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15 A/B testing mistakes I see all the 15 A/B testing mistakes I see all the

15 A/B testing mistakes I see all the - PowerPoint Presentation

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Uploaded On 2020-08-28

15 A/B testing mistakes I see all the - PPT Presentation

damn time and what to do about it by Peep Laja ConversionXL Call to Action Conference 2014 You should test that Dude wtf peeplaja Typical scenario A company runs 100 tests year ID: 808771

testing peeplaja test mistake peeplaja testing mistake test tests conversions data don

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Presentation Transcript

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15 A/B testing mistakes I see all the

damn

time

(and what to do about it)

by Peep Laja, ConversionXL

Call to Action Conference 2014

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“You should test that!”

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“Dude wtf?”

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@peeplaja

Typical scenario:

A company runs 100 tests / year.

After 12 months their conversion rate is still the same.

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@peeplaja

Testing mistake #1:

Precious time wasted on stupid tests

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@peeplaja

Testing mistake #2:

You don’t have a data-driven, learning-oriented hypothesis

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@peeplaja

Testing mistake #3:

You think you know what will work

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@peeplaja

Testing mistake #4:

You run tests when you have no traffic

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@peeplaja

Testing mistake #5:

Your absolute conversions are way too low

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@peeplaja

You need *at least*

250-400 conversions PER variation.

Way more if you want to segment the data

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@peeplaja

Our "thumb rule" is: 3000-4000 conversions per variation and 3-4 week test duration. That is enough traffic so we can even talk about valid data if we drill down into segments.

Testing "sin" nr.1: search in segments for uplifts although you have no statistical validity, e.g. 85 versus 97 conversions. That’s bullshit.

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@peeplaja

Testing mistake #6:

Your tests don’t run long enough

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@peeplaja

Testing mistake #7:

You don’t test full weeks at a time

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@peeplaja

Testing mistake #8:

Test data is not sent to third-party analytics

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@peeplaja

Pro tip:

If you have over 500,000 pageviews / mo, you don’t (necessarily) need to spend $100,000 on GA Premium. Get unsampled data with

Analytics Canvas

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@peeplaja

Testing mistake #9:

You give up after your first test for a hypothesis fails.

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Full case study:

http://conversionxl.com/case-study-how-we-improved-landing-page-conversion/

79.3% uplift in conversions

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@peeplaja

Testing mistake #11:

You’re not aware of validity threats

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@peeplaja

History effect

Instrumentation effect

Selection effect

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@peeplaja

Testing mistake #12:

You’re ignoring small gains

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@peeplaja

5% monthly increase in your conversion rate will result in 80% uplift for the year.

That’s how math works.

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@peeplaja

Testing mistake #13:

You don’t know html/css/jquery - and thus only test the simple stuff

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@peeplaja

Testing mistake #14:

You’re not running tests at all times

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@peeplaja

Testing mistake #15:

You’re late for your lunch break!

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Follow me @peeplaja

@peeplaja

Keep reading ConversionXL!

Thank you

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