Course Overview
Get an overview of the prerequisites and content we’ll cover in this course.
Prerequisites
It is recommended that you have a good understanding of web development, software development, product management, and data analysis to get the most out of this course. The prerequisites include:
A basic understanding of what APIs are and how they work.
Familiarity with programming concepts and experience with web development, as well as an understanding of the software development life cycle and product management concepts.
Prior experience with data analysis and an understanding of KPIs, as the course covers how to design metrics for measuring APIs from the infrastructure, product, and business perspectives, and how to identify the right KPIs for API products and build a product strategy.
Some understanding of user-experience research and user-centered design, as the course covers how to build customer empathy for API products and how to use customer research to inform product development.
What this course covers
Here is a detailed description of what we'll learn in each part of the course.
Part 1: The API Landscape
The objective of this section is to introduce APIs as products and shed light on how large the market is for API products. We'll learn about product management concepts and how they apply to APIs. This part will also explain the life cycle and maturity of an API.
APIs go beyond web products or mobile apps with the UI. In this chapter, we will be introduced to the idea of an API as a product and how a vast universe of products is built using APIs. This chapter will also look at some of the most well-known API companies and how they’ve made successful API products.
API product management has evolved into a specialization with some fundamental pieces that a product manager must understand to effectively make product decisions. This chapter will go over various types of products from a product management perspective and how they require different skill sets.
This chapter will help us understand why the API product life cycle, methodology for establishing API governance, and use of the API maturity model are important for organizations, as they help them to ensure that their APIs are developed and managed in a consistent, efficient, and effective manner, are aligned with the organization’s goals, policies, and standards, and that they can evolve over time to meet changing business needs. This chapter also presents case studies of some of the leading API products and how they present their API maturity to their customers.
This chapter will talk about the unique design challenge of defining an API product MVP. As the API product matures, the challenges can get more complicated, and in addition to growth, retention and churn might also become very crucial in product strategy. At each step of API maturity, the stakeholders’ and customers’ needs and expectations change. This chapter explains what we mean by “API maturity” and how it relates to the API life cycle.
Growth for APIs refers to the process of increasing the usage and adoption of an API by different user groups, such as developers, businesses, and consumers. Growth can be achieved by identifying, helping identify, and helping the target audience; developing a marketing, pricing, and sales strategy that effectively communicates the value and benefits of the API to the target audience; and helping to generate interest and awareness. We can utilize product-led growth and community-led growth for API growth.
The customer support strategy for API products is different from that of other products. This chapter dives into the standard methodologies for creating a robust support model for APIs that scales with the product and delivers value for customers.
Part 2: Understanding the Developer
This section is focused on the primary customer of APIs: the developer. It is important to understand the developer journey in order to establish a growth funnel for the API product. We'll also learn about signals for activation, engagement, retention, and scale.
This chapter describes what product funnels are and how they are established for various types of products. We'll be introduced to concepts such as activation, retention, engagement, and churn.
This chapter covers understanding the goals of both the business and the customer so that roadmaps can be established that build a long-term API strategy for the organization. We'll get an introduction to tools such as CSAT, NPS, and other user-research mechanisms to develop an understanding of customers. We'll learn how to understand our customers so we can get them to use our product, and set up a product strategy that gets customers started in a long-term relationship with our product.
In this chapter, we'll learn about a few key ingredients for creating a great API experience. It is important to understand how some of these experiences have been designed across the industry to be able to shape any API product. We look at things such as API references, status pages, SDKs, CLIs, and so on that are part of the API experience.
Part 3: A Deep Dive into Key Metrics for API Products
This section will introduce us to the reasoning behind API metrics. We'll do a deep dive into all dimensions of the user journey and learn about a vast set of metrics that we can track across the infrastructure, product, and business dimensions of our APIs.
Infrastructure metrics are crucial for APIs that serve a large or a small customer base. It is important that APIs be reliable. In this chapter, we'll learn how to measure infrastructure metrics and various tools that provide an easy setup to get them.
In this chapter, we’ll learn about different metrics we can use to learn more about our customers. The metrics we learn about in this chapter can be used across all the stakeholders in our product to align common goals and priorities.
In this chapter, we’ll learn about the business metrics we need to set up and keep track of regularly in order to measure the business impact of our infrastructure and product development projects.
Part 4: Setting a Cohesive Analytics Strategy
It is not sufficient to merely have metrics set up. It is also important to understand how to evaluate the quality of the metrics and how to make sure they are extensive and robust. This part describes the possible ways in which metrics can be analyzed and evaluated. We'll learn how to remove blind spots and avoid vanity metrics that may not be true representations of product health.
This chapter dives into the evaluation of metrics once a measurement is done. The first step is to establish a baseline and find ways of benchmarking it. Metrics should not be standalone; they need to be evaluated in the context of other metrics. This chapter also establishes the concept of correlation in metrics and dives into how to set clusters of metrics so that there is a set of metrics that are seen in relation to each other and not all metrics at once.
This chapter talks about combining qualitative and quantitative data to form hypotheses and drive insights that may not be easily available without combining these two. This chapter also explains what leading and lagging metrics are and how to find them in a set of related metrics.
In this chapter, we'll learn about counter metrics to remove bias from the metrics-setting process so that blind spots can be addressed. This chapter also introduces the concept of gameability with examples, and explains the consequences of gameable and vanity metrics.
In this chapter, we'll learn about how effective product leadership requires setting short-term and long-term goals and strategically communicating those goals to stakeholders through storytelling. This approach helps to establish a clear direction for the product and the team, aligning everyone around a common vision and enabling the team to work together to achieve success.