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How to Make Dashboards Using a Product Thinking Approach

Source | shopify.engineering | Lin Taylor

It’s no secret that communicating results to your team is a big part of the data science craft. This is where we drive home the value of our work, allowing our stakeholders to understand, monitor, and ultimately make decisions informed by data. One tool we frequently use at Shopify to help us is the data dashboard. This post is a step-by-step guide to how you can create dashboards that are user-centred and impact-driven.

People use the word “dashboard” to mean one of several different things. In this post I narrow my definition to mean an automatically updated collection of data visualisations or metrics giving insight into a set of business questions. Popular dashboard-building tools for product analytics include TableauShiny, or Mode.

Unfortunately, unless you’re intentional about your process, it can be easy to put a lot of work into building a dashboard that has no real value. A dashboard that no one ever looks at is about as useful as a chocolate teapot. So, how can you make sure your dashboards meet your users’ needs every time? 

The key is taking a product thinking approach. Product thinking is an integral part of data science at Shopify. Similar to the way we always build products with our merchants in mind, data scientists build dashboards that are impact-focused, and give a great user experience for their audience.

When to Use a Dashboard

Before we dive into how to build a dashboard, the first thing you should ask yourself is whether this is the right tool for your situation. There are many ways to communicate data, including longform documents, presentations, and slidedocs. Dashboards can be time consuming to create and maintain, so we don’t want to put in the effort unnecessarily.

Some questions to ask when deciding whether to build a dashboard are

  • Will the data be dynamically updated?
  • Do you want the exploration to be interactive?
  • Is the goal to monitor something or answer data-related questions?
  • Do users need to continuously refer back to this data as it changes over time?

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Source
shopify.engineering
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