Ever find yourself steeped in a productive debate only to have someone derail the fun by asking for a source, data, and numbers?
You then go and try to pull the numbers. You Google your face off. You know you’re right, but, for whatever reason, the numbers don’t exist.
Nobody is tracking them.
I have a problem with that. There is a universe of numbers out there, and I want to tell their stories.
For years, I’ve been writing on a whim. Inspired by an idea, a trend I observe as a person who’s stood watching the business and technology world from a relatively unbiased standpoint. And when a premise would strike me - and if it stuck - I’d start to look for proof. I’d look for patterns in human behavior to show a trend, or I’d talk to experts in an attempt to create solid cornerstones of “expert” opinion. And that’s fine if you’re writing fiction (which I also do, but that’s a story for another time).
For years, I covered companies, people, devices, and cultural trends, but it was always based on a hunch or on a guess as to what they were all doing or meaning. Now, I have access to hard data that shows exactly what companies and people are doing:
- Where they're opening stores
- Where they're living
- What they're selling
- What people want
- What they don't want.
- What they're talking about
- Where they're going
- What they're buying
- What they're not buying
For the first time, this vast treasure trove of data at Thinknum peels back the "guess layers" to reveal the hidden truths, the real trends, the actualities that are begging for curious minds to find them, for analytical minds to process them, and for creative minds to tell their stories.
For the first time I have the opportunity to write stories based on real, live data that’s not only accurate, but also publicly available and verifiable by anyone who wants to do so. Sure, anyone else could go and scrape all of this data, but the fact is they aren't doing it.
Now I can write a story about the northernmost place you can buy an iPhone. Or I can compare burrito prices at Chipotle Mexican Grills across the country and attempt to understand why they are the way they are. This is a dangerous place for one's endless curiosity, but that's a good thing for you, the reader.
If you are curious, if you are fascinated by fascinating things, you'll have a good time here.
This is no small operation. In fact, I have a major advantage: An entire company backing me with years of web crawling, number crunching, and the world’s best data engineers working way too many hours to normalize data and help me find the stories within the numbers. What Google did for qualitative search, Thinknum is doing for the quantitative side.
I have the opportunity to write stories based on real, live data that’s not only accurate, but also publicly available and verifiable by anyone who wants to do so.
And one could argue that the quantitative side, in a world filled with so much conjecture, half-truth, and doubletalk, is much more interesting.
So why should you care? I mean, you probably already read great reporting written by journalists who fact check and name solid sources. We’re not out to replace them. Instead, we’re here to augment them, and to tell the stories based purely on the universe’s most factual element: mathematics. In fact, we think they’ll be using us as sources to tell even deeper stories than we can. And we’re okay with that.
Math, numbers, and formulas are the universal truths. They count, they compare, they show movement. They tell stories.
And we’re here to do just that.
We’re Thinknum, and we’re about to tell the stories behind the numbers.
Methodology
We’re not re-inventing the wheel here (maybe we are a little, but it’s equally likely that whoever invented the wheel didn’t know she was doing so at the time), but we are re-inventing the way we, as journalists, come up with and follow through on stories.
Normally, a good story begins with a good idea. A hunch. A journalist sees a trend, discovers an interesting angle or source, and goes after it. That’s still the case here, but in our case at Thinknum, generally those ideas will come from the numbers themselves. Because we’re already crawling thousands of data points in dozens of industries and sectors, we’ll see patterns or stand-outs in the data that will create a chase for a story. Sometimes we’ll find something. Sometimes we won’t.
Regardless of either outcome, our methodology here will be to show our work. That is, we’ll bring you, the reader, on our journey from data discovery, to tracking, to story expansion, and to possible conclusions. However, we won’t draw too many conclusions. Our goal here is to celebrate curiosity and invite others not just into the data, but into conjecture as to what it could mean.
We’ll be the source, the inspiration, and the impartial “look what we found!” to journalists in a media world that is so focused on finding conclusions that it’s lost focus on what we here at Thinknum believe really matters: Discovery.
Every story we do will include the following:
- How we found the data
- What we did with that data to make it meaningful
- Why we thought it was interesting and/or important
- What it could mean
- How it might correlate with other relevant data
Whenever possible, we’ll also include access to the data itself so that you can verify or do with it as you please.
The Data
Thinknum crawls the web for publicly accessible data. That means that any of the data we use in our stories is verifiable to anyone with a web browser. Of course, it also means that any mistakes in the data will make their way into our stories. While we expect such instances will be rare, and we will be first to admit our mistakes, it should be known that we are at the mercy of the data we collect.
That said, when we collect data, we do regular “check backs” that assure that our numbers match those we are crawling. In cases where data is clearly skewed or if it just looks “off”, we either re-crawl or remove the data from our databases. In cases where we find numbers that are clearly off, we will skip them for the sake of journalistic integrity. That said, we’ll look into them, because sometimes those extremes are, in fact, the truth.
What’s Coming
You'll find three levels of stories at Thinknum. First, you'll get quick hits based on data we already have - stats about the retail, finance, tech, food services, real estate, and other industries. These will be simple factoids with top-level analysis and options for further reading. Consider them takeaways for discussion or ponderment on your commute or morning coffee break.
Next, you'll get what we're calling "Correlations." Like quick hits, these will be based on extant data in the Thinknum universe, but Correlations will compare two (or more) data sets to look for inverse or positive relationships, causalities, or just interesting divergences. We may also include what are called data "groups" where we mash divergent datasets together to compare things like geologics, time and events, economic indexes, or more.
Finally, you'll get the occasional "Big Feature" from us. These longer, in-depth pieces will be storytelling exercises in the history of a dataset, interviews with individuals who may (or may not) have influence on the data, and deeper analysis.
We'll also invite you to play with the data in our features as often as possible, inviting further discovery and discussion. And stay tuned for a regular newsletter once we're up and running.
And please do stick around for some deeper blockbusters that’ll knock your socks off (we just started tracking the designer-sock trend in Southeast Asia, and it’s fascinating).
Say hi. Please clap.
We'd love to hear your ideas as to what data, stories, and trends you think we should go after. If it exists in the digital universe, we can track it, trail it, and correlate it. Contact us here if you have an idea for us.
