Data Visualisation

Usage of Media Activities by Age (Prescriptive Data)

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(Data.gov.sg, 2016)

Objectives:

To find out which media activity is used most by age, especially from 15 to 29 years old
Allows us to have an idea of what should or should not be included in Timely and what will attract our persona, Georgina from installing Timely

Findings:

21.74% of non-media related activities are accessed most by 15 - 19 years old
22.41% of non-media related activities are accessed by 20-29 years old.

Recommendations:

Through this data, we can conclude that non-media related activities are popular among all age groups. Thus, we can include upcoming events for each months in our application.

The goal is to have at least 80% of people with busy schedules to download Timely and to book at least one event. To achieve this goal, events based on their interests will be recommended to them, instead of having to look through every events.

Monthly Income below 25 Years Old (Prescriptive Data)

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(Data.gov.sg, 2018)

Objectives:

To find out the average income for ages 25 years and below. This is to determine the ticket prices that our persona Georgina can afford.

Findings:

People below 25 years generally have high monthly income. 21.4% of them have a monthly income of $6,000 - $7,900 which is what most of the total population earns

Recommendations:

The goal is to have at least 70% of app users book events with a ticket price of at least $10. This can be measured by looking at the sales. This is attainable by adding the feature that allows users to choose the budget range or filter when searching for events. This set of data helped to justify our persona's income in terms of being able to afford to attend events.

Overtime Paid Hours by Industries (Descriptive Data)

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(Data.gov.sg, 2021)

Objectives:

To find out which industry and service type has the most overtime paid hours

Findings:

Services is the 2nd highest industry with the number of overtime working hours
Being an accountant falls under “Administrative and support services”, which is the highest number of overtime hours under Services
This proves Georgina’s busy work schedule

Recommendations:

The data proves that "Services" is the second-highest industry with the number of overtime hours, Georgina needs Timely to aid her.

The goal is to have at least 85% of users to link their personal schedule to the app’s schedule. This can be measured by collecting app data to see the number of people who have linked their schedules. To achieve this, we can add a calendar feature into Timely that will allow us to curate event suggestions that can cater to their personal schedules.

Number of Changing Exhibitions (Pivot Chart & Slicer)

Screen Recording 2021-07-08 at 7.37.42 PM.mov

(Data.gov.sg, 2021)

Objectives:

To find out how the number of changing exhibitions (variety in exhibitions) can affect people’s interest in the museum

Findings:

Shows a fluctuation throughout the years
Generally in 2019, there was a slight decrease for National Gallery Singapore and Singapore Art Museum. However, there was an increase for National Museum Singapore

Recommendations:

We will have notifications that will alert Georgina of the new exhibitions at the museums. As this allows her to know how frequently changes are made at the museums and what new exhibitions are available. This is helpful for her as she likes going to museums, but she need a variety of exhibitions as well.

The goal is 100% notification be deployed each time a museum has a new exhibition.

We hope to that our data would benefit up to 80% of the museums or researchers who collaborate with us. As they would be able to see how the number of changing exhibitions affects the number of people buying tickets for a particular museum’s exhibitions.

Visitorship to Museums & Performing Arts Events (Predictive Data)

(Data.gov.sg, 2021)

Objectives:

To find out how many people go to museums and performing arts events
This would also link to how many people actually like museums and this type of events

Findings:

Shows a rather stable trend graph throughout the years

Recommendations:

The goal is to have more than 80% usage on the option filter and chatting platform. The indication on the usage of the chatting platform can tell us whether people are interacting with one another. We aim to have an option filter and chatting platform to serve two of Georgina’s needs. First, she want to go to her favourite events and second, to expand her social circle.

Reflection

We were taught digital transformation and learned about the different data such as descriptive, diagnostic, predictive, and prescriptive data. Subsequently, we did a data visualisation using the data we have collected that relates to events and our persona, Georgina. We presented our data in various types of interactive charts, using Power BI and Excel. With each set of data, we included the objective of the data, what we found out and came up with SMART recommendations on how it relates to our application, Timely, or about the types of events our persona enjoys. This whole process allowed us to think through whether the functions are beneficial and to what extent can our persona benefit from it or what other functions can we have in Timely.

From the different data we have found and the charts that we made, we were able to make findings that helped us come up with ideas that can be included in our application, Timely. It gave us a better understanding of the needs of our audiences and how we could better appeal to them. It was initially challenging to find different sets of data and relate them to our persona, but with a better understanding and analysation of each data, we were able to give recommendations for our prototype.

For example, through the data set on Usage of Media Activities by Age and Overtime Paid Hours by Industries, we focused on targeting these two market segments and improving on our app prototype by adding features that would solve their pain points, as shown under "Recommendations".

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