All language subtitles for 42 - Grouping Charts - lang_en

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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:00,000 --> 00:00:01,965 Let's look at an example. 2 00:00:01,965 --> 00:00:04,110 Here is a line chart showing the average and 3 00:00:04,110 --> 00:00:08,190 median conversion rate across the year of 2016. 4 00:00:08,189 --> 00:00:10,830 As you can see from this line chart, 5 00:00:10,830 --> 00:00:16,035 the average conversion rate didn't seem to go above 0.35. 6 00:00:16,035 --> 00:00:22,454 That is 35 percent of our CRC turned into sale acquisitions on average. 7 00:00:22,454 --> 00:00:27,479 However, if you slice the data by regions, 8 00:00:27,480 --> 00:00:29,894 you see that the story is much more interesting. 9 00:00:29,894 --> 00:00:33,314 In fact, the Eastcoast region was able to demonstrate 10 00:00:33,314 --> 00:00:37,799 a higher conversion rate than 0.35, close to 0.6. 11 00:00:37,799 --> 00:00:42,140 You may even choose to contrast and compare the strategies used by 12 00:00:42,140 --> 00:00:47,020 the sales team in the Eastcoast region and apply those lessons to the other regions. 13 00:00:47,020 --> 00:00:50,425 Perhaps, they did some [inaudible] test that worked better, 14 00:00:50,424 --> 00:00:52,820 and they can be adopted in other regions, 15 00:00:52,820 --> 00:00:54,740 such as the Southwest region. 16 00:00:54,740 --> 00:00:59,480 Or you may find that it is a matter of cities within the eastern coast region, 17 00:00:59,479 --> 00:01:04,519 and the urban locations or high density of grocery stores in urban locations, 18 00:01:04,519 --> 00:01:07,414 food preferences of customers. 19 00:01:07,415 --> 00:01:12,120 All of these factors may be contributing to these differences. 20 00:01:12,790 --> 00:01:19,980 But you can only arrive at these decisions if you slice the data and look at the details. 1778

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