Grouping rows based on keywords and summing the associated total amounts

Hi all,

First of all, you guys are always so insightful and helpful here -- thank you so much! All of my excel knowledge is due to the helpful folks around here and I cannot express my gratitude enough. OK so this next problem I have is a little bit confusing, and so I apologize for the confusing title (I am not sure what the best way is to describe my issue). Here it goes:

I am pulling all my data from a database of different projects that have different (but similar) descriptions -- each project corresponds with a total amount. I would like to group all of the similar projects together into one and sum their corresponding totals. So for example, lets say this is the data:

	A	B	C
1	Date	Project Description	Amount
2	2/2/2015	Amazon ServiceType Service Restack Design California (123)	5,000
3	1/30/2015	Amazon Warehouse FDC Florida (8910)	10,000
4	3/25/2015	Amazon Typical Description Goes Here Random (1YN0)	5,000
5	3/3/2015	Nordstrom Typical Description Goes Here Random (50BN)	8,000
6	3/3/2015	US Food and Drug Administration Typical BUT DIFFERENT NOW Description Goes Here Random (LL6)	10,000
7	1/15/2015	Banana Republic Description Goes here Test (WEB51)	850
8	4/13/2012	Nordstrom Typical Description BUT DIFFERENT A Goes Here Random (50BN)	3,000
9	6/10/2015	Nordstrom Typical Description but different B Goes Here Random (50BN)	6,000
10	5/8/2015	Amazon Warehouse FDC Florida (8910)	15,000
11	10/17/2013	Banana Republic Description Goes Here But it is less (500)	200
12	10/16/2014	US Food and Drug Administration Typical Description Goes Here Random (200006)	10,800
13	9/18/2011	Cabelas Description Goes Here Typical One (BY10)	15,000
14	11/24/2014	Amazon ServiceType Service Restack RANDOM DESCRIPTION Design California (123)	17,500
15	8/4/2014	US Food and Drug Administration Typical Description Goes Here Random (Lot9)	5,000
16	10/15/2013	US Food and Drug Administration Typical Description Goes Here Random (Lot9)	8,000
17	2/13/2015	US Food and Drug Administration Typical Description Goes Here Random (Lot500)	3,000
18	5/1/2015	Cabelas Description Goes Here Number 1 (Random87)	900
19	2/5/2015	Cabelas Description Goes Here but It is less than 20,000 (LOL)	1,200
20	5/28/2015	US Food and Drug Administration Typical Description Goes Here Random (Lot9)	5,000

So above is an example of how the data I'm working with looks like. I have changed the dates/descriptions/amounts for illustrative purposes. I would like to group all projects that have receipts that total over $20,000 when grouped together. So in this example, the final product would look like:

	F	G
1	Client Name	Total Amount
2	Amazon	52,500
3	US Food and Drug Administration	41,800

So the "Total Amount" (column G - second table) is the sum of ALL of the values in the "Amount" column (Column C - first table), and it is grouped by client name -- the client name is usually the first word of the
"project description" (Column B - first table)but it is sometimes the first five words as is the case with "US food and drug administration" since this client name is 5 words long. Also "banana republic" would be an example of a client name that is 2 words long.

Also if the sum of all the values in the "Amount" column is less than 20,000, then I do not want it to be included, which is why only Amazon and the US Food and Drug Administration show up in the second table. The sum of the amounts for Nordstrom, Cabelas, and Banana Republic are all less than 20,000.

Nordstrom: 17,000 (since 8,000 + 3,000+ 6,000 = 17,000)
Cabelas: 17,100 (since 15,000 + 900 + 1,200 = 17,100)
Banana Republic: 1,050 (since 850 + 200 = 1,050)

Thus Nordstrom, Cabelas, and Banana Republic are not included in columns F & G.

I hope this request makes sense. Right now the way that I have been doing it is sorting the data manually by "project description" (Column B), and just summing all the project amounts that have similar project names. But this gets very tedious when I have 6000 rows of data to go through. You guys have always been so incredibly helpful here, I look forward to your amazing insights!