Ways to kill your shopping mojo

My posting been a little sparse lately (not that I really have readers yet . . . ) because I've been taking some exciting trips.  I visited Chicago for the first time (loved it!) and am on my way to NYC (literally, I'm on the Bolt Bus as I speak, er type).

Do you know what the downside is to launching a data-analytics project for your closet before visiting those two cities?  You're surrounded by some EPIC shopping.   But you also, all of a sudden, have all this information on all the things you DON'T need.  It is however probably good for my wallet.

I tried to hide behind the fact that I haven't finished logging everything I own so technically I could pretend that I need a cashmere sweater with a key on it.  But practicality kept rearing it's ugly head. Major. Shopping. Buzzkill.

Let's move on to more positive things. Shall we? The good news is that I have actually started collecting information on my clothes.  Check back tomorrow for an update on how that process is going. (Hint: it's a lot of work)

(Data) Models

The first time I heard of "modeling" outside of the context of fashion models was in a college math class.  (Does it surprise you that I was a math minor?)  In order to satisfy my degree requirements, I had to take an elective called "Mathematical Modeling".  The class was pretty theoretical and since I had a severe case of senioritis, I didn't absorb much.  Luckily (?) for me, that wasn't the last time I came across the idea of models.  In the data world, modeling is usually talked about in the context of building databases or enterprise-wide systems.  Basically it's the concept that you need to build a blueprint of what you want your  "perfect" system to look like to use as a guide when building out your system.  You can also use it as a way to measure the performance of your existing systems.**

Now, I'm not building a database but some of the same principles apply.  If my list of questions are the road map, the "model closet" is the destination.  I know, I know I made fun of those lists that claim to be the ten or twenty essential things you need for your closet, but, in theory, they kind of have the right idea--they offer a blueprint to follow in putting together a functional wardrobe.  The problem is they aren't customized for me, or you, or anyone's (woman, man, merman, what have you) real, individual lives and needs.

So what would my "model closet" look like?  One that's customized for my unique preferences and needs? At this point I still only have a hazy idea, but I do know some of the basic criteria my ideal closet would have to follow.

1. Most of my life is spent inside an office cubicle, so as much as I love casual wear, the majority of my wardrobe should be for my 9-5 job.  On the simplest level, I need to be able to put together at least 20 professional outfits a month (5 outfits a week x 4 weeks)
2. I need to be able to transition through four, distinct seasons (maybe that means a lot of layering pieces, I'm not sure)
3. In order to get the most value out of my closet, I should probably have 2-3 tops for each bottom (skirt or pants).  That's not a scientific number, but it's a personal rule-of-thumb I apply while shopping.  

I know that's pretty basic and it doesn't really look anything like a "model" closet, but that's the dirty little secret of data modeling.  You don't have to get it right the first time.  You start with a vague idea of what something should look like and then as you learn more about your goals or process, you keep tweaking it until you get something that works ;)

**I am by no means an expert in data modeling.  If you're curious about it, this post is an excellent starting point.

Planning: Data Journeys (Continued)

 

Armed with my 6 buckets, the next step was to define the data I was going to capture under each category.  Some things were easy.  Seasons? Four of them (if we’re not counting resort wear). Boom. Stores I shop at? Quick look at my web browsing history. Done.  Then, I got to Item Type and Style and Color . . . and got stuck.  How much detail should I go into? Was it important to distinguish between a blouse and a collared button-up? Should I stick to primary colors or do I want to know how many fuchsia vs. hot pink items I owned? (Answer: one of each).  In the spirit of complete disclosure, I wasted a lot of time on this before realizing that the answer was right in front of me.   A lot of my favorite store websites had nice, user-friendly filters for the exact same things I was trying to define. If Nordstrom and Anthropologie had already done the work for me, why reinvent the color wheel? 

 

With a little tweaking and a couple of additions, voila!

Type	Style/Cut	Color	Purpose	Season	Rating	Brand/Store
Pants Jeans Shorts	Cropped/Ankle Boot cut Straight-leg Skinny Trouser/Wide-leg	Beige Black Blue Brown Green Gray Metallic Off-White Orange Pink Purple Red White Yellow Multi	Work Play Work & Play Dress-Up	Spring Summer Fall Winter	Hate it Meh Like it, Don’t Love it Wardrobe Staple Feel Like a Million Bucks	AG American Apparel Ann Taylor/Ann Taylor Loft Anthropologie Banana Republic Club Monaco Everlane Express Gap H&M J. Crew Madewell Nordstrom Old Navy Paige Urban Outfitters Zara Other
Skirt Dress	A-line Pencil Mini Maxi
Blouse T-Shirt Sweater	Cardigan Collared Button-Up Long-Sleeve Short-Sleeve Sleeveless/Tank Top Tunic
Blazer Coat

Not going to lie, my inner data-nerd is pretty excited by this table.  Probably more than is healthy. Now, I’m going to remind myself I actually socialize with people and don’t just talk to myself on the internet all day.

Planning: Data Journeys

 

So, I had my questions.  Now, I just had to get down to the nitty-gritty details of figuring out what data I actually needed to collect.  In the spirit of full disclosure, when I first started thinking about this project a few months ago, I went a little crazy. The possibilities were endless!!!! I could see how many wool items i had! how many different sizes I bought! The average age of my clothes!  This was the point where my eyes glazed over and my social life took a sharp down turn.  I had to remind myself of one of the first rules in data analytics: "Remember what you're trying to measure". 

 

With my list of core questions as a road map, I came up with 6 buckets of information:

• Item Type and Style
• Purpose
• Season
• Color
• Store/Brand
• Rating--How did it make me feel?

The first three are really key to figuring out what exactly I own and what I need.  The 4th item, "Color", is a way to see if most of my clothes fell into a single color family and to help me in putting outfits together.  The "Store/Brand" category will tell me where most of the things I buy are from.  The last category, "Rating", is something I've been doing in my head for a while.  It all started when I'd go shopping with my husband, and to help me decide if something was worth buying, he'd rate it for me on a scale from 1 to 10.  I may not always agree or follow his recommendations but it's a really easy way of seeing if you absolutely love something and it makes you feel fabulous or if you should hold off for something better. 

 

I may add additional categories or lose some of these as I go along, but they will hopefully be a nice balance between, collecting too much data (a.k.a turning into a crazy cat lady) and getting the information I actually need.

 

**in putting these buckets together, I realized that none of them deal with price, which is one of my side items.  I'm thinking that for now, I'm going to give up tracking that one.  I'm not sure that I want to can remember what I paid for every single item of clothing. 

Planning: Building a Roadmap

As anyone who has done any work in evaluations or data analysis knows, the first step in designing a project is figuring out what questions you want to answer.  Those questions become the guiding post for determining what data you need to collect.  Else you can end up with a lot of interesting "facts" or "trends" but no usable information.

 

Starting out, I had a ton of questions I wanted to answer.  The opportunities were endless! But, I realized that unless I want to give up my social life and spend the next year staring at my closet, I had to whittle the list down and make it more realistic.  (Though, without a social life I guess all I'd need were sweatpants, so problem solved!).  

 

So, here are the questions I'd like to be able to answer.  I've divided them into core questions, that represent my big picture goals, and side questions that it would be nice to answer but I can probably live with out:

 

Big Picture Questions

1. What do I actually own?
2. What do I actually wear and what do I love wearing? (conversely, what can I get rid of?)
3. Given my lifestyle (9-5 job, active, big social circle), what do I need to buy to make my wardrobe more functional?
4. What is my personal style? (not sure if this is a question data can answer for me, but we'll see!)
5. Once I have all the basic pieces, what should I be buying to make my wardrobe more me?

Side Questions--in no particular order:

1. Do I own a lot of any specific color?
2. How much do I normally spend on clothes? 
3. Are the things I spend more on, things I wear more often?
4. What brands do I buy from the most?
5. Ummm, what should I wear on Monday?

A Data Nerd's Approach to Fashion

For years, I've bought things because they were on-sale or a "good deal" or on impulse or out of desperation (i'm glaring at you pantyhose). Please tell me I'm not the first person who's gone on a shopping binge and ended up with a ton of stuff I didn't need and somehow still didn't own a white button up shirt?  And that I'm not the only woman who stands in front of a closet overflowing with clothes but often feels she has nothing to wear?  But, it's a new year and I'm on a mission to revamp my wardrobe, figure out what my personal style is, and hopefully be a smarter shopper.

I've tried using those "ten essential items" lists or "20 things every woman should own".  While helpful, those lists feel incomplete.  First of all, what exactly do I own? Secondly, what do I do with the wardrobe I have (which includes waaaaay more than ten items) and what do I need to buy (or throw out) to make it better?  Plus, what do I need aside from those first ten items to express my own, personal style?

I know . . . deep, deep questions.  Anyway, I had a lightbulb moment a few weeks ago.  In my normal life, not rambling on the internet, I analyze data.  (I know this is the moment you see me as a scary cat lady with spectacles and zero social skills. Don't worry that's a false stereotype.  Though I do wear glasses)  And, I started to think, if I can take a company's financial or personnel records and use them to tell them where they need to hire or cutback, why couldn't I use data, my own data, to be a better shopper?  Thus starts the nerdiest fashion project in the history of the world.