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What Aspects Does Sentiment Analysis of eCommerce Platforms Reveal?

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Customers on eCommerce platforms often check out reviews and ratings of products before making the final buying decision. In India, 48% of consumers make fashion purchases regularly after going through reviews and ratings. Monitoring reviews and ratings have become important for understanding customer sentiment towards the brand, product, seller, etc., across eCommerce platforms. Detecting and categorizing customer reviews as positive, neutral, and negative using mScanIt’s Sentiment Analysis enables to detect product aspect working ‘for & against’ the brand. mScanIt’s sentiment analysis dashboard defines sentiment intensity; segregates the most popular aspects like quality, product, price, etc., under comment themes; helps to find the most/least popular aspect/theme of a brand, etc. Diving deep into these aspects helps to keep track of consumer reviews across multiple eCommerce platforms, the most popular aspects/themes driving the sentiment intensity, pain points of the consumers, etc. mScanIt’s Sentiment Analysis also reveals key aspects of eCommerce platforms, which are useful for brands in multiple ways. A sentiment analysis is done by using What Can Brands Derive through mScanIt’s Sentiment Analysis? The Intensity of Buyer Reviews consumer reviews. Based on the consumer sentiments, a brand can understand the most popular aspect of its products on eCommerce platforms or can detect which aspects are meeting or not meeting to the buyer demands. A comparative view of the same vis-a-vis its competition enables a brand to learn the brand’s standing against its competition. For example, your brand could have a high (700+) positive reviews for ‘price,’ whereas your top competitor only has 200+ reviews on it. So, the consumers appreciate the price of the product and it is probably the leading factor driving your eCommerce sales/revenue under a category. On the other hand, your top competitor could have 500+ reviews on ‘quality’ whereas, you hardly reach 100 reviews on this aspect. Using this knowledge, you can evaluate your own Product Display Page (PDP) against your competition. It could show that the competitor is focusing more on ‘quality-based’ features and is using them in the advertising/marketing campaigns as well as the PDPs. P.S.: mScanIt can also be useful in analyzing PDPs, share-of-shelf, and banner ads. Probable Intent to Purchase According to research, the product purchasing decision of 91% of online shoppers rely on reviews from other customers. Therefore, listings on eCommerce platforms with higher positive reviews can increase add-to-cart actions and conversions. Furthermore, constantly checking sentiment analysis reveals the average sentiment score within a time frame. Therefore, brands can make sales forecasts and strategize accordingly. It’s one of the ways through which brands can understand the best performing ecommerce platform and optimize on their marketing spends. Moreover, the qualities/themes of the sentiment analysis dashboard would offer knowledge about the factors that might likely influence the customer’s intent to purchase. Points of Engagement with the Customers Reviewing mScanIt’s Sentiment Analysis dashboard gives information about the pain points of customers as well as the top-performing qualities of a product. It reveals the emotional triggers that can become responsible for trolling on eCommerce marketplaces under the review and rating section. Brands can use the emotional triggers generated from the ‘for and against’ reviews and ratings in their responses to improve the positive sentiment intensity and diminish the negative sentiment scores. The same information can be relayed to the marketing and customer support team to strategize and enable growth while addressing customer problems and enhancing the customer’s relationship with the brand. Reaching out to the customers at the right time by setting alerts of hyper sentiment intensities can help a brand to avoid trolls under the review and rating section as well as increase the brand’s ‘delightful’ customer base. Gain Insights About New Markets Customers on eCommerce platforms often reveal their pain points, compare the USPs of previously purchased products with recently purchased items, share the change in brand experiences, etc. Monitoring sentiment analysis reveals new buyer personas, untapped markets, trends, etc., which enable brands to build strategies for reaching out to the un-targeted customer base, increase their revenue, and plan marketing/advertising strategies for eCommerce platforms accordingly. Besides managing their sentiment analysis, brands get a chance to monitor competitors’ analysis tool using mScanIt, which expands all these horizons at a massive scale. Conclusion Monitoring sentiment analysis offers insights into customer behavior, such as the probable intent to purchase, points of engagement, responsiveness towards the product listing, etc. Keeping an eye on the sentiment analysis of eCommerce platforms can enable brands to customize their marketing and advertising strategies towards their buyer needs and even resolve problems whenever the negative sentiment intensity spikes up. Schedule a demo with us to learn methods to scale your business using mScanIt’s Sentiment Analysis.

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Your Search Ads Are Under Attack. Know Why?

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Akash is excited to plan his trip to Bali and starts searching for the best deals on the internet. He searches and finds an exciting deal of “Get INR 1000 instant cashback on your first hotel booking”. The deal sounded like a golden opportunity, and he instantly clicked on the ad. It was a renowned travel booking site which made him book his hotel in a hurry without any suspicion. However, he neither received the cashback nor the booking confirmation from the website even after 48 hours. In the end, he ends up being frustrated and is under the impression that he has been fooled by the brand. But in reality, the brand is clueless about this incident. In this case, Akash has been a victim of the search-ad phishing scam. This is one of the few instances which has recently been in the news in terms of cybercrime. Most of these instances often go overlooked due to a lack of awareness and prevention methods. The search ad scams not only result in the wastage of ad spends but also impact the reputation of the brand. Before knowing the impact, know in detail about search-ad phishing. What is Search-Ad Phishing? Also known as Google ad phishing, this is a type of cyberthreat in which the fraudsters hide the malicious links within the sponsored search engine results to fool people into clicking it. It is like phishing emails impersonating your brand just in the case of a search ad. When a person clicks on a search ad link, it redirects either to a fake website impersonating your brand, a spoofed social media account, or a fake phone number. Generally, the fraudsters trick the customers into searching for a website or customer care numbers of retail stores, financial institutions, insurance companies, cloud services, or utility companies. Ways Cybercriminals commit Search-ad Phishing Hacking Devices: The fraudster uses these techniques to trick users into sharing their personal information. Otherwise, they direct the users to an app or website to drop malware and hack their system to steal money or harvest personal information. Creating Fake Offers: The fraudsters also create fake company websites that claim to offer products at low prices for your brand’s products or services. When the customers fall for this bait, the fraudsters can use their personal information or sell counterfeit products using the name of the brand. Impact of Search-Ad Phishing on Brand Consumer Lose Trust: When the user interacts with a spoofed search ad, they are either taken to an impersonated website of a legitimate brand. The user is unaware of this and when they lose their money due to fraudulent practices, they think they have been defrauded by the brand. This eventually leads to consumers losing trust in the brand. Compromised Data: Due to the spoofed search ads, the data from the ad campaigns are highly compromised. This results in the wastage of ad spends and the advertiser unknowingly continues to invest in these tampered ad campaigns without any improvement in ROI. Conclusion Marketers often overlook the impact on brand safety when taking prevention measures from cybercriminals. Along with detecting fraud in ad campaigns, it is essential to act against brand infringement attacks by fraudsters. When the fraudsters attack your brand image, the consumers are impacted first and eventually lose trust in the brand. To protect your brand’s ad spends and brand safety altogether, it is important to partner with advanced ad protection and brand safety solution provider. mFilterIt’s ad traffic validation suite and brand safety suite ensure that your search ad campaigns are protected from invalid traffic and brand infringement attacks. With the right set of capabilities and expert help, protect your brand from the trap of fraudsters.

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Beginners Guide to Share of Voice on Search Engines

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Share-of-Voice is a marketing metric that defines your brand’s visibility versus the competition. On search engines of Google, Bing, Opera, etc., SOV defines the share of your brand’s appearance versus the competition based on keywords. Measuring SOV on a search engine is critical to know your presence on the web and the form of content you are visible on such eCommerce Platforms, Blogs, News, Brand Websites etc. Analyzing SOV is also important for brands as it gives a complete picture of their awareness on the brand, competitor and organic keywords. Brands with higher visibility percentage have a higher chance of boosting their conversions/sales/purchases and giving impression as a market leader. According to Statista, desktop search traffic originating from Google ranges between 8.78% to 94.15% across countries, with the highest results from India. The likelihood that consumers would go to an ecommerce platform using the top three-page results is higher than the pages preceding them. It means that brands have a higher chance of driving traffic from the Google search engine to their product listing on a platform the more times they appear on the top three-page results. Why Does SOV Matter for Your Brand? Measuring the SOV of keywords helps to answer the following questions: Which is the best performing type of content? How much market share does it acquire? What is your market positioning? What is the keyword-based ranking of your brand? What is the share of your paid search keywords? Who has the highest market share? Which ecommerce platform has the highest SOV and for which keywords? How likely will consumers come across your brand? What is your brand awareness? What types of search results do consumers get on your selected keywords? What type of other results appear on your chosen keywords? What is their SOV? Without measuring the SOV, deciphering such results could become impossible on Google, which is one of the most dominant sources of finding the most relevant results. In the U.S., 61.4% of core search queries were generated through Google in January 2022. According to Google, personalized results are generated using an algorithm that relies on commonly used words, expertise sources, location, setting, and other factors to deliver the best results. Appearing as the most viable search results active on Google becomes a priority as it is directly connected with traffic generation, conversion, revenue, etc. Here is an example of mobile SOV for one of our brands: Tracking the share of voice on Google paid searches helped one of our clients take measures to boost their brand website share from 25% to 28% from January to December. The brand’s share of ecommerce marketplaces diminished from 51% to 47%. So, the visibility of the brand’s search results for the ecommerce marketplace also diminished, and marketers should assess the reasons for the change. In short, the advantages of measuring Share of Voice on search engines are as follows: Brand Awareness: Analyzing SOV through mScanIt defines the proportion of your brand’s awareness on organic, paid, and competitor keywords. The higher your SOV, the higher the chance of reaching out to potential customers through the search engine by redirecting them to your website or an ecommerce product listing. Visibility: SOV also defines the proportion of your brand visibility versus the competition. Brands with the highest visibility would captivate more attention and have historically witnessed a higher click-through rate (CTR) & conversion rate. Search Rank: The user often goes through the top twenty or top three-page results before making a buying decision. Higher search rank is directly proportional to higher ranking during recurring intervals. Thus, acquiring a higher market share and revenue. Most Dominant Form of Content: Analyzing SOV also gives a picture of the most dominant content results on the search engine, and such content forms would likely have the highest traffic. Moreover, brands can find paid keywords with the highest and lowest SOV, and marketers can use them to build strategies across channels. Pro Tip: “Search engine analytics reveals information pertaining to your brand’s webpage performance. However, mScanIt defines the presence of your brand and the competition across the web on the keywords or key phrases commonly used for searches. Users today still make buying decisions or deviating to an eCommerce platform through search engines. Therefore, tracking your visibility/brand awareness on search engines keeps you abreast of your consumer interactions.” Conclusion Share of Voice is an important factor for measuring a brand’s awareness, visibility, search rank, etc., on the search engines. mScanIt, powered by mFilterIt, measures the SOV of global leaders, giving them an overview of their likely market share. Analyzing SOV through mScanIt also helps to deep-dive into consumer behavior, showcases the presence of the competition, makes the brands aware of new trends, and more. The paid and organic results enable brands to find areas of improvement, the most visible types of content, the percentage-wise share of each form of content, and more. Schedule a demo with us to learn more about the advantages of eCom Competitive Analytics for your brand.

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How Is The Digital Advertising World Going to Look After the Collapse of Third-Party Cookies?

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The marketers have been feeding on third-party cookies data to reach a wide array of users based on their behavior and preferences. However, with the news of the third-party cookies phase-out, the marketers have to bring innovative ways to curate customer data for targeting the right audience with their ad campaigns. Google has announced that it will fade out the use of third-party cookies by the end of 2023 to bring more privacy to the digital ecosystem. But what will the next phase look like? Most certainly, it will not be that bad. Instead, it might be a start to a more transparent and privacy-first approach in the digital advertising world. Know in detail why third-party cookies are fading and how this will impact the advertisers and publishers. What are third-party cookies? The third-party cookies are used by marketers for ad retargeting and behavioral advertising. Advertisers add a tag to a page to track a user across the web as they visit different websites. This allows them to create a profile of a visitor based on their search habits so that they can show them more relevant ads. Advertisers have very sophisticated parameters for their campaigns to ensure they are reaching their targeted audience. To achieve this, they take the help of third-party cookies. However, third-party cookies have been under the radar of controversy for the longest time and are considered an invasion of people’s privacy. Why third-party cookies are going to phase out? The phase-out of third-party cookies has been in the buzz for quite some time. In February 2020, Google announced the phase-out to protect the privacy of the users. This move was initiated to bring more transparency, choice, and control to the users on how they want their data to be used. Though the search engine giant was the first to make the announcement, Safari and Firefox made the first steps to phase out third-party cookies. Google’s phasing out process will happen over a period of two years to ensure that the online advertising business is not impacted heavily by the change. Impact of Third-Party Cookies Phase-Out On Advertisers Out of all the cookies available on an average website, up to 60% are third-party that are used for marketing and advertising purposes. The third-party cookies are meant for tracking the behavior of the user across the internet. They capture the interests, actions, and behavior of the user as they scan through the websites. Though this data is quite broad and detailed with various data elements, the datasets made by combining cookie syncing and record matching give more comprehensive data for hyper-specific targeting. Due to the loss of this key mechanism, the advertisers will not be able to do retargeting, behavioral targeting, cross-site attribution modeling, and measurement. Without this kind of precision level, the reach and performance of the digital ads will also be impacted. On Publishers As the third-party cookies phase out, the publishers will not be able to provide a targeted audience to the advertisers. As a result, their ad revenue will be directly impacted. However, large publishers can use their first-party data to provide a highly targetable audience for the advertiser. Due to the phase-out of the third cookie, the ad exchanges, supply-side platforms (SSPs), or demand-side platforms (DSPs), addressability to the audience and volume will decline massively. Due to a weak targeted audience, the advertisers will pay a lost cost per impression as the ROAS will be low. How can marketers get ready for the change? The removal of third-party cookies will bring a drastic change in the digital advertising ecosystem. It will push the advertisers to create more authentic connections with customers. The first move after the phase-out will be to leverage the first-party cookie data. The use of first-party data means that the marketers will get access to more accurate and insightful data to measure customer interaction. Marketers have to brainstorm new ideas to build connections with their customers to get their contact details. However, the advertisers have to ensure that the customers trust them with their data. In addition to leveraging the first-party data, other techniques will help marketers to overcome the phasing out of third-party cookies. Some other ways are: Contextual advertising – To ensure that the right audience is targeted, the marketers will be required to focus on the messaging. A focused messaging will help provide a granular view of the interests of the audience. Federated Learning of Cohorts – This is a type of web tracking introduced by Google, but it is still in its testing phase. The basic idea of this technology is that the Chrome Browser will track the browsing habits of the customers and help the marketers to create a targeted messaging to attract the right audience. Will the first-party cookies result in low ad fraud? Unfortunately, No. Online marketers use cookies to gather user information for better ad targeting. While the third-party cookies compromised the privacy of the users sharing their information, their phasing out will not impact ad fraud. Even with first-party cookies, the fraudsters can generate invalid traffic with the help of bots, automated scripts, malware, and other non-human traffic. Though these fraudulent traffic sources can be identified with the help of IP addresses, there are some sophisticated fraud techniques like cookie stuffing which are hard to detect manually. How to protect your ad campaigns from ad fraud? To validate traffic on your web campaigns, it is essential to partner with an ad fraud detection & prevention solution like mFilterIt. We use sets of algorithms and capabilities of AI, ML, and data science to detect invalid traffic sources. Further, to protect your ad campaigns from future damage we do an active blacklisting to eliminate fraud and ensure cleaner traffic. Conclusion The fall of third-party cookies will bring a certain level of privacy and transparency to the digital advertising ecosystem. However, there will be hardly any impact on the ad fraud existing in the advertising world. Instead, the marketers will require strict preventative measures to protect their ad

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Why is DCB Fraud Problematic for Telcos?

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Carrier billing was considered to be one of the safest transaction mechanisms, but unfortunately that’s a myth. Mobile Network Operators (MNOs) provide internet and communication services to their customers directly as part of the telecom package. So, whenever fraud happens in the Direct Carrier Billing (DCB) ecosystem, it creates panic amongst the network’s consumers. Cybercriminals use sophisticated methods for targeting device users, such as malwares, bots, phishing emails/SMS, etc. Their undetectable and continuously evolving mechanisms directly impact the reliance on mobile subscriptions, which is increasing at a rapid pace. According to a source, there would be nearly 1.4 billion more mobile internet users by the end of 2025, and DCB service subscriptions would likely increase by three folds compared to 2019. As mobile internet users and DCB’s Value Added Service (VAS) subscriptions increases, fraudsters are bound to target customers, merchants, and network operators to acquire monetary benefits. Online transaction threats in the DCB subscription model have become problematic for telcos for many reasons. DCB Fraud Threatens Mobile Network Operators (MNOs) Loss of Consumer Trust and Market Credibility Customers making transactions through carrier billing have laid their trust in the MNOs. However, cybercriminals’ blatant disregard for consumer faith remains obvious during financial fraud. Moreover, the users blame the MNOs and merchants for losing their money for unrendered VAS subscriptions, recurring in their bills. While the rising customer complaints remain one flaw of the whole operation, the loss of revenue by paying back a sufficient amount to a larger group of users gives a financial blowback to the telco network. Therefore, it’s a constant battle for the brand custodians to make deliberate efforts to restore the faith of the users and ensure brand’s credibility. Besides fraud in the brand’s DCB transaction-based apps, the customers become victims of financial fraud on other associated apps. According to a research, users’ digital identities are sold for as small value as $25 on the dark web. Disables Telco from Achieving the Highest ARPU Average Revenue Per User (ARPU) is the estimated revenue generated by telcos/MNOs/brands based on active app users in a given period. It is calculated to understand the change in revenue generated per user, the change in total number of subscriptions in a specific duration, the sources that offer the maximum ARPU, etc. ARPU is also a term used in advertising for determining the campaigns generating the highest revenue, deciding the total number of user acquisitions for achieving revenue targets, deciding customer base, pricing strategy, etc. According to a report, the prepaid ARPU in Chile, Latin America, before the DCB service launch was $9 and post-launch was $19, which included an increase of $10 on core services and $9 on DCB. The same report also states that DCB also enhanced the subscription of core services (20%), prepaid recharge amounts (12%) & recharge frequencies (85%) for Telefonica prepaid subscribers. DCB fraud can create a loss of such potential revenue from brands. Moreover, victims of DCB fraud often switch to alternate MNOs that offer secure payments for subscriptions and don’t add unnecessary payments to the carrier bills. Besides, the customers could lose faith in DCB subscriptions and stop the DCB services completely. Drains the Digital Advertising Efforts MNOs across the globe often advertise their Value Added Services on search engines and other sources. In 2019, Google Ads attributed 54% of their ad sales to VAS mobile advertising, whereas affiliate networks generated the remaining advertising traffic. In the succeeding year, the share of Google Ads for VAS mobile advertising reached 62%,i.e., 8% higher. Whenever customers using DCB as payment for VAS subscriptions become victims of DCB fraud, their trust is lost in the MNOs. Moreover, customers often criticize the DCB service providers for the additional charge on their bills for unrendered services. Therefore, the likelihood that customers would click on ads associated with the MNO substantially diminishes, especially across social media handles, which, had a stake of 17% in 2020. What Can and Should MNOs Do to Eliminate the Threat of DCB Fraud? In these evolving times, MNOs need a technology-oriented solution and experts that have understanding about the modes of DCB fraud. Presently, mFilterIt’s DCB anti-fraud solution is a pioneer in the field of DCB. Our core team has more than a decade of experience in telecom network operations. Our solution eliminates the threat of DCB fraud by putting multiple levels of validation that allow brands to receive subscriptions from genuine users. In addition, the sophisticated solution categorizes the threat level and revokes DCB fraud by offering multiple mechanisms for device management. Conclusion The scale of DCB fraud increases every day with the increasing and evolving method of cybercriminal activities. Therefore, the current scenario requires mFilterIt’s DCB anti-fraud solution to validate legitimate subscriptions, avoid the drawbacks of DCB VAS fraud, increase ARPU, and safeguard advertising budgets aligned with VAS. As a MNO, it is also your responsibility to offer safe and secure environments for VAS subscriptions. Otherwise, you may also get penalized or have to stop the services altogether. Incorporating mFilterIt’s fraud prevention tool for DCB offers a resolution to such problems. Schedule a meeting with us to learn about the advantages of including our DCB anti-fraud solution in your consumer’s transaction journeys.

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Referral & Coupon Fraud: How it impacts the Advertiser’s ROI?

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Imagine that you have set up a well-planned referral campaign to gain new customers for your app. It started to pick up speed and referrals started overflowing to claim the rewards. Sounds so good, right? But eventually, you realize that the number of referral claims is high, but the ROI from the referral campaign is low. This might be a sign that you have become a victim of Referral Fraud. This type of fraud not just impacts the marketer monetarily but also leaves a deep impact on its brand reputation. Know in detail about referral fraud and how fraudsters commit it in different forms. What is Referral and Coupon Fraud? This type of fraud happens when fraudulent participants create illegitimate referrals or misuse coupons to commit fraud. They play the system to leverage the benefits of the rewards and discounts, while the advertisers end up wasting ad spends on invalid traffic instead of attracting legitimate new users. How does Referral Fraud happen? First-time User Fraud First-time user fraud is the most frequent fraud that a user does to take benefit of the referral program. In a normal case, a referral code is valid for first-time users only. However, the fraudsters use these codes multiple times by using BOTs, Simulators, Device Farms, etc.  For e.g., in the case of a Ride App like ola/uber, the users desperately try to hunt for free rides via the first-time promo code by creating multiple or fake email ids or by using fake/virtual phone numbers to show themselves as new users and drain the advertiser’s ad budget. Self-Referral Another type of referral fraud is when the same user is the referrer and the referee i.e., the same users find fraudulent ways to get the benefits. They use different fraudulent practices to avail the benefits of the referral program. They use the same email IDs and different phone numbers. And in some cases, they even use the same phone numbers. Fraudulent Coupon Codes Referral codes are a cost-effective way for advertisers to reward loyalty, drive purchases and encourage brand value. Referral code fraud is a lucrative way to gain incentives, rewards, bonuses, etc. However, when running these campaigns, the fraudsters manipulate the coupon codes through scams such as fake or expired coupons. When the user attempts to use this code, they don’t get the benefits claimed by the advertiser. This directly impacts the brand image, and the users lose their trust in the brand. App Cloning App cloning or Parallel Space gives an advantage to the user to log into two different user accounts simultaneously by creating a separate parallel space on Android devices. The user can basically create and manage login for two accounts on one device and create separate profiles for business and personal accounts for the same apps as Facebook, WhatsApp, riding apps, gaming apps, etc. With the help of parallel spacing, they can refer themselves and redeem the benefits of the referral program. An example of app cloning in a device Using Bots/emulators & VPN Proxies The fraudsters use their age-old tools like Bots & VPN Proxies to fake users and redeem the benefits of the referral program by either reinstalling the app or by manipulating the device parameters like Device ID, Advertising ID, IMEI, Device IPs, etc. With the help of VPN & proxies, the fraudsters fake their device location which makes it hard to detect the fraudulent IP addresses. On the other hand, sophisticated bots hack devices to use the genuine user’s information for redeeming the benefits of the referral program. Impact on the brand The advertiser runs referral campaigns to bring in new customers and retain existing customers. However, when the fraudsters seep their way into the campaigns, the advertiser not just loses money but also compromises their brand image. Due to the fraudulent coupon codes and malicious practices happening in referral programs, both the new users and existing users are impacted. The fraudsters engage in referral campaigns which leads to the wastage of the advertiser’s ad budget on invalid traffic. As a result, when new or existing users are unable to avail the benefits of the referral program, they lose interest and trust in the brand. Furthermore, the advertisers incur low ROI and a negative impact on their brand image. How Advertisers Can Protect Their Referral Campaigns Do Manual Checks: The advertiser can do a manual check on the referral campaigns by closely analyzing the phone numbers, emails, and even domains. This way they can do a quick analysis of the incoming traffic and take preventative actions to protect the campaign. However, it is difficult to detect sophisticated bot patterns manually. Partner with Fraud Detection Vendor: To ensure clean traffic and save ad spends on referral campaigns, the advertisers must partner with an ad fraud detection provider. We provide a solution based on the device environment instead of just analyzing the IP repetitions. We integrate our SDK (in the case of the app) & DSS (in the case of the website) to attribute the data coming from referral campaigns. Further, we use key validation checks like device IDs, email (fake/disposable email ids), domain validation, digital reputation, mobile number validation (disposable phone numbers), APP Cloning, and IP data to analyze and detect fraudulent sources. We provide real-time status of the fraud along with fraud score to the advertisers and help in blocking the fraudulent device IDs. Real Case of a Leading Hotel Chain Case Analysis About 23% of the coupon codes were misused. The same coupon code was used multiple times for a device ID. Invalid email IDs were used and were coming as repeated many times. We tracked email IDs with Google (we can validate an email ID without sending an email) and identified bad email IDs. A bot pattern was detected where the simulator was triggering 2 times for a device ID and the same process was repeated for all the new device IDs. We identified the Phone Numbers which were being used were fraudulent. The fake/Virtual phone numbers were being used which did

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How to Build a Robust Approach to Brand Safety?

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Programmatic native advertising is on the rise. It is a technique to incorporate marketing assets and messages into a publisher’s feed. Native ads that are purchased and placed programmatically provide brands with the opportunity to capitalize on increased relevance and personalization. Machine learning and contextual signals allow programmatic native ads to be tailored to the user, resulting in better performance for advertisers. A report shows that 1,900 advertisers invested $2.6 billion in the space between January and May 2021. Compared to 2020, when 926 advertisers spent $1.9 billion, it’s clear that advertisers want native advertising to be automated in order to maximize scale and efficiency. Yet, the growth of programmatic trading also poses a threat to brand safety, with some environments posing a risk of negative associations between buyers and sellers. In one recent instance, the Washington Post and New York Magazine inadvertently featured porn from an adult network whose video platform Vidme, which the publishers were using to embed other video content. The safety of brands is always a concern across the digital advertising industry, but it is particularly crucial for native ads. When ads are seamlessly integrated into their environments, it forms even stronger links between brands, publishers, and the content on the page. In order to maintain and enhance a close relationship with consumers, quality, relevance, and suitability are vital. In order to protect their reputations and identify optimal native placements, brands should consider the following steps. Choose your partners carefully Select ad networks that prioritize media security for programmatic and non-automated native ads, and monitor quality continuously. These trusted ad networks underpin private marketplaces (PMPs), which are where brands can find a reliable portfolio of premium publishers. PMPs establish a direct, transparent connection between the buy and sell sides, so advertisers can be assured that available media is vetted and meets their messaging and values. Brand safety requires careful selection of trading partners and native placements, but how can buyers ensure that they are not limiting their opportunities? To give advertisers granular control over what kind of content surrounds their ads, advertisers typically employ methods such as blacklists, whitelists, and keyword blocking. Despite being extremely valuable, especially when combined with other verification methods, these come with risks of their own. In order to avoid missing out on unexpected opportunities, advertisers need to be prepared to take action proactively. The rise in misinformation in 2020, for instance, led many brands to take a cautious approach to advertise around Covid-19 content. The pandemic was high on the news agenda, and therefore, brands minimized the size of their campaigns when not all content was safe. In fact, authoritative, optimistic, and educational content created positive associations for some brands. In order to take advantage of these opportunities, brands should adopt tools to identify native placements that are not only safe but also highly suitable. Artificial intelligence skills are used to power advanced contextual technologies capable of natural language processing (NLP) and semantic analysis. This technique extracts meaning from sentences and words based on grammatical structure, allowing one to categorize context and measure overall sentiment. Thus, contextual targeting ensures that environments and advertising content complement each other, enhancing brand messaging and engaging receptive audiences. Brands can then make more informed decisions based on the suitability of native placements to their brands. Make sure you ask the right questions Before planning how to mitigate risk, brands should speak with an agency or partner and ask three essential questions: What kind of protection does your solution provide for my brand? One-size-fits-all solutions do not account for the differences in values, objectives, and target audiences between brands. As a result, brands should find partners whose tools support customizable brand safety criteria. They can then select the media that is most appropriate and relevant to their products or industries. Are you able to prove that the technology works? To protect against risk, proven success is paramount when selecting the right partners and tools. Partners should demonstrate, for instance, how advanced brand safety technologies such as semantic analysis and natural language processing result in greater engagement rates. There is predicted growth in the NLP market from $3 billion in 2017 to more than $43 billion in 2025 – and where there is an investment, there is value. Therefore, you should ask the partners utilizing these technologies for results. What impact will your technology have on my reach? A brand’s safety is nuanced, and the technologies used to protect it must reflect this. By understanding linguistic complexities and reading content as the human brain does, brands will be able to take advantage of all possibilities to enhance their reputation through relevant and appropriate native placements. Reaching target audiences in a safe environment shouldn’t mean limiting reach. It is important for brands to make sure their digital advertising complements surrounding content and meets audience expectations. The success of native placements depends on how ads are integrated into the user experience. Conclusion An automated approach can enhance efficiency, but brands need a tailored strategy to determine brand suitability and build connections with ad-weary audiences. For native advertising to be effective, brands must partner with trusted ad networks, discuss brand safety criteria with their partners, and adopt technologies that identify brand-safe placements. By doing so, they will enhance their reputation by delivering relevant and engaging messages in a safe and optimal environment. By implementing mFilterIt’s Brand Hygiene Protection, brands can achieve higher relevance, revenue, and target audience. This solution helps to keep ads away from unsafe environments, fraudulent affiliates, and untrustworthy publishers.

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How Can Brands Optimize Digital Shelf on eCommerce Platforms?

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The Share-of-Digital-Shelf on e-commerce platforms measures the recurrence of a brand’s product listings versus the competition based on keywords. It informs brands about their discoverability on eCommerce platforms like Shopee, Amazon, Flipkart, etc. Higher discoverability through keyword searches could likely trigger higher click-through rates, add-to-cart actions, conversions/sales, etc., of organic and sponsored listings. Brands optimize their Product Display Page (PDP) using SEO and customer-centric information to optimize their discoverability on the digital shelf. Product listings with higher visibility or ranking often have a higher chance of achieving the SOS goals. Optimizing SOS requires enhancing the findability of paid and organic keywords, improving the perfect page analysis scores, finding customer-centric touchpoints, etc. Optimizing the digital share-of-shelf on eCommerce platforms is a dynamic and ongoing process, which can be easily comprehended using eCommerce Competitive Analytics, a.k.a. mScanIt. Moreover, the solution offers advantages like keeping an eye on the competitor’s digital shelf progression across eCommerce platforms and helps to identify opportunities for growth for your brand. How to Optimize Digital Share-of-Shelf on eCommerce Platforms? Table of Content Monitor the Digital SOS Ensure Brand Compliance Across e-commerce Platforms Address Consumer Grievances in Real-Time Discover eCommerce Trends Monitor the Digital SOS The easiest and simplest solution to keep track of digital SOS is by using eCommerce Competitive Analytics. The digital shelf analytics reveals your brand’s share versus the competitors on generic, brand, and competition keywords. Brands with higher discoverability and visibility on keyword searches acquire a higher SOS. In addition, analyzing the digital shelf at category, variant, SKU, and other levels gives in-depth information about the brand’s performance and keeps track of the competitor’s performance in real time. Therefore, brands can find opportunities for scaling up their business by monitoring the digital shelf. Ensure Brand Compliance Across e-commerce Platforms Third-party, or unauthorized sellers of the brand products often give discounts, promotions, offers, etc., that create MAP (Minimum Advertised Price) violations. In addition, it causes the diversion of brand customers to sellers that could even provide duplicate or counterfeit products and create a bad reputation in the market. Besides this, brands need to monitor their PDPs continuously, as consumers constantly share their reviews and ratings, which could include remarks like fake, duplicate, counterfeit, etc., as consumer feedback. Moreover, it could help find sellers not associated with the brand and report them to the eCommerce marketplaces. At times, the product information could also consist of discrepancies and need attention to detail so that the customers no longer get misled by third-party or unauthorized retailers. Address Consumer Grievances in Real-Time The Customer Q&A section of the product pages on eCommerce platforms often consists of problems, queries, tell-tale signs of customer demands, etc. At times, multiple questions might require a similar answer. For example, smartphone brands commonly find this question in different forms – “does it come with an adapter?” Being a proactive brand that monitors and answers consumers’ queries within 24 hours can certainly impact add-to-cart actions and conversions/sales. Similarly, mScanIt’s proprietary Sentiment Analysis consists of sentiment intensity scales. Whenever the negative or neutral scale moves upwards, it is time to find the cause for the same from the word cloud. The word cloud highlights the problematic areas and the number of times they occurred in duration on an eCommerce platform under the sentiment themes. Customers often leave feedback under the reviews and ratings related to packaging, delivery, counterfeit/duplicate products, etc. The brand could allocate the relevant teams to address the buyer issues and might influence the sentiment intensity, as other customers would read the same replies making a decision. Moreover, brands often leave their customer service number in replies, creating a similar impact and enabling brands to control R&R and influence the overall sentiment score. Optimize the PDP with the Search Intent The product listings on eCommerce platforms should match the common searches of the consumers. Monitoring aspects helps brands to find their areas of improvement, such as keywords that have a higher SOS for the competitors and are usable under specific product variants of the brands. Our solution also detects pin code level SOS, which helps brands segregate their product listings based on the SOS of a particular geo. Higher SOS of the competitors would also mean greater frequency of their product listings. Therefore, brands can optimize the PDP of similar variants to increase the recurrence of their listings. At times, brands can find the intent searches by analyzing competitors’ keywords with the highest SOS. Analyzing the title, product description, bullet points, A+ content, and other relevant detail scores can help see the number of mentions of the intent-based search keyword and enable SEO optimization. Conclusion Optimizing the factors influencing the digital shelf positioning and sharing is a brand’s priority, made possible using eCommerce Analytics, a.k.a. mScanIt. The solution detects sentiment analysis, reviews and ratings, Q&A, and other factors in real-time, which helps brands address consumer grievances, optimize product pages, ensure eCom marketplace compliances, etc. Our solution is used by world leaders in finance, banking, food, Q-commerce, Quick Service Restaurants, gaming, beauty, fashion, and other industries.  Get in touch to learn more about the digital shelf.

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Why Does Page Analysis Matter for eCom Brands?

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Page analysis is a part of discoverability and signifies the search rank of your brand’s versus the competition on organic and sponsored listings across ecommerce platforms. Page analysis signals brands that would likely have the highest click-through rate (CTR), create more awareness on e-commerce platforms, etc. Generating brand awareness is crucial for search engine optimization. According to a report, 17.8% of global search rankings of brands are influenced by brand awareness, which is among the leading SEO factors. Besides this, results derived through page analysis often drastically influence a brand’s marketing and advertising decisions across e-commerce platforms like Amazon, Flipkart, BlinkIt, BigBasket, etc. The parameter helps brands make marketing decisions like deciding the type of campaigns they should run on multiple eCommerce platforms, e.g., paid searches, banners, display, etc. Hypothetically assuming that the listing doesn’t appear in the top ten results of any specific  keyword search, or re-appears less than the competition on each page. In that case, your competitors would likely achieve higher search rank, visibility, discoverability, etc. The page analysis could vary across platforms, time frames, categories, etc. Brands could use this detail to create multiple strategies for their listings on these platforms where the product is listed. Moreover, SEO plays an important role in search rankings, and brands with the highest discoverability have likely optimized their listings for specific keywords, which is also an important activity for eCom Brand Managers. It is a well-known fact that brands with the highest eCommerce platform listing often appear higher on search engine listings. It means they would have a higher share of voice than their competition on respective e-commerce platforms. Brands often optimize their product pages to achieve the highest ranking on the keyword search results. Our experts continuously analyze the product description, title, review scores, etc., which helps in enhancing the position of their listings on the Digital Shelf. Another prerogative of page analysis is to check if your brand’s listings make their mark on the prominently searched consumer keywords across e-commerce platforms. Imagine that you are a smartwatch brand that is also running sponsored ads for your product, but consumers don’t find them in the top three pages or the top ten results against the commonly searched keywords. In that case, there is a high chance that your competition must be grabbing that space. How Does mScanIt Help You With Page Analysis? mScanIt helps the brands understand the overall search rank of their brand w.r.t. to the competition and get a more detailed insight on the search rank of multiple pages of any eCommerce platform. Why does page-wise search rank matter? Besides revealing the top-ranking listings on each page, it also states whether your brand listing is visible on the top results/pages and the change in your search ranking over time. eCom Competitive Analysis, a.k.a., mScanIt, powered by mFilterIt, measures the following aspects to reveal accurate page analysis: Search Rank – Overall and Page Wise: The higher the page ranking, the higher the chance of click-through rate. Our solution curates the overall search rank of a brand/product being listed on the first three pages. mScanIt also detects the page-wise ranking of the product or brand versus the competition. Keyword Search Rank: A subset of search rank is the keyword search rank, which establishes your brand’s position versus the competition based on keywords. It is beneficial as it helps you discover your product’s positioning when your brand name is included in the searches or ranking of your brand in your competitor’s brand-based keywords. Pro Tip by Praveen Dhama, Manager, mScanIt: “Lower the search rank higher the chance of product being visible on the top ten listings on the eCommerce platform first-page.” Conclusion Search rank is pivotal for harnessing higher CTR, generating brand awareness, increasing discoverability, etc., on e-commerce platforms. mScanIt helps brands achieve these goals by measuring accurate page analysis through detailed insights and real-time reporting. Measuring page analysis also defines whether your brand meets the product searches of the most commonly searched keywords for any specific product which usually the end consumer is looking for, e.g., running shoes, tablets, and smartphones. Set up a meeting with us to learn more about the benefits of mScanIt’s page analysis for your brand, such as acquiring higher discoverability, easing customer journey, acquiring a higher market share, etc. To know more, get in touch with our experts today!

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brand-safety

Brand Safety: The World Before and after Digital Marketing

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Brand safety has been significantly impacted by the evolution of technology, content, and sharing platforms. In just 25 years, brand safety has evolved from the pre-digital dark ages to the forefront of advertising technology. In the pre-digital era, brand safety largely consisted of tangible issues such as poor product placement, trademark infringement, and bad press. Simple isn’t always better though, it was hard to target, scale, and measure campaigns, and a lot of creative energy was wasted on things computers now can do. A brand’s safety concerns today include more than just traditional print advertising, including websites, blogs, and social media platforms. Marketers and advertisers must now change their approaches to brand safety as a result. Here’s how brand safety has evolved over the years: Prior to Digital Marketing  In the past, advertisers used billboard ads and print ads to entice customers to make a purchase. During that time period, these methods were effective, but they posed brand safety concerns. The placement of ads could negatively impact a company’s reputation. In the past (and still today) advertisers were concerned with: Placing the logo incorrectly. It only takes something like a Turkish Airlines ad on the side of an escalator having an aeroplane flying straight into the ground or a Starbucks sliding door van failure to turn a basic logo placement and brand name into a negative one. You see Starbucks ‘logo followed by “Sucks” as you close the door of the van. This is a prime example of the poor placement of a logo. Poorly placed products. The placement of certain products next to items in the store could also undermine brand safety. Imagine you are in the grocery store and see a display of condoms next to the kid’s section. Your reaction? We’ll let you fill in the blanks, but there’s likely to be nothing positive. Products that are used negatively. The backlash against a brand as a result of products being used for a negative purpose is not new. A famous example of it is the 1994 white Bronco chase involving O.J. Simpson, which predates digital marketing. Thanks to Simpson, the Ford Bronco became infamous. People immediately think of Simpson’s getaway vehicle when they hear the word Bronco. This is not what Ford intended. These are just a few of the obstacles advertisers faced. After digital marketing burst onto the scene, these issues developed into a whole new set of problems. After Digital Marketing  As digital advertising evolved from traditional advertising and reached a wider audience, it also raised concerns about brand safety. Here are some of them: Poor programmatic ad placements. In addition to poor product placement, programmatic ads have also been placed next to non-brand safe images and articles and on unsavoury websites. As an example, Applebee’s dancing cowboy commercial appeared on CNN on a split-screen alongside the headline “Russia invades Ukraine”. The QSR chain reported its disappointment to CNN and stopped spending with the broadcaster. Hijacking your brand by rogue groups. In an anti-marriage equality ad, Meghan Trainor’s brand and likeness were used without her permission. A group of individuals stole her image from the internet and used it to make their own propaganda. Trainer soon found herself dealing with the damage. She’s not the only one. Also, the TIKI torch brand was inadvertently linked to a brand safety issue when they were used at a white supremacist rally. Disastrous PR and influencers. Influencers work with brands to increase audience reach. Nevertheless, sometimes this can backfire for both the influencer and the brand. Consider yourself an influential figure like beauty guru Huda Kattan. You are featured in an ad for Sephora that appears on an unsavoury website. Or perhaps Kattan has a PR disaster, and Sephora is forced to decide whether or not to continue running her ads (not unlike Papa John’s). Either scenario could be disastrous. The negative effects of YouTube. YouTube lost 5% of its top North American advertisers due to brand safety in 2017. The key cause: Ads were being served on extremist content. Top brands such as Netflix, Nissan, Under Armour, and others were affected by this major brand safety issue. Nissan and Under Armour decided to pause their YouTube ads because of this. It’s time to take control of advertising  Brand safety is fluid in digital marketing. It is difficult to enforce and regulate because there is no universal rating system. Advertising placements that are negative for one company may be beneficial for another. What’s more concerning is that YouTube is asking creators to rate their own videos given the massive amount of content they have to control. Creators aren’t unbiased, and most aren’t familiar with offensive or safe content. Marketers and advertisers need to move beyond antiquated thinking and focus on how to deal with brand safety right now. Engage with a brand safety solution provider such as mFilterIt and be assured that your digital assets are devoid of threats. We help in protecting your brand reputation by keeping your assets away from high-risk digital content for both web and app. Get in touch to know more. To know more, get in touch with our experts today!

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