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ASO: A/B Testing your store listing

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Publié le

AppPromotionSummit London 2016 #APSLondon
Appstore A/B test
ASO Conversion
Play Store Experiments
iOS Search Ads
A/A Test

Publié dans : Santé
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ASO: A/B Testing your store listing

  1. 1. 1 1 A/B testing your store listing @Thomasbcn #APSLondon
  2. 2. 2 2 @Thomasbcn #APSLondon
  3. 3. 3 3 ASO has changed… ASO 2.0 / AMO / AVO • App Store search Optimization (ASO 1.0) • Conversion Rate Optimization (CRO) • Search Ads (SEM) • Featuring • App Indexing (SEO) @Thomasbcn #APSLondon
  4. 4. 4 4 https://twitter.com/Thomasbcn/status/690109233510105089 Why? 70% to 90% of App Stores “views” don’t generate an install Testing the listing > Raise install conversion > More installs / less UA costs Sources: Branch / Salesforce / Splitmetrics / SensorTower @Thomasbcn #APSLondon
  5. 5. 5 5 https://twitter.com/Thomasbcn/status/690109233510105089"We have increased install conversions by more than 25% testing content for our app stores” Maria Waters (Kabam) “If we can improve the app store conversion, we actually reduce the load on our marketing team and significantly reduce the budget that we spend on user acquisition” Rajeev Girdhar (Rovio) “I changed my icon to an icon with a unicorn. My daily downloads as well as daily revenue doubled!” Per Haglund (Super Puzzle) Source: Splitmetrics, VB, StoreMaven Why? @Thomasbcn #APSLondon
  6. 6. 6 6 +44% conversion* (but…) @Thomasbcn #APSLondon
  7. 7. 7 7 Gut choices vs testing “Design by committee produces disastrous results” Michael D'Ulisse (TapTapTap) “A/B testing revealed that the images the team preferred reduced the conversion rate of installs by 15%” Fat Fish Games (VB) “I’ve seen pageview to download conversion rates rise double digit percentages through icon optimization” Wilhelm That (Rovio) @Thomasbcn #APSLondon
  8. 8. 8 8 https://twitter.com/Thomasbcn/status/690109233510105089 What to test • Icon • First screenshot (+video?) • Title • (Short) description • Feature graphics @Thomasbcn #APSLondon
  9. 9. 9 9 A/B testing iOS Search Ads “The top app achieved approximately the same amount of clicks on the ‘Get’ button regardless of whether it was a ‘search ad’ or a regular search result” “Users don’t see the difference between sponsored and organic listings” @Thomasbcn #APSLondon
  10. 10. 10 10 How to? Apple AppStore • No official tool • Send paid & owned traffic to an AppStore replica (web) • Providers: Build your own? (Soundcloud) youtube.com/watch?v=v8MXAzYPKFY @Thomasbcn #APSLondon
  11. 11. 11 11 @Thomasbcn #APSLondon
  12. 12. 12 12 Apple AppStore A/B testing caveats… • Misleading users • Organic traffic excluded • Added costs: tool + dropoff “You’ll be losing some users who’ve decided to download your app” Nick Kurat (TestNest) “There was a big drop-off which made the cost to acquire each sample user much higher than expected: greater than $10 on Google Play.” Ilya Shereshevsky (DeNA) Source: TestNest, AppAnnie @Thomasbcn #APSLondon
  13. 13. 13 13 How to? Google Play Store Play Store Experiments • Built-in (Dev. Console) • Includes organic traffic • Test visuals & texts • Up to 5 localized experiments at a time • FREE @Thomasbcn #APSLondon
  14. 14. 14 14 Source: RedKaraoke @Thomasbcn #APSLondon
  15. 15. 15 15 Source: 8fit @Thomasbcn #APSLondon
  16. 16. 16 16 Sources: Iteratingfun, TC, TNW +30% @Thomasbcn #APSLondon
  17. 17. 17 17 Sources: Peter Fodor, FatFish, @Thomasbcn #APSLondon
  18. 18. 18 18 Google Play Store A/B testing limits… • Android & iOS are different • No testing on title • Traffic split uncontrolled & undisclosed • No user behaviour details in app / on bottom line on page • Unreliable statistical relevance… Read more: GP Experiments limits acc. to @Thomasbcn #APSLondon
  19. 19. 19 19 Measuring user behaviour on your listing @Thomasbcn #APSLondon
  20. 20. 20 20 Testing the tool itself : the A/A test @Thomasbcn #APSLondon
  21. 21. 21 21 Counter testing: @Thomasbcn #APSLondon
  22. 22. 22 22 The issue with GP Experiment: Undisclosed statistical significance @Thomasbcn #APSLondon
  23. 23. 23 23 A/B testing listing caveats… • Most A/B tests fail! • Closed variants bring little learnings • Volume required for significance can be high • Improvements curve • Bottom line impact? • Bias/externalities “Only 1 out of 8 A/B tests have driven significant change” @noahkagan “We waste our time testing variants without any real meaningful differences” @justinrmegahan Read more: ConversionXL, Formisimo, Groove @Thomasbcn #APSLondon
  24. 24. 24 24 @Thomasbcn #APSLondon … Believe your guts … Design by committee … Start with close variants … Assume iOS & Android behave the same … Mimick your competition … Conclude on early data … Believe minor uplifts … Believe GP Experiments stats relevance … Test & iterate … Make bold assumptions … Focus on visuals … Localize your tests … Counter-test results … Double-check with tracked sources … Challenge the tools … Challenge yourself
  25. 25. 25 25 A/B testing your store listing @Thomasbcn #APSLondon

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