deployed a solution to scan the multiple digital platforms for solving the potential infringements. The content gathered through OSINT like text videos and images was given a confident score produced by ML. Based on high and low confidence scores the classification is done for further action.    The impressive impact can be seen on the real estate firm between Jan- Jun 2024:    Cases were found around 1300 with 1001 successful removal of instances of illegal content. Across 7 platforms from

Protect your Brand Reputation with Safety & Brand Infringement Suite Read More »

Affiliate Fraud

Affiliate Fraud Uncovered: Protecting Your Brand and Ad Spends

Blog, Brand Safety & Protection /

The darker side of digital advertising is growing deeper and deeper: more and more attention is drawn to issues connected with unnecessary waste in ad spend, brand safety, as well as infringement concerns.   It is estimated that 30% of affiliate marketing losses can be attributed to the phenomenon of affiliate fraud. According to this trend, the losses will amount to more than $1.4 billion in 2024, according to Statista Report. Such fraudulent activities by affiliates take the form of ad fraud and brand infringement which not only wastes marketing spend but also tarnishes the brand image.    Affiliate fraud is the type of fraudulent activity that involves an affiliate’s manipulation of the performance of an affiliate marketing program to generate commissions without actually adding value to the advertiser.   These losses also highlight the necessity of investment in technology that helps in affiliate monitoring and detecting ad fraud to spare the brands from harm and preserve the sanctity of the different models in affiliate marketing.  Major Affiliate Fraud Concerns  The two ways in which any brand gets affected by affiliate fraud is when their marketing spend is wasted and their brand image takes a hit. The major threats from which any brand should be protected is:  Ad Fraud by affiliates running your Ads: Affiliates run bots on advertising campaigns and end up showing fake performance using bots. This results in achieving lower campaign metrics and greater loss of advertising spend. The ROI’s take a hit and the only one who gains is the publisher.  Brand Safety and Infringement Issues: Affiliates and influencers also use brand and advertisers IP like logos, brand keywords and trademarks without their authorization. Moreover, fake brand communication results in the brand suffering major reputational loss.   Affiliate Fraud in the Ads Context   Ad Fraud refers to the illegal practice of falsehood of advertising metrics to generate illegal revenue. This can happen due to fake clicks, fake impressions, fraudulent apps and more. Fraudsters trick advertisers into paying for activities that never actually happened, draining their advertising budget.  Let’s dive into knowing about types of affiliate fraud and understanding the solution to it   Types of Ad Fraud Understanding the various forms that affiliate fraud takes is the starting point in building a countermeasure. These include some of the most common types of affiliate fraud:  Click Fraud: The act of inflating the clicks on an advertisement artificially is known as Click Fraud. It is a scenario where an affiliate uses automated bots or a click farm to artificially inflate clicks, or even incentivizes real users to click on actual ads with no interest whatsoever in the material advertised. Lead Fraud: Lead fraud generates fake leads through fraudulent activities. The affiliates may use the methods of submitting fake information, using stolen data, or automation of lead generation through bots.   Domain Spoofing: Fraudsters will masquerade as valid websites either for deceptions to the advertiser or to get affiliate commissions. They can use similar-looking domain names or replicate the content of an important site.   Cookie stuffing: Cookie stuffing is the placement of multiple cookies on a user’s device without them knowing about it. When the sale is made, the affiliate collects his commission even though he had no justified position for the sale to be triggered.   Solutions to Prevent Ad Fraud  AI-ML Analysis: Such models demonstrate the capabilities of identifying bots and other swindles because of their comprehensive automation pattern and are therefore successfully assisting in easing cases of Affiliate marketing fraud.  Device Fingerprinting: Device fingerprinting, or device signature techniques enable identifying the fraudulent devices that give multiple clicks coming from a single device. Specific attributes of the device, such as browser type, and other hardware configurations, aid in identifying suspicious devices that may be part of a device farm or employ VPNs.  Deterministic, Behavioral and Heuristic Checks: The traffic validation tool should be enabled with deterministic, behavioral and heuristic checks. The pattern of the actions performed by the users is examined for any discrepancies.   Monitoring Affiliates for Brand Infringement & Safety  Monitoring affiliates for brand infringement & safety is crucial for maintaining a brand’s integrity and ensuring compliance with marketing guidelines. Affiliates can sometimes engage in practices that may harm a brand’s reputation or violate its policies.  Types of Affiliate Infringements & Safety Issues  Brand Bidding: Brand bidding is a scenario in which the affiliates are bidding on the branded keywords to attract users to their sites which means brand’s organic may end up being cannibalized. This also leads to increased costs in advertising and misrepresents affiliate performance.   IP Violation & Typo-squatting: IP violation and typo-squatting is when affiliates register domain names, which nearly resemble the official web page of a brand. These domains give way for false redirections from users, thus allowing potential data compromise and brand impersonation.  Misrepresentation of Brand Information: Affiliates sometimes mislead the branding by making false claims, over-expressing the benefits, or using unauthorized promotional content to attract users. Such misrepresentation might create confusion among customers as well as destroy the brand’s credibility.   Misuse of Influencer Coupon Codes: As affiliate programs believe influencer marketing is an integral part, misuse of influencer coupon codes can take the form of an affiliate who publishes them on unauthorized platforms or channels by using those same coupon codes to commit fraudulent transactions. Misuse of Influencer Brand Creatives: Brands have creatives that influencers can promote with, but they may be mis utilized by editing them to make use otherwise than as designated or attaching misleading claims.   Solutions to Prevent Affiliate Infringements & Safety Issues  Automated driven Brand Asset Recognition: Affiliate monitoring and protection are provided in its full scope in the entire digital landscape with complete brand asset validation. Whenever there is such a necessity, clients incorporate advanced algorithms to search and to monitor physical and virtual properties of brands such as logo, trademarks, product image and the contents.  AI driven Multichannel Monitoring: Works as an umbrella on a multitude of online platforms such as websites, social media, paid advertisements, coupon sites, mobile applicators in

Affiliate Fraud Uncovered: Protecting Your Brand and Ad Spends Read More »

ecommerce analytics

eCommerce Analytics: Strike First and Fast in the Battlefield of eCommerce

Blog, Digital Shelf Analytics /

The rapid rise in eCommerce across geographies especially in countries like Indonesia, Thailand, and Vietnam is experiencing rapid growth, with mobile usage and social media penetration being the highest worldwide.     Each country in the SEA region has varying levels of eCommerce penetration and the region’s potential is enormous. Customer behavior is very similar to that of China and Korea where K-pop idols create fashion trends.    SEA has approximately 400 million internet users and platforms such as Shopee, Lazada, and TikTok are leading the way providing customers with an immersive, interactive buying experience that combines social interaction with eCommerce capacity.   The e-commerce market is expected to grow by $234 billion by 2025, emphasizing the need to make data-driven decisions to navigate this battle swiftly.   Every eCommerce participant requires real-time access to actionable business intelligence to meet success metrics.  Let’s understand the common types of eCommerce across geographies and the role of eCommerce analytics in striking first and fast in the race.   Common types of eCommerce  Each of these types serves a particular market need and varies based on the product or service offered to the target audience.   There are various common types of eCommerce such as: Quick Commerce – As the name itself suggests rapid delivery of goods often within minutes or a couple of hours. It focuses on near-instant delivery of groceries, and convenience items such as household necessities. Example – Blinkit, Zepto, and GoPuff are q-commerce platforms that offer quick delivery within (10-30 minutes).  QSR Commerce– That is Quick Service restaurants serve rapid, efficient, with affordable price cuisines. Customers also can dine in, take out, or have delivery at their place.  Example –   McDonald’s serves millions of consumers daily as it is a global QSR business.  According to Statista, the worldwide QSR industry is expected to reach $1.2 trillion by 2028.    Social Commerce- It is an integration of the shopping experience into social media platforms like Facebook, Instagram, TikTok, and others. Social commerce across social media platforms is more effective as it’s not dependent on traffic coming from searches instead consumers are already engaged on the platforms.     Marketplace Commerce – The purchase and sale of products via online marketplaces where various suppliers offer goods. The marketplace concept is gaining traction, especially in developing countries.  Example– 3rd party merchants can list their products on platforms such as Amazon, eBay, and Flipkart providing buyers with a wide range of options.   The FMCG category in marketplace commerce is expected to be the fastest growing with a total market of $375.1 billion by 2025.    Are your products the top drawers? on the above-mentioned common commerce types?    If not, then there is a great need for e-commerce analytics to be incorporated into your brand.    Need for eCommerce Analysis for brands   Visibility is an important component of eCommerce business and digital shelf analytics can help with that. Monitoring a brand’s digital shelf performance such as product availability, pricing, and search rankings allows marketers to ensure that their items are easily accessible and competitive consistently across several eCommerce platforms.   Sales Growth   Improved Visibility  Increased conversion rates   Enhanced Customer Experience Competitors Insights Metrics for Customer Journey Optimizations  It is important to consider the various analytical metrics while forming a strategy to sell on various eCommerce platforms. Customers’ journey is optimized at broader three levels such as:    1.Awareness and interest – It helps brands to track visibility and ensures that the product is accurately featured throughout the marketplace boosting awareness and driving interest from potential customers. It consists   Discoverability tool Competitor analysis banner analysis  Content recommendation 2.Consideration & Evaluation –The system evaluates critical elements such as bestseller analysis to track the ranking of the products and the factors behind top sellers.   Pricing and Discounting analysis  Content Analyzer  Customer feedback analysis gathers ratings and reviews, and Q&A data to assess customer sentiments.   SKU health analysis scores based on content quality, availability discoverability.  Delivery TAT    3.Decision / Purchase – Overseas digital shelf performance by sales analysis with scorecards at brand & category level boosts bestselling products and hero products of the brand.   How eCommerce analytics helps businesses to grow – Case Analysis  Let’s understand this with a case study, a leading FMCG brand was battling to ensure consistent product availability across key geographies.   Challenges faced by the brand   Their product presence fell behind competitors, resulting in missed sales opportunities and a reduced market position both online and offline. The brand’s principal problem was to ensure product availability in numerous regions.   Recognizing the severity of the situation the brand relied on eCommerce analytics intelligence solution mScanIt for actional information.   Solution   Using the eCommerce analytics tool mScanIt through targeted inventory optimization, data-driven insights, and competitor benchmarking gained detailed product availability data from a variety of online sources. Determined which places their product was underperforming in.  Also, identifying the availability against the rivals and areas for improvement in with real-time insights to change online and offline inventory levels ensuring that products are available in the appropriate locations.   Outcome   The brand was able to close the gap against the competitors and was able to overtake a competitor by increasing its availability by 29%.  Fig 1.0 Analyzing the data on availability for the past year Aug 23 – Aug 24  The analytics and solution enabled the brand to not only improve its sales online but also offline too. The case study demonstrates the power of AI-ML data-driven decision–making in enhancing both online and offline retail performance. To sum up   Switching to e-commerce analytics can help eliminate friction in the shopping process and make it easier for customers to complete their journey of purchase, and to edge ahead of their competitors across the digital commerce ecosystem. Business intelligence must be granular to the last detail and scalable across geography and platforms.     Get in touch to learn more about E-commerce Analytics.

eCommerce Analytics: Strike First and Fast in the Battlefield of eCommerce Read More »

ad fraud

The Hidden Cost of Digital Advertising: Understanding and Defeating Ad Fraud

Blog, Digital Advertising /

Considering that ad fraud will cost marketers $ 172 billion by 2028, according to Statista Reports, tackling the fraud becomes crucial to safeguarding advertising investments.  The digital advertising space is continuously in flux, opening new avenues through which businesses can reach their target audiences. These opportunities also bear the ever-growing threat of ad fraud as one of the biggest challenges facing advertisers today.   Ad Fraud is omnipresent across Walled Gardens, direct buying platforms, affiliates, and programmatic channels. It brings a financial drain while weakening the efficiency of advertising campaigns.   AI-driven post-bid solutions must be deployed across campaigns to tackle this problem. They should be backed by ML algorithms and big data analytics. According to mFilterIt reports, average fraud is to the tune of 15-25% depending on the channel and tools help bring ROI efficiencies via automated active blacklisting.     What is Ad Fraud?  Ad fraud is any intentional activity designed to falsify digital advertising impressions, clicks, conversions, or data in general for revenues or metrics manipulation. This might be through bots, fake websites, malicious code, or other devious means. The motive behind such an action most often aims at making money off ad revenue by showing invalid traffic for ads or making the advertiser think the ad is being viewed by real people, which causes ad spend waste and inaccurate performance metrics. To prevent this, it’s helpful to understand how ad fraud works, and the tactics fraudsters rely on.  Types of Ad Fraud  It can be further divided into two key classes – General Invalid Traffic and Sophisticated Invalid Traffic. Both pose various problems for advertisers. Sophisticated fraud is identified with the funnel approach with a post-bid analysis.  General Invalid Traffic (GIVT)  This category includes simpler forms of fraud in advertising, often captured by general filtering.  Blacklisted IP – Fraudsters make use of IP addresses found as sources of invalid traffic. Ad impressions and clicks served to such blacklisted IP addresses are counted as forged impressions and clicks depleting ad budgets.   Geo Fraud – Ads are delivered outside targeted geographical areas, which means money is wasted on irrelevant audiences. This happens mainly in campaigns with tight regional targeting.  VPN and Data Center Hosting (DCH) – The traffic usually comes from VPNs or data centers to mask its origin as though it were real. It is a means of creating fake ad traffic that seems to originate from real users but is fraudulent.  Sophisticated Invalid Traffic (SIVT)  SIVT has some of the more advanced kinds of ad fraud that are trickier to spot and generally require more specialized anti-ad fraud solution.  Fake Attribution – This means fraudsters fudge conversion data to take credit for conversions or actions they had no hand in. It might mean the redirecting of real users through fraudulent paths to lay claim to an affiliate or ad revenue.  Fake Clicks – This form of click fraud involves creating an impression of organic clicks on advertisements through automated bots or scripts without the involvement of real users with intent.   Fake Devices – The fraudster uses device emulators or scripts to fake the user’s behavior of viewing and interacting with an ad, thus creating unreal impressions and interactions.  Duplicate Users – Duplicate Users are those ads reporting metrics for the same user on different devices and or platforms at different times in digital advertising and analytics.   How Ad Fraud Works  To effectively protect against ad fraud, you must understand how it works. Ad fraud isn’t committed against a perfect weak link in the digital advertising ecosystem, but rather fraudsters find ways to game the system to create invalid traffic and deliberately mislead advertisers. Common techniques include:  Bot Traffic – A bot is an automated program masquerading as human traffic. These can result in simulated clicks, views, or impressions. Bots can be very sophisticated, emulating the usage patterns of real users in such a way that simple filters cannot catch them.  Ad Stacking –This is a tactic in which multiple ads are layered on top of each other inside one ad placement, where all a user sees is the top ad. This means that the advertisers will be charged for all the ads as if they had been viewed completely, creating huge financial waste.  Pixel Stuffing – Ads are delivered in a very minute 1×1 pixel, invisible to the web users while the impression is registered in records. This is deceptive and inflates the number of impressions, feigning that ads are viewed.  Domain Spoofing – It is essentially ad fraud in which the domain of an app or website is misrepresented as that of a more trustworthy or premium one than that of their own. This is done to deceive advertisers into believing that they are purchasing ads on credible mediums, while the actual ads are being served on unreliable or fake mediums.  Low-quality Inventory – They are ad spaces that offer almost nothing beneficial to an advertiser. Such ad inventory includes placements on sites that have very little traffic, little to no genuine activity, and are intended purely to generate ad impressions or clicks deceitfully. These are called Made-for-Ad sites (MFAs).  Damaging Effects of Ad Fraud  There are various adverse effects caused by ad fraud towards advertisers and, to an extent, the entire digital advertising ecosystem. Investment Loss   The business world may lose over $100 billion to ad fraud in 2024 alone. That’s a big chunk of marketing money that could be spent on reaching out to the very real public to drive real results and it affects the ROI.  Skewed Metrics      Fraudulent activities result in bloated performance metrics, such as impressions, clicks, and conversions. Assessment of real effectiveness in campaigns and implementing changes in strategy thereby becomes hard.  Lower Reach   Spends on fraudulent ads and fake clicks mean lesser budgets to reach real and quality audiences. The overall reach and impact of ad campaigns are lower this way.   Brand Safety Concerns   It is important to protect the brand’s reputation by

The Hidden Cost of Digital Advertising: Understanding and Defeating Ad Fraud Read More »

trademark infringement

Brand Infringement: Protect Your Brand Across Digital Sphere

Blog, Brand Protection /

Since the advent of digital platforms and unmatched reach, the way brands engage with their audience has been completely transformed. As businesses expand their digital footprints, they are exposed to new challenges and risks that come under the umbrella term brand infringement.    Infringement occurs not just on names of the brand but also on social media handles, site domains, and ad campaigns. According to recent reports the global losses due to brand infringement are expected to reach over $4.5 trillion in 2024, IP theft globally is estimated to cost companies more than $1.2 trillion (source – Intellectual Property Helpdesk).   The numbers clearly show the alarming situation, and it is therefore important for every business to protect their brand and digital assets from impersonation by using AI-ML-driven identification tools & automated takedown management software.   Ultimately, ‘Brand Safety is the Brand’s Responsibility’ to protect the brand from impersonation and customers from fraudsters’ fraudulent activities to ensure the business’s ongoing success.   Let’s delve into the understanding of brand infringement or trademark infringement, its types, and takedowns to prevent it.    What is brand Infringement?  Brand Infringement or trademark infringement occurs when an unauthorized party uses a brand’s name, logo, or elements of its identification without permission, leading to potential confusion among consumers. Customer trust can be undermined, and this misuse damages the brand’s reputation.  For instance, a trademark is a term, symbol, or expression used by a company to differentiate its product from competitors. In the context of business services, a service mark is equivalent to a trademark.   Types of Brand Infringement?      Fake Websites & Helpline Numbers- They mimic legitimate businesses to deceive customers. They are tricked into taking away sensitive information, it is mostly done under popular bank names.     Similar Domain/ Typosqautting – This is done by creating nearly identical web addresses just like the brand’s official domain but with slight variations.    IP infringement- It occurs when someone uses a brand’s trademarks like its logos, or protected content without its permission. Often operated on fake websites to sell these goods and products. Phishing Websites – This is a form of cyberattack that gathers sensitive information like login credentials, bank account numbers, or other financial information.    Deep & Dark Web Monitoring– It involves scanning the hidden part of the internet where illegal activities occur including stealing of brands’ data and misusing them. Fake Brand Communication like Emails- A consumer may receive emails that look like from some famous brands. These fraudulent emails appear to be genuine, but they are sent by scammers.   Fake Social Media Handles and Posts – For example, a counterfeit fashion brand may create an online post to sell fake products using images and logos from a luxury brand, this is how a brand’s intellectual property is misused.    Counterfeit Products – To imitate or create unauthorized replicas of genuine products can deceive consumers into believing they are purchasing a legitimate product. Fake Promotion & Offers – Fake posts and advertisements on discount deals or offers that trick consumers, making them believe that they are getting a real discount deal, and often get trapped and lose their money.  How to protect the brand from the risk of trademark Infringement?   The brands must use comprehensive monitoring detection mechanisms to deal with infringement across the web, social media, and other media platforms. mFilterIt gives a comprehensive solution suited to the above-mentioned types of brand infringement.  Three Pillar Approach   Identification – By scanning various platforms such as websites, social media, YouTube, and IM apps to identify potential brand infringements and trademark violations.   Classification – Identifies and shares potential threats of trademark violation using AI and ML techniques with clients to review for their confirmation.  Action – The URLs of websites, YouTube channels, and IM handles found infringed are added to a blacklist for further actions by the clients.   Platform Coverage for Brand Infringement Detection    Figure 1.0   In the above-mentioned figure 1.0 we can check your performance across these platforms.   Infringement Protection via Takedowns   Inhouse Takedown – Without relying on any formal legal complaints documentation from any law enforcement agencies.  Network collaborations with Internet Service Companies – Collaboration with various individuals to protect brands on various marketplaces websites, domains, cyberlockers, video platforms, mobile apps, and search engines.   Continuous Monitoring – Across the various platforms to combat infringement and safeguard the brand’s digital integrity.   Let’s understand this with a use case of the banking sector   A major Indian bank wanted to protect its online presence to prevent fraud from happening to its customers. It was nearly impossible for them to monitor everything manually.  Bank needed a solution that could easily scale up with their needs and monitoring to protect their online presence.    mFilterIt Brand Protection Solution uses sophisticated technology of open-source intelligence to scan the internet for monitoring potential threats. Through machine learning (ML) a large amount of data is collected such as images, videos, and texts, and there is a confidence score to determine how likely these were fraudulent.   The total number of cases – 2,37,565 (Impact period to Jun)   Successful Takedowns- 231,018 of these threats.   The action was taken across 10 different online platforms on average it took 48 hours to resolve a case and remove the threat. 95% rate of successful takedowns with precision.  Conclusion   As brands navigate the complexities of the digital world, brand protection is no longer optional, it is essential. With social media, anything can be accessed with just a few clicks, be it gaining a reputation or losing it.   Our comprehensive solution combines trademark protection and concerns related to its violation to provide your brand with all-encompassing online protection. By leveraging AI-ML comprehensive monitoring brands can empower themselves to survive in the world of fraudsters and imitators.  Get in touch to learn more about the Brand Infringement.

Brand Infringement: Protect Your Brand Across Digital Sphere Read More »

sentiment analysis to decode customer feedback across digital marketplaces in uae

Sentiment Analysis to Decode Customer Feedback Across Digital Marketplaces in UAE

Blog, Digital Shelf Analytics /

The UAE e-commerce is expected to reach $17 billion by 2025. Further, by 2027, it is expected that global retail e-commerce sales will cross $8 trillion indicating a 39% growth, according to a Statista Report. In such a growing market, sentiment analysis and customer feedback are essential for business success. Unlike brick and mortar where customer feedback is easier to take, in an ecommerce platform customer satisfaction is more difficult to assess. Moreover, it helps brands sell more on e-commerce platforms if it has a good volume of reviews. Building a good volume of reviews and thereby analyzing them is therefore the need of the hour.  According to the Global Statshot Report, 32.5% of customers make online purchase decisions based on customer reviews.  There is a need for every e-commerce player to have access to business intelligence in real-time and in actionable form to ensure the success benchmarks are achieved. Business intelligence needs to be granular to the last detail and scalable by geographies and platforms.     Concept of Sentiment Analysis   In online shopping, customers give reviews and ratings on different social media platforms. Customer sentiment analytic tool analyzes these to discern positive, negative, or neutral emotions. Does the customer express positive, negative, or neutral emotions?   This analysis gives insights that help in the growth of the businesses and find out what makes a product more successful and what creates dissatisfaction among the consumers, which helps to improve customer experience, and brand image, and address negative sentiments before it spread.  Sentiment Analysis Metrics that Brands Must Track:   Monitor Rating & Reviews  Customer Feedback Trend Analysis   Product sentiment tracking across categories, sub-categories, product variants, brands, and sub-brands vis-à-vis competition  Identify Q&A Sentiment themes, with real-time actionable Insights and analytics  Keywords graphically highlighted with word cloud  Identify sentiment themes that are working, gaps, or lags in terms of pricing, quality, packaging, flavor, delivery, etc.    Heat map to reflect sentiment intensity  Why Sentiment Analysis Is Important in E-commerce   Enhanced Service Outcomes and Customer Experience It brings direct insight into real-time perceptions of customers about the brand, its services, and interaction. It not only reveals the surface level of feedback but also gives an idea about the customer’s feelings and sentiments upon interaction. They can alter service strategies, product experiences, and more based on how customers react.   Comprehensive View of Customer Sentiments It gives an overview of a company’s snapshot view of total customer sentiment. It does not just analyze whether the feedback is positive, negative, or neutral, but aggregates sentiments from multiple sources to give a whole view. Whatever the customer feedback source, the sentiment analysis tools will let you decode the sentiment behind each word or comment.   Understand the Customer’s Mood, Tone, and Attitude With sentiment analysis, businesses manage to perceive customers’ moods, tone of voice, and attitude. That insight is rather important for personalized and empathetic support. It will help an organization with the right kind of emotions displayed by customers for their needs and expectations. This also helps a business organization perceive how customers will feel while interacting with your brand.    Enhance Customer Satisfaction with Data-driven Reactions Sentiment analysis will allow the business to understand where to improve based on customers’ feelings and act based on data to offer customer satisfaction. It acts like a compass for direction, guiding businesses on how to plan, focus their efforts, and appropriate resources to areas where they are most needed.   Identify Customer Pain Points Sentiment analysis gives companies insight into customer’s pain points and what usually irks them. It analyzes feedback and sentiment about aspects, features, touchpoints, or journey stages of a product or service. Companies can find out where improvements should be made. This way, they can take up all the concerns and make necessary improvements to enhance customer experiences.   Knowing the emotions underlying customer feedback lets you identify, very specifically, where things may be going awry-be it a glitch in the system, a baffling process, or even a feature that’s more frustrating than useful.    Plan Market Positioning with Informed Insights Knowing exactly where to place your product in the market holds the key to success. Making an informed decision, however, isn’t easy, and a misjudgment may sink your business. Fortunately, constant monitoring of customers’ sentiments may provide you with just what you need. You will get a better understanding of the features that customers would like to see in your products.   Sentiment Analysis in Improving Customer Experience   There are also many instances when customer sentiment analysis helps enrich the overall customer experience of organizations through tools and techniques.  Proactive Resolution of Issues Sentiment analysis is a potent tool for spotting negative sentiments in customer feedback. By sentiment analysis, a business would be well prepared to proactively address issues, resolve complaints, and avoid any potential escalations before this gets bigger and affects a large chunk of the customer base.   Once any negative sentiment is spotted, immediate and remedial action can be taken by a business to restore the situation and provide satisfaction to resolve it. This proactive approach helps in preventing further dissatisfaction among the customers and builds trust and loyalty.   Continuous Product & Service Improvement They help in identifying areas to improve, insights to develop products, and enhancements based on the sentiments of the customers.   Sentiment analysis gives ways through which organizations make continuous improvements. Businesses can review their customers’ feedback and find common themes and trends emerging from their sentiment analysis. Themes may be related to product features, customer surveys and interactions regarding the service, or overall customer satisfaction.   Efficient Resource Allocation Effective allocation of resources can be planned by prioritizing actions based on sentiments. Critical issues that require the most resources must be focused on.   Resource allocation is also an important business management process. Sentiment analysis plays a major role in this matter. It prioritizes feedback, according to urgency and importance, for businesses to optimize resource allocation. This way, they can go ahead and perform an action based on priority through customer sentiments.   Customer Journey Optimization Organizations

Sentiment Analysis to Decode Customer Feedback Across Digital Marketplaces in UAE Read More »

Programmatic ad

Programmatic Ad fraud: The bane of the Branding Campaigns

Blog, Brand Safety & Protection /

The global programmatic advertising market size is expected to grow at a CAGR of 22.8% from 2024 to 2030. Programmatic advertising encompasses a wide range of digital channels, from walled gardens like Google and Facebook to connected television (CTV) and OTT. This variety of channels’ capacity increased the reach of advertisements to even broader groups of audiences.    However, this wider scope of innovation has also opened the door to significant fraud, with programmatic ad fraud becoming a growing concern for marketers worldwide. With the programmatically run advertisements at $546billion in 2023 according to a Statista report, the volume of ad fraud and low-quality impressions stand at 15-20% according to mFilterIt reports.   To make their digital campaigns a success advertisers need AI-ML driven ad fraud analytics to improve ROAS (return on ad spends) and reduce budget wastages.  Are reputed ad platforms, trade desks and walled gardens also affected by programmatic ad fraud?   Programmatic ad fraud broadly refers to the malicious practice of manipulating online ad campaigns through automated software, to generate revenue.   Nowadays new ad platforms, trade desks and reputable walled gardens are coming into the limelight with advertisers having a positive perspective and confidence about them. This confidence stems from the fact that they have positioned themselves as platforms having a clean inventory with superior quality traffic making a differentiated mark from traditional affiliates.   As ad fraud analytics uncovers, it is not the case. These platforms are bigger black boxes than affiliates, and the fraud rates are similar with new tactics uncovering every day. Advertisers need to place a check on these platforms through independent third-party validation tools which can provide a full-funnel analysis.   New tactics that are coming up in the programmatic ad ecosystem are:   Frequency Cap Breaches – Frequency capping is when a brand sets a limit on the number of times its advertisement is displayed to a given user within a specific time frame. Breaching this leads to oversaturation, which means the ads are shown to the same users instead of reaching a broader audience. This not only wastes ad spending but also lowers the reach of the ads and the campaign’s overall efficacy, which is in violation of the objective of the branding campaign. mFilterIt has identified approx. 25% of f-cap violations depending on the campaign.  Inaccurate OTT Viewability Scoring – Viewability metrics are crucial for determining if an ad has been viewed by a human or a bot. Uncertain data from inaccurate metrics might make it challenging for advertisers to assess the success of their efforts. Without accurate viewability, brands may end up paying for impressions that their intended audience never saw.    Low-Quality Impressions –These impressions come from content that mainly attracts visitors who are not genuinely interested in the brand or product. It comes from sites specially designed to generate clicks from clickbait sites resulting in limited reach and exposure. Such sites have poor conversion rates causing brands to waste budget and inefficient ad placements.  These are mostly generated by Made-For Ad Sites (MFAs). The ANA report on ad fraud states that MFA websites represent 21% of impressions and 15 % of ad spend overall.   How do these affect programmatic advertising?   According to ANA, the current $88 billion open web programmatic media ecosystem is rifted with waste.  In addition to revenue losses, there are other ways ad fraud can harm brands. These include:   Damage to the brand reputation as ad fraud can cause advertisements to appear on unsuitable websites and consumers may associate the brand with such negative connotation. Inadequate campaign performance ad fraud distorts data and analytics, producing false campaign performance benchmarks. As a result, decisions are made using erroneous data, which leads to ineffective marketing strategies.    Diminished customer trust potential customer numbers can be lost for brands in the future as well.    Reduced campaign ROI significantly due to fraudulent activities, as a portion of the ad spend was diverted on non-genuine interactions.  mFilterIt Solutions to combat these threats   The simplest and most efficient way to protect the interest of your brand is to use ad fraud detection tool to combat the new tactics of fraud in programmatic ad ecosystem:   In the case of F-Cap Violation using a creative serving hub, that sets the views per user per day to a certain limit with real-time monitoring to ensure no user sees the ad more than that set limit, helps to maximize reach and engagement.    Further, the viewability metrics can be checked by implementing a viewability attention score based on how much attention users give to ads. This can provide a more apt picture of whether the ads are truly seen and engaged by real users or not.    Low-quality impressions through Made-for-Ad Sites can be avoided by detecting and blacklisting these MFA sites. Suppose an ad network red flags a site as MFA, the specialized algorithms will automatically blacklist this site from the ad placement list.    Final thought   Programmatic ad has offered brands the chance to reach audiences with scalability but also opened doors to sophisticated forms of ad fraud that undermine their efforts to outshine the digital ad market. But at the same time, advanced AI-ML solution provider mFilterIt empowers the brands to fight this complex battle proactively.   

Programmatic Ad fraud: The bane of the Branding Campaigns Read More »

Scroll to Top