Book Image

API Analytics for Product Managers

By : Deepa Goyal
Book Image

API Analytics for Product Managers

By: Deepa Goyal

Overview of this book

APIs are crucial in the modern market as they allow faster innovation. But have you ever considered your APIs as products for revenue generation? API Analytics for Product Managers takes you through the benefits of efficient researching, strategizing, marketing, and continuously measuring the effectiveness of your APIs to help grow both B2B and B2C SaaS companies. Once you've been introduced to the concept of an API as a product, this fast-paced guide will show you how to establish metrics for activation, retention, engagement, and usage of your API products, as well as metrics to measure the reach and effectiveness of documentation—an often-overlooked aspect of development. Of course, it's not all about the product—as any good product manager knows; you need to understand your customers’ needs, expectations, and satisfaction too. Once you've gathered your data, you’ll need to be able to derive actionable insights from it. This is where the book covers the advanced concepts of leading and lagging metrics, removing bias from the metric-setting process, and bringing metrics together to establish long- and short-term goals. By the end of this book, you'll be perfectly placed to apply product management methodologies to the building and scaling of revenue-generating APIs.
Table of Contents (24 chapters)
21
The API Analytics Cheat Sheet

Mixing qualitative and quantitative feedback

Quantitative metrics provide objective and numerical data, which can help eliminate bias and subjectivity. By analyzing these metrics, you can make informed decisions about the performance and efficiency of your API without being swayed by personal opinions or preferences.

Qualitative metrics, on the other hand, provide a more subjective evaluation of the API and can help identify areas that may not be captured by quantitative metrics. For example, customer feedback may highlight issues or concerns that are not reflected in numerical data. By gathering this type of data, you can get a better understanding of how an API is being used and perceived by your customers and address any potential blind spots or biases. Qualitative and quantitative data work well together because each kind fills in what the other lacks.

You might see patterns in the numbers you already track. For example, most of your customers don’t use a particular...