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Showing posts with label testing. Show all posts
Showing posts with label testing. Show all posts
Wednesday, 6 May 2026

Leveraging Data for Segment Identification and Personalised Experiences

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In previous articles, I have explored the practical strategies for analysing user behaviour derived from website interactions and A/B testin...
Friday, 24 April 2026

"Click For Free Money" on the Customer Journey

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A few years ago, a colleague of mine highlighted a crucial insight: engagement on a button isn't always a reliable measure of success . ...
Wednesday, 11 February 2026

Why Too Many Cooks Spoil the A/B Testing Roadmap

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Why Too Many Cooks Spoil the A/B Testing Roadmap How to build a lean, decisive testing program without sacrificing collaboration When Consen...
Wednesday, 3 September 2025

Did You Just Code a Distraction?

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In the fast-paced world of web development and digital marketing, creating new features to enhance user experience is not just a common prac...
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Wednesday, 27 August 2025

Do You Know How Well Your Test Will Perform?

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 There are various ways of running tests - or more specifically, there are various ways of generating test hypotheses.  One that I've co...
Sunday, 24 November 2024

Testing versus Implementing - why not just switch it on?

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"Why can't we just make a change and see what happens? Why do we have to build an A/B test - it takes too long!  We have a roadmap,...
Monday, 18 November 2024

Designing Personas for Design Prototypes

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Part of my job is validating (i.e. testing and confirming) new designs for the website I work on.  We A/B test the current page against a n...
Wednesday, 10 July 2024

How not to Segment Test Data

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 Segmenting Test Data Intelligently Sometimes, a simple 'did it win?' will provide your testing stakeholders with the answer they ne...
Friday, 17 May 2024

Multi-Armed Bandit Testing

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 I have worked in A/B testing for over 12 years, and blogged about it extensively.  I've covered how to set up a hypothesis , how to tes...
Wednesday, 10 January 2024

Statistics: Type 1 and Type 2 Errors

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 In statistics (and by extension, in A/B testing), a Type I error is a false positive conclusion (we think a test recipe won when it didn...
Monday, 14 November 2022

How many of your tests win?

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 As November heads towards December, and the end of the calendar year approaches, we start the season of Annual Reviews.  It's time to i...
Thursday, 25 August 2022

Testing Towards The Future State

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Once or twice in the past, I've talked about how your testing program needs to align with various departments in your company if it...