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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 --> 00:00:03,645 So, let's walk through the sales model using a bottom-up approach. 2 00:00:03,645 --> 00:00:06,359 I've kept the overarching themes here on the top, 3 00:00:06,360 --> 00:00:09,720 so you can see what is the motivation for each of these columns. 4 00:00:09,720 --> 00:00:14,234 We start with this column with a row for each sales team member. 5 00:00:14,234 --> 00:00:16,035 This is followed by the company, 6 00:00:16,035 --> 00:00:20,759 which is the company name for which you are going to be selling products in bulk, 7 00:00:20,760 --> 00:00:22,725 and then comes in column C, 8 00:00:22,725 --> 00:00:24,030 the units per month. 9 00:00:24,030 --> 00:00:29,940 So, this is the number of units this opportunity is likely to create a bookings for. 10 00:00:29,940 --> 00:00:34,185 Contract terms shows the number of months each opportunity is for. 11 00:00:34,185 --> 00:00:37,460 Price for all units in one month shows the number of 12 00:00:37,460 --> 00:00:40,939 units times the sales price per unit, 13 00:00:40,939 --> 00:00:42,804 which is $5 here, 14 00:00:42,804 --> 00:00:47,524 and this is showing the sales price for their projected unit over a month. 15 00:00:47,524 --> 00:00:50,225 For example, how much would Joe Smith, 16 00:00:50,225 --> 00:00:51,920 working with company A, 17 00:00:51,920 --> 00:00:56,760 bring in revenues from the sale of 4,000 units per month? 18 00:00:56,759 --> 00:00:59,750 Then you multiply that with the number of months in 19 00:00:59,750 --> 00:01:03,524 the contract term to arrive at the bookings forecast. 20 00:01:03,524 --> 00:01:07,099 We can go one step further and multiply the bookings forecast with 21 00:01:07,099 --> 00:01:11,464 the win probability to show a more realistic weighted forecast. 22 00:01:11,465 --> 00:01:13,219 So, let's look at this example. 23 00:01:13,219 --> 00:01:18,605 We're more likely to get the sales contract with Corey Jones, Company C, 24 00:01:18,605 --> 00:01:21,500 because it has a wind probability of 0.9, 25 00:01:21,500 --> 00:01:24,680 versus this opportunity with Joe Smith, 26 00:01:24,680 --> 00:01:27,890 Company A, which has a lower probability. 27 00:01:27,890 --> 00:01:33,405 So, the 290k is a weighted bookings forecast, 28 00:01:33,405 --> 00:01:38,030 which shows this is a high probability that you'll win this compared to this one. 29 00:01:38,030 --> 00:01:40,614 It takes into account the probability, 30 00:01:40,614 --> 00:01:43,159 so you can get a realistic estimate of 31 00:01:43,159 --> 00:01:46,325 how likely are we getting this amount versus the amount. 32 00:01:46,325 --> 00:01:49,880 So, this is a bottoms-up sales forecast. 33 00:01:49,879 --> 00:01:52,519 As you can see, here we're using 34 00:01:52,519 --> 00:01:59,929 an opportunity level forecast to project out the bookings for the whole company. 2899

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