Earn with create android
mobile apps
Many mobile app-building companies churn out feature set of
relatively different apps, but only several even keep alive in the cutting-edge
market of open-source development, so I can’t really talk about the data
collection systems of these outlier firms. Besides, I can’t get started knowing
how to build such novel systems. But I can tell you some stories which have
taught me quite a bit about building prototypes to figure out (what I’m not
told about these data collection systems is who decides if your data collection
system is novel or not).
A few nights ago, I was talking to our creators at To-do on
Slack regarding the origin of the central business district app they had
developed for The First Bank of Thailand, just for example.
In short, they had started out talking with the “basic and daily
users” of the bank in an informal connection group, where anyone could be a
subject of discussion. Once they had established the small mobile users, they
had targeted users with usually more advanced educations and higher income,
whom the “basic and daily users” largely missed.
This time of commonality got them interested in establishing a
“common form of communication” among the daily users of the business district.
It’s easy to imagine, like how a popular social network would connect local
mayors and mayors at the national level. “Security is the central value” of the
user, and this might be the reason they had picked people who were mostly seen
as safe but also strong users.
As soon as they had about 500 users on the main platform, they
had clearly designed their method of collecting data with verifiable questions
and user answers to be asked, and they would close the information collection
program right before submitting it for review. This design produced high
initial quality of answers, in particular, there was almost no room for a style
or ease of language factor.
As soon as this success was guaranteed, they had been able to
request the feedback from a market research platform. They have decided to
choose a “hybrid” approach of the two tools, which is to either work on
creating an “indigenous” standard for the system that will differentiate the basic
users from future users, or they would be more elaborate with their data
collection systems and apply to those who already use the basic users with the
same ID, if not the exact ID. However, they quickly changed their design
details to more manageable and practical proportions, and their almost all
robust sample data collected before conducting the survey also contributed to a
high quality of their data collection system.
By the time they collected 20% of the user data for the project,
they had conducted their surprise Q&A at a concert and even had a live
participant by surprise, because of their lack of expectations to learn the
answers directly from him. While doing this, they had started a record of the
answers received, which was a great milestone to analyze the data collected
once the system is created.
After years of observation and rigorous vetting of this type of
user psychology, the to-do team was beginning to assess its utility and quality
for their testing method. An especially special exercise is holding an “scrum
session” during which each member of the team asks for a question from an
audience of their design competitors to listen to reactions from the users,
which themselves were also asking questions about the problem.
Next, they tried to experiment with picking app ideas from
competitors which have comparatively low user numbers, but are in every way
different from their ideas, and what worked with them: the app was based on a
combination of their experience with other random Android and iOS mobile
app-making projects where a long conversation with users goes through a stage.
After all, in most cases a comparative phase of app testing
period ends after now we start with fun questions like “How would you create an
app that has a high visual representation of the situation of the community?”
or “What features of the screen should be generated to interact with the user,
for example the time, the weather, schedules and traffic forecasts of the
community?”
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