The document outlines 12 steps for data-driven mobile app development: 1) Collect relevant data, 2) Measure success against benchmarks, 3) Start with identifying questions to answer, 4) Provide actionable data insights, 5) Automate reports and analysis rather than manual work. Key steps also include being proactive, setting milestones, quantifying customer sentiment, learning from mistakes, and taking a long view with relevant sample sizes. The overall goal is to use data insights to effectively drive decisions and ensure app success.

1. 12 steps that will lead you to Data-driven
Mobile App Development

2. There is an endless flow of data to be monitored for
metrics such as
 Bounce rates
 New users
 Exit rates
 Returning users from
innumerable sources

3. People usually feel frustrated or overwhelmed while
integrating data into their development process.
Avoiding the complexities of analytics will only lead
to missing the advantages it could provide.

4. In order to perfect an application, analysis is very
important. Follow these 12 steps to data-driven
mobile app development
• Collecting data
• Measure your success against Benchmarks
• Start with questions
• Provide actionable data
• Don’t pull out records manually
• Leave room for a big win

5. • Being Proactive Vs being Reactive
• Set your milestones
• Quantify customer sentiment
• Learn from your mistakes
• Consider the long view
• Measure relevant sample
size

6. Collecting data
Remember all the data that is collected will answer
questions one day or the other. Be smart to collect all
relevant information that is needed.

7. Measure your success against Benchmarks
Focus on company-wide KPIs and keep probing
yourself about how your app could contribute to
them.

8. Start with questions
Always remember to determine the needs that are
to be tracked in order to give actionable insights
later.

9. Provide actionable data
Free flow of information will keep analytics stream
fresh and open to changes.

10. Don’t pull out records manually
Reports should be set up with analysis and time
focused on answering questions.

11. Leave room for a big win
Give some space for your analytics analyst for some
free rein, the output and the insight will be
surprising.

12. Being Proactive Vs being Reactive
Be proactive and think of fixing the road ahead
instead of looking in the rear-view mirror.

13. Set your milestones
Decide on significant metrics, set your goals and
share it with your users and media to reach your
target

14. Quantify customer sentiment
Monitor reviews and received mails to analyze the
usability improvements

15. Learn from your mistakes
Keep record of the updates of what works and what
doesn’t.

16. Consider the long view
Always look beyond, set longer timeframes and see
bigger trends.

17. Measure relevant sample size
Keep a statistical data set about the number of users
and the time taken

18. So accordingly, it’s the illuminating insight that is
gleamed from combining quantitative and qualitative
data that will effectively make data the driver to your
app decision. The most valuable role played by a data
is the app’s success.