In my last Lip Destash post, I talked about how I characterized the RGB values of all my lipsticks. RGB is what I know when it comes to classifying colors. When I was much younger, I used to do a lot of bbcode for online forums, and part of what I would do involved using RGB codes not just to change the color of text but to create a “color gradient” with text. I felt at ease using RGB for this project because I understand it.
I’m sure many of you reading this know something about RGB. It stands for Red, Green, and Blue, and it’s essentially just a scale for how much of the three basic colors go “into” the color you’re looking at. Essentially, if a color has a high value for red, the color looks more red. If it’s high in red and blue, it will look purple. Red and green look more yellow. Green and blue is a cyan color… and all colors can be represented by some combination of red, blue, and green. However, we are dealing with quantities now, not just the quality (reddish, bluish, greenish).
Facts about RGB:
- Each component (red, green, and blue) are on a scale from 0-255. The value shows how much of that component is in your color
- The higher the number, the more of that color there is.
- 0,0,0 is black, and 255,255,255 is white.
- The higher the highest number is, the brighter the color will look
- If you up the other two as well, the color gets more white.
When we start to look at quantities, you will most likely find you do not have any colors that are equal to each other completely. Under RGB, there are 16,777,216 possible colors. It’s highly unlikely to get an exact dupe match, especially considering that this whole thing is fairly imprecise. So how do we determine dupes?
Consider this image.
Do you see all the purples? If you look closely, they all look slightly different, but for practical reasons, they’re about the same. Perhaps one looks more muted, or maybe it looks slightly cooler. However, if you owned these 6 colors as lipsticks, you’d probably realize that you only need one of those colors.
All of these purples have red, green, and blue values that are +/- 10 points away from each other. If you don’t believe me, test it yourself, but I made this image myself! The first four in that cluster are actually only about +/-5 away, and the two squares have more difference to them. Even, though, when each component differs by 10 points, the color is not radically different. This +/- 10 “pattern” is the foundation for this dupe test.
Everybody sees color a bit differently, and for some cases, you may want to widen or narrow the pattern. In some instances, I expand my search to +/-10 or I may narrow it down a bit. This isn’t supposed to find Perfect Dupes. This is supposed to find products with seemingly similar colors so you can then swatch all of them together.
So the next big step in the process: organize your data.
Step 6: Sort Your Data by RGB
- First, select your whole chart. You can select the headers or you can leave them out, but don’t select the whole book, just the data you’ve entered.
- Under “Data,” there is a button that says “Sort.” Click it.
- You’ll get a pop-up similar to the image above. Find the column you want to sort by- I recommend sorting by Red first- and order it from Largest to Smallest. If you included your header in your selection, check “My data has headers.” If not, uncheck the box. If you included headers, your columns will be named by the headers. If not, your column will be named by a letter (Column A, B, C, D, etc)
- I recommend you sort by Values, Largest to Smallest. Click “OK.”
- All your lipsticks should now be sorted by Highest Value of Red. But we aren’t done sorting yet.
- Next, select data that is within your “pattern” for the Red value. Here, I am doing Red between 241 and 231. I chose NOT to select my header this time because sometimes you will be sorting mid-chart, and it’s not feasible to always have the header.
- Sort this data in the same way, but use your BLUE (not red) to sort, largest to smallest.
- You can do this for several different “pattern groups.” I usually like to find where there are more natural breaks. You’ll be coming back to this step many times, though, so don’t worry about getting through your whole list.
Step 7: Analyze your data in search for dupes- colors that are within your “pattern.”
- The initial sort that we just did in step 6 was more of a “help yourself do 7.” By sorting/organizing our data, it’s much easier to find data points that fit. Here’s an example of the selection I did above.
- You can see here that I’ve found a few “dupes.”
- The Nat Repub #05 and elf Dewy Berry have values that are very close- the same R value, only off by 1 in for Blue, and only by 6 for Green.
- The next three (with red ink near them) show that NYX Respect the Pink and Hikari Peony (yes, I mistyped it into my spreadsheet) are even closer- they’re almost the same color. Now, right below you see LOC Punchline. This is very close in Red, is within 10 in Green, but is 11 off for Blue. This is a possible dupe- and you can choose to “accept” it into the group or not.
- The next pair of dupes: NYX Life’s a Beach and SMLC 33. These are compared in blue.
- You’ll notice there are two there, Heimish 04 and L’oreal 111, that are marked in black. These are not dupes and it does not appear that I have any “close dupes” for these lipsticks. The Heimish color has too high of a blue value to fit with Life’s a Beach and SMLC 33, but it’s green is too low to fit in with any other category.
- Depending upon your collection, it may be wise to categorize “dupe groups” by number or letter. For instance, I could call the highlighter group “A,” the red group “B” and so on. This may be better than trying to highlight them different colors.
This process takes a lot of time, so work on it at your own pace. Lip destashing is not a race, and neither is this process. I’m currently still in this process myself. Once I’m done, I’ll go into Step 8, which is the “dupe group swatch” step!
Now, I mentioned in my first post that I honestly prefer using HSV values instead of RGB… what if you used HSV? The process for HSV is very similar. HSV is a different way of classifying color, though. I’m currently in the process of converting my RGB to HSV, and once I get that done, I’ll walk you through how to use HSV to find dupes instead (note: it’s actually easier, IMO!)