Building better SaaS dashboards: the basics and the longtail features

Creating a functional dashboard for a SaaS platform might seem straightforward at first. However, crafting something genuinely unique that truly delights users involves much more than just an appealing design.

A big challenge is addressing the feature ‘longtail’ that caters to the diverse needs of your users, including the variety of ways they like to consume and interact with data, as well as the myriad formats they require to incorporate the data into their unique workflows.

For technology platforms, the iterative process of gathering feedback and implementing enhancements is crucial for developing a dashboard that not only meets basic requirements but also offers a deeply personalized and efficient user experience.

Having built Trevor.io and now Embeddable.com (this service!), we’ve collected such feedback over the course of several years.

In this piece, we take a closer look at some examples of the basics and the longtail features that can elevate a dashboard from ‘it’s ok’ to ‘wow, this is a reason I would choose this tool over its competitors’. But before we dive into those features – let’s take a minute to go exactly what is embedded analytics, and why they’re so beneficial to the user

What is embedded analytics?

Embedded analytics refers to analytics, reporting and data visualization capabilities that are directly available within a software application – so users can access insights without using a separate business intelligence (BI) tool. If you're comparing the two approaches, take a look at our guide to embedded analytics vs business intelligence.

Unlike traditional BI platforms, embedded BI software brings dashboards, reports and interactive data visualizations into the existing workflows where users already spend their time, whether that's a CRM, ERP, customer-facing SaaS application or an internal ops platform.

Modern analytics solutions often include features like real-time analytics, role-based access control and mobile analytics support, but more advanced platforms might also offer natural-language querying, automated insights generation and AI-powered anomaly detection engines, to help users uncover trends more quickly.

For SaaS companies, embedded analytics can increase product value, transforming data into a core part of user experience. Whether you’re building customer-facing dashboards, operational reporting or executive scorecards, the goal is always to deliver actionable insights from within your existing application.

If you're new to the concept, our guide on what is embedded analytics explains how embedded analytics differs from traditional BI, and why it's become a key capability for modern software.

The benefits of embedded analytics

So why do embedded analytics matter? To start with, they’re no longer a nice-to-have. Users increasingly expect to be able to explore data, track performance and generate insights natively within the products they use everyday.

The right embedded analytics features can have a significant impact on how your product is perceived and used. For instance, it can help users find answers faster, make more informed decisions and get more value from their platform, potentially turning analytics into one of the primary reasons customers choose your product over a competitor.

Advanced analytics can also reduce the pressure on product and engineering teams, as users have more control over how they access and interact with their data. That spares your teams from constantly responding to requests for new reports or custom data exports.

When you’re evaluating your embedded analytics requirements, it’s important to think beyond basic dashboards and consider which embedded analytics features will deliver the most value for your customers – both today and as their needs become more sophisticated.

Want to see examples of how different organizations apply these capabilities? Explore these embedded analytics use cases – or if you’re looking for a deeper dive on the business case, see our guide to embedded analytics pricing and benefits.

The basic features of embedded analytics

(1) Interactivity: A fundamental aspect of an engaging dashboard is the ability to engage and interact with it in different ways:

1. Filters: Let users view data by specific criteria, such as genre or artist on a music platform.‍
2. Drilldowns: Provide deeper insights, like viewing detailed song plays from a monthly engagement overview.‍
3. Dynamic sorting: Allows rearranging data, like sorting by ‘most popular’ or whatever makes sense in the context of your business.‍
4. Interactive time series: Adjust time ranges on graphs to explore different periods.

(2) Internationalization: Many software platforms have an international, or sometimes even global,  user base. Internationalization ensures the dashboard is accessible to people given their:

1. local language.
2. local number formats (e.g. in places like Spain and Germany, the number 2.3 is written instead as 2,3).
3. local date formats (e.g. 5th February 2024 in the US is: 02/05/2024, and in the UK is: 05/02/2024).
4. local timezone (i.e. when showing with dates).

(3) Downloads and exports: This gives users the ability to actually do something with the data.  For instance

1. Download as CSV (e.g. to manipulate the data in a spreadsheet)
2. Download as PNG (e.g. to include in a presentation)
3. Connect to Zapier (e.g. to build workflows across tools).

(4) Accessibility features: Guarantees that the dashboard is usable for everyone, including individuals with disabilities, promoting inclusivity.

(5) Mobile optimization: Supports key dashboard functionality on mobile devices, allowing users to manage and monitor their services anytime, anywhere.

The longtail features of embedded analytics

1. Historical data comparison: The ability to compare time series data across multiple periods (e.g. this week to last week, or last month to the previous month).
2. Self-serve functionality: This empowers users to tailor the dashboard to highlight or add metrics important to them, enhancing the dashboard's relevance and usability. For instance, Stripe’s payments dashboard includes features like configurable reporting and self-service analytics.
3. Custom colours and branding: Many customers, especially in the Enterprise segment, look for white-label embedded analytics capabilities that allow them to use their own colors and branding.. It doesn’t come up that often as an embedded dashboard solutions request, but it allows for visual alignment with their brand and can improve the aesthetic appeal, especially if they’re exporting the whole or parts of the dashboard to include in company reports.
4. Real-time data processing: Essential for platforms like music streaming services, allowing for instant insights into listener trends and behaviors.
5. Advanced analytics and predictions: Utilizes past data to forecast future trends.
6. API integration: Enables seamless connections with other tools and systems, streamlining workflows and enhancing operational efficiency. Zapier is a platform that’s commonly used to achieve seamless API integrations for SaaS organizations
7. Notifications and alerts: This enables users to set up personalized alerts for specific metrics or events, ensuring they're always informed of significant changes or milestones.
8. Dark mode: A popular feature that many users prefer, particularly in low-light environments, and it can also help with  saving battery life on mobile devices.
9. Advanced customization of reports: Beyond basic self-serve functionality, users often want embedded reporting tools that enable them to customize report  layout, format, and content directly within the dashboard. Take a look at Salesforce’s reporting tool for a widely used example of an advanced custom report builder.
10. AI-powered insights: This feature enables users to ask questions in natural language and receive insights directly from their dashboard. This capability makes data more accessible for users who aren’t used to looking at graphical charts. It can help users to make faster, more accurately informed decisions  by allowing for quick, conversational data exploration and the generation of actionable insights based on historical data patterns and predictive analytics.

By deeply understanding and implementing these longtail features, SaaS platforms can offer more than just a dashboard; they provide a critical, customizable tool that meets the diverse needs and preferences of users.

These are also important features to consider when choosing from the different embedded analytics platforms available. Do they provide any of these features out of the box? Are they on the roadmap? Or will they be sorely lacking? And these are also the capabilities you’ll want to prioritize if  you’re planning on building embedded analytics into your app yourself.

For a SaaS dashboard, it’s often this level of customization and flexibility that transforms the experience into a central component of users' daily operations and strategic decision-making, which can ultimately contribute to higher engagement and better user retention, which is one of the most important metrics for most SaaS platforms.