Delivering Embedded Analytics to Your Customers

More and more companies are making embedded analytics a core part of their product offering. Companies like Medium, Spotify, Slack, and Intercom are leveraging data as a core product offering to drive results.

This isn’t just happening within high growth tech startups. Any size company can benefit from using software programs and applications that deliver embedded analytics because these analyses can aid businesses in critical decision making related to marketing, revenue, and growth.

Embedded Analytics Definition

Consulting Agency Gartner Inc. perhaps says it best when it defines embedded analytics within software programs and applications as “a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application.”

Typically, they are “narrowly deployed around specific processes such as marketing campaign optimization, sales lead conversions, inventory demand planning and financial budgeting.”

Transforming Data With Intelligence (TDWI) reported that companies “credit embedded analytics for increasing overall revenue, [and] boosting customer satisfaction.” According to their report, 95 percent of companies “say embedded analytics has helped them increase overall revenue,” and “68 percent of application teams are able to charge more for their products because of the value embedded analytics brings.”

Regardless of your industry or company size, you might have thought about ways to use data to engage your users, demonstrate product value, or create opportunities for upselling and differentiation.

Whatever your objective, delivering embedded analytics to your customers can be a significant undertaking and addition to your product roadmap.

You’ll need to tackle questions like:

  • What is the purpose of having analytics for our customers?
  • How will you display data to customers?
  • Will you let your customers run their own analysis of data?
  • Will you build in-house or leverage existing technology?
  • How many engineering resources can you dedicate to this?
  • What is the timeline?

We’ve put together a framework for thinking through all the moving parts of delivering embedded analytics to your customers so you’ll be best set up for success.

Define your analytics objective:

  • Can data help drive customer engagement?
  • How will providing embedded analytics to your customers differentiate your product?
  • Do you have dedicated resources to help build out this product?
  • Do you have executive buy-in?

Data Readiness:

  • Do you currently have customer data stored?
  • What sources do you need to collect data from? Are there APIs you can utilize for third-party providers?
  • How clean is your data?
  • What format is your data in? Will you need to extract, load and transform it?
  • What are the key KPIs your customers care about?

Embedded Analytics Security and Access:

  • How strict are the security requirements of your customers? What type of compliance do they require?
  • How granular do you want to get security permissions? Securing by company, by department, by role?
  • What are your hosting and infrastructure requirements?

Application UX:

  • How do you want to display the analytics within your application?
  • How much control do you want customers to have over their analytics? Do you want to make it exportable? Do you want them to run their own queries?
  • Do you know where in the user flow you’d like to incorporate analytics?
  • Do you have a support structure set in place for customers who engage with your analytics service?


  • How real-time do your customers need their data to be?
  • Do you have a sense of how many queries and how often you’ll need to run these queries per customer?

Engineering Resources:

  • What are your current resource constraints?
  • Do you have data engineering and data modeling expertise?
  • Do you have a UI Engineer to design the look and feel of analytics into your application?
  • What additional resources will you need?

Delivery & Extensibility:

  • Do you have a sense of the timeline to deliver an MVP?
  • How often do you expect your customer metrics to change?
  • Can you dedicate full-time resources to build this?

Want to reference this list later? We’ve created this handy PDF checklist for you to print off. We also curated a list of 25 companies that are delivering analytics to their customers for fun inspiration.

Happy building! If you’d like to chat about how we’ve helped companies deliver analytics to their customers, give us a shout or request a demo.

This article was originally published January 2017 and was updated January 2020.