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Getting Started with MOBILE ATTRIBUTION & MARKETING ANALYTICS 2016 Edition Chapter What’s in the Guide Page 1 INTRODUCTION .......................................................................3 2 THE BASICS OF APP MARKETING ..................................6 2.1 MAPPING THE MOBILE MARKETING ECOSYSTEM .................................................. 6 2.2 COMMON PRICING MODELS .................................................................................10 2.3 THE IMPORTANCE OF NON-ORGANIC INSTALLS ................................................... 11 2.4 BREAKING DOWN MOBILE ANALYTICS ................................................................ 12 3 MOBILE ANALYTICS UNDER THE HOOD ....................16 3.1 WINDOWS OF OPPORTUNITY ............................................................................... 17 3.2 ATTRIBUTION METHODS — HOW DOES IT WORK? ............................................19 3.3 THE DEEPLINKING DIVE ......................................................................................26 3.4 INTEGRATED PARTNER ECOSYSTEM .....................................................................27 3.5 UNBIASED VS. BIASED ATTRIBUTION PROVIDERS ................................................31 3.6 MOBILE RETARGETING ATTRIBUTION ..................................................................35 3.7 TV ATTRIBUTION .................................................................................................37 HOW TO SQUEEZE THE DATA LEMON WITH 4 ATTRIBUTION & MARKETING ANALYTICS ............... 38 4.1 IN-APP EVENTS TO GET STARTED WITH .......................................................... 40 4.2 RETENTION - KEEP USERS COMING BACK FOR MORE ..................................... 44 4.3 COHORT ANALYSIS ............................................................................................. 46 4.4 ONE FORMULA TO RULE THEM ALL ................................................................. 48 4.5 REPORTING - DASHBOARD, PULL & PUSH APIS .............................................. 49 4.6 MOBILE AD FRAUD - NO LONGER THE ELEPHANT IN THE ROOM ................... 50 5 THE 10 COMMANDMENTS OF MOBILE ADVERTISING ANALYTICS ............................................... 53 6 CONCLUSION ......................................................................... 54 Getting Started with Mobile Attribution & Marketing Analytics CHAPTER 1 INTRODUCTION Before the dawn of the mobile era, digital (web) marketers were able to accurately measure the impact of their campaigns and make smart decisions about their ad spend. Thanks to the cookie, advertisers were able to anonymously identify users in the browser, and that completely redefined traditional spray-and-pray and contextual online advertising. But then the mobile revolution turned things upside down and the cookie began to crumble because it wasn’t supported on applications and was deactivated by default on Apple’s Safari browser. That left the mobile cookie with extremely limited reach. IDFA IDFA IDFA Advertising ID IDFA Advertising ID IDFA www.appsflyer.com 3 Getting Started with Mobile Attribution & Marketing Analytics The mobile world is deeply fragmented. The problem with mobile is that it is deeply fragmented: There are different operating systems (iOS, Android, Windows Phone), different environments (in-app, mobile web) and different identifiers (Apple’s IDFA, Google Advertising ID, Google Play Referrer, etc). Can targeted, personalized advertising work and thrive in a post-cookie and mobile-first world? The answer is a resounding yes. This guide will show you how. www.appsflyer.com 4 “ THE TREND HAS BEEN MOBILE WAS WINNING. IT' S NOW WON.” ERIC SCHMIDT Getting Started with Mobile Attribution & Marketing Analytics CHAPTER 2 THE BASICS OF APP MARKETING 2.1 Mapping the Mobile Marketing Ecosystem The mobile ecosystem can be divided into the following main groups: BUY SIDE SELL SIDE Brands App Agencies Ad Publishers Developers Networks DSPs Ad SSPs Exchanges ANALYTICS Independent Marketing App In-App Attribution Analytics Store OTHER Mobile Marketing Anti-Fraud Automation Specialists www.appsflyer.com 6 Getting Started with Mobile Attribution & Marketing Analytics Buy Side Brands. Companies that usually have an established presence on the web and/or offline. They are often classified by verticals such as retail (like Macy's or Amazon), travel (American Airlines, Hotels.com), entertainment (HBO, Netflix) and CPG (Coca Cola, Kraft). App Developers. App owners whose only business is mobile apps (like Supercell, Tinder, Clean Master). Agencies. A company that creates and manages ad campaigns for multiple advertisers (usually brands). DSPs. A Demand Side Platform is an advanced software that connects multiple ad exchanges together, automatically making complex media buying decisions to determine how much to pay for a single ad impression — mostly through a process called real time bidding (RTB). www.appsflyer.com 7 Getting Started with Mobile Attribution & Marketing Analytics Sell Side Publishers. A publisher is a mobile website or app that sells ad inventory on its property. SSPs. A Supply Side Platform helps publishers automatically and efficiently manage the selling of their inventory to multiple buyers in order to maximize their inventory yield. Connecting the buy side to the sell side Ad Networks. A company that matches supply from mobile websites and apps to the demand of advertisers. A key industry player. Ad Exchanges. An automated marketplace that connects advertisers and publishers to buy & sell mobile ads, mostly in real time. Analytics Independent Attribution Analytics. Unbiased providers serving as de-facto ecosystem regulators that are able to accurately attribute credit for an install or a re-engagement to a single source (or multiple sources in the case of multi-touch attribution). By definition, truly Independent Attribution Providers are impartial and do not engage in the buying or selling of mobile ads. This is why they are trusted both by players on the buy and sell side to measure and report on campaign performance, and settle reporting discrepancies. Marketing Analytics. By connecting attribution to in-app activity, marketers can understand which source (network, campaign, publisher and even creative variation) delivered real value (engagement, revenue, lifetime value, return on investment). Attribution firms commonly include marketing analytics in their offering. www.appsflyer.com 8 Getting Started with Mobile Attribution & Marketing Analytics App Store Analytics. A category divided into (1) the app stores themselves that offer basic analytics on installs, and (2) specialized companies that provide more advanced analytical tools & data slicing. In-App Analytics. Companies that specialize in measuring and analyzing app usage patterns. Such insights can be used to improve user experience, retention rate, and user lifetime value. Other Mobile Marketing Automation. Providers that develop software that simplifies communication with customers and prospects. In mobile, this involves an ever-growing set of channels such as push notifications, in-app messaging, wearable device notifications, and SMS (or MMS). Anti-Fraud Specialists. Firms that develop advanced data-driven mechanisms to combat the threat of ad fraud, as it applies to mobile (particularly install fraud and in-app event fraud). www.appsflyer.com 9 Getting Started with Mobile Attribution & Marketing Analytics 2.2 Common Pricing Models HIGH PERFORMANCE Cost Per Cost Per Action Install CPA CPI Payment Terms: Pre-determined Payment Terms: Pre-determined price price paid for every in-app action paid every time a user installs the defined by advertiser (revenue or application on his or her device. engagement related). Pros: Performance model and reduced Pros: Pure performance model risk; organic uplift following increase in that’s connected to users’ real value CPI-driven campaign installs. actions; adopted by the savviest data-driven advertisers. Cons: Risk of non-transparent networks driving a high volume of low quality or Cons: Can be more costly; may hurt incentivized traffic to drive installs; in reach as networks are more cautious hyper-competitive app economy the buying media as they assume install KPI is losing ground to engagement heightened risk. and retention-driven KPIs. LOW HIGH ADOPTION Cost Per Cost Per ADOPTION Mille Click CPM CPC Payment Terms: Pre-determined price Payment Terms: Pre-determined price for every 1,000 impressions (cost per paid every time a user clicks on an ad mille – mille being the Latin term for one thousand). Pros: Easier to analyze user engagement through ad creative A/B testing; primary Pros: Maximal brand awareness, reach, model used by tech giants Facebook, lower cost. Google and Twitter. Cons: Non-performance model; greater Cons: "Fat fingers" phenomenon means chance of fraud and non-transparent you risk paying for unintended clicks and networks sending low quality damaging your brand name with awful impressions. user experiences; higher cost than CPI if you don’t have the resources to optimize click-to-conversion path; lack of robust analysis tools; vulnerable to fraud. LOW PERFORMANCE www.appsflyer.com 10 Getting Started with Mobile Attribution & Marketing Analytics 2.3 The Importance of Non-Organic Installs in Today’s App Economy With about 1.5 million apps on both iTunes and Google Play, the chances of making it on organic installs from app store discovery alone are about as slim as winning the lottery. That’s why apps need to
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