Project

Project

Project

Markopolo

Markopolo

Markopolo

Role

Role

Product designer

Product designer

Scope

Scope

End to end design

End to end design

© 2023

© 2023

© 2023

Role

Product designer

Scope

End to end design

00.

00.

00.

RESULTS

RESULTS

RESULTS

Facilitating faster, predictable workflows for teams

Facilitating faster, predictable workflows for teams

Facilitating faster, predictable workflows for teams

01.

01.

01.

CONTEXT

CONTEXT

CONTEXT

Why building Markopolo matters

Why building Markopolo matters

Why building Markopolo matters

Being a non technical team member can feel like a disability sometimes

In the case of the team this tool was build for, 4 of the 8 fully remote team members were non technical.


When it came to accessing data on the blockchain, they were at the mercy of the technical team members. Causing big delays for the non-techies when they were making marketing, product, and administrative decisions.


My role as a Product Designer is to take the data hiding in the jungle of backend tech, and bring it forward in an accessible and palatable format for non technical team members. Giving non technical team members autonomy when it comes accessing data, and freeing the developers from tedious repetitive tasks.

Being a non technical team member can feel like a disability sometimes

In the case of the team this tool was build for, 4 of the 8 fully remote team members were non technical.


When it came to accessing data on the blockchain, they were at the mercy of the technical team members. Causing big delays for the non-techies when they were making marketing, product, and administrative decisions.


My role as a Product Designer is to take the data hiding in the jungle of backend tech, and bring it forward in an accessible and palatable format for non technical team members. Giving non technical team members autonomy when it comes accessing data, and freeing the developers from tedious repetitive tasks.

Being a non technical team member can feel like a disability sometimes

In the case of the team this tool was build for, 4 of the 8 fully remote team members were non technical.


When it came to accessing data on the blockchain, they were at the mercy of the technical team members. Causing big delays for the non-techies when they were making marketing, product, and administrative decisions.


My role as a Product Designer is to take the data hiding in the jungle of backend tech, and bring it forward in an accessible and palatable format for non technical team members. Giving non technical team members autonomy when it comes accessing data, and freeing the developers from tedious repetitive tasks.

02.

02.

02.

RESEARCH METHODS

RESEARCH METHODS

RESEARCH METHODS

How do we know what to solve?

How do we know what to solve?

How do we know what to solve?

I was building a custom tool for a team of 6, I decided to carry out interviews with each of them

I was building a custom tool for a team of 6, I decided to carry out interviews with each of them

I was building a custom tool for a team of 6, I decided to carry out interviews with each of them

Ethnographic user interviews

Ethnographic user interviews

Ethnographic user interviews

  • Understand the different demands and constraints which both technical and non technical team members were facing.

  • Get to see people in the environment where they perform tasks

  • Able to pick up on details the user might not be aware of

  • Understand the different demands and constraints which both technical and non technical team members were facing.

  • Get to see people in the environment where they perform tasks

  • Able to pick up on details the user might not be aware of

03.

03.

03.

SUMMARY OF FINDINGS

SUMMARY OF FINDINGS

SUMMARY OF FINDINGS

Layers of problems

Layers of problems

Layers of problems

Time consuming

Time consuming

Time consuming

The current process of manually requesting data from the devs is time consuming for both technical and non technical teams.

The current process of manually requesting data from the devs is time consuming for both technical and non technical teams.

The current process of manually requesting data from the devs is time consuming for both technical and non technical teams.

Key problem

Key problem

Key problem

01

01

01

Interpretability

Interpretability

Interpretability

Data comes back raw in the format of spreadsheets. This makes it harder for users to understand.

Data comes back raw in the format of spreadsheets. This makes it harder for users to understand.

Data comes back raw in the format of spreadsheets. This makes it harder for users to understand.

Key problem

Key problem

Key problem

02

02

02

Predictability

Predictability

Predictability

Working remotely and asynchronously means time is always of the essence, and waiting on people outside of expected workflows is inefficient.

Working remotely and asynchronously means time is always of the essence, and waiting on people outside of expected workflows is inefficient.

Working remotely and asynchronously means time is always of the essence, and waiting on people outside of expected workflows is inefficient.

Key problem

Key problem

Key problem

03

03

03

04.

04.

04.

DATA REPRESENTATION

DATA REPRESENTATION

DATA REPRESENTATION

What the data currently looks like

What the data currently looks like

What the data currently looks like

One of the key issues faced for team members was the way the data was represented by default.


The data was raw and took time to synthesise for both technical and non technical team members.


Below are examples of what the data looked like in the database.

One of the key issues faced for team members was the way the data was represented by default.


The data was raw and took time to synthesise for both technical and non technical team members.


Below are examples of what the data looked like in the database.

One of the key issues faced for team members was the way the data was represented by default.


The data was raw and took time to synthesise for both technical and non technical team members.


Below are examples of what the data looked like in the database.

How do we fix this?

How do we fix this?

How do we fix this?

the way you represent data depends on what you want to do with that data. Some common tasks with data are


  • Compare different items (Thing A vs thing B)

  • See trends (Compare through time)

  • Orient yourself (Sell through rate is x%)


Talking to the team to understand the data and what they do with it is the best way to understand how to represent it.

the way you represent data depends on what you want to do with that data. Some common tasks with data are


  • Compare different items (Thing A vs thing B)

  • See trends (Compare through time)

  • Orient yourself (Sell through rate is x%)


Talking to the team to understand the data and what they do with it is the best way to understand how to represent it.

the way you represent data depends on what you want to do with that data. Some common tasks with data are


  • Compare different items (Thing A vs thing B)

  • See trends (Compare through time)

  • Orient yourself (Sell through rate is x%)


Talking to the team to understand the data and what they do with it is the best way to understand how to represent it.

05.

05.

05.

USER STORY

USER STORY

USER STORY

One of the key user stories we uncovered

One of the key user stories we uncovered

One of the key user stories we uncovered

As a Product manager, When I launch a new feature, I want to see the data on the product ,So I can make informed decisions

As a Product manager, When I launch a new feature, I want to see the data on the product ,So I can make informed decisions

As a Product manager, When I launch a new feature, I want to see the data on the product ,So I can make informed decisions

06.

06.

06.

DATA ANALYSIS

DATA ANALYSIS

DATA ANALYSIS

Card sorting from interviews

Card sorting from interviews

Card sorting from interviews

After asking the team members what data they used, through a workshop, we grouped the ones they felt were most similar.

After asking the team members what data they used, through a workshop, we grouped the ones they felt were most similar.

After asking the team members what data they used, through a workshop, we grouped the ones they felt were most similar.

07.

07.

07.

WIREFRAMING

WIREFRAMING

WIREFRAMING

Tackling the issue

Tackling the issue

Tackling the issue

08.

08.

08.

LoFi USER TESTING

LoFi USER TESTING

LoFi USER TESTING

Testing the designs with the team

Testing the designs with the team

Testing the designs with the team

09.

09.

09.

VISUAL DESIGN

VISUAL DESIGN

VISUAL DESIGN

Creating a consistent look and feel

Creating a consistent look and feel

Creating a consistent look and feel

10.

10.

10.

RESULTS

RESULTS

RESULTS

What was the outcome of all this work?

What was the outcome of all this work?

What was the outcome of all this work?

Predictable, Faster Workflows

Predictable, Faster Workflows

Predictable, Faster Workflows

By giving everyone open access to essential product data, asynchronous team members are able to more predictably scope, execute, and review sprint cycles. Going from waiting between 5 minutes and 28hours, to on demand.

By giving everyone open access to essential product data, asynchronous team members are able to more predictably scope, execute, and review sprint cycles. Going from waiting between 5 minutes and 28hours, to on demand.

By giving everyone open access to essential product data, asynchronous team members are able to more predictably scope, execute, and review sprint cycles. Going from waiting between 5 minutes and 28hours, to on demand.

11.

11.

11.

USER INTERFACE

USER INTERFACE

USER INTERFACE

What the final product looks like

What the final product looks like

What the final product looks like

12.

12.

12.

REFINEMENT, LEARNINGS, REMARKS

REFINEMENT, LEARNINGS, REMARKS

REFINEMENT, LEARNINGS, REMARKS

A recap of the experience and what I’d do next

A recap of the experience and what I’d do next

A recap of the experience and what I’d do next

Learnings

Learnings

Learnings

I learned a lot about data representation and the importance of clarity in conversation and representation data. I learned about how different team members will use the same data for different things.

I learned a lot about data representation and the importance of clarity in conversation and representation data. I learned about how different team members will use the same data for different things.

I learned a lot about data representation and the importance of clarity in conversation and representation data. I learned about how different team members will use the same data for different things.

Moving forward

Moving forward

Moving forward

  • More in depth, dynamic data representation and interaction

    • Allowing users to view and interact with a data set in multiple ways would give them multiple perspectives on on their data which may aid in better decision making.

  • Sharing features and snippets

    • The ability to have sharing features for the dashboard would allow for better collaboration in decision making and expression of ideas; especially for asynchronous teams

  • More in depth, dynamic data representation and interaction

    • Allowing users to view and interact with a data set in multiple ways would give them multiple perspectives on on their data which may aid in better decision making.

  • Sharing features and snippets

    • The ability to have sharing features for the dashboard would allow for better collaboration in decision making and expression of ideas; especially for asynchronous teams

This project although simple, was not easy, I enjoyed the challenge of learning about data representation and adding it to my locker. I feel I have grown through this project by builing such bespoke tools for a niche community

This project although simple, was not easy, I enjoyed the challenge of learning about data representation and adding it to my locker. I feel I have grown through this project by builing such bespoke tools for a niche community

This project although simple, was not easy, I enjoyed the challenge of learning about data representation and adding it to my locker. I feel I have grown through this project by builing such bespoke tools for a niche community

IMANI MUREITHI

PRODUCT DESIGNER

IMANI MUREITHI

PRODUCT DESIGNER

IMANI MUREITHI

PRODUCT DESIGNER