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26986Re: [webanalytics] Re: Why does A/B testing work?

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  • Craig Sullivan
    Nov 6, 2010
      My book list on this stuff:

      * Neuro web design - Susan M Weinshenck
      * Filling in the blanks - Luke Wroblewski
      * Influence - Robert Cialdini
      * Always be testing - Bryan Eisenberg
      * Forms that work - Jarrett & Gaffney
      * What every body is saying - Joe Navarro
      * Why we buy - Paco underhill
      * The design of everyday things - Donald Norman
      * Buyology - Martin Lindstrom
      * Emotionomics - Dan Hill
      * Neuromarketing - Renvoise & Morin
      * Landing page optimization - Tim Ash
      * Web analytics - an hour a day - Avinash Kaushik
      * Don't make me think - Steve Krug
      * Search Analytics - Hurol Inan

      All these have helped in some way as inputs to our testing.



      On Sat, Nov 6, 2010 at 2:01 PM, Craig Sullivan <sullivac@...> wrote:

      > Hi,
      > Some great points there.
      > I don't agree with Ophir on one thing though - it isn't impossible to know
      > for sure - you may not know the winning combination of elements in a test
      > but you can bias the results towards positive in a seriously big way.
      > What I'm saying is that the *directionality* of your testing can be
      > influenced by:
      > * Usability testing
      > * Eye tracking
      > * Previous test results
      > * Persuasive copy techniques
      > * Books
      > * Surveys
      > * Exit (funnel) surveys
      > * Analytics data
      > * Simply listening lots to customers
      > * And last of all, something you learn to focus on for mobile - removing
      > CRUFT
      > A good example of previous tests (we do 3M a month) is when we introduced
      > 'goal oriented' words into the 'call to action' button wording.
      > We quickly discovered that stuff focusing on the end result (on our site -
      > Fix my Glass) had a huge (for a single piece of wording) affect on
      > conversion on a page. So, the next tests include more of these (but still
      > keeping lots of new stuff & wildcards). We also found out what sort of
      > people images to use, where they should look, what body language they should
      > have, what they should hold in their hands etc. I can tell, for example,
      > that a small benefit is gained by having the person look right at you or
      > slightly towards the call to action button. This does not mean that I then
      > assume these work all the time, forever - just that there is a huge freaking
      > hint there for me!
      > Usability testing is extremely important too - this helped uncover many
      > things that either needed to be fixed or were ideal candidates for testing
      > and yes, this directionality helps too.
      > As human beings, we constantly go through the process of learning patterns
      > of interaction ourselves. When we do testing, we also begin to learn design
      > patterns that work. We then find we can load the tests with new stuff, left
      > of field suggestions but most importantly, variants on things that actually
      > worked before. From this work, you begin to build a library of things (or
      > approaches) that are likely to succeed in tests.
      > I may not know the final combination but when working on variables, we
      > *can* stack the deck of cards in our favour.
      > Based on some ad-hoc tests I've done, usability people are far better at
      > guessing than executives who often make the decisions on test or page
      > design. Jakob Nielsen has observed this effect in a study (
      > http://www.useit.com/alertbox/guesses-data.html) and I see it in my work
      > with people who do testing and optimisation - those that keep the user focus
      > laser sharp often design better tests.
      > What is starting to collide for me is that the combination of user
      > experience techniques, testing and web analytics - a winning combo. Combine
      > this with data segmentation and we arrive at a scenario where you type
      > 'windshield repair' into google and get a page previously optimised for that
      > segment (from tests).
      > Even after all of that, I still guess wrong about 20% of the time on
      > whichtestwon.com, so what the heck do I know?
      > Regards,
      > Craig.
      > On Mon, Nov 1, 2010 at 5:11 PM, fredeilam <prusak@...> wrote:
      >> Hi David,
      >> Great question!
      >> Just to make sure we're on the same page, I'm going to re-phrase your
      >> question as such:
      >> When doing A/B split testing, we often see that version X converts better
      >> than version Y.
      >> The question is: Why does version X convert better than version Y?
      >> The short answer is that it's impossible to know for sure. There are
      >> dozens of factors that will influence a person's online behavior.
      >> The long answer is that most of these factors have been studied and
      >> written about. Here are a few books that cover the factors in online
      >> behavior:
      >> - Influence: The Psychology of Persuasion
      >> - Type & Layout: Are You Communicating or Just Making Pretty Shapes
      >> - Don't Make Me Think: A Common Sense Approach to Web Usability, 2nd
      >> Edition
      >> - Landing Page Optimization: The Definitive Guide to Testing and Tuning
      >> for Conversions
      >> - Web Design for ROI: Turning Browsers into Buyers & Prospects into Leads
      >> - Neuro Web Design: What Makes Them Click?
      >> Ophir
      >> --- In webanalytics@yahoogroups.com <webanalytics%40yahoogroups.com>,
      >> "Dave" <tregowandave@...> wrote:
      >> >
      >> > Hello everyone,
      >> >
      >> > Why does A/B testing work?
      >> >
      >> > I mean this question to be perhaps more philosophical than technical.
      >> I've run a [small] number of A/B tests, and yes, I've shown that creative A
      >> generates a higher click-through rate than creative B. But why?
      >> >
      >> > I frequently face the argument that "If people are looking for blue
      >> widgets, they'll find them anyway" when I recommend a link be moved above
      >> the fold, or made more prominent in some other way. And to some extent, the
      >> argument holds - blue widgets are more popular than green widgets, no matter
      >> if you make the green widget link bigger, bolder or more obvious. This can
      >> be especially frustrating if we're targetted on the sale of green widgets
      >> online.
      >> >
      >> > So - why does A/B testing work? "Buy one green widget, get one free -
      >> click here" may perform better than "Green widgets half price - find out
      >> more" but why is that? If someone wants to buy green widgets, won't they
      >> click either link with equal enthusiasm? Or are we hoping to persuade the
      >> undecided? Do we suspect or believe that there's a core contingent of
      >> green-widget fans who want a green widget, and that A/B testing will work
      >> better on visitors who want a cheap widget, or a better widget or are just
      >> browsing?
      >> >
      >> > Have I answered my own question? This is entirely up for debate, and I'm
      >> very interested in people's opinions.
      >> >
      >> > David
      >> >
      > --
      > Craig Sullivan
      > http://www.linkedin.com/in/craigsullivan
      > +44-(0)7711-657315
      > +44-(0)208-318-9290
      > Not sent from my blackberry <grin>

      Craig Sullivan

      Not sent from my blackberry <grin>

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