Colored Goodwill tags

Results: Cost vs Retail

Logo small6 November 2014

Six months later, as of the first of November this year, I have accumulated more than I need but here is a summary of the finer items of clothing:

Name Suits Coats Overcoats Shirts Pants Ties Total
Armani 7 15 11 14 27 74
Bill Blass 2 2 2 2 5 12 25
Brioni 1 2 1 1 2 7
Burberry 2 2 3 3 10
Canali 4 1 2 7
Christian Dior 2 4 4 1 16 27
Ermenegildo Zegna 2 15 13 5 27 62
Givenchy 1 5 6
Gucci 1 7 8
Hermes 13 13
Hugo Boss 5 1 11 3 7 27
Valentino 2 1 1 11 15
Versace 3 3 6
Yves Saint Laurent 1 10 11

I will update the graph to show you the comparison of the approximate 1,250 items I have purchased in all total.

2 December, 2014

A major goal was reached this past weekend. It is incredible the mark up in the price of some clothing. For example, a pair of pants I purchased for $3.49 retails for a whopping $900 per pair. Don’t believe me? Click on this link for the pair of Brioni pants I located.  What a nice find. It is items like this that have increased the price for the retail vs what I pay to 64 times the Goodwill price. Just don’t tell them!

Following is the updated chart to show that for less than $5,000 I have closets full of clothing with a retail value that just went over $300,000.

A major goal has been reached!
A major goa



5 May 2014

I wanted to share with you the data to support why I created this site. Is it worth your time to visit your local Goodwill stores?  Read this article and decide for yourself. Your results, should you fall victim to this exercise, will be different depending upon other variables in your locality.

The chart below shows the current, May 2014, expenditure and retail value of merchandise if purchased new. My expenditure is shown as the red line ($2,176.31), the suggested tagged price at Goodwill is the blue line ($3,978.92) and the suggested retail price (new) found on the Internet is the green line ($89,275.82). I use a spreadsheet to keep up with a lot of detailed data to support my conclusion here.

May 2014 chart

The spreadsheet has a summary sheet pulling from a number of categories broken down into individual category sheets as follows: suits, suit jackets, overcoats, shirts, sweaters, pants, ties, hangers, shoes, pocket squares, accessories, and then one for everything that is a single copy of all items purchased in chronological order. The numbers don’t match up exactly due to duplication errors but they are close enough to present my case. I am now paying 55% of the tag price due to taking advantage of the 20% off coupons, half off every other Saturday, half off colored tag days, 25% off for teachers on Sundays and $1 tag Thursdays. You would expect my savings to be greater than 55% but I have learned that if I really want an item, I had better put it in the buggy right then and there and pay the full price which was still a great savings. Too many times I have returned the next day to find the item I wanted gone. Following is the Summary of all of the items to this date. The data is calculated from the original numbers for each item in its individual category sheet.

May 2014 Summary

In order to offer you more detail as to how I come up with these numbers, the Suits sheet below illustrates how I get the numbers shown on line 6 above. The updated numbers are automatically carried over to the Summary and updates the information as I purchase different items. With this amount of data I can derive certain patterns of which items are quickly purchased and which are less desirable. As an example, the valley Goodwills are naturally good places to find high quality winter clothing. The snow birds come here to spend their remaining days and find that they can clean out the cold weather overcoats they brought from Alberta and Minnesota. Not much need of this article in Arizona.

May 2014 suits calculations

Trends: Taking the information from the price tag, description of the item, and other bits of information you can come up with some helpful trends to follow. The spreadsheet is especially good for this but sorting on the different columns generated. I can tell which items are most sought after, to some extent, by the number of days they are left on the racks or shelves. I subtract the day provided on the tag the item was put on the floor from the day purchased. This gives me the “On Rack” in column Q. Notice that the Towncraft suit I bought for a dollar was on the rack for 30 days vs the Burberry suit I grabbed that had been available since the day before. I was lucky to find the $2,300 suit for the half price of $9.98. I have a link on the price to the web page where I found this price should anyone question the numbers in that cell. It’s always good to reference your sources.

Having the “Value” of an item helps differentiate one of demand/quality vs excess/junk. This isn’t always the case but is a good yardstick to let you know that, for example, the Valentino suit ($2,295) might be a name worth looking for over the more prevalent Jos. A. Bank suits ($650). I was not familiar with the name Bardelli but bought it since it was made in Italy but more importantly that the material came from Ermenegildo Zegna. Found that it commanded the same price as the Valentino. It’s all a learning curve but the more you know, the better the decision you can make thereby keeping your closet a bit more lean of good, quality clothing.

I have also found that certain manufacturers fit me with one size a little larger or smaller than normal. This shows up in the spreadsheet and lets you know that at a glance what to look for since the clothes are sorted at the Goodwill by size. You don’t have to waste as much time in the changing room trying on clothes if you know what fits with what manufacturer. On that topic, be sure to look in the other size racks as some clothes are not tagged correctly or customers will hide what they want later in an area you would not expect to find it.

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