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# System prepended metadata

title: Take Home Challenge

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# Take Home Challenge
#### Product Analytics Data Scientist, Matcha



## Purpose

This exercise is designed to be emulative of some of the types of things you might do at 0x. We realize timed, live interviews aren’t always necessarily perfect indicators of future success, and want to give you an opportunity to showcase your skills in a practical fashion. We think/hope you’ll find it fun!

### Pre-requisite: try [matcha.xyz](http://matcha.xyz/) 

*If you haven’t tried Matcha, here are the instructions —*

In order to address the points below, you are strongly encouraged to try to use Matcha. If you don't already, you will have to setup a wallet. We recommend you [setting up Metamask (a popular browser extension) and connect it to Polygon](https://medium.com/stakingbits/setting-up-metamask-for-polygon-matic-network-838058f6d844), where you will spend low gas fees.

Once you’re done, share the wallet address with us and we will provide you with some $MATIC tokens to play with. You should be able to use the product yourself! Feel free to try and trade your $MATIC with other tokens, and get a feel of the experience.

Don’t hesitate to email danning@0xproject.com (@sui414 on Telegram) with any questions along the way!

## Prompt

### Part 1 - Product Analytics using Website Data

Currently, Matcha team utilizes Mixpanel and Heap for their reporting purposes. User signals are collected in the front-end and passed to these platforms. 

We have snapshotted a portion of data in the history in [Mixpanel environment](https://mixpanel.com/project/2815255) for you. Please reach out to Danning if you didn’t receive invite with your contact email.

It includes a slice of real user activities data between July 1st, 2022 - Sep 24th, 2022. Note that we didn’t import any **User** profile property data so you cannot create cohorts, but users’ properties are captured in the event data as **Event Properties**.

We are interested in how you would construct:

* **A daily stand-up dashboard** for Matcha’s key tracking metrics. You have full creative freedom on how to create the dashboard - of which type of reports and how many or layout. This topline metrics dashboard is the first thing you and the Matcha Product Manager would be opening in the morning. A few tips:

    * Focus on quality rather than quantity. This dashboard should be easily digestible and provide important insights (e.g. anomalies that can be grasped in a 30 second scroll.)
    * Play around with the Event Properties breakdown — it can provide helpful insight in the distribution change at a glance.
* **A funnel analysis report** that includes the key action steps and highlights the biggest drop-offs of users in Matcha’s checkout flow. Document your major findings and insights from the chart. Analyze it by playing around different dates or properties. Tips:
    * You can find all the events being tracked in the Data Management → Lexicon tab in Mixpanel. 
    * If you believe there are data signals missing from the key actions above, feel free to recommend what signals you would ask the engineers to add in the Front End. 
* **Design an AB test experiment** based on the funnel data — analyze the potential bottleneck in the web design and propose potential change to test, with implementation details. For the experiment, a template for the details can be but not limited to (all open ended, if not enough data to give accurate estimate):

    1. What might be the potential issue causing the high dropout?
    2. Potential change in the design you suggest test that can lift up the conversion rate at that step
    3. How will you divide user into control and experiment group? (i.e. which cohort and how many?)
    4. How long will you run the experiment to get enough data for significant result?
    5. What is the metrics to monitor and evaluate after the experiment?


### Part 2 - User Segmentation using Onchain Data

While data signals flowing into Mixpanel and Heap are crucial to learn how users are using the product, on-chain data isn’t captured and that can provide additional insights. In fact, blockchain data is public and we are able to access and process user attributes even of prospective users that have not traded on matcha, but rather traded on other competitor products (e.g. 1inch.exchange, Paraswap, Slingshot). These signals also give us better visibility on their trading habits (average trade size, frequency, preference for pairs etc.).

In the following set of dashboards, you will find variety of user metrics created from the on-chain analysts community, comparing Matcha with its competitors:

[1inch, Matcha, Uniswap](https://dune.com/nat_nomad/1inch-Matcha-Uniswap) 
[Matcha and 1inch](https://dune.com/nat_nomad/Matcha-and-1inch)
[From what project newcomers come from](https://dune.com/nat_nomad/From-what-project-newcomers-come-from)

Imagine the team brings the question to you: Do we know who our users are, or how we can profile them across all the DEX users? In particular, the team is interested in defining for what pockets of users Matcha to provide the most value (power users), and how to shift more of them from competitor products.

Dune.com is a free to use website and please feel free to fork the queries from above and create new metrics based on the queries. You have creative freedom on how to massage (you should expect some level of noise) and process the data. Share your insights in the form you find the most useful (slides, pdf, google doc...).

If you encounter any blocker in using Dune, please reach out to Danning on Telegram and we'd love to help clear out blockers!



## Output

##### For Part 1
You will create reports and a dashboard directly in the Mixpanel space; Share your analysis & experiment design in any document or slide form.
##### For Part 2
Share your analysis and findings in any document or slide form, along with your dashboard or queries links from Dune.



##### For Onsite, if proceeding
You should prepare a 20 minute presentation (including a deck, no need to be done at this take-home phase, but only when preparing onsite)  to explain your design thinking and output for both Part1 and Part2. You have a fair amount of creative control over what you want to focus on and the ideal way to present it. 

As part of your onsite interview, you’ll present your work to our team and discuss what you found interesting, what you found challenging, what you might do differently, etc. That said, your deck should provide a narrative in and of itself.




##### Estimated Time Required
You should aim to spend a maximum of 10 hours doing analysis and preparing this report. We will compensate you at a rate of $59 / hour for work done during this take-home. Please aim to have this back to us within a week if possible. If you think you’ll need more time, just let us know.

