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So as promised I decided I would document much or most of what I’ve been doing with regards to Lavado, my new startup. Of the things I worked on this week (building a billing system, copywriting, starting out the site, creating a budget), one of the most important things was the development of my customer personas.

So for those of you who aren’t familiar with what customer personas are, and I honestly wasn’t an expert on this, you are effectively trying to paint a picture of who your potential customers are. You want to build a profile of each person because that will help you know how to market to them and segment your marketing efforts and track your ROI and all that. Prior to launch, you don’t really know exactly who your customers are ,and you might end up being surprised. So in this case with lavado, I was trying to think, who are people who would:

a. not be likely want to do their own laundry
b. not be in a situation where someone in their household is doing laundry for them
c. would have enough to disposable income in order to afford laundry service.
d. value the time savings they get by not doing laundry

What I’m building with Lavado isn’t an impulse buy. This isn’t something you just say, ‘Alright it’s not a no brainer.’ It’s pricey enough that you have to justify doing it but if you are in a certain sort of sweet spot, it actually is a no brainer. At least that’s my assumption from a time and cost perspective.

To start of our first customer persona, I’ll start looking at single males. If I’m following along stereotypes i would assume single males are the ones who are most likely to not want to do their own laundry.

So then let’s break it down to you further. ‘Single males’ is great but there are tons of them, it’s such a wide audience.

Now let’s look at single males who are between the ages of 23 and 40. Then I want to look at perhaps jobs that could afford someone the disposable income. Because single males between 23 and 40 who works at McDonalds as fry cooks are not going to be able to afford this. But some of the single males who are attorneys or doctors or bankers will be able to afford this. So I started narrowing down different jobs and see who is a good fit.

Then the next thing I start looking at was, where do these people shop? Or what activities do these people do? So I started looking at gyms and the key here is I want to look at gyms or activities that are expensive. So clearly you have a lot of disposable income if you’re spending $200/month on gym membership vs. a $10/month planet fitness membership. This test doesn’t really indicate you’re a in a position of greater purchasing power, however this is not an exact science (yet). Now we have these different factors, I can create a profile and I can look for businesses where my potential customers might be patrons.

miami real estate heatmap
Next up, I looked at different geographic attributes. So I want people who live in certain zip codes (I looked at heat maps like this to get a better idea of rental pricing)
. The reason I’m doing this to target certain zip codes is that I’m trying to roll this out in selective areas first rather than county-wide. By selecting a few zipcodes to start my trial with, I can also control the variables better and not have to drive all around town to problem solve, should that arise.

So my customer personas could be dozens and they should be dozens. Because you want to better see and accurately track who you’re targeting and why and what makes sense logically to as far as marketing through these people. Because I could very easily just try and target any male in Florida but that doesn’t really help because I’m also targeting women. There is a big sector of men and women who are used to outsourcing services; you know cleaning services, yard services, cooking services, etc.

So at the end of the day I ended up with close to 20 different customer personas. Whether or not they’re too narrow or not, that remains to be seen but we’ll find out soon enough which ones make the most sense, which assumptions were correct and which ones weren’t and whether or not I need to reanalyze or refocus my marketing campaigns.

Here is a sample of one of my personas (I’m tracking them all in Asana):
Mike the crossfitter: 24-28 year old, crossfit fan, likes paleo, bmw, and lives in 33131. There are probably only 500-1000 Mikes in this zipcode (but there are easily 20,000 people living in this zipcode so I can create 5-10 personas for this zipcode if I wanted to).

Once I have my list of personas, I can start targeting ads at them, and see which people convert more often to which ads, and hopefully hit the sweet spot of ROI on my marketing. I have zero intention of spending money on ads which don’t convert well or generate a profit.

Now there are tons of guides on how to do this more efficiently, or effectively. Here are a few:

header image credit Ogilvy