In this spotlight session at #mtpcon San Francisco, sponsored by Insightssoftware, Dustin Richardson, Senior Product Manager, Embedded Analytics, and Natasha Callender, Director, Solutions Engineering, Embedded Analytics, examine the difference between product analytics and embedded analytics, and discuss why it’s beneficial to consider using both.
What is product analytics?
Opening the session, Dustin explains how product analytics can help gather insights to improve the customer journey. “Product workflows, demographic data, and user data can give product teams an understanding of what kind of experience the user is receiving,” Dustin says.
We need analytics to understand the actual vs subjective, Dustin adds. Analytics can add to the wider picture view of your customer base. For example, a customer interview can give you a qualitative, subjective perspective, while analytics can add to that wider image by giving you the data story for the user journey.
In terms of who would use product analytics the most, Dustin says those who create an experience for the user normally need this the most, from product managers to developers.
Using analytics to make better product decisions
Product analytics can help drive informed decision-making, Dustin explains. “We want to make decisions based on validated data that is qualitative, quantitative, behavioural, and preference driven. It helps us understand that full picture of how the user behaves.”
It’s more than just seeing where your users are clicking. It creates a story behind data and helps product teams to understand a 360 view of users.
Embedded analytics
Natasha explains how embedded analytics is a complete analytics experience embedded into the framework of your application. What is the main use of this function? To connect data from any source to create and share visual insights with your users.
She adds that giving end-users insights is key, and product teams can do this through embedded analytics to improve the overall experience. “From customisable reports, interactive dashboards, and end-user self-service, embedded analytics empowers product teams to reduce their development hours and provide their end users with an analytics experience. The function helps create any user experience to meet demand and takes the pressure off developer teams.” Natasha says.
Why do you need both?
Dustin explains that while both types of analytics use data to provide insights, they solve different use cases. Comparing the two, there a several differences. Consequently, it’s important to consider both:
What is the main objective?
Product analytics: Information collection for your product
Embedded analytics: Information dissemination for data democracy
What time of information?
Product analytics: Limited to product data
Embedded analytics: Any type of data that is consumed by the end users
Why do we need it?
Product analytics: Collect better insights about product
Embedded analytics: Insights to improve business outcomes, embedded experience to enhance business benefits
Who consumes it?
Product analytics: Predominantly, product managers
Embedded analytics: End-users (Anyone along the user’s journey in embedded experience)
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