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How to Use Comparisons to Find & Tell Stories in the Data

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In this ‘How to’ webinar Ray Poynter looks at the way comparisons can be used to help you find and communicate the story in the data. Whenever we compare time periods or compare the views of different groups we are using comparisons. When a retailer explains that 40% of their revenue is generated during the 8 weeks around Christmas and New Year, they are highlighting the importance of these 8 weeks by making a comparison with the rest of the year.

This webinar is a part of a series of How To webinars.
See the whole series at: http://newmr.org/events/2018/how-to-webinars-videos/

This webinar was live on 6th February 2019.

Published in: Education
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How to Use Comparisons to Find & Tell Stories in the Data

  1. 1. How to use comparisons to find and tell the story in the data Ray Poynter NewMR Please Wait – The Webinar will begin shortly
  2. 2. Agenda 1.  Example 1 2.  Key learning points 3.  Example 2 4.  Review 5.  Questions and Answers
  3. 3. How Tall Are the Petronas Towers in Kuala Lumpur? Image: By Ali Zifan - Own work; Used data from Emporis.com, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=41356641 452 metres The internet tells us that the Petronas Towers are 452 metres tall. But do we have a real sense of what 452 metres looks like?
  4. 4. How Tall Are the Petronas Towers in Kuala Lumpur? Image: By Ali Zifan - Own work; Used data from Emporis.com, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=41356641 452 metres These comparisons give a better sense of how big the Petronas Towers are.
  5. 5. How Tall Are the Petronas Towers in Kuala Lumpur? Image: By Ali Zifan - Own work; Used data from Emporis.com, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=41356641 452 metres Tokyo SkyTree Adding in the Tokyo SkyTree gives a comparator that helps a Japanese audience appreciate what 452 metres looks like. 634 metres
  6. 6. Avoidable Deaths Per 100000 of population - 2012 Eurostat - http://goo.gl/r2q526 Deaths that could have been avoided, if people had exercised, drank less alcohol, stopped smoking and followed advice.
  7. 7. Avoidable Deaths Per 100000 of population - 2012 Eurostat - http://goo.gl/r2q526 Comparison 1, Women versus Men
  8. 8. Avoidable Deaths Per 100000 of population - 2012 Eurostat - http://goo.gl/r2q526 Comparison 1, Women versus Men Comparison 2, sorting the data from highest to lowest Eastern Europe, the old Soviet block
  9. 9. ITU Mobile Phones Per 100 People   2010 2011 2012 2013 2014 2015 2016 2017 Australia 101.7176 105.8239 106.6434 107.7288 106.7534 108.2793 110.0521 112.6886 Cambodia 56.9635 94.6286 129.2907 134.8927 133.9288 134.3668 126.3484 116.0421 China 63.1734 72.1219 80.8723 88.8862 92.5173 92.4809 97.2521 104.5817 Fiji 81.1582 83.8440 98.3073 105.7622 98.9129 108.2723 116.2363 114.1814 Hong Kong, China 196.3458 216.4354 230.6025 237.4339 235.7260 230.8188 240.7962 249.0243 Indonesia 87.1213 101.6679 113.2915 124.2805 127.6139 131.2928 147.6640 173.8402 Japan 95.9046 103.3117 109.8912 115.2554 123.1687 125.4618 130.6103 133.4504 Korea (Rep. of) 102.4507 105.5526 107.3514 108.9928 113.7039 116.4871 120.6797 124.8645 Malaysia 120.4409 128.0291 141.6663 144.7652 148.6323 143.5530 139.3678 133.8798 Myanmar 1.1843 2.4600 7.3149 13.2801 55.9072 78.2268 95.6532 89.8458 New Zealand 107.7788 109.0901 110.1675 105.5002 111.6780 121.3558 124.4413 136.0019 Philippines 88.7156 98.8579 105.2771 104.4095 111.2123 115.8497 116.2376 110.3956 Singapore 145.5308 150.5849 153.0576 157.4027 148.7388 148.7391 150.4805 148.2402 Thailand 106.7216 114.6881 125.3052 137.7235 141.9184 149.9353 173.7771 176.0347 Viet Nam 126.1072 142.3556 145.5732 135.2335 147.1157 128.5904 127.5261 125.6177 Here is data showing mobile phones per head of population. The decimal places obscure the message. Source: ITU https://www.itu.int/
  10. 10. ITU Mobile Phones Per 100 People Sorting is one type of comparison. ITU Phones per 100 2010 2011 2012 2013 2014 2015 2016 2017 Hong Kong, China 196 216 231 237 236 231 241 249 Thailand 107 115 125 138 142 150 174 176 Indonesia 87 102 113 124 128 131 148 174 Singapore 146 151 153 157 149 149 150 148 New Zealand 108 109 110 106 112 121 124 136 Malaysia 120 128 142 145 149 144 139 134 Japan 96 103 110 115 123 125 131 133 Viet Nam 126 142 146 135 147 129 128 126 Korea (Rep. of) 102 106 107 109 114 116 121 125 Cambodia 57 95 129 135 134 134 126 116 Fiji 81 84 98 106 99 108 116 114 Australia 102 106 107 108 107 108 110 113 Philippines 89 99 105 104 111 116 116 110 China 63 72 81 89 93 92 97 105 Myanmar 1 2 7 13 56 78 96 90
  11. 11. ITU Mobile Phones Per 100 People Indexing allows us to compare changes over time, in combination with sorting. Indexed on 2010 2010 2010 2011 2012 2013 2014 2015 2016 2017 Myanmar 1 100 208 618 1121 4721 6605 8077 7586 Cambodia 57 100 166 227 237 235 236 222 204 Indonesia 87 100 117 130 143 146 151 169 200 China 63 100 114 128 141 146 146 154 166 Thailand 107 100 107 117 129 133 140 163 165 Fiji 81 100 103 121 130 122 133 143 141 Japan 96 100 108 115 120 128 131 136 139 Hong Kong, China 196 100 110 117 121 120 118 123 127 New Zealand 108 100 101 102 98 104 113 115 126 Philippines 89 100 111 119 118 125 131 131 124 Korea (Rep. of) 102 100 103 105 106 111 114 118 122 Malaysia 120 100 106 118 120 123 119 116 111 Australia 102 100 104 105 106 105 106 108 111 Singapore 146 100 103 105 108 102 102 103 102 Viet Nam 126 100 113 115 107 117 102 101 100
  12. 12. Comparing with a fixed case We can compare with a fixed case, e.g. the mean, the total, or a particular country or region. Note most countries below the mean. ITU Phones per 100 2010 2011 2012 2013 2014 2015 2016 2017 Hong Kong, China 196 216 231 237 236 231 241 249 Thailand 107 115 125 138 142 150 174 176 Indonesia 87 102 113 124 128 131 148 174 Singapore 146 151 153 157 149 149 150 148 New Zealand 108 109 110 106 112 121 124 136 Malaysia 120 128 142 145 149 144 139 134 Japan 96 103 110 115 123 125 131 133 Viet Nam 126 142 146 135 147 129 128 126 Korea (Rep. of) 102 106 107 109 114 116 121 125 Cambodia 57 95 129 135 134 134 126 116 Fiji 81 84 98 106 99 108 116 114 Australia 102 106 107 108 107 108 110 113 Philippines 89 99 105 104 111 116 116 110 China 63 72 81 89 93 92 97 105 Myanmar 1 2 7 13 56 78 96 90 Mean 99 109 118 121 127 129 134 137
  13. 13. Charts – less data, more clarity This comparison shows Japan is very similar to the mean. And this has not changed over time. 0 20 40 60 80 100 120 140 160 2010 2011 2012 2013 2014 2015 2016 2017 携 帯 電 話 Mobile Phones Per 100 People Japan Mean
  14. 14. Which countries are most similar/different? For every country we can measure the distance in terms of phones per 100 people per year. ITU Phones per 100 2010 2011 2012 2013 2014 2015 2016 2017 Hong Kong, China 196 216 231 237 236 231 241 249 Japan 96 103 110 115 123 125 131 133 Japan - Hong Kong -100 -113 -121 -122 -113 -105 -110 -116 Squared 10,088 12,797 14,571 14,928 12,669 11,100 12,141 13,357 Sum 101,652 Square root 319 Distance 319 Note, the slides for downloading will have notes on this formula and how to create the values in Excel.
  15. 15. Which countries are most similar/different? By sorting the distances we can compare the countries. Distance from Japan Distance Japan 0 Korea (Rep. of) 21 New Zealand 22 Philippines 34 Australia 39 Indonesia 46 Fiji 48 Cambodia 54 Malaysia 64 Viet Nam 69 Thailand 75 China 87 Singapore 101 Myanmar 223 Hong Kong, China 319
  16. 16. Which countries are most similar/different? Charting the data makes the comparison with Hong Kong and Myanmar even clearer. Distance from 日本 Distance 日本 0 Korea (Rep. of) 21 New Zealand 22 Philippines 34 Australia 39 Indonesia 46 Fiji 48 Cambodia 54 Malaysia 64 Viet Nam 69 Thailand 75 China 87 Singapore 101 Myanmar 223 Hong Kong, China 319 0 50 100 150 200 250 300 350 Korea (Rep. of) New Zealand Philippines Australia Indonesia Fiji Cambodia Malaysia Viet Nam Thailand China Singapore Myanmar Hong Kong, China Distance from Japan, in terms of number of phones per 100 people from 2010 to 2017
  17. 17. Comparing with key countries Once you have found the story, select the comparisons that help tell your story. You cannot and should not show everything. 0 50 100 150 200 250 300 2010 2011 2012 2013 2014 2015 2016 2017 携 帯 電 話 Mobile phones per 100 people Hong Kong, China Singapore Japan Myanmar
  18. 18. Key Points 1.  Most values are meaningless on their own •  A comparison provides a context for comprehension 2.  Choose comparisons that create light •  Usually items the audience is familiar with 3.  Create comparisons from the data •  Sub-groups (e.g. male vs female) •  Sorting •  Differences and Similarities 4.  Use comparisons to help tell the story •  Japan is similar to the mean •  Hong Kong and Myanmar are very different to Japan These four steps highlight how we can use comparisons to help find and tell the story in data.
  19. 19. What research tools are examples of Artificial Intelligence? •  NewMR study •  305 responses •  66% say that Chatbots in market research are an example of Artificial Intelligence •  Is that a high number or a low number? You can see more about this study at http://newmr.org/artificialintelligence2018/
  20. 20. Which Market Research tools are AI? Compare Chatbots to other MR tools and it is the highest. 66% is a high score in this context. 13 6 8 16 18 45 53 58 66 None of the above Survey dashboards Cluster analysis Webscraping tools Adaptive conjoint interviews Text analytics software Automated sentiment analysis Automated facial coding Chatbots % Saying Yes, this is an Example of Artificial Intelligence
  21. 21. What everyday items are AI? Chatbots are comparable to Siri and Alexa – so 66% is a high number. About one-in-eight say nothing on the list is AI. 13 9 31 33 36 57 66 68 70 None of these Bank ATM Sat nav route planning Number plate recognition Robot vacuum cleaners Facial recognition at immigration Chatbots Alexa Siri % Saying Yes, this is an example of Artificial Intelligence
  22. 22. Example from ESOMAR Congress 2018 Time comparison – prices are falling. Key Markets versus Global – differences disappearing 0 5 10 15 20 25 30 2010 2012 2014 2016 2018 Median Price USA $ 000s Simple U&A, N=500, No analysis/presentation Online KM Online KM Key Markets •  USA •  UK •  Japan •  Germany •  France
  23. 23. Using Images to Make Comparisons Before and After
  24. 24. Using Images to Make Comparisons Compare value, one red ‘worth’ more than three greens
  25. 25. Using Images to Make Comparisons Framing the ‘just right’ option Too Big Too Small Just Right
  26. 26. Using Images to Make Comparisons Use comparators that make sense
  27. 27. Good and Bad Swimming Pools Usually ‘an Olympic-sized swimming pool’ is a poor comparator
  28. 28. Good and Bad Swimming Pools Usually ‘an Olympic-sized swimming pool’ is a poor comparator They ‘explained’ “So just how much rain is 10 trillion gallons? Well, we crunched the numbers and figured out that's enough to fill 15 million Olympic-sized swimming pools. Or it's enough water for you to take about 581.4 billion showers.”
  29. 29. Good and Bad Swimming Pools But there are exceptions – especially when shock is used, where the comparison does not meet our expectations. Answer: All the gold ever mined by humans would fit in three to four Olympic-sized swimming pools.
  30. 30. Key Points 1.  Most values are meaningless on their own 2.  Choose comparisons that create light 3.  Create comparisons from the data 4.  Use comparisons to help tell the story
  31. 31. Thank You Ray Poynter NewMR Follow me on Twitter @RayPoynter Connect with me on LinkedIn linkedin.com/in/raypoynter
  32. 32. Q & A Betty Adamou Research Through Gaming Ray Poynter NewMR
  33. 33. Becoming a NewMR Patron •  Patreon, supports creative endeavours, by pledging a small sum each month. •  You earn thanks and can access additional goodies. •  For example: •  $1 a month ‘Thanks’, our thanks and being listed as a supporter •  $10 a month ‘In the Loop’, includes our monthly list of 3 things to read •  $25 or $100 a month, ‘In the Know’, which adds consultancy with Ray Patreon.com/NewMR
  34. 34. NewMR 2018 Sponsors Communication Gold Silver

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