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Maximizing Satisfaction by Learning while Earning

Gui Liberali Erasmus School of Economics Sloan School of Management, MIT

Website Morphing Algorithms Have Been Published and Generated Quite Some Buzz… •  Morphing trilogy (Website, Banner and Time-to-Morph) published at Marketing Science (twice),

Management Science (forthcoming), Sloan Management Review •  Discussed in dozens of blogs and magazines

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BT Experiment

•  Content areas of home page

•  All saw the same landing page

•  Each content area present the info differently

Source: Hauser, Urban, Liberali and Braun, 2009

Trick: Match cognitive styles and website characteristics

Cognitive-style dimensions (2 x 2 x 2 x 2) •  leader vs. follower •  analytic/visual vs. holistic/verbal •  impulsive vs. deliberative •  active vs. passive

Website characteristics (2 x 2 x 2) •  graphical vs. verbal presentations •  small- vs. large information load •  focused vs. general content


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Key Challenges Fundamental Problems are general and application

independent (morphs can be sites, products, ..)

•  How do we update our beliefs about the cognitive style of each user?

•  Given these beliefs, what is the optimal morph (optimal website version? Optimal product to show?)

To keep it simple we will look at an application that morphs sites.

© 2008 MIT Sloan School of Management

Optimal solution with Gittins’ indices (assume we know cognitive style)

Gittins’ indices for the eight morphs.

Morph that was chosen.

0

1

2

3

4

5

6

7

8

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Visitor

Cho

sen

Mor

ph

0.35

0.45

0.55

0.65

0.75

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Visitor

Gitt

ins'

Indi

ces

Morph 0 Morph 1 Morph 2 Morph 3 Morph 4 Morph 5 Morph 6 Morph 7

System experiments with Morph 3 for a while before settling back to Morph 2.


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Empirically-grounded synthetic visitors (normalize profit to 1.0)

Expected Reward

Improve-ment Efficiency Relative

Efficiency No Gittins’ loop nor knowledge of cognitive styles. 0.3205 0.0% 80.4% 0.0% No morphing. Website chosen optimally by Gittins’ loop. 0.3625 13.1% 91.0% 53.9% Morphing: Match characteristics to cognitive style Bayesian inference of cognitive styles (10 clicks) 0.3844 19.9% 96.5% 82.0% Bayesian inference of cognitive styles (50 clicks) 0.3865 20.6% 97.0% 84.7% Perfect information on cognitive styles, Gittins’ loop.* 0.3879 21.0% 97.4% 85.5% Perfect information on style and purchase probabilities* 0.3984 24.3% 100% 100%

*Upper bounds. BT does not have perfect information on either cognitive styles or purchase probabilities.


Estimated impact for BT Group

•  Gen-2 Results – 80,000 visitors –  Gittins’ loop alone – find the best static = $52.3 M –  10-click Bayesian loop adds + $27.4 M

– Gittins’ plus Bayesian = $79.7 M –  50-click Bayesian loop adds + $2.6 M –  perfect information adds + $1.8 M


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Website Design Recommendations Morphing Theory relies heavily on website design

Website will morph efficiently when

•  It is able to rapidly identify the user style from clicks: we learn style from link choice •  It chooses the optimal morph for that style

Designing links •  A click is choice among alternatives: if alternatives are different, a click is informative •  Design webpages so that are links with different cognitive cues in the same page

Designing Morphs •  Best morph for one style should (ideally) be worst for another style •  Design various morphs and test them in priming study. Then you can pick the most

discriminating morphs before going live


For more details

[email protected]

http://people.few.eur.nl/liberali Hauser, J., Liberali, G. & Urban, G (2014). Website Morphing 2.0: Technical and

Implementation Advances and a Field Experiment. Management Science. Urban, G, Liberali, G., Bordley, R, Macdonald, E & Hauser, J. (2014).

Morphing Banner Advertising. Marketing Science, 33(1), 27-46. Hauser, J., Urban, G, Liberali, G. & Braun, M. (2009). Website Morphing. Marketing

Science, 28(2), 202-223