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Building an efficient dashboard for your users from scratch: your step-by-step checklist

With ever-evolving user needs, shifting priorities, and busy product roadmaps, leading an in-house analytics project and getting your dashboards to market fast is no easy feat.

Pinpointing the exact needs your new analytics features will fill, designing user-friendly dashboards, sourcing the right data… We know how resource-intensive and complex these steps can be.
Here at Toucan, we live and breathe for data storytelling. Creating engaging dashboards is our bread and butter. So we’ve packed together our +8 years of R&D and the learnings from hundreds of data visualization projects in a 7-steps checklist. We hope to help CPOs and product managers lead their analytics projects smoothly.


7+1 essential steps to building an in-house dashboard

In this checklist, we’ll walk you through the most important steps to managing a large-scale analytics project:

  • Understanding your user’s decision-making needs
  • Designing an outcome-oriented dashboard
  • Defining the adequate underlying data-architecture
  • Choosing the right visualization method
  • Bug-proofing your dashboards
  • Making sure your dashboards will stand the test of tim
  • Bonus step: building an easy-to-use interface for non-technical teams

For each of these steps, we’ll list the necessary time and resources.

Some of the actions we’ll break down for you

Through the different steps, we cover crucial actions including:

  • Defining end-user personas and understanding their data-literacy level
  • Choosing the right KPIs to be featured on your dashboard
  • Assessing available data sources, determining adequate refresh time intervals and granularity levels
  • Integrating responsiveness to meet mobility requirements
  • Building a future-proof API
  • Understanding how to hierarchize explanations and information through data storytelling

We tried to make our checklist as comprehensive as possible based on our experience, but we do realize it is not exhaustive. Every analytics project is different and depends on the particular context of the company. We welcome any feedback or suggestions for improvement!

Let us know what you think, and if you find this resource useful, feel free to share it with your network!



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