Crunching Leaves… And Numbers

It’s Fall, soon to be Winter. For some people that means pumpkin spice lattes, or snuggling by the fire, or decorating for Christmas.

For me, it means leaves. Lots and lots of leaves.

This weekend, we raked. I raked. My wife raked. The kids… well, they didn’t rake, but they helped compact (i.e., jumped in) the piles of leaves. I raked our driveway four times – four times! – this weekend alone.

Small Business Customer Data Analysis

Not that raking is awful. It’s easy enough to do, burns a few calories, and gives my mind a chance to shift into idle and just wander where it wants to. This weekend, as I slung leaves around and hauled bags to the curb, my brain was chewing on a data analytics issue I was working on for a client.

Yes, I’m a nerd.

Anyway, I stopped to stretch and happened to look up just as a gust of wind blew, and hundreds more leaves drifted down onto the lawn I’d just raked. On a different day that might have been enough to make me realize the futility of what I was doing, and just go inside and watch TV. But this particular day was different. My mind was on data, and as I watched all the leaves fall to the ground, it seemed a beautiful analogy.

I’m in the business of data. I help my clients understand what data they have, what data they need, how to get it, and what it all means for their business. As I meet with clients of all sizes and in all industries, I’m consistently struck by two things: how much data they have at their disposal, and how little they generally do with it. And I don’t mean that in a critical way — as I looked around at the ground covered with leaves, with more falling every second, and even more still drooping from the branches above, I could relate to the temptation to just go back inside and ignore it all. But we can’t ignore it. Just like the leaves in my yard, there’s data everywhere. And letting it sit there won’t do anyone any good.

So I kept raking. And as I did, I realized that two of my strategies for data analytics were serving me well.

2 Ways a Small Business can Utilize Customer Data

  • The perfect is the enemy of the good. If I decided that my front yard had to look perfect, I’d never be able to put down the rake. I’d never get the job done, so I’d never move on to more important things. When it comes to raking, I don’t try to get every leaf. If I don’t get everything in one pull of the rake, so be it. Same goes for customer data. You can spend 8 hours a day trying to perfectly align the data you have about your customers, and never get back to the rest of your job. Or you can identify the point where good enough is good enough, and stop when you get there. That’s not always easy to do, but it’s important unless you have unlimited time and/or money.
  • You don’t have to do everything to do something. I didn’t set out this weekend to rake the whole lawn. I wasn’t even sure I’d get done with half of the front lawn. But I knew I needed to do something about all those leaves piling up, and I knew that any work I did now was concrete progress even if it felt like one step forward, two steps back. The same goes for data analytics. Baby steps are fine. You don’t have to start by connecting all your different data sources. You don’t even have to start by knowing every piece of data you have. But you do have to start something, or you’ll keep falling behind.

You can’t open a business magazine anymore without reading about Big Data. And Big can be overwhelming. So don’t think Big.

Think Small.

Don’t try to solve all your problems at once. Just pick something, one thing. Look at your web analytics to see where most of your new visitors are coming from. Or do a SurveyMonkey survey and invite your customers to share their feedback with you. Or look at your sales data to see which types of products are commonly purchased together. Or look at your biggest spenders and see what you can learn about them based on the products they buy.

You’ve got the data. What are you waiting for? Jump in!

Take steps to understand and use your collected customer data

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