A non-technical introduction to mobile analytics. Learn how it managed, analyzed, and how it drives business and product decisions.
This presentation focuses on in-app-analytics.
Important aspects it covers:
1. The tool covers Flurry for in-app-analytics: active users, retention, events, funnels, segments, user acquisition
2. It introduces App Annie for sales analytics
3. Case studies from Cammy and Skater
2. 2
• Digital Producer background
• Worked online for 7 years
• Next Digital, Deloitte, Airbnb
• Love TV series, movies & sports
• Twitter: @inspiredworlds
Head of Product Development at Tapmint
ABOUT ME
3. 3
• We make mobile apps for ourselves and for
consulting clients. We can also help you
with mobile analytics.
• Website: http://tapmint.com
• Twitter: @tapmint
• Apps we have made include 3 language
game apps (http://nativetongue.com)
• 450,000 downloads
ABOUT US
4. 4
• Learn the basics of the mobile application ecosystem in
terms of data collection and analytical tools.
• Understand the steps and skills needed to analyse a
mobile app from start to finish.
• Learn to make informed decisions on designing,
marketing, and developing mobile apps.
• Understand the basics of managing the app
development process through analytics.
TAKEAWAYS
5. 5
1. Identify the main metrics to follow on mobile
2. Setting up tracking
3. Funnels & goals
4. Ability to analyse mobile app/mobile site for design purposes. With
information I can share with my clients to improve their trust in
me when designing for mobile.
5. Flurry vs GA
ONE THING YOU WANT TO LEARN - SURVEY RESPONSES
6. 6
1. Why is mobile analytics important?
2. Key Concepts For in-app-analytics
3. Exercises
4. Choosing an analytics tool
5. Appendix
1. Advanced Flurry analytics
2. Sales analytics
3. Case study - Skater
4. References
OUTLINE
8. 8
• Every aspect of a product is a hypothesis about what users want
• Build - measure - learn cycle
• Critical to making decisions
• From opinions to facts
• Qualitative vs Quantitative
• ROI
WHY MOBILE ANALYTICS IS IMPORTANT
9. 9
• Shorter cycles for feature releases
• Don’t go live without analytics
• Start by measuring one metric
RULES OF THUMB
14. 14
• Downloads
• DAU, WAU, MAU (Daily, Weekly, Monthly Active Users)
• Retention rates (Day 1, Day 3, Day 7, Day 30, Day 365)
• ARPU - Average revenue per user
• ARPPU - Average revenue per paying user
• Paying User Conversion Rates (1st, 2nd, nth purchase)
• First time user funnel dropoffs
WHAT METRICS SHOULD I BE TRACKING?
15. 15
• User paths
• Social sharing events
• User acquisition
• Custom events
• Funnels
• Segments
WHAT METRICS SHOULD I BE TRACKING?
16. 16
• Popular tool
• Free
• Designed for mobile
• Easy to use
• Customise events, funnels, segments
WHAT WE USE : FLURRY
17. 17
• Usage
• Retention
• Audience
• User acquisition
• Events
• Errors
• Technical
FLURRY OUT OF THE BOX (OOTB)
18. 18FLURRY OUT OF THE BOX (OOTB)
• Usage: new users, active users, sessions, session length
• Retention: return rate, rolling retention
• Audience: geography, personas, interests, age
• User acquisition: source, CPA, quality of install
• Events: event summary, user paths, funnels
• Errors: crash reporting
• Technical: top devices, firmware
19. 19IN-APP ANALYTICS
DOWNLOADS
• Downloads is often the most quoted statistic.
• Easiest to measure and understand by the public.
• Important but only shows one perspective.
21. 21IN-APP ANALYTICS
NEW USERS
• A new user is a user who has just started using your
application.
• Users are identified by unique phone IDs (which vary by
platform) to ensure that a user is in fact a unique new
user and not just an installation.
23. 23IN-APP ANALYTICS
ACTIVE USERS
• A user that has had at least one session with your
application during a given time period (days, weeks,
months).
• If a user launches more than one session during a given
period, they will only be counted once.
24. 24IN-APP ANALYTICS
ACTIVE USERS
• DAU – daily active users
• WAU – weekly active users
• MAU – monthly active users
Can be expressed as total number and %.
26. 26IN-APP ANALYTICS
SESSIONS
• Number of user sessions: A session is one use of the
application by an end user. When the application is
launched and ends when the application is terminated.
• Length of sessions: The session length is defined simply
as the length of time between the start application event
and the end application event.
27. 27
• Return rates – percentage of users who return to
your app on a given day, week or month
• Day 1, Day 3, Day 7, Day 30, Month 1 vs Month 12
• Measured by cohort (install date)
IN-APP ANALYTICS
RETENTION
28. 28
• Measured by cohort
(install date)
• Heatmap of
returning users
IN-APP ANALYTICS
RETENTION
29. 29
• Custom events that you set up to track specific
items or actions.
• Examples:
• How many users complete level 1
• How many users bought an IAP (in-app
purchase)
• How many users shared their activity to
Facebook
IN-APP ANALYTICS
EVENTS
30. 30
• Events have two elements:
1. Actual event
2. Parameters (details)
• Requires title for the event and a description for
the event
• Use similar wording across apps
• Limit of 300 events
IN-APP ANALYTICS
EVENTS
40. 40
• For this exercise, consider your own app or one that
you are familiar with.
• 1. What are your business goals? Choose one goal.
• 2. How could you measure this goal using standard
mobile analytics?
• 3. How could you measure this goal using a custom
event?
CLASS EXERCISE 1
41. 41
• A series of steps or events create a funnel
• Funnels track users as they execute a
defined set of steps
• Must be completed in the order of steps
• See how many users that started a given
process completed it.
• For those that did not complete the
process, funnels show you at which step
they exited.
IN-APP ANALYTICS
FUNNELS
43. 43
• Funnel created with 3 events
1.Launched App
2.Played Stage 1 for Animals language pack
3.Purchase IAP for “Clothing & Vegetables language pack”
• Want to know how many people in Stage 1 have bought the first
IAP, which is the first IAP.
• Will lead to investigation into questions such as:
• How can I increase the conversion of the first IAP?
• How does this compare to conversion of other IAP’s?
• How does this conversion compare to other stages?
FUNNEL EXAMPLE : SPANISH SMASH (iOS) APP
44. 44FUNNEL CASE STUDY : CAMMY - CCTV ON YOUR SMART PHONE
• Cammy is a free app that
connects with most WiFi
cameras, smartphone
cameras and webcams.
• Allows you to remotely
monitor the places and things
you care about.
46. 46FUNNEL CASE STUDY : CAMMY
• Cammy has an android app, iPhone app, web app.
• They want to use the same tracking across all these apps.
• Using mixpanel analytics.
• They are tracking:
• Screenflow: What steps a user has done
• Where do users fall off the funnel?
• Whether a user has successfully added a camera
• How many active cameras a person has
• Common error messages in using the product
47. 47FUNNEL CASE STUDY : CAMMY
•Has mobile metrics influenced the product?
•Yes, to some degree.
•Updated the user flow.
•Added triggers to assist people when they fall off the funnel.
•MixPanel vs Google Analytics
•Chose mixpanel as it can monitor property per user.
•Mixpanel is an enterprise product. Pricing based on number
of actions.
•GA is free. It aggregates data. Doesn’t show properties of
individual users
48. 48EXERCISE 2: FIRST TIME USER EXPERIENCE FUNNEL
•Should I require my users to register before using the app for the
first time?
•How much content should I show them before initiating the
registration process?
•Do my conversion rates improve if I enable customers to register via
their Facebook or Google accounts?
•Are new users able to immediately experience an “AHA” moment?
49. 49FUNNEL EXERCISE: FIRST TIME USER EXPERIENCE
• Social game example
• It requires a user to complete a tutorial then create a profile to be
matched
with similar users.
• Where are people falling off the funnel? What can we do?
50. 50FUNNEL EXERCISE: FIRST TIME USER EXPERIENCE
• After completing the tutorial, 69% of people “Create account”
• What is impacting the conversion of the “create account”?
• Things to investigate:
• Are there too many fields to be filled out?
• Why do we need to ask for these fields?
• Could there be another method to sign-in that is easier e.g. Facebook
or Google Account?
• Should we require a sign-up before a user can play?
• Can we include sign-up information in the tutorial?
• 95% of people have finished the tutorial so this is not a problem area
51. 51
• Userflow
• How do users behave in the app?
• Where do they go?
• At what point do they convert?
IN-APP ANALYTICS
USER PATHS
53. 53
• Where do users go after the first view (laugh selection screen)?
• Why are not more users going to the second view (send to a
friend)?
• From speaking to users and also checking the database, some
users are reluctant to connect to Facebook to send a laugh to a
friend.
• We can create an event for Facebook login
• Then see what happens after user connects to Facebook
HAHA case study
54. 54
• Drill down to a specific group based on events and other
dimensions
• Example 1: All Chinese users that have completed level 2
• Example 2: All users that have bought 4 in-app-purchase packs i.e
all our available IAP’s.
• Example 3: All users that have only bought one specific IAP
(Clothing & Vegetables pack).
IN-APP ANALYTICS
SEGMENTS
57. 57
• Measure the impact of specific campaigns or channels on
your user base
• When you create a campaign, it gives you a campaign URL
to put in the ad campaign to track
• Review metrics:
• Clicks on ads
• Installs
• Quality of install (funnels, segments)
• Post install tracking
IN-APP ANALYTICS
User acquisition
58. 58
• Which app?
• Metrics they are tracking?
• How has it impacted your business?
• Metrics they care about?
• Tools?
IN-APP ANALYTICS
User Acquisition: Verbal Case Study
60. 60
• Figure out which one is the best for your business
and needs
• We want to empower you with the ability to choose
the one that is right for you
CHOOSE THE RIGHT TOOLS FOR YOU
61. 61CHOOSE THE TOOLS THAT IS BEST FOR YOU
• Flurry
• AppAnnie
• Google Analytics (Universal Analytics)
• MixPanel
• KissMetrics
• AppFigures
• MopApp
• Crashlytics
• AppSee
• HasOffers
• and many more
62. 62CHOOSE THE TOOLS THAT IS BEST FOR YOU
WHAT TO CONSIDER
• Purpose
• Easy to install?
• Easy to setup and use?
• Mobile or mobile/web
• Value
• Price
• ROI
• Do other people know how to use it?
63. 63
• We use Flurry
• Popular tool
• Designed for mobile apps
• Free
CHOOSE THE TOOLS THAT IS BEST FOR YOU
64. 64
• Free
• Great for sales analytics
• Revenue, Rankings, ASO, Advertising, Reviews
CHOOSE THE TOOLS THAT IS BEST FOR YOU
WHAT WE USE : APPANNIE
65. 65
• We make mobile apps for ourselves and for
consulting clients. We can also help you
with mobile analytics.
• Email hello@tapmint.com
• Website: http://tapmint.com
• Twitter: @tapmint
NEED ANALYTICS HELP?
68. 68
• Cross-sells – allows you to see how many users of one app
go on to install another app in your portfolio
• Up-sells – lets you see how many users of the free version
of your app eventually purchase the paid version
• Cross app usage
• Cross app funnels
IN-APP ANALYTICS
CONVERSIONS
69. 69CROSS SELLS
• Cross-sells: If a conversion takes place between two different
applications, it is considered a cross-sell.
70. 70UPSELLS
• Up-sells: If a conversion takes place between the free and paid
versions of a given application it is considered an up-sell.
80. Case Study: Skater
1. What is your business?
• Action sports games for smart phones.
• Focusing on one main product "Skater" for iPhone
2. What are your business goals?
• Product: First deep penetration and high engagement in a niche. Then
spread to capture broad audience with adaptation of product, pricing and
brand partnership model.
• Financial: $500k+ within first 24 months from launch as first benchmark.
81. Case Study: Skater
3. What are the mobile metrics you are tracking to meet these business
goals?
Our learnings were:
• 1st attempt: Used Mixpanel for first launch. But we were tracking
enough data to cost $20k/mth. Mixpanel does not let you access any data
unless you pay full amount for what you track.
• 2nd: Implemented Parse analytics. Tests in dev worked but when
implementing for next release used white spaces in property names.
Although seemingly undocumented this is not allowed and no data points
were tracked.
• 3rd: Soon to be released next version with Flurry.
82. Case Study: Skater
Currently the analytics we have had to work from are:
• Facebook SDK basic stats including device type, geo, age, gender, etc.
• Parse basic usage stats including retention, DAU, requests / sec, etc.
• Info derived from the cloud systems. The game stores player profiles in
the cloud on Parse so we can see player progress, vanity item purchase
and selection, contribution to and engagement with user generated
content per player.
83. Case Study: Skater
4. How has mobile metrics impacted your business & product decisions?
1. Retention (DAU and engagement with user generated content) figures
validated value of online content system and this will continue to be a focus
of refinement in future updates. Plan to make system more relevant to the
player's local social graph in future to increase personal investment and
incentive.
2. Tracking player progress: We found sticking points which after some
discussion with users we learned there was poor communication about some
of the more novel aspects of how the game works. A high % of players are not
getting value from what we intended to be the most valuable parts of the
game.
84. Case Study: Skater
5. Action point from metric insights?
There is a big chunk of players (~40%!!) for whom we can unlock this value
in the next updated with some small design changes to expose the correct
way to use the game:
• How to engage with the online content
• The mechanism for progression
• Unlocking of content
85. Case Study: Skater
6. How are you tracking paid customer acquisition?
Facebook conversions using the Facebook SDK.
Everything else using Kochava links short-linked to bitly links.
86. Case Study: Skater
7. What analytics tools are you using to track mobile metrics? Why?
Mixpanel looks really cool and would stick with it but the pricing model is
bananas for our needs.
Would consider GA in future as it looks powerful and flexible. I hear it's not
that heavily supported though as not a paid product.
Using Flurry for next update as it's free, has large user base and is straight
forward. As we're lacking even basic data points at the moment just want
something working in there ASAP so can start getting lowest hanging fruit
as far as learnings.
87. Case Study: Skater
8. Where can we find out more about the Skater app?
• Nominated for mobile game of the year by IGN!
• Check out the launch trailer
89. APPENDIX
References and additional reading
• Mobile app analytics directory presentation, MobyAffiliates
• Retention in Flurry Analytics, Flurry
• Funnels in Flurry Analytics, Flurry
• Funnel tutorials, Flurry
• Events & Event Reporting, Flurry
• Events - News App Sample Events, Flurry (doc available on Paperzz)
• How to calculate retention and user uplift, Streethawk
90. 90
• We make mobile apps for ourselves and for
consulting clients. We can also help you
with mobile analytics.
• Email hello@tapmint.com
• Website: http://tapmint.com
• Twitter: @tapmint
NEED ANALYTICS HELP?