Blog - mfilterit

Listen to Your Customers: They Know the Best.

Leave a Comment / Blog, Digital Shelf Analytics / Noopur Mathur

How analyzing reviews helped an FMCG brand to optimize their packaging? In India, we have a saying, “ग्राहक हमारे भगवान हैं” which means “customer is our god.” Ratings and reviews are invaluable sources of getting to know your customers. The shoppers share their personal buying experiences through them. They share the qualities and experience they love with the product, things they are disappointed with, inform about unfocused or undermined USPs of the product, at times talk about better experience with competitor products and lot more. The information customers provide through reviews is invaluable for brands as it helps to understand buyer personas, find new trends, and resolve brand / authorized seller or product issues, influencing the buying decision of the on-lookers. Brands constantly need to weigh the value of their customer’s positive, negative, or neutral reviews to figure out the change in market perception, competitive edge, outcomes, and more. A couple of interesting facts that showcase the impact of reviews for eCom brands: 19-25% of customers believe in the authenticity of customer reviews, and a large proportion makes final purchase decisions based on them. 92% of customers stay away from brands with negative reviews. We also analyzed the impact of reviews on a few brands and discovered that packaging was a significant issue constantly faced by one of our FMCG clients. Our analysis revealed the following challenges: The Struggles of the Brand Even after over 50 years of serving their customers, the FMCG brand was having trouble assessing the challenges that people were facing in context to their products. They wanted to deep dive into the feedback by the customers to understand the market sentiment for their products. The lack of transparency in feedback, which in offline case used to be from the distributors, made it difficult for the brand to identify the source of issues, whether the production issues or the delivery issues. E-commerce platforms have become mediums, wherein brands can directly understand the customers’ feedback of the product, brand, or seller by analyzing the reviews and ratings section. Unfortunately, the rapidly growing rate of reviews on multiple product variants made it challenging for their marketers to develop a subjective view, and sight the biggest problem or categorically segregate the riveting pain points of the reviewers. This was the time when collaboration between the brand and mScanIt started. How Listening to Customer Helped them Grow? Our eCom Analytics solution, mScanIt was deployed and collected data from all of the areas that affect a brand’s performance. This information helps in understanding customer personas and scaling up the consumer base. Using these insights, brand could make more intelligent decisions based on the data, and eventually, propel the growth in terms of revenue. Let us explain the step by step approach: Our program gathered and analyzed consumer evaluations and ratings of a product, sorting them into categories such as delivery, taste/flavor, quantity, packaging, and availability. It further classified the comments and assigned a sentiment value (Positive/Negative/Neutral) to them based on the consumers’ purpose of leaving a review. We reflected this data on the dashboard & showed the complete listings and all the comments made by consumers. We also analyzed the word clouds of negative reviews fetched from the website. This way brand can notice the negative keywords being used for its negative reviews. Interactive Insights from this data are shown through charts, which helps the brand to understand the areas of improvement. Success Enjoyed by the Brand The brand witnessed huge success in terms of brand equity and customer satisfaction. The insights provided by our solution helped them create a strategy to manage product reputation. The issue with packaging was highlighted and corrective measures were taken resulting in drastic reduction of negative reviews. The competitive analysis helped the brand to gain a competitive edge. Our technology assisted the business in to get insights about the page content, convincing shoppers to buy their products. The accuracy of data is 92-95 percent. Furthermore, the firm was able to keep an exact account of its product feedback because of the real-time updates and daily reports it received. The dashboard of our solution displayed sentiment values, sentiment scores, and themes based on consumer reviews enabling them to create relevant strategy. Conclusion Ratings and reviews are fantastic ways to get feedback. Keeping an eye on ratings & reviews daily enables the brand to keep a competitive advantage. Besides this, mScanIt’s dashboard reveals key takeaways under the insights segment, allowing brands to take corrective measures at the right stage. E-commerce marketplaces have a high competition among brands. A single source of truth and trust that delivers insights into competitive intelligence metrics like share of shelf, stock availability, banner visibility, etc., can become crucial in making business decisions. Our eCom solution, mScanIt, is a one-stop solution for monitoring such metrics of your products vis-a-vis the top competitors and gain competitive edge. Get in touch with us to schedule a demo and avail the advantages of eCom Competitive Analytics for your brand.

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You’re Losing Genuine Users. Know Why?

Leave a Comment / Ad Traffic Validation, Blog / Expert Opinion

Imagine you’re running an ad campaign to generate leads for your clothing brand. You have also partnered with an ad fraud detection solution to detect and eliminate invalid traffic. However, one of your legitimate consumers raises a concern. Their card was blocked while making the transaction. Who could be responsible for this? You can blame the fraud detection vendor as they might have flagged a genuine consumer assuming it to be a fraudulent source. While ad fraud prevention is an essential element to eliminate fraudulent sources from ad campaigns, there must be a holistic way to differentiate between a genuine user and a bot without compromising the security of the ad campaigns. This mistake not only costs the brand their revenue, but also the trust of a legitimate user. Know how brands are impacted by this and what you must look for in an ad fraud detection vendor to avoid the case of false positives. What is a false positive? A false positive happens when a legitimate transaction is flagged as suspicious resulting in declining of payment or blocking of a genuine account. As a result, a request from a genuine customer is identified as a fraudulent source. This error happens when a non-fraudulent transaction is flagged by a fraud detection system resulting in the decline of the transaction. Why do false positives take place? The fraud detection systems are programmed to detect fraud patterns in a campaign. However, sometimes the system fails to accurately differentiate between a legitimate and a fraudulent request. As a result, the brand has to bear the collateral damage of false positives. To reduce the consequences of false positives, organizations have experimented with different approaches to try and differentiate between a legitimate and fraudulent user. Based on a checklist This list includes the details like IP addresses, email addresses, and Device IDs that have been identified and marked as either “safe” or “unsafe”. For example, if an IP address is flagged for being a source of malicious or fraudulent activity, then it will be “blacklisted”. Unfortunately, these lists are no longer viable to detect fast-evolving fraud. These lists require continuous refreshing as they get outdated in a short span of time. And these manually designed lists are often imprecise, corrupted, or at the worst expired. As a result, these reputation lists often lead to an increase in the number of false positives. Based on Rules The rules engines are software that is programmed to take actions based on specific criteria. For example, if a business has made a rule check to analyze the billing country and IP country. In this case, any mismatch will be an indication of a malicious account. These rules can be effective in some cases, but it has many limitations. The rules are highly reactive, and the results are based on past experiences. Furthermore, the rules are hard to manage especially in the case of large-scale data. As a result, the false positive number goes up. Based on Rule-based Machine Learning In this process, a training dataset is processed with the help of AI and ML. In this case, all the possible outcomes are programmed with the correct answers to train the algorithm. With the help of supervised machine learning, the brands can detect certain patterns and insights from a set of data. This is further used to make predictions about future outcomes. This is a strong tool for fraud detection, but it has its own limitations. For example, in SML the algorithms require a certain command to perform their tasks. This limits the ability to detect new and unknown fraud attacks. And as the fraudsters adapt to new techniques at a faster pace, it is impossible for an SML-based solution to keep pace. Why do brands need to act against false positives? Friction in users: Due to false positives, a genuine customer becomes the biggest victim. The most common case is when a customer attempts to pay to make a purchase, but for some unknown reason, the payment gets declined. A decline of a payment for an interested user can turn into a case of inconvenience and they drop out to purchase from a different brand or platform. Reputational damage: According to a report, 38% of online shoppers abandon their purchases when asked for an additional security check. They consider switching to a different brand when they experience poor service. Legitimate customers consider multiple layers of security and payment declines as an insult and often don’t take it in a positive light. Due to the inconvenience, sometimes they also end up spreading negative word-of-mouth which is a nightmare for the brands and tarnishes their brand reputation. Loss in revenue: Due to false-positive cases, not just the genuine consumers get impacted but also the brands. The brands lose the real customers and the potential revenue from genuine sales. In this case, the credit card companies have to bear the cost as they don’t get their fees. Questions to Ask your Ad Fraud Vendor to Reduce False Positives Do they analyze the entire lifecycle to ensure comprehensive protection? Do they look at all the possible types of fraud attacks? Do they identify and take preventive actions for new & emerging threats? Do they differentiate between legitimate and fraudulent activity in real-time? How mFilterIt ensure to reduce false positives? When detecting fraudulent sources in the ad campaigns, we expect an average of 4-5% false-positive cases. However, to ensure that the brand doesn’t have to lose genuine customers to protect its ad campaigns from fraudsters, our ad traffic validation suite ensures to focus on various parameters like: Deeper Fraud checks Evaluation for every data set to make a decision on Prioritization for sources that will convert Able to detect sophisticated BOTS and emerging threats Analysis based on Behavioural and Deterministic data Conclusion A true ad fraud detection and prevention solution must be effective enough to help the brand in different parameters. A successful fraud detection will happen for a brand when it enhances the customer experience and nurtures them while keeping

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Why Should Brands Measure the SOS of Their Sponsored Listings?

Leave a Comment / Blog, Digital Shelf Analytics / Anukirti Jain

Share-of-Shelf of your sponsored listings on eCommerce platforms like Amazon, Bigbasket, Flipkart, etc., measures the percentage of your brand’s discoverability vis-a-vis the competition on paid keywords. Paid search is a massive opportunity for brands, as it allows them to rank ‘at the top’ for the specific keyword searches on eCommerce platforms. However, brands could get outbid on keywords by their competition, which impacts their rankings. Therefore, monitoring and measuring the SOS of the sponsored keywords has become vital for brands. Another aspect of measuring the SOS of the sponsored listing is knowing the brands with the highest discoverability. Through this, a brand can detect the focused or targeted keywords of its competitors. Moreover, the brand can also detect whether or it is discoverable on the most popular keywords? If it isn’t, then, the brand needs to check the Product Display Pages (PDPs) and optimize them with the most popular keywords to become discoverable on the eCommerce search engine. According to a report, the worldwide retail eCommerce sales from Amazon accounted for $468.78 billion between 2017 and 2021. In India, 47% of the digital advertising expense on the eCommerce industry was through paid searches. It means a significant proportion of paid search campaigns were running on multiple eCommerce platforms. Brands that ran campaigns on Amazon acquired a piece of the sale and increased their revenue. Therefore, becoming discoverable on eCommerce platforms certainly aids sales/conversions. Besides revenue, brands run paid search campaigns on eCommerce platforms to acquire higher traffic, increase the ranking, enhance visibility and brand awareness, etc. So, whenever their competitors have a higher proportion of the digital shelf, especially on brand-specific keywords, it is a problem that needs an immediate solution. How to Effectively Measure the SOS of Sponsored Listings on eCommerce Platforms? Top Product Results by Keywords Searches The positioning of a sponsored product listing on an e-commerce platform, based on keywords tells many stories to a brand. It could inform the brand that is bidding the highest on a specific keyword and the type of keywords (generic, competitor, and brand) that have the highest share of digital shelf for your brand vis-a-vis the competitors. Brands can use the information to detect the top performing paid searches of their competitors on each eCommerce platform in their respective categories. By evaluating the results of the sponsored digital shelf results brands can build strategies to get an edge over the competition. How? It can build campaigns around the most relevant keywords and attract a higher audience base. Moreover, it can use the keywords in the title of its multiple variants to increase consumer interest in the product and intent to purchase the product. Brands with the higher number of sponsored listings acquire a higher share of shelf for keywords. Moreover, the share of shelf for the sponsored listings is often calculated for the top ten search results and the top three pages. Therefore, building strategies around sponsored listings based on the SOS can boost the positioning of the listing and the visibility of the brand. My suggestion to the brand’s is to “use a keyword-mix which includes competition brand keywords, along with their own brand keywords, which is hardly practiced by most brands and would help you to acquire a larger Share-of-Shelf.” Share of Sponsored Listings on a Sub-Category Level Imagine you are a pickle manufacturer and are running campaigns on ‘mango pickle’ keyword of an e-commerce marketplace. Consumers use the same keyword from their respective geo-locations to buy the product, however, your sponsored product listing is at the bottom of page. Do you think they would make an effort to scroll down and add your product to cart, especially if you are a new brand? Most probably ‘No.’ Enhancing the page position of your brand’s products and thereby enhancing visibility of your sponsored listings is necessary to influence the buyer behavior towards your brand. It is possible by: Evaluating the overall SOS of sponsored listings at a sub-category level, Detecting & retargeting the top and most relevant keywords of your competitors under specific sub-categories, and Finding the top sub-categories that would increase the SOS of sponsored listings. By taking these measures, your brand can substantially increase its SOS of sponsored listings on multiple sub-categories. Besides higher revenue, your brand could enhance its consumer base and find new target audience in its niche. Recently, we shared a case study in which a brand used the strategy of monitoring competitor keywords. By doing so, it found that the SOS of its sponsored listings for competitor keywords was 5%; however, after gaining information on the competitor’s top performing keywords, it started bidding on some of them. Within a short span of time, SOS of its paid searches jumped to 14%. (Read more) SOS Overview of Sponsored Listings Monitoring the SOS overview of sponsored listings would give a clear analysis of the best performing brands based on paid searches. Moreover, you can evaluate the presence of your brand vis-a-vis the competition on an eCommerce marketplace through keyword bidding. As a result, you can find the best performing platforms for your brand. Additionally, your brand measured the share of shelf for sponsored listing using specific keywords. Therefore, you can find the best performing keywords of your competitors across multiple eCommerce platforms. By doing so, you can revamp the keyword bidding strategy to enhance your overall share of shelf for sponsored listings. You can even share the information across the organization using exportable reports through eCommerce Competitive Analytics, a.k.a., mScanIt’s dashboard. The actionable insights would enable your e-commerce managers to evaluate the platform-wise strategies and take measures for boosting the SOS of paid search results. Conclusion Share-of-Shelf of sponsored listings can bring insights related to products, brands, and competitors. Measuring the success of paid searches on eCommerce platforms through eCommerce Competitive Analytics is possible by deep-diving at a sub-category, search rank, overall, and other levels of SOS. The insights and intelligence derived through eCommerce Competitive Analytics, a.k.a. mScanIt, enables your brands to change your ongoing/upcoming advertising and marketing campaigns across multiple eCommerce platforms. For the

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DCB Fraud: A Distress for All

Leave a Comment / Blog, Direct Carrier Billing / Expert Opinion

Direct Carrier Billing (DCB) is a subscription model offered by carrier providers. The charge of the availed subscriptions is added to the monthly mobile bill or deducted from the available balance, and generally transactions are made using a single click. According to a source, the DCB market is expected to grow by 9% between 2018 and 2022. Offering convenience through this model has substantially increased purchases & eliminates the need to fill in card details and account sign-ups. The user is already using the existing carrier number. The estimate number of smartphone users in India would reach 1132.9 million by 2025. India’s Average Revenue Per Paying User (ARPU) reached $3.9 by March 2021. Cybercriminals have been infiltrating mobile devices through general trojans, ransomware, password trojans, and others , with an average 93.93% of devices affected by general trojan malware. The Biggest Challenge of Operators Fraudsters use baits like malware/bots, Potentially Harmful Apps (PHAs), copycat apps, pirated content for downloading, etc., to acquire device access of unassuming device owners. Their two most crooked methods for DCB VAS frauds are iFrame and device farms. The bots/malware installed on the user device can even bypass USSD, CAPTCHA, and OTP & cause DCB fraud. DCB fraud means the carrier user is wrongly charged for subscriptions they have not made. Customers often disregard the charges, as they are minuscule, and rectifying them would take a toll of their time, with the added burden of talking with customer care, which often has long queues. End-user often becomes a victim of fraudulent charges. The mobile users who are victims of the unprovided/un-availed services blame the carrier providers for it. The operator must also answer to the telecom regulatory authority and face heavy fines or stop the services entirely. The lost faith in the carrier provider redirects revenue to competitors. Creates Complications for the Merchants Merchants suffer a loss of revenue if they become a victim of DCB fraud. They become as much liable as the MNOs, and in some instances, even more. Merchants often use marketing/advertising to increase their VAS subscribers. Unfortunately, fraudsters have found loopholes in their traffic generation methods. The actions of the cybercriminals lead to large-scale claims accumulated through defrauded customers, which evidently leads to fines, service cuts by the regulators & telcos, or suspensions. Regulators may adopt new methods for enhancing their payment security, which could diminish the VAS subscriptions, as consumers constantly face frictions and might even increase abandoned carts. Solution Against DCB Fraud mFilterIt’s DCB fraud solution offers a solution that helps brands across the globe to separate real users from bots/malware through our AI, ML, and data science. The solution validates the incoming traffic in real-time and safeguards brands at every step of the journey. It is an integrated fraud management solution for aggregators and operators. DCB fraud solution uses deterministic, heuristic, behavioral, and probabilistic parameters for classifying frauds. It eliminates frauds by risk scoring and real-time blocking. The live dashboard and real-time alerts optimize customer value management, enhance LTV, drive ROI, and diminish DCB fraud complaints. A Few Other Tips Don’t click on unnecessary URLs or visit suspicious pages/untrusted sources. Analyze the loss of partnership, revenue, and brand value caused by DCB fraud and take measures to overcome them by implementing mFilterIt’s anti-fraud solution for DCB. Take advice from our core founder and management team on the best practices or methods of implementing our solution and eliminating ad fraud. Conclusion The safety of the consumers also falls on the carrier provider in case of DCB frauds. Brands also lose trust, revenue, and customers if they cannot trust the carrier provider. The need to eliminate and restore the faith of the customer is now. This scenario is possible through DCB anti-fraud solution and implemented by global brands that want to keep their market reputation and sustain their market share. Moreover, the solution helps to detect and eliminate threats of real-time bot/malwares. Connect with us to learn more about the advantages of eliminating frauds in the DCB VAS ecosystem.

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What Aspects Does Sentiment Analysis of eCommerce Platforms Reveal?

Leave a Comment / Blog, Digital Shelf Analytics / Expert Opinion

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?

Leave a Comment / Blog, Digital Advertising / Expert Opinion

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

Leave a Comment / Blog, Digital Shelf Analytics / Anukirti Jain

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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4 Signs to Update Your Product Page on eCommerce Platforms Now!

Leave a Comment / Blog, Digital Shelf Analytics / Expert Opinion

The product page of most eCommerce platforms provides relevant, helpful, and user-friendly information that enables customers to make the final buying decision. It includes the technical know-how, price, delivery, & key, USPs, or standalone features differentiating it from the competitors. Simultaneously, it also consists of Q&A and reviews & ratings, which play an important role in the final buying decision. According to our research, 35% of customers are most inclined to buy a product with positive reviews. The reviews or Q&As could consist of unanswered queries, the positive aspect of the product listing, the brand/seller details, delivery timing, etc. Customers tend to notice whether the most commonly asked question in the Q&A have been unanswered or answered by the seller. Based on the response the customers may make the decision of engaging or disengaging with the brand. If they disengage, buyer might choose alternative sellers or competitor products. However, this is just a single sign which states that the product page needs updation. Here are a few more: 4 Reasons to Update Your Product Page, as of Now! Competitors Have Started Using Your Un-Mentioned USPs as Features If you are failing to take advantage of eCommerce Competitive Analytics to your advantage, competitors have taken that leap by monitoring your brand’s product listings in real-time. The ongoing smartwatch trend is the best example of this. “Sleep monitoring” became a key feature that most brands considered a general feature. Did you know? The global Sleep Economy, i.e., products, applications, or services associated with sleeping, would reach $551 billion by 2023 (Source: Statista). However, post analysis, one of the brands discovered that the product pages of some of the smartwatch variants that included this feature had minimal mention. In contrast, competitors capitalized on it by displaying it in images, product descriptions, general information box, etc. Certainly, customers looking at this feature in smartwatches developed an interest in the brand once it added the feature to the content spaces on the product page. But unfortunately, the brand failed to discover that potential customers continually asked about it in the Q&A section. A real-time eCommerce analytics solution could have triggered an alert to the brand to address the customer queries for the select variants. Therefore, it lost an opportunity window for increasing the overall revenue, especially when smartwatch trends were high. Change in eCommerce Trends Customers on eCommerce platforms like Shopee, Lazada, Amazon, etc., often come across trending products as bestsellers and discover features that were originally unknown. As a result, brands keep updating their product listings on eCommerce platforms to match the growing needs/demands of the consumer, boost add-to-cart actions, and eventually increase monthly revenue. At times, a seller receiving a high level of product reviews in a particular duration could become a favorite choice for customers. Consumers might leave feedback that states eagerness to buy the product from the particular seller. Therefore, monitoring the reviews and ratings across eCommerce platforms becomes important for brands. It nurtures themes that provide information about the most/least demanding features of a product listing. Brands could also come across competitor trends, such as cost savings with bundled products, variants with qualities not mentioned in similar brand products, etc. Tweaks in Product Page Scores of the Competitors According to a report, 15% of online shoppers made their purchasing decision based on exclusive content or services offered by the brand. The percentage seems small; however, the global number of eCommerce buyers and internet users is continually increasing each year, likely meaning larger revenue for the eCommerce brand. So it doesn’t seem small now? Does it? Tapping into the consumer’s mindset or finding the ongoing buyer personas is not an easy task. Still, it certainly offers its perks (higher CTR, add-to-cart actions, and revenue/sales). If your competitor has suddenly improved the product page scores and outranks yours, it would most likely bend the trends more towards the competitors. Revamping the product page to achieve the highest scores at all levels becomes the solution to this problem. Your brand would need eCommerce Competitive Analytics to keep track of the competition and measure the scores in real-time. Uninformative/Disengaging/Inaccurate Details Curating customer-centric details while managing the brand persona can become challenging for eCommerce marketers; however, it is the need of the hour. At times, disengaging/disassociating with certain form of details can even build a better brand perception in the minds of the consumers for the particular listings. Wasn’t this engaging and informative? Exactly! The content of the product pages on eCommerce platforms revolves around the same concept/idea. However, the content sometimes becomes outdated or is no longer aligned with the ongoing trends and changing buyer personas. But brands can discover inaccurate information through consumer reviews or the negative word cloud of sentiment analysis. Brands need eCommerce Competitive Analytics, a.k.a., mScanIt, powered by mFilterIt to find their areas of improvement on multiple eCommerce platforms. Continually reviewing the perfect page analysis scores and setting KPI triggers can enable brands to resolve customer-centric issues at variant, sub-category, sub-brand, and other levels. Conclusion Monitoring product listings on multiple eCommerce platforms can enable brands to find signs for updating the product page to meet the growing demands of consumers or the changing buyer personas. Brands across the globe and with sizable number of product variants understand the scope of monitoring product listings across eCommerce platforms, which goes beyond sales/revenue. For example, meeting consumer demands by updating the details on the product page gives an impression of awareness of the ongoing market trends. Schedule a demo with us to learn the advantages of implementing eCommerce Competitive Intelligence.

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

Leave a Comment / Blog, Digital Advertising / Expert Opinion

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?

Leave a Comment / Blog, Direct Carrier Billing / Expert Opinion

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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