Deconstructing the organic Traffic in the Apple App Store - Hamburg Mobile Summit 2020 - Sven Juergens

Deconstructing the Organic Traffic
in the Apple App Store
Sven Jürgens
Tivola Games GmbH
Hamburg Mobile Summit 2020 | Tivola Games GmbH

Agenda
• Introduction
• Organic Traffic
• Design the MVP
• Summary

Introduction

About Tivola
• Publisher and Developer of Mobile Games in Hamburg
• Founded in 1995 and published +100 games for PC, Nintendo and Mobile
• Over 120 Mio. Downloads on Google, Apple and Amazon
• Focusing on cute games with animals
• 70% female players

About me
• 2019 – present
• Marketing Lead @ Tivola Games GmbH
• 2017 – 2019
• Senior UA Manager & UA Lead @ AppLike GmbH
• 2015 – 2017
• Marketing Manager @LITE Games GmbH
• 2012 – 2015
• Master of Arts, Kassel University
• Thesis: Gamification in HR
• 2008 – 2012
• Bachelor of Science, Pforzheim University of Applied Sciences
• Thesis: In Game Advertising
Sven Jürgens

Organic Traffic

Organic Traffic – Where does a user come from?
Important
factor

Organic Traffic – Further breakdown
• Nearly a 50:50 split between search and browse traffic
• But what about the „You may also like“ section?
• We didn’t know too much about it
• Let’s find out more!
?Which apps are
linking to our games?

Design the MVP

Design the MVP
• Goal:
• Better understanding of the „You may also like“ Black Box and learn from it
• Which app is the biggest traffic driver for our „organic browse traffic“?
• Process overview
• We need data!
• Building a web scraper to get data from the Apple App Store
• Open the Store page of an app 🡪 read out app recommendations
• Data: Ranking position, recommended games
• Find out app download volume
• We will need that for estimating the organic browse traffic that comes through „you may also like“
section from other games
1. App Store
2. DL
Estimates
3. Combine 4. Result
Your app as starting
point for the web
crawler

Program infrastructure
HTML
apps.apple.com
sensortower.com/api
Apple App Store for App IDs and relationships:
apps.apple.com/us/app/pet-world-mein-tierheim/id529818833
Scraper.py
JSON
Sensortower for Download estimates:
sensortower.com/api/ios/landing_page/report_card?app_id=529818833

1. Get Data – Read out HTML of the App Store
Parent App Child Apps / Recommended Apps
Open Browser Dev Tools:
Right click  Inspect
#2

2. Get Data – Download volume estimates
• We now have the iOS App IDs from reading out the App Stores HTML site
• pass the IDs to Sensortower for volume estimates
• apps.apple.com/us/app/farm-story-2/id619481402
• sensortower.com/api/ios/landing_page/report_card?app_id=619481402
Limit the requests per
timeframe!

3. Combine Data and estimate CTR
• Assumption:
• The higher you rank, the more clicks you will get
• Click Rate will decrease with every position
• Our simple model:
• We used basic Google Search CTR data to estimate the traffic proportion of the browse traffic
• Traffic Share = 0.3*[Ranking_Position]^-1.3*[Download_Volume]
More clicks for
top positions

3. Results – the organic browse traffic sources

Summary and learnings

Things we have learned – Network graphs are pretty cool
;)

Summary I
• This is a first step – feel free to take it from here ☺
• Where is the browse traffic (probably) coming from?
• See which apps are linking to us and what is our ranking
• Which app is the biggest traffic source?
• We could create our own „App Overlap“ tool
• e.g. part of Sensortowers Usage Intelligence Toolset
• Or the „Similar Apps Feature“ of TheTool
• Learn more about our app neighborhood
• What are our users playing?
• Which monetization and game design mechanics do they use?
• Check the genres, IAP pricepoints, languages of the apps

Summary II
• Next Steps
• Why is our recommendation ranking position better/worse?
• E.g. „We lost 0.5 stars in rating and our crash rate went up 10%?, so we lost 5 spots?“
• PageRank algorithm could help to identify ups and downs in organic traffic
• Read out and understand the ASO texts of your competitors
• E.g. using fastText library (Facebook) for sentiment analysis
• Rate limits and bot detections are a problem
• Using VPN and proxy networks
• Do not overuse it

Thanks a lot!
Keep in touch:
sven@tivola.de
linkedin.com/in/svenjuergens/
slideshare.net/Sven_Juergens/

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