API Analytics for Product Managers

API Analytics for Product Managers

by Deepa Goyal
Released February 2023
Publisher(s): Packt Publishing
ISBN: 9781803247656

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Book description

Research, strategize, market, and continuously measure the effectiveness of APIs to meet your SaaS business goals with this practical handbook

Key Features

  • Transform your APIs into revenue-generating entities by turning them into products
  • Meet your business needs by improving the way you research, strategize, market, and measure results
  • Create and implement a variety of metrics to promote growth

Book Description

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.

What you will learn

  • Build a long-term strategy for an API
  • Explore the concepts of the API life cycle and API maturity
  • Understand APIs from a product management perspective
  • Create support models for your APIs that scale with the product
  • Apply user research principles to APIs
  • Explore the metrics of activation, retention, engagement, and churn
  • Cluster metrics together to provide context
  • Examine the consequences of gameable and vanity metrics

Who this book is for

If you’re a product manager, engineer, or product executive charged with making the most of APIs for your SaaS business, then this book is for you. Basic knowledge of how APIs work and what they do is essential before you get started with this book, since the book covers the analytical side of measuring their performance to help your business grow.

Table of contents

  1. API Analytics for Product Managers
  2. Foreword
  3. Contributors
  4. About the author
  5. About the reviewers
  6. Preface
    1. Who this book is for
    2. What this book covers
    3. To get the most out of this book
    4. Download the color images
    5. Conventions used
    6. Get in touch
    7. Share Your Thoughts
    8. Download a free PDF copy of this book
  7. Part 1:The API Landscape
    1. The pandemic effect
    2. Great for business
  8. Chapter 1: API as a Product
    1. Building with APIs
    2. Software-as-a-Service
    3. Establishing APIs as products
    4. Types of APIs
    5. Business models for API products
    6. Who builds APIs and who uses them?
    7. Notable API products that are shaping the API landscape
      1. Twilio
      2. Printful
      3. Twitter API
      4. Plaid
      5. Tealium
      6. IMDB
      7. Amazon Selling Partner API
      8. Postman
      9. Marqeta
    8. Defining success for a product
    9. Summary
  9. Chapter 2: API Product Management
    1. The role of the product manager
      1. Product thinking
      2. Stakeholder management
      3. Understanding the product life cycle
      4. Market research
      5. User research
      6. Experimentation and hypothesis testing
      7. Agile methodology
      8. Data analytics
      9. Customer feedback channels
    2. Types of product management roles
    3. The responsibilities of an API product manager
      1. Useful terminology for API product managers
      2. The short-term and long-term API strategy
      3. Development and release
      4. API governance and maturity
      5. API experience
      6. API analytics
    4. Summary
  10. Chapter 3: API Life Cycle and Maturity
    1. The API product life cycle
      1. API development workflow
      2. Stakeholder alignment
      3. Retiring an API
    2. API governance
      1. API governance through the API life cycle
    3. API maturity
      1. Case studies
    4. Summary
  11. Chapter 4: Building and Managing API Products
    1. APIs in the digital value chain
    2. Leading with the API strategy
    3. The API development team
    4. Managing an API as a product
    5. The API proposal
    6. Designing APIs
    7. Starting with an MVP
    8. Building and releasing APIs in an iterative way
    9. Building long-term and short-term roadmaps
    10. Summary
  12. Chapter 5: Growth for API Products
    1. Understanding what growth means for APIs
      1. Internal APIs
      2. Partner APIs
      3. Public APIs
      4. Identifying the target audience
      5. Methods to calculate TAM
      6. Marketing strategy
      7. Pricing strategy
      8. Sales strategy
    2. Product-led growth
    3. Community-driven growth
    4. Low-code and no-code integrations
    5. Summary
  13. Chapter 6: Support Models for API Products
    1. The producer and consumer life cycle
    2. Designing customer feedback loops
    3. Customer feedback at scale
    4. Setting customer expectations of support and SLAs
    5. Scale-based support models
    6. Support metrics
      1. Ticket volume
      2. Customer satisfaction (CSAT) score
      3. First response time
      4. Average resolution time
      5. Ticket volume to active user volume
      6. Segmentation of tickets
    7. Summary
  14. Part 2: Understanding the Developer
    1. Walking in customers’ shoes
    2. Meet the customers where they are
  15. Chapter 7: Walking in the Customer’s Shoes
    1. Prioritizing user research
    2. Establishing user personas
    3. Mapping the developer’s journey
      1. Discovery
      2. Evaluation
      3. Integration
      4. Testing
      5. Deployment
      6. Observability
    4. Determining customer touch points
    5. Identifying the points of friction and conversion
    6. Summary
  16. Chapter 8: Customer Expectations and Goals
    1. Conducting qualitative and quantitative research
      1. Qualitative research methods
      2. Quantitative research methods
      3. Combination of qualitative and quantitative methods
    2. Creating user empathy maps
    3. Identifying customer use cases
    4. Identifying customer pain points
    5. Aligning stakeholders
    6. Summary
  17. Chapter 9: Components of API Experience
    1. Industry standards for API experience
    2. Creating API documentation
      1. API references
    3. Developer portal
      1. API credentials
      2. API status
      3. API changelog
      4. Sample code and demos
    4. Integration guides and tutorials
    5. Providing developer tools
      1. Sandbox
      2. Public GitHub repositories
      3. Developer communities
      4. SDKs
      5. CLIs
      6. Postman Collections
      7. Low-code and no-code tooling
    6. Instrumenting support mechanisms
    7. Summary
  18. Part 3: Deep Dive into Key Metrics for API Products
    1. Translating touchpoints to measurable metrics
    2. A holistic approach to analytics
  19. Chapter 10: Infrastructure Metrics
    1. Key success factors (KSFs) for APIs
    2. Infrastructure as the foundation for API analytics
    3. Performance metrics
    4. Uptime and availability
      1. Errors per minute
      2. Average and maximum latency
      3. 90th-percentile latency by customer
    5. Usage metrics
      1. Requests Per Minute (RPM)
      2. CPU usage
      3. Memory usage
      4. Error code distribution
      5. Concurrent connections
      6. Top endpoints
      7. Usage by segments
    6. Reliability metrics
      1. Mean Time to Failure (MTTF)
      2. MTTR
      3. MTBR
      4. The Rate of Occurrence of Failure (ROCOF)
      5. Probability of Failure on Demand (POFOD)
    7. Summary
  20. Chapter 11: API Product Metrics
    1. Defining product metrics
    2. Discovery
      1. Unique visitors
      2. Page views
      3. Sign-ups by channel
      4. Reading level or text complexity analysis
      5. Link validation
      6. Search keyword Analysis
    3. Engagement
      1. Average time on page
      2. Bounce rate
      3. Engagement with homegrown tools
      4. Customer engagement score (CES)
    4. Acquisition
      1. Daily user sign-ups – new users
      2. Time to first hello world (TTFHW)
      3. Software development kit and version adoption
    5. Activation
      1. Time to first transaction (TFT)
      2. Time to value (TTV)
      3. Cohort analysis
      4. DAU/MAU/WAU
    6. Retention
      1. Recurring daily, weekly, and monthly usage
      2. Customer retention
      3. API calls per business transaction
    7. Experience
      1. Unique API consumers
      2. Top customers by API usage
      3. Conversion rate
      4. Daily support tickets per active users
      5. CSAT
      6. Net Promoter Score (NPS)
    8. Summary
  21. Chapter 12: Business Metrics
    1. Defining business metrics
    2. Measuring revenue
      1. MRR
      2. Revenue versus forecast
      3. ARPA
      4. Average transaction value (ATV)
      5. Revenue by acquisition channel
    3. Adoption tracking
      1. SDK adoption
      2. Feature adoption
    4. Churn analysis
      1. Churn rate
      2. Cohort retention
    5. Optimizing for growth
      1. Lead response
      2. Growth rate YoY
      3. Quota alignment
      4. Net sales revenue
      5. CAC
      6. Cost per lead (CPL)
      7. CLV/LTV
    6. Measuring operations’ efficiency
      1. Support metrics
      2. Beta versus General Availability (GA)
      3. Paid support subscription rate by tier
      4. Cost of infrastructure
      5. Incidents per month
      6. Cost of outage
    7. Summary
  22. Part 4: Setting a Cohesive Analytics Strategy
    1. Short-term and long-term goal setting
    2. Strategic roadmapping
  23. Chapter 13: Drawing the Big Picture with Data
    1. Setting the data strategy
    2. Methods for analyzing data
      1. Cluster analysis
      2. Cohort analysis
      3. Regression analysis
      4. Predictive analysis
      5. Data mining
      6. Text analysis
      7. Time series analysis
      8. Decision trees
      9. Conjoint analysis
      10. Factor analysis
    3. Interpreting data
      1. SWOT analysis
      2. Benchmarking and baselining
      3. Making decisions without data
      4. The Delphi method
    4. Goal setting with data
      1. SMART framework
      2. The OKR framework
      3. Key performance indicators (KPIs)
      4. North Star metrics
      5. The HEART framework
    5. Summary
  24. Chapter 14: Keeping Metrics Honest
    1. Mixing qualitative and quantitative feedback
    2. Validating your insights
    3. Defining the right product metrics
      1. Leading and lagging indicators
      2. Input and output metrics
    4. Framework for storytelling with data
      1. Identify the audience
      2. Develop a narrative
      3. Choose the right data and visualizations
      4. Draw attention to key information
      5. Engage your audience
    5. Summary
  25. Chapter 15: Counter Metrics to Avoid Blind Spots
    1. Establishing counter metrics
    2. Avoiding gameable metrics
    3. Avoiding cannibalizing metrics
    4. Aligning incentives
    5. Avoiding cognitive biases
      1. Confirmation bias
      2. Selection bias
      3. Anchoring bias
      4. Framing bias
      5. Overconfidence bias
      6. Status quo bias
      7. Outliers
      8. Recall bias
      9. Confounding bias
      10. Association bias
    6. Summary
  26. Chapter 16: Decision-Making with Data
    1. Bringing it all together
    2. Short-term goals
    3. Long-term goals
    4. Writing a product one-pager
    5. Sample strategy document
    6. Strategic storytelling
    7. Leading the team to success
    8. Summary
  27. The API Analytics Cheat Sheet
  28. Index
    1. Why subscribe?
  29. Other Books You May Enjoy
    1. Packt is searching for authors like you
    2. Share Your Thoughts
    3. Download a free PDF copy of this book

Product information

  • Title: API Analytics for Product Managers
  • Author(s): Deepa Goyal
  • Release date: February 2023
  • Publisher(s): Packt Publishing
  • ISBN: 9781803247656