Book Club: The DevOps Handbook (Chapter 17. Integrate Hypothesis-Driven Development and A/B Testing into Our Daily Work)

This entry is part [part not set] of 25 in the series DevOps Handbook

The following is a chapter summary for “The DevOps Handbook” by Gene Kim, Jez Humble, John Willis, and Patrick DeBois for an online book club.

The book club is a weekly lunchtime meeting of technology professionals. As a group, the book club selects, reads, and discuss books related to our profession. Participants are uplifted via group discussion of foundational principles & novel innovations. Attendees do not need to read the book to participate.

Background on The DevOps Handbook

More than ever, the effective management of technology is critical for business competitiveness. For decades, technology leaders have struggled to balance agility, reliability, and security. The consequences of failure have never been greater―whether it’s the debacle, cardholder data breaches, or missing the boat with Big Data in the cloud.

And yet, high performers using DevOps principles, such as Google, Amazon, Facebook, Etsy, and Netflix, are routinely and reliably deploying code into production hundreds, or even thousands, of times per day.

Following in the footsteps of The Phoenix Project, The DevOps Handbook shows leaders how to replicate these incredible outcomes, by showing how to integrate Product Management, Development, QA, IT Operations, and Information Security to elevate your company and win in the marketplace.

The DevOps Handbook

Chapter 17

All too often in software projects, developers work on features for months or years, spanning multiple releases, without ever confirming whether the desired business outcomes are being met, such as whether a particular feature is achieving the desired results or even being used at all.

Before building a feature, teams should ask themselves: “Should we build it, and why?”

A Brief History of A/B Testing

A/B testing techniques were pioneered in direct response marketing, which is one of the two major categories of marketing strategies. The other is called mass marketing or brand marketing; it relies on placing as many ad impressions in front of people as possible to influence buying decisions.

In previous eras, before email and social media, direct response marketing meant sending thousands of postcards or flyers via postal mail, and asking prospects to accept an offer by calling a telephone number, returning a postcard, or placing an order.

Integrating A/B Testing Into Feature Testing

The most commonly used A/B technique in modern UX practice involves a website where visitors are randomly selected to be shown one of two versions of a page, either a control (“A”) or a treatment (“B”).

A/B tests are also known as online controlled experiments and split tests. Performing meaningful user research and experiments ensures that development efforts help achieve customer and organizational goals.

Integrate A/B Testing Into Releases

Fast and iterative A/B testing is made possible by being able to quickly and easily do production deployments on demand, using feature toggles and potentially delivering multiple versions of our code simultaneously to customer segments.

Integrate A/B Testing Into Feature Planning

Product owners should think about each feature as a hypothesis and use production releases as experiments with real users to prove or disprove that hypothesis.

Hypothesis-Driven Development:

  • We Believe that increasing the size of hotel images on the booking page.
  • Will Result in improved customer engagement and conversion.
  • We Will Have Confidence To Proceed When we see a 5% increase in customers who review hotel images who then proceed to book in forty-eight hours.

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