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The Impact of Choice Environment on Consumer Choice Behavior


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This presentation explores how the user interaction design of online choice environments such as booking sites can impact consumer choice behavior. The format of this presentation is a narrative; a powerful way to present study results in an engaging, inspiring and informative way. The work is based on two academic papers and has been presented before at an Advanced Analytics (ADAN) workshop of the Market Research Society in London, November 10, 2016

The Impact of Choice Environment on Consumer Choice Behavior

  1. 1. The impact of choice environment on choice behavior Studio GerART Gerard Loosschilder
  2. 2. ONCE UPON A TIME …
  3. 3. … there was a Princess by the name of Astrid. Astrid was preparing for a lifetime of governing as Queen Astrid, …
  4. 4. … but for now, she liked to spend her time traveling and seeing the world.
  5. 5. Also, she was highly engaged in good causes and animal welfare.
  6. 6. ONE DAY ….
  7. 7. Animal Welfare Conference Princess Astrid received a letter from the Animal Welfare Association. They invited her as a keynote speaker to their Global conference…
  8. 8. … which would take place in the beautiful city of Istanbul, Turkey.
  9. 9. Astrid happily accepted the invitation. She got to work on it straight away. She booked her own travel as a part of the adventure. She consulted a booking site to find a hotel.
  10. 10. Call to action Hotel Chain, Type & Style Distance to city center Placement of 50 hotel on the results page - top to bottom Review Score on cleanliness, staff and facilities; result in a mean score and a label Including room price per night The booking site contained several helpful features to help her search a hotel room. 50 rooms were listed top to bottom and Astrid had to scroll to see the lower entries. Also, the brand of the hotel chain, the type and style of rooms available were listed along with their distance to the city center, review scores, room price, and a call to action that suggested that Astrid had to act fast.
  11. 11. Astrid was distressed. As a princess, she got easily stuck with all of these options….
  12. 12. For example, usually her personal assistant would take care of all of her travel. Astrid did not know about things like hotel brands, room styles and types, …
  13. 13. Also, Astrid did not understand the meaning of the distance to a city center, because her security detail would take care of travel on site, …
  14. 14. Her domestic staff did her cleaning so Astrid did not understand room reviews and ratings on such concepts as “cleanliness, staff and facilities” …
  15. 15. Astrid was seriously challenged to book her flight and hotel and she ended up what many visitors do: click on one of the first hotels that appeared in her booking app.
  16. 16. When the day had come, Astrid went on the flight to Istanbul …
  17. 17. And she ended up in a terrible hotel, which made her cry her heart out.
  19. 19. We meet Oscar, revenue manager at the booking site that Astrid used …
  20. 20. Astrid’s bad room experience is a side effect of the way the site, and Oscar, work.
  21. 21. Oscar knows that consumers tend to gravitate to the top for their choices and leave the rest alone ….
  22. 22. … so Oscar adapted the fee structure to charge the highest commission fees for the top entries.
  23. 23. By playing the game of placing hotels strategically in top positions and charging fat commission fees for it, Oscar produced record-breaking revenues.
  24. 24. It went sometimes at the expense of visitors like Astrid, who pay the price if margin is spent on booking fees instead of room quality.
  26. 26. Charlotte recently started at the booking site as an interaction designer
  27. 27. Charlotte likes working at the booking site because she likes traveling herself. She wants to do well to her fellow travelers, and give them access to great rooms and deals.
  28. 28. When Charlotte started working on the interaction design of the booking site, she was surprised at the rudimentary design. She wondered where the support functions were.
  29. 29. Filter functions on price and ratings Sort functions on price and rating She decided to give the site some extra functionality to reduce the cognitive burden on the consumer: sort and filter functions. The goal was to drive choices to entries towards the bottom of the page and thereby achieve a better distribution of choices.
  30. 30. Charlotte explained her work to Oscar who listed attentively first, but once he understood what the sort and filter functionalities could do…
  31. 31. … he got upset because it would disrupt his revenue model.
  32. 32. They got into a fight …
  33. 33. … but then they decided to be professional about it and they agreed on a multivariate A/B test to see the effects of the changes.
  34. 34. BACK TO ASTRID One year later
  35. 35. Meanwhile, Astrid had gotten the hang of traveling. She was now a member of a ring of celebrities of NGOs and good causes.
  36. 36. She was invited back to Istanbul for the next installment of the animal welfare conference.
  37. 37. She got to work on it straight away. Astrid went back the booking site, but now armed with more knowledge and skill.
  38. 38. She was surprised to learn that the booking site now contained functions that she used to set bottom limits for prices and ratings. After all, she was still a spoilt princess.
  39. 39. Because she really wanted to explore the city, she now also explored other amenities such as the distance to the city center.
  40. 40. Along with the brand, type and style of hotel.
  41. 41. So that by the time she went to Istanbul …
  42. 42. She knew that she would end up in a nice hotel, and she was satisfied with her choices and the way she had gotten there.
  43. 43. THE RESULTS ARE IN! Meanwhile, back in the office …
  44. 44. Of those having the functions available 67% uses sort and/or filter functions at least once across the four tasks 47% uses the filter function at least once 42% uses filter on price 27% uses filter on rating 40% uses the sort function at least once 34% uses Sort on price 11% uses Sort on rating 33% does not use the functions, not even once To see how the sort and filter functions were used, Charlotte created a plot. She learned that 67% of her visitor used the sort or filter functions; 33% did not. It was disappointing. 47% uses a filter function at least once; 40% used the sort function, so filtering is more popular than sorting. 42% filtered on price versus 27% on rating, so it is more popular to filter or sort on price than on rating. Charlotte did not know if these numbers are high or low; at least she had some benchmark numbers and time will tell.
  45. 45. 0% 2% 4% 6% 8% 10% 12% 50 47 44 41 38 35 32 29 26 23 20 17 14 11 8 5 2 Likelihood of choosing a room Positionontheresultspage Ideal situation Ideal situation Ideally, the choices of rooms would be uniformly distributed across the search result page; at 50 entries, each entry would have an equal 2% chance of being chosen.
  46. 46. 0% 2% 4% 6% 8% 10% 12% 50 47 44 41 38 35 32 29 26 23 20 17 14 11 8 5 2 Likelihood of choosing a room Positionontheresultspage Situation before redesign S&F not available Yet, before the change and the addition of the sort and filter functions, there were many people like Astrid and choices on the booking site are skewed towards the top, and surprisingly, to the bottom. At the bottom there is also an option to choose none of the hotel rooms. The visitor had to scroll all the way down to find it.
  47. 47. 0% 2% 4% 6% 8% 10% 12% 50 47 44 41 38 35 32 29 26 23 20 17 14 11 8 5 2 Likelihood of choosing a room Positionontheresultpage Sort & filter made available S&F available To her positive surprise, Charlotte observed that after she had added the sort and filter function, the distribution of choices was flatter than when they were not available.
  48. 48. 0% 2% 4% 6% 8% 10% 12% 50 47 44 41 38 35 32 29 26 23 20 17 14 11 8 5 2 Likelihood of choosing a room Positionontheresultspage If sort & filter are used S&F used The effect was strongest among those who actually used the sort and filter function: the ideal flat distribution was approximated!
  49. 49. 0% 2% 4% 6% 8% 10% 12% 50 47 44 41 38 35 32 29 26 23 20 17 14 11 8 5 2 Likelihood of choosing a room Positionontheresultspage If sort & filter are not used S&F not used The effect was offset by those who did not use the sort and filter functions, and whose choices skewed even more strongly towards the top entries.
  50. 50. 0% 2% 4% 6% 8% 10% 12% 50 48 46 44 42 40 38 36 34 32 30 28 26 24 22 20 18 16 14 12 10 8 6 4 2 Likelihood of choosing the room Positionontheresultpage All compared S&F not available S&F used S&F not used S&F available In all, Charlotte had gotten the effect that she was looking for: the distribution of choices was flatter after the redesign than before it, and the result of those using the functions, were encouraging enough to stay on this path.
  51. 51. Top box satisfaction if sort and filter are ... Not available: 56% Available: 62% Also, Charlotte was happy to learn that visitors were happier with the task after the redesign than before it. After the redesign, there was 62% top-box satisfaction, versus 56% before the redesign.
  52. 52. OSCAR STRIKES BACK But then,
  53. 53. Average room price if filter is... Not available €123 Available €116 Not used €126 Used €102 He noticed that the average price of the room booked was down from 123 Euros to 116 Euros after the redesign and the introduction of the sort and filter functions. This was due to those using the functions at an average room price of 102 Euros.
  54. 54. Use of the none option, if filter was Not available: 12% Not used: 12% Used: 17% Also, the site had started to suffer more from what we may call the empty basket syndrome: visitors leaving the site or the choice task without making a choice, or here, using the none option. It was up from 12% when the filter function was not available or used, to 17% if the filter was used.
  55. 55. WHO DID WIN? So what?
  56. 56. It is in Astrid’s favor that room choices were much better distributed across the results page if the functions were added, which could drive up the real estate value of the page. Also, satisfaction was up which may mean that visitors are more likely to come back to the site. That’s two points for Astrid. However, the average room price booked is going down and the number of people not chosing a room, goes up. Both result in a significant loss of revenue. That’s two points for Oscar.  Flatter distribution of choices  Higher task satisfaction  Lower room prices  Higher drop-out rates
  57. 57. And because we don’t know if Astrid and other people are more likely to come back to the booking site, we discount the last point for Charlotte. Based on this test, we declare Oscar the winner, much to the dismay of Charlotte and Astrid.  Flatter distribution of choices  Higher task satisfaction  Lower room prices  Higher drop-out rates
  58. 58. WHAT’S IN IT FOR YOU? Dear Colleagues
  59. 59. By bringing it to you as a story, I may have been more engaging, you may have understood the results of the study better, you may remember it better and you may be more likely to act upon it. But that’s only a part of the deal here. Dude it’s just a story
  60. 60. Stories are usually about change. It is embedded in storytelling formats: once upon a time; every day, one day, and then…, until ... The change has happened and a new situation kicks in. Stories are a great way to engage people and to inspire the change. CHANGE AHEAD
  61. 61. Change involves stakeholders, and not all stakeholders may take the change lightly because of different vested interests. Research-based stories are a good way to explore and share the implications for the stakeholders and support their informed decision making, taking everyone’s interests into account. Stakeholder the market Stakeholder, protagonist Stakeholder antagonist
  62. 62. Also, purchase environment matters a lot and can change the results of a study. In our case, it was the addition of two user interface functions, sort and filter. It is a challenge to implicit assume of conjoint analysis that the purchase environment does not have an impact. It shows that we should conduct our choice exercises in a virtual environment representative of the future environment to improve external validity.
  63. 63. This is what we do in our initiatives in which we play and experiment with e-commerce environments. We believe it is the future of conjoint to replicate consumer behavior in these kinds of environments.
  64. 64. Experiment with us Gerard Loosschilder, Paolo Cordella, Jean-Pierre van der Rest and Zvi Schwartz