Quick Summary
- Embedded applications can increase user engagement, differentiate core products, and provide monetization opportunities among other benefits, with top performers saying they gain up to 20% of their total annual revenue from embedded offerings.
- Ultimately, success in embedded analytics comes with understanding the value your application will bring to each user and matching product capabilities to the user’s needs.
Applications generate a massive amount of data. To help users make actionable sense of that data, more than 90% of developers have taken to embedding data visualizations in those applications, consequently improving product adoption and helping these developers stay relevant in a bloated market.
In fact, 98% of commercial software companies perceive definite ROI (return on investment) from their analytic offerings, with application teams estimating that these analytics contribute to more than half of the total value of their applications. Competitive advantages of embedded analytics also include reduced churn rate, increased revenue, improved product adoption, increased sales and a sustainable unique selling proposition (USP).
Want to succeed with your analytics offering? Optimal user adoption comes from implementing the following five tips when embedding analytics in modern applications.
In this article...
Embed in the admin panel
Add embedded analytics to your admin panel. Include real-time reports on how frequently the team logs in, how long they stay in the app, how many modules they use, and which features are used most frequently.
Helpful data visualizations include: pie charts for comparing variables, heat maps or geographic maps for contrasting intensities or locations, bubble charts or scatter-charts for multivariate data and for tracking associations, polar charts for cyclic data such as sales per month, gauges for mapping information on the dial, and area charts for charting changes in quantity over time.
With reports, you can include dropdowns and filters for users to slice and dice data.
Tips for designing embedded analytics
- Display only the content most relevant to the user. Group related data together, and limit the amount of information on any given screen.
- Use iconography instead of text to save space.
- Stick to a single font. Use bold font sparingly and only for titles and/or important information.
- Use bright colors, with four or five different colors at the most.
ALSO READ: What is Embedded Analytics?
Embed Analytics at All Relevant Touchpoints in the Tool
Think of the responsibilities of end users and how these customers will likely use your application. For example, if you’re embedding a dashboard for a sales team that needs real-time data on the status of its documents, you could plug that data into its customer relationship management platform (CRM), so users don’t have to constantly swap between the business intelligence (BI) platform and the CRM to consult those documents for closing deals.
Do you want to know how customers actually use the app? Certain developers conduct on-site usability studies with select customers to see how they can improve their user experience.
Tips for eliciting useful feedback
- Ask participants to draft and prioritize enhancement requests.
- Ask them to rate aspects of the app.
- Ask them to complete specific tasks, and watch when they get lost or frustrated.
A good idea is to get regular feedback for both internal and external stakeholders — each uses the app in different ways. Build enhancements as demand dictates, design test prototypes early, and review these with your internal and external stakeholders for feedback on how you can improve the product. This turns participants into advocates of your product and helps you stay focused on user experience.
Match Customers to One or More Personas, and Embed Analytics in Those Spots
In the world of embedded analytics, one size does not fit all. Information consumers prefer visualizations and reports that have been customized for them. Content creators want to query evidence-based data, create educational digital content and reports, and share what they’ve created with others. Data analysts like to conduct their own explorations, using the data to unearth their own sources.
With that same laser focus on the user, you could also plug dashboards with insights that make their lives easier.
Tips for creating reports relevant to specific customer personas
- Add third-party data for additional insights into customer behaviors and preferences. For example, if you’re embedding a business expense management solution, you may want to consider integrating anonymized consumer spending data from U.S. credit card companies.
- Integrate your own insights to help users understand their data. For example, if you’re embedding a payment and loyalty platform for restaurants, you can embed insights that chart not only how many credits were earned, redeemed, or spent, but also embed an area chart to measure that impact.
Match the Functionality of the Analytics to User Needs
Rather than bombarding users with information overload, go slow at first, then release more graphic features and data as adoption grows and more questions arise.
Ways to match functionality
- Use a capabilities map to match users to the features they need. The capabilities map visually represents what the company does and can do.
- Create mock-ups to test how your various visual elements work together.
- To create stickier applications, consider more collaborative analytics where users can insert their own datasets and analysis.
- Provide guided analytics built for non-technical users, with proper context, to help them understand the insights.
On top of titles and descriptions, the analytics should include tips, alerts, a glossary, and HTTP Keyserver Protocol (HKP) for optimum data security. Such highly actionable analytics enable users to take action, such as sharing reports with others.
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Ease and Depth of Application
Start with a BI tool that has a modern interface, clean and simple to use and effortless to manage from your end. You want an application that’s easy to rebrand as your own, so end users don’t perceive a difference between the rest of the application and your embedded analytics.
Look for an embedded analytics platform with the following:
- It has analytics capabilities that are customizable
- It supports automated analytics, with no user intervention needed for updating embedded analytics.
- It supports the full stack of integrated analytics from reports and dashboards to data storytelling and augmented analytics.
Also, consider selecting an embedded analytics solution with open-source tools, where end users can add their own contributions to the application — also known as self-service analytics.
User Experience is Key to Successful Embedded Analytics
Embedded applications can increase user engagement, differentiate core products, and provide monetization opportunities among other benefits, with top performers saying they gain up to 20% of their total annual revenue from embedded offerings. That’s as long as you laser in on the user experience, making the analytics seamless, attractive, and useful. Strategies include embedding strategic charts and designs at relevant touchpoints, matching the functionality of the analytics to persona and user needs, and practicing seamless integration.
Ultimately, success in embedded analytics in modern applications comes with understanding the value your application will bring to each user and matching product capabilities to the user’s needs. The Agile model keeps you from being overwhelmed. It’s one user, one persona, one problem, and one report at a time for iterative improvement.
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