All language subtitles for 42 - Grouping Charts - lang_en

af Afrikaans
sq Albanian
am Amharic
ar Arabic Download
hy Armenian
az Azerbaijani
eu Basque
be Belarusian
bn Bengali
bs Bosnian
bg Bulgarian
ca Catalan
ceb Cebuano
ny Chichewa
zh-CN Chinese (Simplified)
zh-TW Chinese (Traditional)
co Corsican
hr Croatian
cs Czech
da Danish
nl Dutch
en English
eo Esperanto
et Estonian
tl Filipino
fi Finnish
fr French
fy Frisian
gl Galician
ka Georgian
de German
el Greek
gu Gujarati
ht Haitian Creole
ha Hausa
haw Hawaiian
iw Hebrew
hi Hindi
hmn Hmong
hu Hungarian
is Icelandic
ig Igbo
id Indonesian
ga Irish
it Italian
ja Japanese
jw Javanese
kn Kannada
kk Kazakh
km Khmer
ko Korean
ku Kurdish (Kurmanji)
ky Kyrgyz
lo Lao
la Latin
lv Latvian
lt Lithuanian
lb Luxembourgish
mk Macedonian
mg Malagasy
ms Malay
ml Malayalam
mt Maltese
mi Maori
mr Marathi
mn Mongolian
my Myanmar (Burmese)
ne Nepali
no Norwegian
ps Pashto
fa Persian
pl Polish
pt Portuguese
pa Punjabi
ro Romanian
ru Russian
sm Samoan
gd Scots Gaelic
sr Serbian
st Sesotho
sn Shona
sd Sindhi
si Sinhala
sk Slovak
sl Slovenian
so Somali
es Spanish
su Sundanese
sw Swahili
sv Swedish
tg Tajik
ta Tamil
te Telugu
th Thai
tr Turkish
uk Ukrainian
ur Urdu
uz Uzbek
vi Vietnamese
cy Welsh
xh Xhosa
yi Yiddish
yo Yoruba
zu Zulu
or Odia (Oriya)
rw Kinyarwanda
tk Turkmen
tt Tatar
ug Uyghur
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

Can't find what you're looking for?
Get subtitles in any language from opensubtitles.com, and translate them here.