mFilterIt Experts

Decoding complex digital challenges like ad fraud, brand safety, brand protection, and ecommerce intelligence for brands to help them advertise fearlessly.

Bot Detection

What Should Marketers Look for in a Bot Protection Tool?

In today’s digital marketing landscape, bots impacting your campaigns, website analytics, and overall performance is becoming an enormous issue with all the organizations running any kind of advertising campaign. To put a stop on the ad fraud that is caused by bots, having bot detection tools is vital.  After all, how can you put a stop to bots if you can’t detect.   Unfortunately, many firms struggle to detect bot traffic, and the methods they employ are not all created equal. Choosing the right bot detection tool is essential for safeguarding your marketing efforts. Here’s a comprehensive guide to help you select the best tool for your needs. What Is Invalid Traffic and How Does It Relate to Bots?  Bot fraud in digital advertising generally falls in the category of invalid traffic by the marketers no matter good or bad since the bots are not the target audience and cannot be converted into a protentional lead.   Types of Invalid Traffic:    General Invalid Traffic (GIVT) : It is one of the simplest bots that can be detected easily, and a lot of good bots traffic comes under GIVT as they are not meant to fool the bot detection tool. But some fraudsters may also deploy GIVT as they are easy to make and work against some of their targets.   Sophisticated Invalid Traffic (SIVT) :  SIVT detection is the bots that one should look out for as these are more capable and are often designed to target to bypass cybersecurity and ad fraud prevention tool. For Example – sophisticated bots might imitate how a human would use a website so it would be difficult to identify between a human and bot. SIVT is common in ad fraud schemes. How Bots Impact Your Marketing Campaigns  Bots can have a negative impact on your digital marketing campaigns in several ways:  Wasted ad spend: Bots can boost your impressions and clicks, resulting in ad spend burn. For example, if you bid on a brand term that costs $1 per click and a click bots on your ad 1000 times, you would have wasted $1000.  Inaccurate reporting: These bots can alter your reporting data, making it nearly impossible to track the actual performance of your campaigns. For Example, if a bot is boosting your impressions by 50%, your CTR will appear to be much higher than it is.   Damage to your brand: So, if your brands are revealed to internet bots, it might damage your brand reputation. For example, if a bot clicks on your ad for a product the customer is not interested in, the user will consider your ad spam.  How to Detect Bots?  Bots often use IP addresses that are associated with known botnets. Here some of the most common methods include  IP address analysis: Bots often use IP addresses that are associated with known botnets so by analyzing the traffic by these IP addresses you can easily identify the bot traffic. Behavioral analysis: Bots frequently engage in unusual behavior, such as rapidly clicking on adverts or viewing several pages in a short amount of time. So, by examining the behavior of your traffic, you may detect bot traffic. Traditional Bot detection tools: They can only detect basic bot patterns and don’t have the capability to identify sophisticated bot patterns like click spamming or lead punching.  Limitations in traditional bot detection tools However, there are some limitations of using traditional bot detection tools.  Over time, bot patterns have become increasingly sophisticated, enabling them to mimic human behavior and carry out complex tasks such as completing sign-up forms or generating leads. Traditional bot detection tools often fall short in identifying these advanced bot activities due to their limited capabilities. Some key limitations include:  Only Impression-level detection: Many tools rely on impression-level analysis, which may not be sufficient to identify advanced bots. This approach often overlooks nuanced behaviors that occur across multiple impressions or sessions.  Limited to Pre-bid monitoring: Many fraud detectors focus on pre-bid detection because it is easier to conduct checks because they only need to consider two factors: geolocation and browser, and the success rate is only 2%.   Key Features to Look for in a Bot Detection Tool  Utilization of the Latest Technology: One of the key features to look out for in a bot detection tool is whether it is using the latest technology to detect ad fraud. When looking for a bot detection tool, evaluate their technology. Many traditional ad fraud solution depend on outdated methods like 1×1 pixel tracking, offering limited visibility. In contrast, to identify sophisticated bot patterns the bot detection must use the latest technology. We use cutting-edge technologies like VAST and JavaScript to assess over 70 parameters of bot traffic for effective identification.  Deeper and Comprehensive Checks: The bot detection tool will be able to provide deeper insights with a post-bid analysis. With a comprehensive full-funnel check the success rates are boosted by 30%-40%. This approach is reliable and eliminates blind spots in detecting bot activity or ad fraud.  Omnichannel Coverage: An advanced ad validation solution provides robust protection across multiple platforms, including programmatic advertising, Connected TV (CTV), Over-The-Top (OTT) platforms, and Made for Advertising (MFA) websites. This comprehensive coverage effectively addresses all potential avenues for fraudulent activities.  Real-Time Insights: The platform detects and assesses fraudulent behavior in real-time, allowing advertisers to take proactive measures to minimize losses and protect their advertising budget.  100% Transparency: A critical feature of an advanced fraud detection tool is source-level transparency, this provision of detailed, source-level data enables advertisers to trace fraudulent activities back to their origins, ensuring accountability and enabling more targeted counter measures.  How mFilterIt help to detect sophisticated bots?   mFilterIt is known for its effective bot detection and ad fraud prevention capabilities. Ad fraud detection (Valid8) by mFilterIt offers real-time detection, granular insights, and comprehensive protection across the entire campaign lifecycle. By utilizing machine learning, behavioral, and heuristic checks, it ensures the detection of advanced-level bots leading to fraud-free campaigns, making it ideal for advertisers seeking

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tracking

Pixel Tracking Guide: How to Track Conversions Easily

Tracking conversions is essential for measuring the effectiveness of your marketing efforts, and one of the most reliable ways to do this is through a conversion pixel. A conversion pixel is a small piece of code embedded in your website or landing pages, which tracks specific actions users take, like making a purchase or subscribing to a newsletter. This helps you evaluate your ads’ performance and refine future campaigns. How to track conversions using a pixel: 1. Install the Pixel: The first step is setting up a pixel on the platform you’re using, such as Meta Ads, Google Ads or mFilterIt Visit Pixel. These platforms typically provide easy-to-follow instructions for adding the pixel to your website. You’ll either add the pixel code directly to your site’s header or use a tag manager to simplify the process. 2. Define Your Conversion Goals: After adding the pixel, you need to define what actions you want to track as conversions. This could include activities like making a purchase, submitting a lead form, or completing a registration. Most platforms let you set up multiple conversion events to capture various types of user actions. 3. Test the Pixel: Once the pixel is installed, it’s important to test it to ensure it’s working correctly. Tools offered by platforms like Meta allow you to check if the pixel is firing as expected. If you find any problems, double-check your website’s code or try reinstalling the pixel. 4. Analyze and Optimize: When users complete the defined conversion actions, the pixel sends the data back to the platform, giving you valuable insights into your conversion rates. Use this information to see which ads or traffic sources are performing best and adjust your campaigns to optimize results. Tracking conversions with a pixel is a powerful way to evaluate return on investment (ROI), refine targeting strategies, and ultimately enhance the success of your marketing campaigns. Connect with us, to start your conversion tracking.

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Brand Bidding

Protection from Brand Bidding with AI and Automations for Brands and Ad Networks

Competitors or affiliates may bid on your brand keywords, potentially driving up costs and diluting your brand’s presence. A comprehensive affiliate monitoring tool needs to be in place to safeguard your affiliate marketing spend and protect your brand reputation.  Identify affiliate and competition bidding on your brand keywords along with whitespaces across locations for own and competition keywords.    Brand bidding fraud costs approx. $1.3 billion each year as competitors bid on branded keywords. Over 60% of brand terms are targeted by competitors, inflating cost-per-click (CPC) by up to 30% and reducing conversion rates by 5-10%. This not only drives up advertising costs but also dilutes brand recognition, as 50% of users may click on a competitor’s ad when searching for a brand name. This leads to confusion and lost customers.   Businesses must actively monitor and optimize their paid search campaigns while implementing robust brand safety solutions to mitigate these risks.  What is Brand Bidding? Brand bidding refers to a practice that falls under paid search marketing. It’s a digital marketing strategy where brands bid on their own brand keywords in search engine advertising platforms like Google Ads and when someone searches for your brand name, your company’s sponsored listing is more likely to appear at the top of the search results page.   But this turns into a brand reputation threat and leads when aggressive affiliate bids, potentially aiming to capture traffic and drive sales through affiliate programs or competition bids on your brand keywords.    Why is affiliate monitoring needed for Advertisers? Affiliate monitoring ensures the integrity of campaigns, protects brand reputation, and optimizes performance.   Concerns in Brand Bidding:   Campaign Integrity: Monitoring affiliate activities ensures that campaigns are running as intended. It helps to identify if affiliates are engaging in practices like brand bidding, misleading advertising, or promoting the brand inappropriately.  Protecting Brand Reputation: When affiliates are bidding on brand-specific keywords (e.g., your company’s name or a competitor’s), it can confuse customers or misdirect them to other sites. Without monitoring, there’s a risk that your brand reputation could be damaged if affiliates don’t align with your brand values or make misleading claims.  Optimizing Performance: By closely tracking affiliate performance, advertisers can identify high-performing affiliates and cut out low-performing ones. This ensures that advertising spend is allocated effectively, improving overall return on investment (ROI).  Organic poaching: A major concern that brands should be careful about. It occurs when affiliates or competitors bid on a brand’s keywords, capturing traffic that would have naturally come to the brand’s website. This misappropriates organic leads and increases costs as the brand must pay commissions to affiliates for traffic that would have come organically.  Ensures unauthorized affiliates are not bidding on brand keywords or misdirecting customers. Prevent unnecessary commissions and preserve your organic search efforts.  Prevent affiliates from hijacking brand visibility, ensuring the brand stays front and center for potential customers without competitors benefiting from organic traffic.  Stopping organic poaching ensures that their customers are consistently directed to the brand, which enhances trust and customer loyalty.  Case Study 1: Brand Bidding for a Popular Shoe Brand Problem statement: Brand was facing challenges in ensuring effectiveness of keyword the brand bidding on across multiple geographies and wants to identify competitor bidding on their brand keyword.   mFilterIt Solution: mFilterIt analysis and insights into the effectiveness of brand bidding, we conducted a comprehensive analysis of a well-known shoe brand across major Indian cities.   We meticulously monitored 35 keywords related to the brand, including brand keyword variations across 35 cities. This allowed us to understand the search queries users were employing to find the brand.   The brand garnered a significant search volume across time slots. This indicated strong interest in and demand for the brand.   A substantial 50% of the total searches were Google Ads for the brand’s keywords. This demonstrated the competitive landscape and the efforts of various entities to capture search traffic.   We identified 28% were competitors count which were actively bidding on the brand’s keywords. This highlighted the intense competition for visibility and market share.    22% of the total came from affiliates and coupon websites who were also bidding on the bidding keywords. This revealed that affiliates were also using brand keywords and running ads.   mFilterIt Impact Here are some key observation and Findings:   Organic Poaching by aggressive Affiliate Bidding: Affiliates & coupon websites were particularly active in bidding on brand keywords, potentially aiming to capture traffic and drive sales. They were capturing organic users. This is called organic poaching. The brand was having to pay commissions to affiliates where the customer would have come organically.   Competition on Brand Keywords: Competitors were actively bidding on the brand’s keywords, which meant that competition keyword strategies needed to be built within the marketing approach.  AI based Optimization in Brand Bidding with mFilterIt LOCOKS LOCOKS (Location & Campaign Optimization Keyword Strategy) with AI-ML powered automation of brand bidding process can make identifying and bidding on brand keyword more efficient and controlled. It also prevents overspending on keyword bidding and can schedule when to start or stop the bidding and limit the budget spent for a particular time slot.   Geo Based Tracking: Our tracker runs in different cities and analyses the different sources of traffic related to a set of keywords coming from various sources  Intelligent Reporting: Identify when competitors invest more or less and on which keyword. Discover key periods when keyword competition increases or decreases and take action on the findings   Time Based Tracking: Tracks on-the-basis of day – parting, hourly tracking, ad scheduling strategies of competitors and affiliates   Seasonal Sales/ Discounts: As most frauds occur during the flash sales such as Black Friday, Prime day etc., we track the user journey to check the source.   Case Study 2: mFilterIt LOCOKS Solution for Optimizing Competition Keywords and Brand Visibility Problem Statement: An advertiser was struggling with white spaces in their campaign where both competition keywords and brand keywords were not targeted. They wanted to identify such whitespaces and explore new opportunities. Here with take up the sample of 8

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Programmatic Advertising

Ai in Programmatic Advertising Fraud Detection to Deliver Performance and Sustainability

The rise of programmatic advertising has shifted the focus towards accuracy and automation. It surged from $9.75 billion in 2023 to $12.46 billion in 2024, an annual growth rate of 27.8% and is expected to continue expanding, reaching $28.12 billion by 2028 at a compound annual growth rate (CAGR) of 22.6%. However, with AI coming into the picture, performance programmatic platforms are prone to ad fraud even more. The need for optimization of programmatic media buying with comprehensive ad fraud solution  across the advertising funnel is the necessity to yield results.   More and more advertisers are pushing for a stronger and harder success KPIs in programmatic advertising. The shift from visibility only to performance-first is underway. With new and upcoming programmatic platforms selling inventory on impressions, it is today evident that impression fraud is 10-15% of campaign spends in the MENA region, as per mFilterIt reports. There is a ROI uplift of 7-10% when advertisers identify and block for Made-For-Ad sites and Ad Frequency cap violations.  For advertisers, an ad traffic validation tool is the need of the hour to weed out fraud, optimise programmatic traffic and improve the hard KPIs of their campaigns. Also, programmatic platforms & ad networks have started providing ‘Certificate of Verification’ to advertisers to ensure their ad inventories are validated.    Let’s dig deeper into the explore how programmatic ad fraud detection can help elevate performance of ad campaigns and what are the key challenges.   Why Programmatic Ad fraud prevention? Protect your brand with programmatic ad fraud prevention. Ensuring the invalid traffic is blocked from malicious sources not only safeguards advertising budget but also protect brand reputation.   Safeguard Your Programmatic Ad Campaigns from Fraud-Explore Our Expert Solutions. Here’s how mFilterIt guides with trust and transparency in programmatic advertising:  Impression fraud Impression Fraud analysis is better at the post-bid stage than pre-bid, measuring performance beyond viewability metrics. In pre-bid analysis, i.e. before the ad is served, fraud can be identified based on only two parameters, IP and User Agents. Also, the time for analysis is limited to 10 milliseconds. This results in a meager 2% fraud identification.      This is where a post-bid analysis trumps a pre-bid impression validation. Now that we have several more parameters fraud detection is done on deterministic and heuristic measures as well. This results in the detection of higher invalid impressions of 15-20%.  This results in improved ROI on Ad spending. Post-bid impression analysis is a more beneficial method for detecting ad fraud.  Made for Ad sites Advertisers spend an average of 15% of their programmatic budget on MFA sites, but some may spend as much as 42%. While 35% of programmatic spending is wasted on low-value environments like MFA sites, according to a recent study by ANA (Association of National Advertisers).  By focusing on robust ad fraud detection advertisers can combat the various forms of fraud that undermine their campaigns across digital advertising platforms. Prioritizing impression validation is essential for maximizing return on investment and maintaining trust in the advertising ecosystem.    MFA Sites not only drain budgets but also pose a challenge to a brand’s safety. Limited reach and exposure, no real user engagement misleading clicks,  click fraud, artificially inflated metrics, poor conversion rates, low-quality/intent traffic and brand un-safe content tarnished brand image and lead to budget drainage.   mFilterIt identify ad placement on MFA sites with   Deep Content Analytics: A multi-faceted analysis using NLP & image & video analysis to identify brand unsafe content. Advanced AI-ML Sophisticated Algos: AI –ML driven analytics for extraction of meaningful insights, patterns, and information.  Regional & Contextual Understanding: Local language, cultural nuances and domestic norms lead to overall risk assessments. Extensive MFA Repository A collection of websites & metric measurement is gathered with regular updates & feedback loop  Fig. 1: The site has multiple ad-stacked ads with high refresh rates. It’s also brand-unsafe promoting gambling.   Ad Frequency Cap Violations The most common and often neglected issue is Frequency Capping  (F-Cap) violations along with bots spamming impressions for burning media budget. Brands need to be vigilant and identify F-cap violations to make sure their ad reaches the broader and relevant audience and is not seen by similar sets multiple times to generate impressions leading to ad fatigue, not conversions.  A quick succession of impressions generated from the same google advertising ID. Distribution for a genuine user could be distributed throughout the day.  These impressions were not only coming so excessively but were also being shown quickly. Multiple Impressions in a Short Period.  A single GAID generates multiple impressions quickly.  Impression Injection from subnets which reflect that the usage of device farm to fire multiple impressions. Subnets divide a larger network into smaller, more manageable sections. IP Repetition with Same IP, different users. It reflects high chances of fake impressions being injected with different GAIDs.  Same IP, Different Impressions. This issue is not limited to IP repetition, but it extends further with the same IP generating multiple unique GAIDs and different impressions.    Viewability & Attention metrics Instead of focusing on a single data signal, check on attention metrics along with viewability encompassing a range of data points. These are processed by a machine-learning model to estimate the probability that a specific media environment and ad creative will capture the attention of a hypothetical audience member.  However, Viewability only itself does not help in taking decisions when it comes to effectiveness or attention. Multiple factors need to be measured, monitored and acted upon swiftly. The Viewability and Attention Model encompasses several key factors that determine the effectiveness of an ad in capturing audience attention. Viewability refers to the percentage of an ad that is actually visible to users and the duration it remains in view.   It must also include:  Viewability Metrices % of ad viewability and number of second viewed based on IAB standards   Display ads should be at least 50% of the ad’s pixels are visible in the browser window for at least one second   Video ads must be at least 50% of the ad unit

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Mobile Ad Fraud

Mobile Ad Fraud: Challenges for Advertisers in the USA

As mobile app ads have become more pervasive, advertisers are facing growing concerns around app installation fraud and the complexity of detecting fraudulent activity, especially in markets like the USA, where the stakes are high. The U.S. market mobile ad fraud, with estimated losses of around $1.2 billion. The focus is on safeguarding the organic traffic stolen, preventing APK fraud and referral fraud along with full-stack fraud prevention that can help optimize ad campaigns and build trust and transparency across the digital advertising ecosystem.  Let’s dive deeper the unveil the various aspects of mobile ad fraud and how to combat them.  Challenges of Mobile Ad Fraud in the USA The mobile app ecosystem is growing and evolving and expanding across the global especially in the BFSI industries, the rise of Fintech apps and lending apps has also raised the stake of fraud prevention in app ecosystem.  Most app fraud prevention apps don’t cover the sophisticated and dynamic nature of ad frauds that lead to fake installs and thereby low return on investment.   Here are some of the major challenges:   Organic hijacking via Click Spam: Theft of organic traffic is one of the biggest hurdles in mobile app advertising. Deceptive techniques to mimic legitimate installs and generate traffic that appears organic, resulting in inflated numbers that distort performance metrics. It leads to skewed insights for advertisers who rely on authentic user data and affects the return on investment (ROI).    Click Fraud: Validating traffic with comprehensive click fraud prevention is a must for advertisers to excel in the competitive landscape and ensure that budget is spent on valid clicks only. The deterministic, heuristic and behavioral checks with google approved mFilterIt click tracker can help combat fraud like no other.   APK installs: Fraudulent mobile app ads are created to mislead users into downloading fake apps or counterfeit APK files. This compromises devices or artificially boosts install metrics. Detecting APK fraud is essential for ensuring that advertising budget is spent effectively and that users are protected from malicious content and bring true performance to their campaigns.  Referral fraud: Fake referrals or incentivized clicks driving traffic inflate numbers that affect campaign efficiency. Fraudulent end users use the coupons codes multiple times either by cloning the app or by using VPN/Proxies etc. creating multiple device environments in the same device.  By exploiting referral programs, fraudsters generate fake installs and impressions, tricking advertisers into paying for traffic that doesn’t convert. Implementing mobile ad fraud detection systems can protect advertisers who rely on mobile app ads to drive real user engagement.  How can advertisers combat mobile ad fraud? Make Payout for validated traffic and work with Trusted Publishers Validate traffic and pay for only genuine engagement. Identify the publishers the bring in influx of invalid or fraudulent traffic to your campaign and work with only trusted published to protect integrity of your ad campaign.   Encourage Good practice by Ad Networks to give a ‘Certificate of Validity’ Ad traffic validation could also support ad networks to authenticate and validate based on the performance to safeguard the interest of advertiser and builds clean and transparent digital advertising ecosystem.   Ask MMPs the right questions Do not trust the MMPs blindly, a third-party validation removes the suspicion around traffic validation as fraudsters bypass MMP fraud detection. Mobile Measurement Partners (MMPs) have become pivotal for marketers and businesses, especially in tracking app installs, user engagement, and campaign performance. However, recent developments highlight the limitations of solely depending on MMPs for ad fraud detection.  How deploying independent Third-Party validators build transparency? The most effective way for advertisers to combat mobile ad fraud is by using independent third-party validators—an unbiased, external layer of protection. Validate the fake traffic and interactions associated with an ad campaign. mFilterIt offers a comprehensive ad fraud detection system powered by advanced artificial intelligence and machine learning algorithms. It can identify suspicious patterns with deterministic, heuristic, and behavioral checks.   It enables advertisers to identify and block fraudulent activities before they drain their budgets and ensure that only genuine traffic is counted, reducing the risk of fraudulent interactions, like click fraud, bots, and fake impressions. As an essential step in the fight against ad fraud and invalid traffic, it is important to validate before advertisers, ad networks and agencies collaborate with publishers.  Monitor and verify each install or click with Mobile ad fraud detection solutions. It helps in identifying APK fraud, referral fraud, and protects organic traffic from being stolen. Proactive fraud prevention using data-driven strategies preserves the integrity of mobile advertising campaigns and ensures it delivers true value.  Impression Integrity: Start with checking up impression integrity with Impressions validation, ad visibility and post-bid validation.   Click Integrity: Weed out invalid or fraudulent traffic and bots with click fraud prevention.   Install Validation: Check if the installs are by genuine customers or bots also follows up tracking soft KPIs and events triggered such as registration, logins or signups.   Re-engagement & Post-back Blocking: Hard KPIs such purchases, deposits, and transactions also need to be validated for efficient re-engagement and post-back blocking.  Advertisers and developers need to adopt robust ad fraud detection systems with advanced algorithms and machine learning tools to identify suspicious patterns and block fraudulent activities. As an essential step in the fight against fraud, validate before collaborating. Trusted ad networks and ensured transparency in mobile ad transactions.  Here are some benefits of proactive mobile app fraud prevention:  Weed out fraud to improve ad campaign efficiencies  Enabling brands to take better-quality business decisions  Show funnel visibility & transparency basis performance  Optimizing the publisher ecosystem  Case Study: How FinTech App identified high volume of Fake Installs Problem Statement Fake app installs were significantly inflating the user acquisition costs and reducing the efficiency of marketing campaigns. They needed to identify sources of such fake installs and block them. High volume of fake install adversely affects the overall return on investment (ROI).   The Challenges Inability to accurately measure genuine user engagement and conversion rates. Due to a lack

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Stock Availability

Is lack of Accurate Stock Availability Metrics Impacting your Ecommerce Revenue?

Product availability is the key issue for brands looking to expand their presence across the fast-paced E-Commerce landscape. With the expansion of new categories that cater to shoppers’ last-minute needs, quick commerce platforms are expanding their horizons. There is a need to measure and monitor stock availability performance across platforms and geographies. Customer loyalty is affected by availability issues as the industry figures suggest that 20-30% of customers may switch to competitors permanently after encountering product unavailability. Also, Tier 2 and 3 cities may face upto 20% more disruptions due to logistical challenges caused by lack of accurate and high-quality availability metrics.  Let’s dive deeper and assess the core issues that brands face on ecommerce and quick commerce platforms. It is important that digital first customer-facing product-oriented brands today understand that reducing out-of-stock occurrences can lead to a lift of revenue by 5-8% with real-time business intelligence and insights.   Are you getting the right numbers on e-commerce and quick commerce platforms?   Every quick commerce and e-commerce platform has its own set of challenges, but getting out-of-stock poses a major challenge for brands looking to strike hard at the moment customers is looking for them. This not only puts them out of the race but also lose a loyal customer looking for your brand.   What should brands do to maintain stock availability? Keep track of every SKUs in real-time, drill deeper to find out which product is out-of-stock or about to be out-of-stock on which platforms and at which dark store under a pin-code. In-depth analysis and actionable insights are the only way to keep you ahead in this fast-paced race on online shopping platforms.   A brand stock-out or going out of stock (OOS) can occur due to various reasons like supply shortage, poor inventory management, inaccurate forecasting of demand or unexpected demand surge, etc. The key is digital commerce intelligence on stock availability and real-time alerts on Out-of-stock status.  The availability monitoring should not be limited, it should be a more granular update such as on certain pin codes where is your product available? Where they stand vs competition? On which platform brand need to stock it up?  For instance, a shopper looking for a specific product of the brand might search on multiple platforms as well.   This means brands must monitor their presence across platforms at the pin-code level and on the platform’s dark stores. Here are some key metrics that brands must track within the stock availability monitoring:   Brand availability trends versus competition   Availability share versus competition  City-wise availability trends – monthly, weekly, daily, and hourly  Platform-wise & geography-wise analysis  Heat map to identify new geography to target  Tracking Bottlers’ (Sellers) performance  Maintaining Out-of-Stock product lists & real-time alerts  This is where mScanIt, digital commerce intelligence comes in handy as it covers all aspects of product availability monitoring across platforms and geographies. Leading brands from FMCG, electronics, beauty and personal categories trust us as it covers more than 150 e-commerce and quick commerce platforms across the world, drilling deeper within city-level analysis along with global coverage of multiple geographies.   Case study: How a global leader in the beverage industry improved availability across platforms and geographies Problem Statement A global leader in the beverage industry faced challenges in ensuring consistent product availability across digital platforms in key AMESA (Africa, Middle East, and South Asia) markets. In September, product availability in the KSA region on prominent platforms like Quick Market, Carrefour, and Nana was inconsistent, reported at:  Quick Market: 28%  Carrefour: 57%  Nana: 86%.  This lack of availability led to:  Missed sales opportunities  A weakening of consumer trust and brand loyalty  Limited visibility in a competitive digital landscape  The company aimed to bolster its market presence by enhancing availability through real-time monitoring, identifying supply chain inefficiencies, and ensuring sellers maintained optimal stock levels.  How mFilterIt helped the brand boost its brand presence to match the competition across geographies To address these challenges, the company partnered with mFilterIt to implement the Digital Shelf Monitoring, mScanIt a cutting-edge solution designed to monitor product availability across multiple platforms and geographies along with other KPIs such as keyword share, product page content, Feedback analysis of rating & review and product pricing and promotions. Here’s how our capabilities lead the way.   Real-Time Monitoring with Regular updates on product availability and stock levels across Quick Market, Carrefour, and Nana.  Alerts for out-of-stock (OOS) items, enabling immediate corrective actions.  Gap Analysis helps identify bottlenecks in the supply chain impacting stock availability.  Provided detailed insights into seller performance and platform-specific challenges.  Actionable Recommendations helped develop region-specific strategies to enhance stock levels, such as improving coordination with bottlers and distributors.  Prioritized high-demand SKUs to maximize availability during peak shopping periods.  Performance tracking with continuously targeting improvements in availability and visibility.  The results with digital commerce intelligence and shelf monitoring By the end of November, significant improvements were observed across platforms:  Quick Market: Availability rose from 28% to 51% (+82%).  Carrefour: Achieved 100% availability, up from 57% (+75%).  Nana: Improved from 86% to 94% (+9%).  Fig. 1: Product Availability Across Platforms September to November   These improvements translated into:  Enhanced customer trust and satisfaction by ensuring products were consistently available.  Strengthened market share and sales across key platforms, solidifying the brand’s position in the AMESA region.  Through mScanIt, digital commerce intelligence and shelf monitoring – availability analysis, the beverage leader transformed its operational approach, leveraging data-driven insights to achieve exceptional results in a competitive market.  Optimize Customer Journey with Digital Commerce Intelligence Do not limit to just stock availability tracking! It’s essential to consider various analytical metrics to optimize the customer’s journey across e-commerce and quick commerce platforms. Each stage requires a tailored approach to ensure that the brand’s presence is effectively communicated, and customer engagement is maximized across the digital shelf.  This journey can be optimized at three broad levels with digital commerce intelligence:    Awareness and Interest Stage Brands must track visibility and ensure that products are accurately featured throughout the marketplace. This phase boosts awareness and

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Quick Commerce

Rise of Quick Commerce in UAE: Are You Monitoring Where You Stand vs the Competition?

The Quick Commerce revolution is reshaping the e-commerce business landscape in the UAE at an unprecedented speed.  Convenience and customer-centric services are at the forefront pushing businesses to embrace a rapid online shopping model. As per recent projections by Statista, the Q-Commerce (quick commerce) market in the UAE is expected to reach a revenue of $3.27 million in 2024, with a compound annual growth rate (CAGR) of 7.71% from 2024 to 2029. This growth could drive the market volume up to $4.74 million by 2029 with 1.2 million users.  In this competitive landscape local players are building hyper-efficient delivery networks to compete alongside international giants. For brands, staying ahead requires market and competitive intelligence across platforms and geographies. Leveraging advanced tech-stack for Quick Commerce analytics to gauge where they stand compared to rivals, identify gaps, and explore new opportunities is the need of the hour. Today, it is not only helping brands to stay ahead of competition but also growing business and making it more profitable.   Quick Commerce in UAE  The Quick Commerce market in the United Arab Emirates is experiencing a surge in demand due to the country’s high population density and fast-paced lifestyle. Understanding the dynamics with quick commerce analytics and preparing brands for a transformative journey into the future.   Q-Commerce companies like Noon, Talabat, Carrefour etc. typically operate their own “dark stores” or cloud stores, where personal shoppers fulfill online orders, offering fast, last-mile delivery. The market is dominated by grocery and essential goods deliveries, often fulfilled within an impressive timeframe. With a densely populated urban environment and a significant population of expatriates, the UAE is becoming a prime environment for Quick Commerce growth.   Local providers are responding by enhancing app-based ordering and expanding their services beyond grocery items to include pharmaceuticals, home essentials, and even fresh foods.   Local special circumstances United Arab Emirates has a large expatriate population, many of whom are time-poor and willing to pay for convenience which has created a strong quick commerce market. Additionally, it is fueled by the hot climate in the region, due to which customers are often reluctant to leave their homes to shop.  Quick Commerce Analytics to Lead the Market  UAE’s competitive Quick Commerce landscape requires brands to prioritize performance monitoring through digital commerce intelligence and analytics. Here are some key areas where Quick Commerce analytics help drive product performance vs competitions: Track global & local competitors’ products performance vs yours across eCommerce platforms  Monitor Search of Search and Visibility Share across platforms & locations  Identify new opportunities -demographics or geographies to target in your market segment  Set market strategies based on insights & analytics  Enhance content to suit the local shoppers’ needs by identifying high-performing keywords  What metrics should brands track in Quick Commerce Analytics in UAE  Quick Commerce focuses on ultra-fast delivery, often within an hour or even less. Analytics helps identify any bottlenecks in the process. Real-time actionable insights allow brands to adapt. Monitoring Key KPIs such as pricing, availability, keyword share – discoverability, product detail page performance, etc. across platforms and geographies helps brand to stay ahead of the competition and leverage data-driven decisions.  – Pricing & Discount Trends  Real-time price tracker and comprehensive competitive analysis can help brand set dynamic pricing to ace the game on quick commerce and e-commerce platforms.   – Availability Monitoring  Keep Track of your stock availability across platforms and geographies at a granular level. Going out-of-stock can push your product into highly competitive marketplaces and platforms and lose brand credibility. – Content Analysis (Perfect page analysis) Keep your product detail page title, description, product images of high quality and optimized can give a massive boost to visibility. On Quick commerce platform, it is mostly about the product title that it should pop up when searched. – Digal Share of Shelf Monitoring Key track of your share of search and presence on the digital shelf. Product discoverability is key to staying ahead of the competitors across the digital marketplaces. – Sponsored Banners Performance  Sponsored listing on e-commerce and quick commerce platforms is critical to reach the right audience. Automate the process of sponsored ad spend and bidding process to ensure your budget gets optimized not wasted.   Case Study: Monitoring Availability across Q-com platforms   Objective & Problem Statement: One of the biggest multinational F&B conglomerates wanted to measure, track and grow platform presence and stock availability in the AMESA region. They were already working with an ecommerce intelligence tool but suffered due to limited scaling capability and platform coverage. Moreover, they were not able to customize data insights for the brand.   mFilterIt Deployment: The F&B conglomerate had deployed mFilterIt e-commerce intelligence stack for its presence on all e-commerce and quick commerce platforms in the region. They monitored the products across multiple KPIs across the Middle East & North Africa region. In the UAE region they mainly focused on enhancing its market presence with monitoring availability and optimizing share of search.  mFilterIt Analysis & Inferences: In the UAE they focused on optimizing availability on key platforms Careem, Carrefour, Noon and Talabat for Beverages, Nutritious Food and Snack category.  Fig. 1: Before and after using mScanIt last year at multiple locations on Q-commerce platforms They identified and acted on performance gaps with global dashboard monitoring availability and other core KPIs. With limited availability and platform presence they were losing out on sales. As they started tracking zip-code wise availabilities, the internal teams could be activated for improved performance in every region. This led them to optimize availability versus competition across platforms and geographies on various categories and sub-categories. With growth of around 41% in availability share across platforms the brand expanded its presence and reached the shoppers.   The first checkpoint on optimizing the customers is staying in the race – prevent stock out. The brand grows availability at the dark store level to make sure the availability doesn’t fall behind the competition. A momentary lapse in availability can lead to losing a potential customer. Frequent stock-outs also affect brand reputation

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Impression Validation: Ensuring Your Ads Reach the Right Audience

In the world of digital advertising, getting your ads seen isn’t enough, you need to ensure that the ad is seen by your targeted audience. It’s about making sure those impressions—when someone sees your ad—are valid and genuinely reaching the right audience. This is where impression validation becomes crucial. It’s the process of verifying that your ad impressions are not only seen but also viewed by the right people who have a higher likelihood of engaging with your content. Why impression validation matters: Eliminating Fake Views The digital advertising space is vast, and not all impressions are created equal. In some cases, ads may be shown to bots, low-quality traffic, or irrelevant audiences. Impression validation helps you filter out these “fake” impressions, ensuring that real people who are interested in your product or service are the ones seeing your ads. This helps you avoid wasting your budget on views that don’t matter. Understanding User Intent Validating impressions is also about understanding how likely a viewer is to engage with your ad. Are they truly in your target demographic? Did they spend time on your page after seeing the ad, or did they scroll past it without a second glance? fraud Detection help assess these behaviours to ensure your ads are reaching the most relevant audience. Optimizing Ad Spend By validating your impressions, you’re able to allocate your budget more effectively. Instead of throwing money at impressions that aren’t adding value, you can focus on those that are likely to drive conversions. This leads to a better return on investment (ROI) and more meaningful interactions with your audience. In the end, impression validation isn’t just about counting views—it’s about ensuring your ad budgets are well spent by reaching the right people with genuine potential to convert into a lead or generate a sale. By focusing on valid impressions, you can optimize your campaigns for greater success and better engagement. To learn more about impressions validation, reach out to mFilterIt.

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Click-Tracker

Click Tracker: How Accurate Click Tracking Can Save Your Ad Campaign

Digital advertising demands proactive measures to ensure every click is measured and validated.  Approved Click Trackers are now mandatory if anyone wants to track p-max or demand gen campaigns. However, click tracking needs to be backed up with comprehensive monitoring to ensure genuine engagements that reflect the impact of an ad campaign. This is the gap fraudsters exploit manipulating clicks to divert ad budgets without driving real results  Let’s explore what advertisers can do to for click protection, ensuring click integrity and the role of efficient click tracker.   Why use a Click Tracker?  Click Tracker approved by Google helps advertisers track clicks on their ads while maintaining compliance with Google’s advertising policies.   Compliance with Google policies ensures the prevention of malicious or deceptive tracking practices that could negatively impact user experience. Google-approved click tracker meets these standards, ensuring that ad clicks are tracked accurately and provide enhanced transparency. This helps reduce the risk of ad abuse and misreporting, which could otherwise cost advertisers money and distort performance metrics.  Click trackers enable advertisers to monitor ad performance precisely by tracking user behavior. This data includes metrics such as conversions, session duration, and user journey, allowing marketers to better understand the effectiveness of their campaigns and optimize accordingly. Since Google’s ad platform integrates seamlessly with approved click tracker advertisers can implement these tracking solutions without compatibility or functionality issues. By accurately tracking ad clicks and subsequent actions, advertisers gain valuable insights into which keywords, ad formats, and targeting options drive conversions, ultimately leading to higher ROI and relevance through data-driven decisions.  Click Fraud Detection Our google-approved click tracker is more than just a click counter or measurement instead it’s an extension of our capabilities. The follow-up measurement should be clicking fraud prevention differentiating genuine clicks from fraudulent ones with advanced algorithms to analyze traffic, identifying patterns associated with fraud, such as repetitive or high velocity clicks from the same source, and filters them out.   mFilterIt can help advertisers gain visibility into every stage of the conversion funnel, from initial clicks to meaningful user actions. Safeguard ad budgets from making payout for fraudulent clicks and ensures engagements are genuine.  Preventing Click Spam Click spam is where fraudsters generate fake clicks to earn ad revenue or inflate engagement metrics and skew campaign performance metrics. It makes analyzing ad campaign performance difficult with inflated numbers.   Combat click spamming using multi-layered analysis techniques that include deterministic, heuristic, and behavioral checks. This ensures clicks are coming from legitimate IPs or devices, detects suspicious patterns, like a high volume of clicks from a single source, indicating potential fraud. Looks deeper into user behavior to ensure it aligns with expected patterns, filtering out traffic that doesn’t show genuine user intent.   Effective click spam prevention ensures that ads reach genuine users who are more likely to convert, rather than wasting impressions on fraudulent traffic.  Ad Campaign Performance optimization Accurate measurement of clicks and conversions is crucial for assessing ad campaign performance and scaling effectively. Without a reliable click fraud protection, advertisers run the risk of making decisions based on inflated or inaccurate metrics. Click tracker provides the data necessary to analyze and evaluate campaigns with confidence, ensuring that reported clicks translate into real, user-driven events.  Optimize Ad Spend By focusing on genuine conversions rather than inflated click numbers, ad spend is optimized toward high-quality traffic.  Scale Campaigns Effectively Accurate data enables advertisers to scale successful campaigns without worrying about ad fraud undermining performance.  Build Trust Transparent and accurate metrics foster trust between advertisers and their stakeholders, creating confidence in ad effectiveness.  Accurate and fraud-free metrics allow marketers to make data-driven decisions, increase ROI, and scale campaigns based on reliable results.  How mFilterIt help in Click tracking along with Full-funnel protection Brands heavily invested in online display and video ads across websites to build brand awareness and drive engagement. This ensures that transparency in the ad campaign is of utmost importance not just to safeguard ad spending but also to protect brand reputation.  One of the major challenges is when the companies notice a sharp increase in ad impressions and clicks on their ad campaigns, but the result is minimal impact on key engagement metrics. Such discrepancies suggested ad fraud was wasting the company’s budget and skewing data, making it difficult for their marketing team to understand genuine campaign performance and target the right audience.  mFilterIt ad fraud detection and prevention tools for a comprehensive approach to tackle ad fraud, identified and filtered out fraudulent activity across multiple dimensions, ensuring the company’s ad spend was optimized toward genuine engagement.  Real-Time Conversion-Based Analysis  Analyzed traffic in real-time to detect abnormal patterns, such as sudden spikes in clicks from specific regions, devices, or IPs.  To complement click and impression verification, mFilterIt also tracks user interactions beyond clicks. By analyzing click-to-event conversions filtering out fraudulent clicks that did not lead to real user engagement, ensuring their ad spend was driving actual interactions and interest.  Bot Detection and Elimination  Artificial intelligence and machine learning algorithms are used to identify bot behavior, distinguishing between automated traffic and real users as bots often mimic human behavior. Our heuristic and behavioral checks flag them off and ensure swift blocking and blacklisting source with automated process.   Domain and Ad Placement Verification Fraudsters disguise low-quality sites or non-existent domains to pass as premium inventory. mFilterIt ad verification tools helped ensure the company’s ads appeared only on legitimate, brand-safe websites by matching domain data, placement information, and ensuring alignment with the campaign’s target audience.  Conclusion Click tracker serves as a first line of defense, ensuring ad budgets are directed toward genuine traffic, followed by multi-layered full funnel approach with integrated brand safety to optimize campaign performance. It allows brands to measure click-to-event conversion, giving a clearer picture of campaign impact.   As digital advertising continues to grow, so does the need for mFilterIt Click Tracker and Valid8 for full funnel protection, ad traffic validation, ad fraud detection and lead optimization that bring transparency, accuracy,

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Pricing Intelligence with Real-Time Price Tracking

An effective pricing strategy is crucial for driving sales and staying relevant. With the rapidly advanced technology, companies now leverage pricing intelligence through ecommerce analytics tools and dynamic pricing mechanisms powered by artificial intelligence (AI). Pricing intelligence not only enhances competitive positioning but also maximizes profitability and customer satisfaction, especially on the digital shelf, where visibility and relevance directly impact purchasing decisions. According to McKinsey & Company Report, businesses using pricing intelligence see revenue increase of 5-10%.  What is a Digital Shelf? The digital shelf is the virtual presentation of products on online retail platforms. Like the physical shelf in a shop, the digital shelf displays the product offer of a brand, prices, promotions, and other product information. A digital shelf is much more complex and dynamic as it cuts across different e-commerce platforms and requires constant updates to remain competitive.  Working in this virtual realm requires keeping track of and analyzing so many metrics to ensure products are salient and provided at the best possible prices.  Pricing is critical on the digital shelf on online retail platforms. According to Harvard Business Review, real-time price tracking can reduce pricing errors by up to 30%.  Why is pricing important on the digital shelf?  Pricing is an important aspect of the digital shelf because consumers shop around based on price comparisons between sellers. In case prices are too high, it is likely that intending customers will go shopping elsewhere to find a better price offer from the competition. On the other hand, if prices are too low, profit margins are depleted. Therefore, there must be a balance struck in using data-driven pricing to drive consumer interest and secure brand positioning. According to Forrester Research, organizations using dynamic pricing report a 20-30% increase in conversion rates during peak sales periods.  The following are key reasons why prices are important on the online shelf:  More Sales- Competitive pricing attracts more customers in price-sensitive markets where shoppers are generally quick in comparison.  Improved Conversion Rates- Value-based pricing reduces the abandonment rate at the final stages of purchasing and helps improve conversions.  Better Brand Positioning- An appropriately priced product helps to communicate a value proposition. Either this could be in terms of affordability or high quality.  Customer Loyalty- Fair and consistent pricing will instill confidence and loyalty, ensuring repeated purchase behavior and long-term relationships with customers.  Why is Price Tracker Analytics Important?  The tool is powerful for the observation of the pricing level of the competition and, hence, strategy is price tracker analytics. It tracks prices to keep the brands in the digital shelf position without trailing behind competitors. Here’s why price tracker analytics is of prime importance:  Competitor Analytics  Pricing monitoring allows for the tracking of competitor pricing and promotional activity in real-time to make necessary adjustments in market positioning. For instance, when the competition goes ahead to introduce a discount, they can respond with a similar promotion or value-added services.  Optimized Pricing Strategies  Advanced e-commerce analytics helps businesses understand the optimal pricing structures for specific segments and markets to optimize them. Pricing intelligence enables brands to understand their ideal price points, which maximizes demand while ensuring healthy profit margins.  Dynamic pricing capabilities  With real-time analytics and AI-based dynamic pricing, the outcomes can permit automatic adjustments due to changes in demand fluctuations, seasonal patterns, and fluctuations in competitor pricing. In this way, revenue maximization occurs through supply balance with market demand with a higher flexibility of pricing.  Improved Margin Management  Price trackers do analytics on price trends and enable brands to be best on margin management. Brands can price effectively in real time through actual data on profitability without losing the competitive edge in the market.  Why is a real-time price tracker important?  Real-time price tracking allows businesses to monitor and adjust prices in real time, a necessity in the ever-evolving e-commerce environment. Brands stand to lose customers to competitors better at responding to changes in pricing if they do not track prices in real time.   Here’s why having a real-time price tracker is important:  Instant Price Adjustments   The company can adjust prices right away using real-time data to keep the competition going when competitors do. For example, when a competitor lowers their price, a real-time price tracker will allow the brand to respond quickly and be at the same price, even cheaper, so they won’t lose potential sales.  Informed Decision-Making   This kind of real-time tracking of actionable insights enables brands to make data-driven decisions. They can experiment with price variation discounting, or a package offer and check which performs better and fine-tune it over time, thereby using real-time analytics to do so.  Increased Agility with Dynamic Pricing   Dynamic pricing is very important in high-competition industries, for example, electronics or fashion. AI-driven price trackers allow for dynamic pricing according to demand, time of day, or geographic location to improve the effectiveness of prices without human intervention.  Customer-centric pricing   In customer-centric pricing, through real-time price tracking, the brand will be able to sustain it in terms of affordability and relevance for the potential buyers. This in turn encourages greater customer satisfaction and loyalty because the customer realizes the brand’s commitment to fair and competitive prices.  Metrics That Every Brand Should Track  Real-time price tracker tool enables brands SKUs they wish to track:  Product price across multiple e-commerce and quick commerce platforms   On various pin code  Also, SKUs Product Code, Product URL, Title, and Brand  Track Stock Status  Product ASP, MRP, and Discount   Seller information   Conclusion  Consumers can rapidly compare prices and product options; pricing intelligence is what brands need to stay ahead of the game. The use of price tracker analytics, dynamic pricing, and AI-powered e-commerce analytics tool enables businesses to navigate the complexities of the digital shelf and respond quickly to market changes. Optimal pricing that resonates with customer expectations and aligns with competitive conditions will allow brands to boost conversions, improve profitability, and foster long-term customer loyalty. A strong pricing strategy will make sure that the brands gain real-time insights into keeping the

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