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A/B-testing 
H OW, WH E N , E X A M P L E S & P I T T FA L L S 
L e a n C o n f e r e n c e – N o v e m b e r 1 7 t h - M a n c h e s t e r 
To n We s s e l i n g – C E O – Te s t i n g . A g e n c y
Manchester 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Should I go for Ci ty? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Should I go for Uni ted? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Manchester 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing 
A/B-testing != CRO 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing 
CRO != user knowledge 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing 
A/B-testing 
== 
user knowledge 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing 
HOW & WHEN 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing 
EXAMPLES 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing 
PITTFALLS 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Ton Wessel ing | @ TonW 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 
 More testing 
 Quality Assurance 
 Lower pricing
Onl ine Exper iments – A/B- test ing 
Default 
Variation 
B 
Variation 
Winner! 
A 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Hyper l ink junky 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Digging through log f i les 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Trying to improve 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Over and over again 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
What most star t -ups do 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
That is: 
0 / 1 Testing 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Why can this lead to fai lures? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
0/1 Test ing: weekly change? 
26 out of 44 weeks: over 5% change! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Test ing should be l ike: 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Scient i f ic approach 
A / B Testing 
Live Online Research 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Exper iments 
“If you double the number of 
experiments you do per year 
you’re going to double your 
inventiveness” 
Jeff Bezos, CEO Amazon – 2004! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Growth l ike Amazon 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 
German Ecommerce market, thank you André Morys
Exper iments per year 
1000+ 
(but it did not start like that) 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Growth curve 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Phase 1: test solut ions 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Fake adwords test ing 
Do they 
click 
on your idea? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Fake facebook test ing 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 
Do they 
like 
your idea?
Fake landing page test ing 
Do they 
subscribe 
to your idea? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Make sure i t ’s not 
0 / 1 Testing 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Once you br idged the gap 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
The growth phase! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Dupl icate? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
I t ’s t h e w e b , i t ’s scalable! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
You need to opt imize! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Over and over again 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
I t takes many exper iments to win 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Maximize your test capaci ty 
Time 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 
Conversion%
Speed up – more people 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Growth l ike Amazon 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 
German Ecommerce market, thank you André Morys
Real growth 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
I t takes heavy exper iment ing 
250+ in a year 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Not every exper iment is successful 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
I t takes a ful l stadium a week for 250+ 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Or roughly 
1000+ 
conversion points 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Too slow? Energy wi l l run out ! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
And you wi l l never get this 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
You need the real fast paced cul ture 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
How does Bi l l win? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Emot ion vs Rat io 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Why is your user here? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
How can you 
help your user ’s brain 
to fullfil it’s needs? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
I t ’s not about A/B- test ing 
Growth is about learning 
how to serve brains! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Test ing costs t ime 
Use it to LEARN 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
FA C T & A C T – 7 s t e p s t o l e a r n 
Find Analyze Create Test 
& 
Analyze Conclude Tell 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
N o w : f o c u s o n C TA 
Create 
Test 
Analyze 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Create = Data & Psychology 
Analyze 
& 
Experiment 
Digital Data Persuasion Psychology 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Wheel -of-Persuasion.com 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Persuasion on forms 
+25% sales 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Same technique 
Signi f icant more 
submi ts, but . . 
Less registrat ions 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A smal l sentence 
+18% 
sales 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
But also 
+10% appl icat ions 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Mot ivat ion 
Winner 
(sales) 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Win your own form A/B- test 
http://testing.agency/manchester 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
And social proof? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 
Many went before you 
In november 1.675 
people applied for 
a loan at MoneYou. 
Winner 
(sales)
Chunk your U S P ’s 
+14% 
sales 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Wi th learning: Phase 3 becomes easier 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Test ing becomes user knowledge 
Conversion	Op miza on	 Market	Research	 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Pi t t fal ls 
How NOT to test 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing can be 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
D o n ’ t t rust your A/B- test analyt ics 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
It keeps you away f rom this fai lure 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Enough t raff ic & conversions? 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Low signi f icance levels 
 Big chance the winner is not a real winner 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Low power levels 
 Big chance a real winner is not recognized 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Tested percentage is a spread! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Example test -setup 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Average power : 40% 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
So: 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Another er ror warning: 
 You just go and dig unitil you find something 
(you will always find something that seems true BUT is 
not!) 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
OK, resul ts are in 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Not signi f icant 
 It’s not a winner, stop 
 But, it’s does not mean it’s a loser! 
 Average: 30% of your tests will have winners 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
More? 
http://ondi.me/contentverve 
http://ondi.me/conversionxl 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Conclude 
 Do nothing? 
or 
 Re-test? 
or 
 Implement? 
or 
 Scale? 
and 
 Continue or change test roadmap 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Knowledge l ibrary: ABtestguide.com 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
I t ’s not about A/B- test ing 
Growth is about learning 
how to serve brains! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
So you wi l l get this curve 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Growth l ike Amazon 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 
German Ecommerce market, thank you André Morys
A/B- test ing 
HOW & WHEN 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing 
EXAMPLES 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
A/B- test ing 
PITTFALLS 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Sl ides & more 
http://testing.agency/manchester 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
Be l ike Bi l l , and win! 
T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
ht tp: / / testing.agency/manchester 
H OW, WH E N , E X A M P L E S & P I T T FA L L S 
L e a n C o n f e r e n c e – N o v e m b e r 1 7 t h - M a n c h e s t e r 
To n We s s e l i n g – C E O – Te s t i n g . A g e n c y

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Leanconf2014 - A/B-testing - How, When, Examples & Pittfalls by Ton Wesseling

  • 1. A/B-testing H OW, WH E N , E X A M P L E S & P I T T FA L L S L e a n C o n f e r e n c e – N o v e m b e r 1 7 t h - M a n c h e s t e r To n We s s e l i n g – C E O – Te s t i n g . A g e n c y
  • 2. Manchester T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 3. Should I go for Ci ty? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 4. Should I go for Uni ted? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 5. Manchester T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 6. A/B- test ing A/B-testing != CRO T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 7. A/B- test ing CRO != user knowledge T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 8. A/B- test ing A/B-testing == user knowledge T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 9. A/B- test ing HOW & WHEN T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 10. A/B- test ing EXAMPLES T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 11. A/B- test ing PITTFALLS T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 12. Ton Wessel ing | @ TonW T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4  More testing  Quality Assurance  Lower pricing
  • 13. Onl ine Exper iments – A/B- test ing Default Variation B Variation Winner! A T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 14. Hyper l ink junky T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 15. Digging through log f i les T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 16. Trying to improve T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 17. Over and over again T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 18. What most star t -ups do T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 19. That is: 0 / 1 Testing T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 20. Why can this lead to fai lures? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 21. 0/1 Test ing: weekly change? 26 out of 44 weeks: over 5% change! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 22. Test ing should be l ike: T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 23. Scient i f ic approach A / B Testing Live Online Research T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 24. Exper iments “If you double the number of experiments you do per year you’re going to double your inventiveness” Jeff Bezos, CEO Amazon – 2004! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 25. Growth l ike Amazon T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 German Ecommerce market, thank you André Morys
  • 26. Exper iments per year 1000+ (but it did not start like that) T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 27. Growth curve T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 28. Phase 1: test solut ions T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 29. Fake adwords test ing Do they click on your idea? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 30. Fake facebook test ing T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 Do they like your idea?
  • 31. Fake landing page test ing Do they subscribe to your idea? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 32. Make sure i t ’s not 0 / 1 Testing T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 33. Once you br idged the gap T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 34. The growth phase! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 35. Dupl icate? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 36. I t ’s t h e w e b , i t ’s scalable! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 37. You need to opt imize! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 38. Over and over again T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 39. I t takes many exper iments to win T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 40. Maximize your test capaci ty Time T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 Conversion%
  • 41. Speed up – more people T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 42. Growth l ike Amazon T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 German Ecommerce market, thank you André Morys
  • 43. Real growth T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 44. I t takes heavy exper iment ing 250+ in a year T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 45. Not every exper iment is successful T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 46. I t takes a ful l stadium a week for 250+ T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 47. Or roughly 1000+ conversion points T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 48. Too slow? Energy wi l l run out ! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 49. And you wi l l never get this T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 50. You need the real fast paced cul ture T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 51. How does Bi l l win? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 52. Emot ion vs Rat io T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 53. T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 54. Why is your user here? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 55. How can you help your user ’s brain to fullfil it’s needs? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 56. I t ’s not about A/B- test ing Growth is about learning how to serve brains! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 57. Test ing costs t ime Use it to LEARN T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 58. FA C T & A C T – 7 s t e p s t o l e a r n Find Analyze Create Test & Analyze Conclude Tell T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 59. N o w : f o c u s o n C TA Create Test Analyze T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 60. Create = Data & Psychology Analyze & Experiment Digital Data Persuasion Psychology T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 61. Wheel -of-Persuasion.com T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 62. Persuasion on forms +25% sales T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 63. Same technique Signi f icant more submi ts, but . . Less registrat ions T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 64. A smal l sentence +18% sales T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 65. But also +10% appl icat ions T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 66. Mot ivat ion Winner (sales) T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 67. Win your own form A/B- test http://testing.agency/manchester T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 68. And social proof? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 Many went before you In november 1.675 people applied for a loan at MoneYou. Winner (sales)
  • 69. Chunk your U S P ’s +14% sales T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 70. Wi th learning: Phase 3 becomes easier T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 71. Test ing becomes user knowledge Conversion Op miza on Market Research T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 72. Pi t t fal ls How NOT to test T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 73. A/B- test ing can be T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 74. D o n ’ t t rust your A/B- test analyt ics T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 75. It keeps you away f rom this fai lure T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 76. Enough t raff ic & conversions? T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 77. Low signi f icance levels  Big chance the winner is not a real winner T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 78. Low power levels  Big chance a real winner is not recognized T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 79. Tested percentage is a spread! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 80. Example test -setup T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 81. Average power : 40% T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 82. So: T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 83. Another er ror warning:  You just go and dig unitil you find something (you will always find something that seems true BUT is not!) T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 84. OK, resul ts are in T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 85. Not signi f icant  It’s not a winner, stop  But, it’s does not mean it’s a loser!  Average: 30% of your tests will have winners T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 86. More? http://ondi.me/contentverve http://ondi.me/conversionxl T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 87. Conclude  Do nothing? or  Re-test? or  Implement? or  Scale? and  Continue or change test roadmap T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 88. Knowledge l ibrary: ABtestguide.com T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 89. I t ’s not about A/B- test ing Growth is about learning how to serve brains! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 90. So you wi l l get this curve T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 91. Growth l ike Amazon T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4 German Ecommerce market, thank you André Morys
  • 92. A/B- test ing HOW & WHEN T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 93. A/B- test ing EXAMPLES T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 94. A/B- test ing PITTFALLS T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 95. Sl ides & more http://testing.agency/manchester T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 96. Be l ike Bi l l , and win! T o n We s s e l i n g | @ T o nW # l e a n c o n f Ma n c h e s t e r 2 0 1 4
  • 97. ht tp: / / testing.agency/manchester H OW, WH E N , E X A M P L E S & P I T T FA L L S L e a n C o n f e r e n c e – N o v e m b e r 1 7 t h - M a n c h e s t e r To n We s s e l i n g – C E O – Te s t i n g . A g e n c y

Editor's Notes

  1. Laten zien: kleine circles -> naar grote stappen Inzoomen kleine details
  2. “If you double the number of experiments you do per year you’re going to double your inventiveness” Jeff Bezos, CEO Amazon – 2004!
  3. Insight designers
  4. Insight designers
  5. Te vroeg stoppen Te lang doorlopen Graven naar resultaat Zeggen: verliezer doet niets Bij te lage significantie goedkeuren Doorverwijzen naar URL’s coversionXL en contentverve.com Fase 3 groei -> met learnings -> innovatie Einde -> dus als je gaat groeien -> scale je test capaciteit tot maximaal mogelijk op je website Test dat waar het brein op reageert Op de juiste manier
  6. Te vroeg stoppen Te lang doorlopen Graven naar resultaat Zeggen: verliezer doet niets Bij te lage significantie goedkeuren Doorverwijzen naar URL’s coversionXL en contentverve.com Fase 3 groei -> met learnings -> innovatie Einde -> dus als je gaat groeien -> scale je test capaciteit tot maximaal mogelijk op je website Test dat waar het brein op reageert Op de juiste manier
  7. Laten zien: kleine circles -> naar grote stappen Inzoomen kleine details