<div class="sub-cat-page-holder"><div class="sub-cat-page-img"><img src="https://persona.ly/glossary/wp-content/uploads/2020/02/secure-shield.svg"/></div><div class="sub-cat-page-h-holder"><h2 class="sub-cat-page-title">Fraud prevention</h2><h4 class="sub-cat-page-subtitle"><span class="sub-cat-page-subtitle">Attribution Manipulation &#8211; Click Spamming and Click Hijacking</span><span class="csr-page-counter"> -> Page <span class="max-for-title">1 of <span class="sub-cat-max-page"></span></span></span></h4></div></div><div class="search-sidebar-holder"><a href="/glossary/"><h3 class="search-sidebar-holder-title">UA Glossary</h3></a>[vc_widget_sidebar sidebar_id="single-page-sidebar" el_class="front-page-sidebar-holder"]<div class="search-sidebar-footer-holder"></div></div>{"id":1151,"date":"2021-01-04T14:57:00","date_gmt":"2021-01-04T14:57:00","guid":{"rendered":"https:\/\/persona.ly\/glossary\/?page_id=1151"},"modified":"2021-01-05T11:52:10","modified_gmt":"2021-01-05T11:52:10","slug":"attribution-manipulation-click-spamming-and-click-hijacking","status":"publish","type":"page","link":"https:\/\/persona.ly\/glossary\/fraud-prevention\/attribution-manipulation-click-spamming-and-click-hijacking\/","title":{"rendered":"Attribution Manipulation &#8211; Click Spamming and Click Hijacking"},"content":{"rendered":"<p>[vc_row el_class=&#8221;front-hero-section&#8221;][vc_column width=&#8221;1\/2&#8243; css=&#8221;.vc_custom_1582730807176{background-image: url(https:\/\/persona.ly\/glossary\/\/wp-content\/uploads\/2020\/02\/group-19.svg?id=58) !important;background-position: center !important;background-repeat: no-repeat !important;background-size: contain !important;}&#8221; el_class=&#8221;hero-first-section&#8221;][vc_column_text el_class=&#8221;page-heading&#8221; css=&#8221;.vc_custom_1593096796228{margin-top: 30px !important;}&#8221;]<\/p>\n<h1><a href=\"\/glossary\/\">UA <span class=\"color-ancient\">Glossary<\/span><\/a><\/h1>\n<p>[\/vc_column_text][vc_column_text]<p>Your source for everything mobile UA, from the basics to contentious standards, the glossary can help and inform both aspiring growth managers and experienced mobile app developers<\/p>\n[\/vc_column_text]<div class=\"ult-spacer spacer-69d2922e14e03\" data-id=\"69d2922e14e03\" data-height=\"105\" data-height-mobile=\"0\" data-height-tab=\"\" data-height-tab-portrait=\"\" data-height-mobile-landscape=\"0\" style=\"clear:both;display:block;\"><\/div>[\/vc_column][vc_column width=&#8221;1\/2&#8243;][vc_single_image image=&#8221;60&#8243; img_size=&#8221;full&#8221; alignment=&#8221;center&#8221; el_class=&#8221;hero-section-image&#8221;][\/vc_column][\/vc_row][vc_section css=&#8221;.vc_custom_1583429011820{background-image: url(https:\/\/persona.ly\/glossary\/\/wp-content\/uploads\/2020\/03\/bg_repeater_with_bg_svg.svg?id=320) !important;}&#8221; el_class=&#8221;post-content-section archive-page-custom single-subcat&#8221;][vc_row el_class=&#8221;covered-grace-font&#8221;][vc_column width=&#8221;2\/3&#8243; el_class=&#8221;gap-in-end-single&#8221;][vc_column_text][\/vc_column_text][vc_column_text]<style>.wp-show-posts-columns#wpsp-1153 {margin-left: -2em; }.wp-show-posts-columns#wpsp-1153 .wp-show-posts-inner {margin: 0 0 2em 2em; }<\/style><section id=\"wpsp-1153\" class=\" wp-show-posts\" style=\"\"><article class=\" wp-show-posts-single wpsp-clearfix post-1155 post type-post status-publish format-standard hentry category-attribution-manipulation-click-spamming-and-click-hijacking tag-attribution-fraud tag-click-flooding tag-click-hijacking tag-click-injection tag-click-spamming tag-mobile-ad-fraud tag-mobile-fraud\" itemtype=\"http:\/\/schema.org\/CreativeWork\" itemscope><div class=\"wp-show-posts-inner\" style=\"\">\t\t\t\t\t\t<header class=\"wp-show-posts-entry-header\">\n\t\t\t\t\t\t\t<h1 class=\"wp-show-posts-entry-title\" itemprop=\"headline\"><a href=\"https:\/\/persona.ly\/glossary\/attribution-manipulation-click-spamming-and-click-hijacking\/\" rel=\"bookmark\">Attribution Manipulation &#8211; Click Spamming and Click Hijacking<\/a><\/h1><div class=\"wp-show-posts-entry-meta wp-show-posts-entry-meta-below-title post-meta-inline\"><span class=\"wp-show-posts-posted-on wp-show-posts-meta\">\n\t\t\t\t\t<a href=\"https:\/\/persona.ly\/glossary\/attribution-manipulation-click-spamming-and-click-hijacking\/\" title=\"2:59 pm\" rel=\"bookmark\"><time class=\"wp-show-posts-entry-date published\" datetime=\"2022-01-04T14:59:33+00:00\" itemprop=\"datePublished\">January 4, 2022<\/time><time class=\"wp-show-posts-updated\" datetime=\"2022-12-11T12:40:44+00:00\" itemprop=\"dateModified\">December 11, 2022<\/time><\/a>\n\t\t\t\t<\/span><\/div>\t\t\t\t\t\t<\/header><!-- .entry-header -->\n\t\t\t\t\t\t\t\t\t\t\t<div class=\"wp-show-posts-entry-content\" itemprop=\"text\">\n\t\t\t\t\t\t\t<p>[vc_row][vc_column el_class=&#8221;normal-text&#8221;][vc_column_text]<span style=\"font-weight: 400;\">When it comes to fraud in mobile marketing we think it\u2019s important to understand which vulnerabilities each fraud technique abuses, how it works, what are its consequences, and how it can be detected.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the subject of attribution manipulation we\u2019ll focus on two opposing types of fraud that both revolve around the abuse of the way attribution technically works (i.e, by faking attributed installs by taking over organic or other paid installs). <\/span>[\/vc_column_text][vc_custom_heading text=&#8221;Click Spamming in Mobile Marketing&#8221; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-heading blue-back&#8221; link=&#8221;url:%23|||&#8221;][vc_custom_heading text=&#8221;How Does Click Spamming Work? &#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">Click spamming is a technique that<\/span><b> abuses the last touch attribution model<\/b><span style=\"font-weight: 400;\"> in order to \u201csteal the credit\u201d for an install. The most commonly used attribution model is \u2018<\/span><a class=\"custom-link-content\" href=\"https:\/\/persona.ly\/glossary\/attribution\/types-of-attribution\/?utm_source=glossary&amp;utm_medium=post&amp;utm_campaign=click_spam_hijack\"><span style=\"font-weight: 400;\">last touch\u2019<\/span><\/a><span style=\"font-weight: 400;\">, in which the latest UA partner who was attributed with a click on the ad that preceded the install will be attributed with the install, assuming the attribution window is still open. In short, the last click on an ad before the install will be credited for the install.\u00a0<\/span>[\/vc_column_text]<div class=\"aio-icon-component   info-noty blue-noty style_1\"><div id=\"Info-box-wrap-9814\" class=\"aio-icon-box left-icon\" style=\"\"  ><div class=\"aio-icon-left\"><div class=\"ult-just-icon-wrapper  \"><div class=\"align-icon\" style=\"text-align:center;\">\n<div class=\"aio-icon-img \" style=\"font-size:71px;background:rgba(255,255,255,0.01);display:inline-block;\" >\n\t<img class=\"img-icon\" alt=\"Info Container\" src=\"https:\/\/persona.ly\/glossary\/wp-content\/uploads\/2020\/03\/combined-shape-2.svg\"\/>\n<\/div><\/div><\/div><\/div><div class=\"aio-ibd-block\"><div class=\"aio-icon-header\" ><h3 class=\"aio-icon-title ult-responsive\"  data-ultimate-target='#Info-box-wrap-9814 .aio-icon-title'  data-responsive-json-new='{\"font-size\":\"\",\"line-height\":\"\"}'  style=\"color:#191536;\">Attribution Modeling<\/h3><\/div> <!-- header --><div class=\"aio-icon-description ult-responsive\"  data-ultimate-target='#Info-box-wrap-9814 .aio-icon-description'  data-responsive-json-new='{\"font-size\":\"\",\"line-height\":\"\"}'  style=\"color:#191536;\"><span style=\"font-weight: 400;\">In order to understand how click spamming abuses the \u2018last touch\u2019 model, you can read our entry <\/span><a href=\"https:\/\/persona.ly\/glossary\/attribution\/types-of-attribution\/\"><span style=\"font-weight: 400;\">Types of Attribution<\/span><\/a><span style=\"font-weight: 400;\">, where we dive deeper into this and other models, explain attribution windows, and the advantages and disadvantages of the different models.\u00a0<\/span><\/div> <!-- description --><\/div> <!-- aio-ibd-block --><\/div> <!-- aio-icon-box --><\/div> <!-- aio-icon-component -->[vc_single_image image=&#8221;1184&#8243; img_size=&#8221;full&#8221; alignment=&#8221;center&#8221; el_class=&#8221;single-post-image-back&#8221;][vc_column_text]<span style=\"font-weight: 400;\"><a class=\"custom-link-content\" href=\"https:\/\/persona.ly\/blog\/2022\/11\/the-vicious-cycle-of-click-spamming\/\" target=\"_blank\" rel=\"noopener\">Click spamming<\/a> happens at the time of an ad impression. It can be an in-app banner ad or a pixel \u201cad\u201d on a webpage. Once there\u2019s an impression, the ones conducting the fraud trigger a series of clicks (20 or even 30 clicks), as if there were multiple ads being displayed to a single user and all of them were clicked. This process is called <\/span><a class=\"custom-link-content\" href=\"https:\/\/www.appsflyer.com\/mobile-fraud-glossary\/ad-stacking\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">ad stacking<\/span><\/a><span style=\"font-weight: 400;\">.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">In the next stage of the process, the app store opens. Since the ad wasn\u2019t originally clicked by the user, this happens in the background without the user\u2019s knowledge, and all of these clicks are registered for future attribution purposes, but there\u2019s no install, yet.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Click spamming works on assumption, and targets click to apps who are likely to be installed organically by large groups of users (apps who have a buzz around them, new services, apps that new devices tend to install, and more).\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">What happens eventually is that users install after the ad was \u2018clicked\u2019, and the spammer gets attributed for the install. It\u2019s guesswork, but imagine the probability of running 20 to 30 different clicks (for popular apps) per a single impression. You\u2019re bound to \u2018win\u2019 some installs.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;The Collateral Damage of Click Spamming&#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<!-- Widget Shortcode --><div id=\"custom_html-7\" class=\"widget_text widget widget_custom_html widget-shortcode area-sidebar-form-mobile \"><div class=\"textwidget custom-html-widget\"><div class=\"subscribe-footer-from-holder sidebar-form-intouch\">\r\n<h3>Looking for app growth opportunities?<\/h3>\r\n<p>Leave your email and we'll get \r\nback to you!<\/p>\r\n<form class=\"subscribe-footer-from\">\r\n\t<div class=\"subscribe-footer-from-email-holder\"><input type=\"email\" class=\"subscribe-footer-email\" placeholder=\"Enter your email\"><\/div>\r\n<button class=\"subscribe-footer-submit\">\r\n\tGet in Touch\r\n<\/button>\r\n<\/form>\r\n<\/div>\r\n<div class='subscribe-footer-from-thankyou gsifthy'>\r\n\t<img alt=\"\" src=\"\/glossary\/wp-content\/uploads\/2020\/08\/02.svg\">\r\n<h3>Thank you for your interest!<\/h3>\r\n<p>Our team will contact you with more details.<\/p>\r\n<\/div>\r\n<div class=\"search-sidebar-footer-holder gisf\"><\/div><\/div><\/div><!-- \/Widget Shortcode -->[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Click spamming hurts almost all sides involved in the ad serving process &#8211; the advertiser, legitimate UA partners (ad networks and DSPs), and the users.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;The Advertiser: &#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">If your app is the targeted app (i.e, you\u2019re it\u2019s advertiser), it means you end up <\/span><b>paying for your organic installs<\/b><span style=\"font-weight: 400;\">. One of the most infamous cases where a company claimed they\u2019ve been paying for organic installs is Uber, in the case of <\/span><a class=\"custom-link-content\" href=\"https:\/\/www.adexchanger.com\/ad-exchange-news\/wednesday-09202017\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Uber vs. Fetch<\/span><\/a><span style=\"font-weight: 400;\">.\u00a0 <\/span><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\"><br \/>\n<\/span><span style=\"font-weight: 400;\">Fetch was Uber\u2019s ad agency, which means they hired and handled the ad networks that ran Uber\u2019s paid ad campaigns. Uber claimed that Fetch hired ad networks who used click spamming, resulting in Uber paying, both Fetch and the ad networks, for installs that were attributed to the ad networks, but in reality originated in organic installs.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Fetch, on the other hand, claimed they work tirelessly to minimize fraudulent activity and that Uber\u2019s invoices went unpaid for months. <\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">While there seems to be some additional tension between these two companies, click spamming is a well-known issue in the industry, one any UA and Growth manager should be aware of.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">According to a <\/span><a class=\"custom-link-content\" href=\"https:\/\/www.appsflyer.com\/resources\/the-state-of-mobile-fraud-h1-2019\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">report by AppsFlyer<\/span><\/a><span style=\"font-weight: 400;\">, $20.3B in ad spend was exposed to app install fraud in the first half of 2019 with 22.6% of non-organic app installs globally are currently identified as fraudulent.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;A Negative Effect on Store Ranking: &#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">An app store ranking is decided based on multiple factors that differ between the stores. One of the deciding factors is <\/span><b>the ratio between store visits to installs<\/b><span style=\"font-weight: 400;\">, if the conversion rate is lowered over time (i.e, a lot of users open the store but only a few download the app) the store\u2019s ranking will decrease. If your app is subject to click spamming this means that even your store ranking will be negatively affected.\u00a0\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;The UA Partner (Ad Networks and DSPs):&#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">The second party to get hurt by this technique is the trusted UA partners. A partner that ran an honest, fraud-free campaign might have been losing it\u2019s <\/span><a class=\"custom-link-content\" href=\"https:\/\/persona.ly\/glossary\/attribution\/view-through-attribution-2\/?utm_source=glossary&amp;utm_medium=post&amp;utm_campaign=click_spam_hijack\"><span style=\"font-weight: 400;\">view-through attribution window<\/span><\/a><span style=\"font-weight: 400;\"> (an impression that preceded the install) to click spammers.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">View-through attribution windows are significantly shorter so as to only be counted when they can actually be considered to have led to an install. If a click occurs while a view attribution is still open the click \u201cwins\u201d the attribution (even if the impression occurred closer to the install). This means that even if the impression from the trusted ad network led to the install, the click (that occurred without the user\u2019s knowledge or intention) will be attributed for the install.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;The Users:&#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">For some users, data plans are billed by usage (instead of a monthly package). This means that in devices that are subject to click spamming, the increase in data usage will be costly since opening the app store for 20 clicks per ad takes a fair amount of data usage, for people whose data is a limited resource, click spamming can lead to a lot of frustration, as it can\u2019t be easily ascertained that it even occurred.<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;How to Recognize Click Spamming&#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">There are a couple of KPIs that should be tracked and monitored to rule out click spamming.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In click spamming, the conversion rate (click to install) will be low, and in many cases extremely low (0.01%-0.05%) since there will be a whole lot of clicks but a relatively minuscule amount of installs. In past occurrences where we helped our partnered advertisers detect click spamming, we saw examples like ~2,000,000 clicks and ~300 installs (0.015%), and the conversion rates were sometimes <\/span><span style=\"font-weight: 400;\">even lower<\/span><span style=\"font-weight: 400;\">. \u00a0 <\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">The CTIT (click time to install) will be longer. There are benchmark CTIT to compare to, but our recommendation is to take them with a grain of salt. Benchmarks vary between apps, and the best thing to do is to compare it with other campaigns for your own app if you can.<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">And lastly, in click spamming, as soon as a new click spamming \u2018source\u2019 is added to your buying, you\u2019ll see a decline in your organic installs, because, at the bottom line, those are the installs that click spamming targets and hurts the most.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;Click Spamming in a LAT (Limited Ad Tracking) Environment &#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">A LAT environment makes fraudsters&#8217; life easier, since attribution tracking relies on <\/span><b>fingerprinting<\/b><span style=\"font-weight: 400;\">, instead of relying on device IDs, rendering it probabilistic as opposed to deterministic. If click spamming is executed on a device with LAT enabled, anyone on <\/span><b>the same IP address<\/b><span style=\"font-weight: 400;\"> who organically installed the app will end up attributing the fraudster with an additional install.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">The lack of a deviceID in a LAT environment makes it harder to track the connection between a click and an install. Having a lot of devices on the same IP address and tracking an already popular app, means it might have just been installed organically by a different device than the one with the open click attribution window.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Without click spamming, fingerprinting is estimated to be 98% accurate when the time between the click to the install is 10 min or less, but as time passes the likelihood that the click and install actually originated from the same device, decreases.\u00a0<\/span>[\/vc_column_text][vc_column_text]<\/p>\n<blockquote><p><span style=\"font-weight: 400;\">&#8220;As the time between click and conversion increases, fingerprint attribution becomes increasingly inaccurate. After three hours, accuracy drops by 85%. At the 24-hour mark, it drops to 50%; and beyond that, fingerprint attribution is more likely wrong than right.&#8221;<\/span><\/p>\n<p><a href=\"https:\/\/medium.com\/@gsimmons\/your-attribution-may-be-more-wrong-than-right-903cde0ce4ca\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Grant Simmons, VP @ Kochava Foundry, &#8220;Your Attribution May Be More Wrong Than Right<\/span><\/a><\/p><\/blockquote>\n<p>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Keeping in mind the inaccuracy in fingerprinting (especially the longer the CTIT is) and adding click spamming, means UA managers need to be especially careful and monitor their LAT sources, always suspect inflated click volumes, and have a minimal understanding of how those sources generate these clicks.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">As an advertiser, a good precaution would be to limit your fingerprinting attribution window to decrease the chances of click spamming in a LAT environment. Granted, this is hard to detect, but if your UA partner runs both LAT and non-LAT in-app campaigns and in both cases can\u2019t provide you with device IDs, it should raise your suspicion and lead to further questioning, as there are very little (if any) legitimate reasons to not use deterministic attribution where it\u2019s available.\u00a0<\/span>[\/vc_column_text]<div class=\"aio-icon-component   info-noty blue-noty style_1\"><div id=\"Info-box-wrap-3193\" class=\"aio-icon-box left-icon\" style=\"\"  ><div class=\"aio-icon-left\"><div class=\"ult-just-icon-wrapper  \"><div class=\"align-icon\" style=\"text-align:center;\">\n<div class=\"aio-icon-img \" style=\"font-size:71px;background:rgba(255,255,255,0.01);display:inline-block;\" >\n\t<img class=\"img-icon\" alt=\"Info Container\" src=\"https:\/\/persona.ly\/glossary\/wp-content\/uploads\/2020\/03\/combined-shape-2.svg\"\/>\n<\/div><\/div><\/div><\/div><div class=\"aio-ibd-block\"><div class=\"aio-icon-header\" ><h3 class=\"aio-icon-title ult-responsive\"  data-ultimate-target='#Info-box-wrap-3193 .aio-icon-title'  data-responsive-json-new='{\"font-size\":\"\",\"line-height\":\"\"}'  style=\"color:#191536;\">iOS14 and Click Spamming<\/h3><\/div> <!-- header --><div class=\"aio-icon-description ult-responsive\"  data-ultimate-target='#Info-box-wrap-3193 .aio-icon-description'  data-responsive-json-new='{\"font-size\":\"\",\"line-height\":\"\"}'  style=\"color:#191536;\"><span style=\"font-weight: 400;\">With <\/span><a class=\"custom-link-content\" href=\"https:\/\/persona.ly\/glossary\/attribution\/user-acquisition-and-retargeting-in-ios-14\/?utm_source=glossary&amp;utm_medium=post&amp;utm_campaign=click_spam_hijack\"><span style=\"font-weight: 400;\">the depreciation of the IDFA in iOS 14<\/span><\/a><span style=\"font-weight: 400;\">, UA campaigns in this environment will run similarly to LAT campaigns. This means that these campaigns will run without device IDs allowing for deterministic attribution, and the only way to track and attribute installs will be through fingerprinting, and again, it will open up the possibility for undetectable click spamming.\u00a0<\/span><\/div> <!-- description --><\/div> <!-- aio-ibd-block --><\/div> <!-- aio-icon-box --><\/div> <!-- aio-icon-component -->[vc_custom_heading text=&#8221;Click Hijacking (AKA Click Injection) in Mobile Marketing&#8221; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-heading purple-back&#8221; link=&#8221;url:%23|||&#8221;][vc_custom_heading text=&#8221;How Does Click Hijacking Work?&#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_single_image image=&#8221;1167&#8243; img_size=&#8221;full&#8221; alignment=&#8221;center&#8221; el_class=&#8221;single-post-image-back&#8221;][vc_column_text]<span style=\"font-weight: 400;\">Click hijacking differs from click spamming significantly. It can only occur in-app, the hijacker has to have it\u2019s code natively on the device (either through an app or an SDK), and it\u2019s much more targeted in its nature. While click spamming is about sending massive amounts of clicks for different apps hoping to catch a few, click hijacking is very specific and hijacks already-clicked ads.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Once the infected user clicks the app store button to install an app (whether he got there organically or through a paid click), the fraudster recognizes it, checks if he has access to a campaign promoting the app that\u2019s about to be installed, and hijacks the click, resulting in the fraudster being attributed with the install.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">The vulnerability that\u2019s taken advantage of in click hijacking occurs much earlier compared to click spamming and comes from the core &#8211; the app stores. When a new app is submitted to the app store it must go through a review process\/ approving new apps to be added to the store.<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">So far, some fraudsters were able to pass this barrier on both platforms, but in an ideal world, more thorough testing would be done at this stage, and hopefully all, apps containing malicious software would be detected and banned.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;The Rube Goldberg Effect of Click Hijacking &#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">One by one, several different aspects of the advertiser\u2019s UA efforts are affected. First, click hijacking hurts the app developer in a very clear and deliberate way, similarly to click spamming, organic installs are written off as paid installs which means the advertiser is paying for something he already owns., but there\u2019s more to it. It completely obstructs setting the app\u2019s marketing KPIs. The fraudsters\u2019 results might look good on paper, but it won\u2019t represent actual performance, and will simultaneously hurt other partners\u2019 performance.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">If other UA partners are targeting relevant users for your app, but are not successfully converting them (since those installs are being hijacked), their performance report is off as well. Their campaigns are underperforming, their CAC (customer acquisition costs) are higher, and they\u2019ll try to optimize and improve while running on false, manipulated data.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">This leaves advertisers confused. The fraudulent campaign will thrive while the non-fraudulent will underperform (since those installs are hijacked). If the underperforming campaigns are paused, the fraudulent campaign will see a decline as well (since the performance of the hijacked campaign is directly reliant on the work of other campaigns), but might still not clear the air and reveal the hijackers.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Whether or not it\u2019s done consciously, the \u2018host\u2019 app (which enables click hijacking) gains from this fraud. As many installs are generated for the ad placements inside it, as the hijackers usually only trigger their malicious code in some percentage ratio of all impressions (something like 1\/10 or 1\/15 impressions is hijacked, for example), it can still be labeled by legitimate bidders as a prime ad placement for user acquisition, which means it would get higher CPM bids for its inventory.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;How to Detect Click Hijacking?&#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_single_image image=&#8221;1168&#8243; img_size=&#8221;full&#8221; alignment=&#8221;center&#8221; el_class=&#8221;single-post-image-back&#8221;][vc_column_text]<span style=\"font-weight: 400;\">In click hijacking, your CR will appear to be high (since these users are prequalified), while the CTIT would be low (since the hijacker is attributed with the click right before the install occurs). If your <\/span><a class=\"custom-link-content\" href=\"https:\/\/persona.ly\/glossary\/attribution\/mmps\/?utm_source=glossary&amp;utm_medium=post&amp;utm_campaign=click_spam_hijack\"><span style=\"font-weight: 400;\">attribution platform<\/span><\/a><span style=\"font-weight: 400;\"> offers some form of user journey tracking you\u2019ll notice the fraudulent company constantly popping up between other UA partners and their installs.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">A famous case of <\/span><a class=\"custom-link-content\" href=\"https:\/\/snyk.io\/blog\/sourmint-malicious-code-ad-fraud-and-data-leak-in-ios\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">a malicious SDK is the Chinese company Mintegral <\/span><\/a><span style=\"font-weight: 400;\">that allegedly disguised itself as a tool to help app developers and advertisers monetize their apps \u2018effectively\u2019 with ads. It was discovered that the SDK allegedly had malicious code within it that worked to steal potential revenue from other ad networks.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Mintergal made it harder to detect their alleged fraudulent activity. Instead of supposedly hijacking the attribution of all the clicks, they would only hijack one out of ten, making it seem like an ordinary ad network activity.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Another case that was made famous back in 2018, named two Chinese companies &#8211; <\/span><a class=\"custom-link-content\" href=\"https:\/\/www.buzzfeednews.com\/article\/craigsilverman\/android-apps-cheetah-mobile-kika-kochava-ad-fraud\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Cheetah Mobile and Kika Tech<\/span><\/a><span style=\"font-weight: 400;\">. In the article published by <\/span><a class=\"custom-link-content\" href=\"https:\/\/www.buzzfeednews.com\/article\/craigsilverman\/android-apps-cheetah-mobile-kika-kochava-ad-fraud\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Buzzfeed<\/span><\/a><span style=\"font-weight: 400;\">, it was claimed that these companies used their SDK across different, self-owned, wildly-popular apps in order to perform click hijacking.\u00a0<\/span>[\/vc_column_text][vc_column_text]<span style=\"font-weight: 400;\">Their activity was discovered by <\/span><a class=\"custom-link-content\" href=\"https:\/\/www.kochava.com\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">Kochava\u2019s <\/span><\/a><a class=\"custom-link-content\" href=\"https:\/\/persona.ly\/glossary\/attribution\/mmps\/?utm_source=glossary&amp;utm_medium=post&amp;utm_campaign=click_spam_hijack\"><span style=\"font-weight: 400;\">attribution platform<\/span><\/a><span style=\"font-weight: 400;\">.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;How to Detect Click Hijacking?&#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">If you have cause to suspect click spamming or hijacking from a new UA partner, take a better look at your campaigns\u2019 ad placements. Both of these attribution manipulations tend to use \u2018hardcoded placements\u2019.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If your data indicates a few repeating well-performing placements over long periods of time, it might be hardcoded and fraudulent. In reality, many new ad placements are created on a daily basis as new apps are released, and you should expect a healthy dynamic nature in the placements that are prominent for your UA campaigns in the in-app ecosystem. In some cases, in click spamming, the ad placement will indicate an app that doesn\u2019t even run ads, so double-check for that as well. <\/span><\/p>\n<p>[\/vc_column_text][vc_custom_heading text=&#8221;The Ramifications of Raising Capital Under Falsely Calculated CAC &#8221; font_container=&#8221;tag:h3|text_align:left|color:%23191536&#8243; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-subheading&#8221;][vc_column_text]<span style=\"font-weight: 400;\">Monitoring your campaigns under falsely calculated CAC is a problem in and of itself, but the issue is much bigger when it involves investors, people outside your organization, operating under false assumptions regarding the app\u2019s growth potential.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">When your app\u2019s paid acquisition data consists of many organic users falsely claimed as acquired ones, your costs seem lower than they actually are, and funds raised under these assumptions won\u2019t pay themselves back over time, as the growth potential of the product itself isn\u2019t what it seems to be.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This means that if you\u2019ve raised capital, your app grew, your team grew, and your acquisition investments grew as well, but in the end, the expected results weren\u2019t delivered and the investment was deemed to be a failure.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In the worst-case scenario, this will result in new hires being laid off, shrinking teams back down, losing not only the funding, but the trust of the investors, which will also lead to negative public coverage, and more.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">An app with actual potential can still be a victim of mobile fraud, and though it had everything it needed to become a success, the mishandling of UA in the early stages of the app could\u2019ve hurt in an irreparable way.\u00a0<\/span>[\/vc_column_text][vc_custom_heading text=&#8221;How to Avoid Click Spamming, Click Hijacking, and Other Fraud Techniques &#8221; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-heading blue-back&#8221; link=&#8221;url:%23|||&#8221;][vc_column_text]<strong>\u2022 <b>Due Diligence &#8211; <\/b><\/strong><b><span style=\"font-weight: 400;\">ask your UA partners the hard questions &#8211; how they target, ask to learn more about how their SDK works, and their ad units, and get familiar with their process. In this day and age offering transparency is basic and DSPs should be able to make their information accessible to the advertiser. Not getting definite, clear answers should raise a flag.\u00a0<\/span><\/b><\/p>\n<p><strong>\u2022 <b>Adjust Your KPIs &#8211;<\/b><\/strong> <span style=\"font-weight: 400;\">make sure your organization is setting the right KPIs for the UA campaign. Some organizations are still focusing on volume instead of quality (i.e install volume vs. active and engaged users, depositors, etc\u2019.) By focusing solely on volume and not testing the quality of the users, you essentially attract possible fraudulent activity to your app and hurt the overall performance of your app (getting a lot of new users who open once and never come back means lower retention rates.)\u00a0<\/span><span style=\"font-weight: 400;\"><br \/>\n<\/span><\/p>\n<p><strong>\u2022 <b>Monitoring and Tracking &#8211; <\/b><\/strong><b><span style=\"font-weight: 400;\">Keeping track of your user base, shifts in the percentage of organic and paid users, shifts in overall app performance, etc\u2019 can serve as great indicators of malicious activity. In both click spamming and click hijacking you\u2019ll see a decline in organic installs. Though a more substantial hit in organic installs will most likely be detectable in click spamming.\u00a0<\/span><\/b>[\/vc_column_text]<div class=\"aio-icon-component   info-noty blue-noty style_1\"><div id=\"Info-box-wrap-8339\" class=\"aio-icon-box left-icon\" style=\"\"  ><div class=\"aio-icon-left\"><div class=\"ult-just-icon-wrapper  \"><div class=\"align-icon\" style=\"text-align:center;\">\n<div class=\"aio-icon-img \" style=\"font-size:71px;background:rgba(255,255,255,0.01);display:inline-block;\" >\n\t<img class=\"img-icon\" alt=\"Info Container\" src=\"https:\/\/persona.ly\/glossary\/wp-content\/uploads\/2020\/03\/combined-shape-2.svg\"\/>\n<\/div><\/div><\/div><\/div><div class=\"aio-ibd-block\"><div class=\"aio-icon-header\" ><h3 class=\"aio-icon-title ult-responsive\"  data-ultimate-target='#Info-box-wrap-8339 .aio-icon-title'  data-responsive-json-new='{\"font-size\":\"\",\"line-height\":\"\"}'  style=\"color:#191536;\">Tracking the Journey With Assisted Installs <\/h3><\/div> <!-- header --><div class=\"aio-icon-description ult-responsive\"  data-ultimate-target='#Info-box-wrap-8339 .aio-icon-description'  data-responsive-json-new='{\"font-size\":\"\",\"line-height\":\"\"}'  style=\"color:#191536;\"><a class=\"custom-link-content\" href=\"https:\/\/www.appsflyer.com\/\"><span style=\"font-weight: 400;\">Appsflyer <\/span><\/a><span style=\"font-weight: 400;\">tracks what they call \u2018<\/span><a class=\"custom-link-content\" href=\"https:\/\/support.appsflyer.com\/hc\/en-us\/articles\/207040506-Assisted-installs-explained\"><span style=\"font-weight: 400;\">assisted installs<\/span><\/a><span style=\"font-weight: 400;\">\u2019. Assisted Installs show you the touch-points that weren\u2019t the last touch that preceded the install. Assisted Installs includes information both about the engagement type (click or impression) as well as the engagement time (when it occurred).\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">If you repeatedly detect one UA partner getting clicks seconds after other UA partners, and their specific clicks tend to convert better than you should suspect click hijacking.\u00a0<\/span><\/div> <!-- description --><\/div> <!-- aio-ibd-block --><\/div> <!-- aio-icon-box --><\/div> <!-- aio-icon-component -->[vc_custom_heading text=&#8221;Choosing Your Partners &#8221; use_theme_fonts=&#8221;yes&#8221; el_class=&#8221;styled-heading blue-back&#8221; link=&#8221;url:%23|||&#8221;][vc_column_text]<span style=\"font-weight: 400;\">Since these are attribution-related manipulations there are two key partners who can help avoid, prevent, track, and recognize the fraudulent activity.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Different <\/span><b>attribution platforms<\/b><span style=\"font-weight: 400;\"> offer different tools to track fraud and notice abnormalities in the data. Taking the time and choosing<\/span><a class=\"custom-link-content\" href=\"https:\/\/persona.ly\/glossary\/attribution\/mmps\/?utm_source=glossary&amp;utm_medium=post&amp;utm_campaign=click_spam_hijack\"><span style=\"font-weight: 400;\"> the right attribution platform for your app<\/span><\/a><span style=\"font-weight: 400;\"> can help with the early detection of fraud.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Choosing a <\/span><b>trusted and reliable DSP<\/b><span style=\"font-weight: 400;\">. Our glossary entry <\/span><a class=\"custom-link-content\" href=\"https:\/\/persona.ly\/glossary\/real-time-bidding\/choosing-a-dsp\/?utm_source=glossary&amp;utm_medium=post&amp;utm_campaign=click_spam_hijack\"><span style=\"font-weight: 400;\">choosing a DSP<\/span><\/a><span style=\"font-weight: 400;\"> covers the different types of DSPs and which mobile growth opportunities they offer. Adjust also <\/span><a class=\"custom-link-content\" href=\"https:\/\/www.adjust.com\/blog\/choosing-the-right-mobile-dsp\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">wrote extensively<\/span><\/a><span style=\"font-weight: 400;\"> about choosing a DSP.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">As we\u2019ve mentioned before, as we steer further from ad networks and transition to programmatic and ML-based campaigns, transparency is a basic expectation from a UA partner. <\/span>[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n\t\t\t\t\t\t<\/div><!-- .entry-content -->\n\t\t\t\t\t<\/div><!-- wp-show-posts-inner --><div class=\"wpsp-clear\"><\/div><\/article><\/section><!-- .wp-show-posts -->[\/vc_column_text][\/vc_column][vc_column width=&#8221;1\/3&#8243; el_class=&#8221;gap-in-end-single single-subcat-widget&#8221;][vc_column_text][\/vc_column_text][vc_single_image image=&#8221;962&#8243; img_size=&#8221;full&#8221; alignment=&#8221;center&#8221; 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