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App Store Optimization Using Math
Nathan Mellor is an independent app developer and author. He has developed top grossing Android apps and written books on app development. In this presentation, he discusses app store optimization (ASO) using data and analytics. He reviews the process of acquiring, engaging, and monetizing users. He shows the math behind key metrics like searches, discovery, installations and explains how to measure and improve performance at each stage through ASO techniques like keyword research, promotion, and virality. The goal is to understand user behavior and make more money through an optimized app listing, descriptions and marketing.
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App Store Optimization Using Math
- 1. • Nathan Mellor •CritterMap Software LLC • Follow up at http://eepurl.com/d9tZj App Store Optimization using Math
- 2. • Formerly softwareengineer at Hewlett-Packard • Independent App Developer since 2009 as an apprenuer, not a contractor or consultant • Author of Top grossing Android App • Trained in Internet Marketing at University of San Francisco online program • Author of Apps for Profit My Background
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- 5. Objectives • Review stagesof the process of getting users to your app. • Show the math behind them • What you can do to improve numbers in all parts • Make more money
- 6. Population Android ActivationsPer Day 1000000 Per Day 1000000 Target Audience Searching for your app today 5% 50000 5% 50000 Search See your App’s icon 15% 7500 34% 17000 Discovery Click Through to App Listing 20% 1500 30% 5100 Acquisition Install the app 4% 60 6% 306 Conversion Active user 10% 6 20% 61.2 Monetizatio n Make money for you $1.40 $8.40 $2.10 $128.52 Loyalty Buy something else later $0 $8.40 $0.34 $149.33 Sharing Influence someone else to buy 1% $8.48 5% $156.79
- 7. Target Audience • Howmany people are looking for an app like yours today? int searchesCount = 0; Searches searchesToday= Today.getAllSearches(); Set<Keyword> keywordSet = searchesToday.getKeywordSet(); foreach(Keyword k in keywordSet) { int frequency = searchesToday.getFrequencyofKeyword(k); if(app.isKeywordRelevant(k)) searchesCount += frequency; }
- 8. Target Market •Can youexpect to change the number of people looking for an app like yours? •Probably NOT. •What can you do? • Measure the relative popularity of you best app ideas
- 9. Competitive Analysis • Findthe category your app will be in • Start at the top • Find the highest ranking app that has a similar target audience • Set your goals for how high you want your app to rank. • Tool:App Annie
- 10. Search • How manytimes does your app appear in a search?
- 11. Searches in GooglePlay • 12% search for apps daily • 50% search weekly • 6 million unique search phrases are used each week. • (Source: Google I/O 2013).
- 12. Searches showing yourapp int views= 0; Searches searchesToday= Today.getAllSearches(); Set<Keyword> keywordSet = searchesToday.getKeywordSet(); foreach(Keyword k in keywordSet) { int rank = app.rankForKeyword(k); int frequency = searchesToday.getFrequencyofKeyword(k); List<Search> searchesK = searchesToday.forKeyword(k); foreach( Search search in searchesK ) { int L = search.visibleLength(); if(rank<L) views +=1; } } L = 7+ for Google Play on the phone L= 24+ for Google Play on the web + ScrollLength
- 13. Which can youknow precisely? RANKING: int rank = app.rankForKeyword(k); -You can track this. FREQUENCY: int frequency = searchesToday.getFrequencyofKeyword(k); - Google’s not telling you this :( RELEVANCE: app.isKeywordRelevant(k) -You only think you know this - subjective (see next hour)
- 14. • A keywordis generally a multi word search phrase • You want to estimate • RELEVANCE • FREQUENCY • DIFFICULTY Keyword Research
- 15. ASO tools • AppStore Optimization • Searchman.com • mobiledevhq.com • appnique.com • sensortower.com • appcodes.com
- 16. What to lookfor in your ASO Tool • Done well: • Track 50+ keywords over time • Track competitors and their keywords • Could always be improved: • Estimate Relative Traffic for a keyword - guess • Estimate Relative Difficulty for a keyword - guess • Suggest more keywords
- 19. Relevance • How likelysomeone using a particular phrase is looking for your app, will install it, keep it, and make you some money • Determined by your knowledge of the target market of your app. • Still a guess until you’ve measured it • Best source: Google Adwords Campaign
- 20. Frequency • How manypeople are using a particular search phrase (relative to others) • Estimated with ASO tools - a guess • Better Measure:Adwords Campaign
- 21. Difficulty • How likelyyou can actually attain a top position for a particular search phrase • Is context dependent • ASO tools have numbers - a guess
- 22. Rookie Mistakes • Thinkingthat there are only six or so phrases for your app • Thinking that you already know the two most important ones. • There are always more phrases than you think • The ones that you think are most important may not be • Try for 500, then narrow it down to 50
- 23. Broadening your scope •Come up with a number of seed words • Think of synonyms and variations • Think of related products or services that your target customer would search for • Think of how they would search for your competitor’s app • Consider common brand names in the field.
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- 25. Video Chat example •describe it in a few ways • Video chat,Video conferencing, video call, video conference • Add popular brand names • skype,google talk,google hangout, facetime, • Add related apps • oovoo, tango, and camfrog • Put in Adwords Google Keyword planner
- 27. Adwords Keyword Planner • Useexact phrase • Apply to a category • Many categories are available • “Computers and Consumer Electronics”
- 29. Where can weuse these keywords • Title • Description • Outside Links • Paid Promotions (ie Adwords). • Organic Promotions
- 30. Title • Most importantkeyword • More influential than description • Only 30 characters (no paragraphs like iOS titles).
- 31. Branded Title vsKeyword Title Branded Keyword Examples Pandora Amazon BackCountry Navigator Music Player Online Book Store GPS and Maps Recognizable Trademark Yes Often not Word of Mouth and reputation Helpful Less helpful Functional conveyance Maybe Probably Search term? Only if already familiar Valuable Can you do both in 20-30 characters?
- 32. Description • Your primaryand secondary keywords • Keep it short if you have a small number of very important keywords • Longer if you need to target more keywords. • Mentioning a keyword about five times might be about right • Use the full phrase if possible.
- 33. Differences from iOS iPhoneGoogle Play Apps per page 1 7-8 Reaching app #25 25 flicks 1 Flick App Title Very Important (approved by Apple) Very Important 30 characters (25 seen) Tags (secret keywords) Very Important (approved by Apple) 100 characters Not used. Description keywords Unclear if used in search Important in search 4000 characters Other factors in search Unclear Installs and Uninstalls Ratings Links from outside Google Play
- 34. Factors Influencinging all rankings •Installs in the last week (determines your category ranking) • Active installs • Long Installs • Number and quality of ratings
- 35. Factors Influencing a KeywordRanking • Keyword search history - relevance • Active Installs • Long lived installs • Links from outside web sites with anchor text
- 36. Other phenomenon • Googlewill make app suggestions for people in Google search. • These are starting to show up in Google Analytics. • Keywords used in comments will influence ranking
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- 39. Target Audience (Searching foryour an app like yours today) Search (sees your app name and icon) What happens later effects what happens earlier Discovery (see your app Listing ) Conversion (take actions) Loyalty (repeat revenue) Advocate (recommends product) Monetization (give you revenue)
- 40. Paradox • You can’tget enough traffic because you don’t rank well enough for some good keywords • You don’t rank well enough for some good keywords because you don’t have enough traffic • How to get the process going?
- 41. Are New AppsSpecial? • Mostly Not. • Top complaint of IOS Developers that port to Android • No human review process like Apple • Top New Paid/Top New Free • Last 30 days (globally) • Ordered by downloads
- 43. Discovery: Clicking Through tothe listing • Large App Icon • Title • Company • Overall Rating
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- 45. Acquisition: Getting the install •Can now be tracked in Google Play console.
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- 47. Getting an install •Promotional Screenshot • Stats • Lead sentence • Screenshots • Reviews • Descriptions
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- 49. Conversion • End userchanges their religion • User completes an action that you want them to complete • Can and should be measured in analytics.
- 50. Analytics: study ofuser behavior • Attribution = where users come from • MetaData = attributes of the users or the install • Events - what users do in your app (can have monetary value) • Limitation: • Tells what happened • Does not say *why* it happened
- 51. Analytics homework • Listthe major actions you want your users to do • List
- 52. Which analytics? Library withAnalytics Other things Google Analytics Adwords ads, Admob,Google Play Services, Facebook Mobile Ads, Fan Pages, AppsFlyer Attribution, Facebook Marketing Partner Localytics Attribution, Facebook Marketing Partner, Push Notifications, In app messages, remarking (Probably more than one)
- 53. Monetization • Won’t happenwithout Conversion • Different models
- 54. Model Development Effort Flexibility Tracking Bestfor Free with Ads Low Medium (with mediation) Fuzzy High usage scaleable costs Paid App Very low Low Horrible Simple, fixed value proposition Inapp Purchase: Managed Medium Medium Good Small number of fixed products Inapp Purchase: Subscription Medium Medium Okay Service with willing payers Inapp: Virtual Currency Higher High Good Virtual Goods Download credits
- 55. Loyalty • Will theybuy something from you later? • New inapp purchase • Your next app
- 56. Viralization • Sharing yourapp via an unpaid sales force • Users can contribute in multiple ways: • Give you a good rating in google Play • Google Plus the page • Like or share your app link in social media
- 57. GoingViral: the dream •You only have to tell one person about the app. • They each tell two friends • In 32 days, everyone with an Android phone will have your app! Installations(t) = 2^(t)
- 58. More realistic goal. •In real life, a viral ratio > 1.0 is rare. • Think compound interest p = number of people 100 people can influence to buy Installations(t)=n*(1+p/100)^t
- 59. Encouraging Sharing • Multipleways: • Make invitations - within the app • Get users to join a network • Make invitations within the network
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- 62. • Nathan Mellor •CritterMap Software LLC • Follow up at http://eepurl.com/d9tZj App Store Optimization using Math Part 2
- 63. Objectives • How toperform experiments that will improve the performance of your app • Use the knowledge to improve the app • Paid advertising for small or large budgets
- 64. Target Audience (Searching foryour an app like yours today) Search (sees your app name and icon) The App Marketing Funnel Discovery (see your app Listing ) Conversion (take actions) Loyalty (repeat revenue) Advocate (recommends product) Monetization (give you revenue)
- 65. Experiments • Free: DeveloperConsole • Free or paid: in app or push messaging • Expensive: dynamic app behavior • Paid: advertising
- 66. Google Play Experiments • Inconsole
- 67. App Messaging • Couldcost money depending on provider
- 68. Dynamic App Behavior •Multiple Implementations of the same feature • Dynamically chosen • Expensive because of development cost
- 69. Disadvantage: • You arelimited to the traffic you already have.
- 70. Paid Advertising • Perception:throwing money at problem • Reality: you can invest as much creativity in advertising as in coming up with apps or features
- 71. Goals for paid advertising •Optimize your app’s marketing funnel • Find out your app’s true value • Bring in a positive ROI • Buy your way into the top ranks (or higher ranks) • Not be at the mercy of free traffic
- 72. Prerequisites • Including theproper libraries • Tracking events • Determining LTV (long term value), short term value, or estimated value
- 73. Math • Revenue(Install) andCost(Install) are not static numbers. Cost(install)<Revenue(install)
- 74. • Optimizing Appfor Conversions • Targeting the right audiences • Targeting • Pruning the tree • Bidding • Optimizing • Timing Cost(install)<Revenue(install) Math
- 75. Example Source CPI ARPU January,Organic 0.26 Facebook Installs, Free App 0.40 0.07 November, Organic 0.19 Google Adwords Installs, Free App 0.37 0.12
- 76. Continuum • Experimentation -R < C • Some Profitability- R > C (sometimes) • Consistency - R > C (more often) • Scaleability - R > C for extremely large values of C.
- 77. Less Effective Structure •Linked List All possible target audiences One Message One graphic
- 78. More Effective Structure • Nary tree Ad Campaign Targeting Ad
- 79. Where to try-what to learn • Google Adwords • Behavior based targeting • Keyword relevance • Refine messaging • Facebook Mobile Install Ads • Profile based targeting • Refine images • Refine message • Learn more about your target audience
- 80. Targeting • Behavior basedtargeting • Example: keyword search • contextual targeting • Apps on a relevant website or app • Behavior targeting converts 3X better
- 81. Targeting • Demographics • Location •Age and Gender • Likes • Past behavior • Profile
- 82. Bidding types • CPM- cost per 1000 impressions • CPC - cost per click • CPI - cost per install • CPA - cost per action
- 83. Bidding • Your objective: •CPI • Or CPA - specific action • Track your objective.
- 84. Bidding Approaches • Biddirectly on your objective • Usually not guaranteed • Not always possible • Not always cost effective • Trust level of network: • Just give me as much as you can at the best price • Let the network track your objective • Micromanage and track results
- 85. Other ways tocontrol cost • Daily or lifetime budgets • Improve targeting • Prune the tree • Timing
- 86. Using keywords inPaid advertising • Test keyword phrases • Test Calls to Action • Find the perfect message for your first line • Test out images and icons
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- 88. Defining install asa conversion
- 89. Paid Advertising -ROI Text Drop the losers and keep the winners
- 90. Results from paid experiments •Find the high converting keywords • Target them more aggressively in Google Play • Use them in internet marketing promotion and links
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- 92. Facebook Targeting • LookalikeAudiences
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- 94. Some results • Rankingsin Different Countries
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