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

Summary

In this chapter, you learned how to set up a data strategy that lets you collect the right data points and make an iterative plan for building a lot of analytics for your product. You also learned ways to look at data, such as cluster analysis, data mining, predictive analysis, and so on. This gave you the tools you need to start exploring data.

Setting a data strategy and using various methods for analyzing and interpreting data can be extremely helpful in effective goal setting with data. A data strategy is a plan that outlines how an organization will collect, analyze, and use data to support decision-making and drive business objectives. By setting a data strategy, organizations can ensure that they are collecting and analyzing the right data to inform their goals and objectives.

There are many different methods for analyzing and interpreting data, such as statistical analysis, ML, and visual analysis. By using these methods, organizations can gain insights and understand...