I don’t care which party you belong to or if you belong to no party, I think it’s pretty clear our political modeling is very broken. The recent Georgia runoffs have illustrated that yet again. Many who have typically championed the use of polling in elections are finally beginning to realize that there are problems, even admitting that election modeling is broken. Yet, they are still charging ahead in the belief that big data all by itself is the way of the future.
This is silly in a couple of different ways. One is simply that on one hand, they are saying that their techniques are fundamentally broken and on the other that they know exactly how to fix it using the exact same kind of information they currently don’t know how to use. Another is that they seem to be relying on the idea that they just need more data, as though merely having more data will solve problems. As stated, that is a rather silly notion. If all you have is bad data, it doesn’t matter how much you have, it’s still bad and will lead you to bad conclusions. It also helps if you know what to do with it. Otherwise, piles of good data don’t help you anymore than piles of bad data.
How so? Often polling sizes are extremely small. A sample of one or two thousand is taken to represent a population of millions. This is totally ridiculous. There is no way that kind of sample can be truly representative. For one, it is very tempting to do your survey in a limited area. And while no area is truly monolithic in its voting patterns, it’s well known that cities tend to vote one way and everywhere else another. If you over sample a particular geographic region then you are going to overrepresent one point of view while underrepresenting the other. Even if you try to sample over a large area, it’s still hard to consider such a poll accurate unless the sample size is much more significant. There is also the fact that different political inclinations will affect whether or not a person will even talk to the pollsters. Conservatives in general are much less likely to even talk to most pollsters, which creates a massive deviation in the polls.
What about knowing what to do with certain data? One of the things that polling agencies have been doing is looking at local shopping habits to predict how a given area will vote. The idea would seem to be that if lots of people are in the line at the local Starbucks, then they will be voting for the Democrat and all the people at Cabela’s will be voting Republican. Certainly that fits into stereotypes. Yet, if you are trying to be accurate in your polling then you need more than stereotypes. After all, republicans also drink coffee (even from Starbucks) and Democrats have even been known to go hunting and fishing on occasion. That person ordering the tofu wrap with the long hair may be walking out to a pickup with a couple cattle panels in the back. The neighbor who just loaded half a dozen guns into the back of a minivan for a day at the shooting range may be more at home sitting in the corner of a coffee shop eating a scone while reading Voltaire. Individuals are much more complicated than what one or two shopping preferences could ever entail. You simply can’t make accurate predictions based on these kinds of models. To really develop an accurate election model, you need to be able to get down to the individual level. What motivates a person to vote a certain way, or at all? If a person has voted for one party the last fifteen years but suddenly switches, the why is incredibly important.
How does a pollster develop this kind of connection and collect this kind of data? Through TARTLE of course. A pollster can sign up with us and connect with people willing to share their political preferences and go into why they think one policy might be better than another. Such information could be particularly useful to pollsters or campaign managers, both of whom are interested in determining what messages resonate with which voters. The kind of connection that TARTLE offers could also be a great help to those interested in forming a different party, one looking to deal with the concerns of most people, rather than trying to get people to care about the things the party is most concerned with.
What’s your data worth?
The recent Georgia runoffs have illustrated that yet again. Many who have typically championed the use of polling in elections are finally beginning to realize that there are problems, even admitting that election modeling is broken. Yet, they are still charging ahead in the belief that big data all by itself is the way of the future.
Speaker 1 (00:07):
Welcome to TARTLE Cast with your hosts, Alexander McCaig and Jason Rigby. Where humanity steps into the future and source data defines the path.
Alexander McCaig (00:24):
Jason.
Jason Rigby (00:25):
Yes.
Alexander McCaig (00:25):
We've had Deflate-gate with the Patriots. We've had Pizza-gate.
Jason Rigby (00:32):
Yes.
Alexander McCaig (00:32):
We've had Champagne-gate on The Bachelor. We've had, and we're moving into, there's going to be a Data-gate.
Jason Rigby (00:39):
There's a Data-gate.
Alexander McCaig (00:39):
I guarantee it.
Jason Rigby (00:40):
There is.
Alexander McCaig (00:41):
When politics gets involved, there's going to be a Data-gate.
Jason Rigby (00:44):
Well, we're having an interesting situation happen right now. So the Georgia Senate run-off is really big and it's happening right this minute.
Alexander McCaig (00:52):
And I want to stipulate, I don't carry a political party.
Jason Rigby (00:56):
Yeah, yeah, same.
Alexander McCaig (00:58):
At all. I don't know jack about politics. I just know how to bring out value in human beings. That's about it, right?
Jason Rigby (01:09):
Personally, I can't lock myself into a party, and I think that's most Americans, I would say majority Americans...
Alexander McCaig (01:15):
Jason, that would be separative.
Jason Rigby (01:16):
Yes.
Alexander McCaig (01:16):
It would be devolutionary to do something like that. And it forces someone to be the other.
Jason Rigby (01:22):
Yeah, exactly.
Alexander McCaig (01:22):
It's like political racism.
Jason Rigby (01:25):
Yeah, exactly. And just to be able to say, "Well, I'm this, and so I agree with a hundred percent of all this, yeah."
Alexander McCaig (01:31):
Nonsense. I'm too flexible for that. I'm like Gumby.
Jason Rigby (01:34):
So the Georgia Senate runoff is huge because it's going to decide whether the Republicans or Democrats, who has the majority. From this one Senate runoff.
Alexander McCaig (01:45):
Are you talking about in the house?
Jason Rigby (01:46):
Yeah. So Georgia Senate runoff using predictive analytics and big data properly.
Alexander McCaig (01:50):
Okay.
Jason Rigby (01:51):
So that's the title, right? Now, I want you to listen to the next sentence.
Alexander McCaig (01:57):
Using it properly. Operative word.
Jason Rigby (02:02):
So, that title, pretty conservative, sounds great and stuff. Listen really close to this.
Alexander McCaig (02:07):
Please.
Jason Rigby (02:08):
Are you ready?
Alexander McCaig (02:08):
Yeah, Alex Jones me on this.
Jason Rigby (02:11):
Even though election modeling as it is currently practices broken, we remain firm believers in the overall power of big data and predictive analytics when done properly.
Alexander McCaig (02:22):
Can we stop for a second? Everything we've been telling the public, all of our polling is a broke system. We still use it. And we are believers, and the word believer is an operative word because belief, says that you don't know the facts.
Jason Rigby (02:41):
It's that televangelist.
Alexander McCaig (02:43):
Yeah. It's the televangelists and they tell you how to think.
Jason Rigby (02:45):
CNN or Fox News. Televangelists.
Alexander McCaig (02:47):
Yeah and we're like, "Wow, we really feel that big data's going to solve polling." Having swaths of data does not solve your broken political system.
Jason Rigby (02:56):
Especially if you run it through a pollster's mentality. Because you can make data, you know as well as I, this is simple. I can make data say whatever I want.
Alexander McCaig (03:05):
You can manipulate it.
Jason Rigby (03:05):
We were just looking at data for TARTLE, with age groups.
Alexander McCaig (03:09):
With age groups.
Jason Rigby (03:10):
Right, and saying who signs up the most.
Alexander McCaig (03:12):
And we'll tell everybody our age bracket for majority of our users run from-
Jason Rigby (03:14):
It's like 18 to 35.
Alexander McCaig (03:15):
18 to 35,
Jason Rigby (03:18):
Some of those conversions, now we can manipulate that all we want, we can turn around and say, "Well, the conversions of the 18 year olds that are only 18 and they really don't matter and they're more susceptible dah, dah, dah, dah, dah. And somebody that's 45, that 45 year old is worth far more." And then we can get into lifetime value of how many packets are sold per age group.
Alexander McCaig (03:37):
Exactly.
Jason Rigby (03:38):
We can shift it however we want.
Alexander McCaig (03:40):
We can pitch that story however.
Jason Rigby (03:41):
And that's what these two parties-
Alexander McCaig (03:43):
Are doing.
Jason Rigby (03:44):
Are doing. Yes.
Alexander McCaig (03:45):
So if you really want to evolve politics, if you want to really evolve polling and policy research, politics, those people are put in place to speak for the people.
Jason Rigby (04:01):
Yes.
Alexander McCaig (04:02):
So if using a broken system that you're saying is representative of the people, red flag.
Jason Rigby (04:08):
Yes.
Alexander McCaig (04:08):
If you're putting policies together on a broken system, another red flag. The way to fix that is to go and discuss or purchase data directly from the individuals.
Jason Rigby (04:20):
Yes.
Alexander McCaig (04:20):
Not aggregate polling centers or any of that other crap I'm talking about, you can have a direct data connection with all of the people in the United States while they're at home, in the office, on the subway, you name it.
Jason Rigby (04:31):
Dude this is how it's so fucked up. Pardon my French. But that's what it is.
Alexander McCaig (04:36):
Bleep.
Jason Rigby (04:37):
This is how bad it is. They are looking at the pollsters were looking at, when they're getting data, collecting data in this article I was reading, they were getting data off of shopping patterns and deciding if they're Republican or Democrat. There is no way in hell, bro. You know me, there was no way in hell that they could take my shopping data and say that I'm this or that. My shopping data is so screwed up.
Alexander McCaig (05:02):
I think one pertinent example is, did that gentleman go in Cabela's? I know he's a right winger. You know what I mean?
Jason Rigby (05:08):
Why is this guy going into Cabela's has a Prius.
Alexander McCaig (05:10):
Yeah.
Jason Rigby (05:11):
And then he walks out with the gun.
Alexander McCaig (05:12):
Yeah I go to Cabela's, and I got my Subaru with all the rugged tires on it, I did have long hair and I'd just go waltzing in. And they're like, "Well, what are you going to get?" "Well, I don't know. Maybe I like looking at the weaponry."
Jason Rigby (05:26):
Yeah. You were looking at a bow.
Alexander McCaig (05:30):
Yeah. I was looking at a bow.
Jason Rigby (05:32):
And you don't even hunt, but you like to shoot archery.
Alexander McCaig (05:34):
I just like to shoot archery. So what do you think I'm going to go out there and start knocking down some deer, some big elk?
Jason Rigby (05:39):
Yeah. So it's like, "Well, Nope." Yeah. So here's a guy going into, Bella's looking at a bow that drives a green Subaru for us. And now you're going to try to label him off of your shopping data.
Alexander McCaig (05:50):
I got two cattle dogs in the back, am I a farmer?
Jason Rigby (05:52):
Yes. Yeah. Exactly.
Alexander McCaig (05:53):
Not a chance. Do I have any cattle? No, but I do love them.
Jason Rigby (05:56):
You can't go off of shopping data. That's what they were going off of.
Alexander McCaig (05:59):
What a ridiculous algorithm to go through and say, "Oh, this is defining how a person is." Stop defining people without having a direct connection to that person.
Jason Rigby (06:09):
Yeah. So this is interesting. We believe this silence, because they're talking about-
Alexander McCaig (06:12):
Believe. I can't stand the word believe.
Jason Rigby (06:16):
They're talking about this Senate runoff. That's really important right now in Georgia, but these pollsters and data scientists are all being silent right now.
Alexander McCaig (06:23):
Why does pollster just sound like Satan, it's like a nasty negative thing?
Jason Rigby (06:28):
Yeah. And there's only a percentage of it actually is. The silence is especially shocking given that the Senate majority hangs in the balance. So it's the Senate. We believe this silence reflects a larger reality that people have given up on the polls and that the loser in the election for many, was neither Trump nor Biden, but data science and particularly the field of social data science."
Alexander McCaig (06:47):
That, you know where social-
Jason Rigby (06:48):
That's the loser, they're saying.
Alexander McCaig (06:49):
That's the loser? Social data science is the key driver of everything. You know what the loser was? Their ability to facilitate proper social data science.
Jason Rigby (06:57):
Yes.
Alexander McCaig (06:58):
Why? Because they're not using the proper avenue. There's one avenue to do something like that. It's not sending a hard piece of mail to someone, that's at an address that they're no longer at. Okay. It's not doing something in a newspaper. It is not putting an advertisement on TV.
Jason Rigby (07:13):
But you're not understanding the cinema of the people. When you look at Trump and Clinton, the reason Trump-
Alexander McCaig (07:18):
Trump and Clinton?
Jason Rigby (07:19):
Yeah. Remember when it was Trump Clinton 2016?
Alexander McCaig (07:21):
Back in the day. Yeah. Thank you.
Jason Rigby (07:22):
Yeah. So there was an underlying, and we all know this, everyone knows this, the polls got it all wrong then.
Alexander McCaig (07:28):
They still got it wrong.
Jason Rigby (07:29):
They had Clinton as a landslide. But everybody knows there was something up. Everybody knows this, I don't care if you're Democrat or Republican. Everybody was like, there's something kind of suspicious about Hillary. I just, she didn't resonate with the people.
Alexander McCaig (07:43):
She didn't resonate with the people and her policies didn't resonate with them because she never connected with them.
Jason Rigby (07:48):
And they're like, "Well, I saw this guy. He's kind of an asshole but he seems like a business guy. So yeah let's try him."
Alexander McCaig (07:55):
Let's try him.
Jason Rigby (07:55):
Yeah. That's what happened.
Alexander McCaig (07:56):
They had no idea. And you know what kills me on CNN from a data aspect? They're showing the electoral votes and it says 22% accurate.
Jason Rigby (08:03):
Mm-hmm (affirmative).
Alexander McCaig (08:03):
I'm sorry, what? You have 22% accuracy across the United States. We don't have a proper system involved. With TARTLE. You're going to know exactly who's going to get voted before even one person goes into a voting booth.
Jason Rigby (08:16):
Yes.
Alexander McCaig (08:17):
That's changing political research. If you're trying to institute a policy, that's going to affect a lot of people, ask the people before you institute that policy or before you say something stupid on TV, right? You don't want-
Jason Rigby (08:29):
Yeah. And they say this, "For the general public, at least the counts of it being off are substantially less problematic than being off by a lot." We disagree. So this is the Jerusalem Post that says this. We disagree. Accurately taking the nation's temperature from a small sample is important to the smooth working of democracy.
Alexander McCaig (08:45):
Small sample? That is, it is so ridiculous. We are so interconnected.
Jason Rigby (08:51):
Right.
Alexander McCaig (08:52):
When you say, "I only need to take a small population sample to represent everyone." Bad idea.
Jason Rigby (08:57):
Yes.
Alexander McCaig (08:57):
Represent everybody and have them... well sample everybody and have them represent themselves.
Jason Rigby (09:02):
Yeah. Predictive analysis with small samples, you're going to be at 22% then.
Alexander McCaig (09:06):
You're going to be at 22% stop, how many times do you and I have to say stop guessing?
Jason Rigby (09:10):
Yes.
Alexander McCaig (09:11):
If we're all trying to elevate each other, elevate politics, elevate research, data science, social data science.
Jason Rigby (09:16):
Right.
Alexander McCaig (09:16):
That requires everybody's collective effort.
Jason Rigby (09:19):
Well, I mean, not only that, you are looking at misallocated donations, you're looking at-
Alexander McCaig (09:25):
Misallocated advertisement funding. And that's a huge one.
Jason Rigby (09:29):
Yeah. What if you're in an area, let's say you're in the Hamptons and it's primarily blue, but you take a small section. And so now with COVID, here's what's happened, a lot of wealthy people have purchased or are leasing homes in the Hamptons and got out of the city.
Alexander McCaig (09:45):
Or they're just leave and go to Denver.
Jason Rigby (09:47):
But they're temporary, they're not residents of Hampton, but you're a local official and you do a small poll. Next thing you know, you're getting wrong aggregated data.
Alexander McCaig (09:57):
It's completely inaccurate.
Jason Rigby (09:58):
Yes.
Alexander McCaig (09:58):
You want to know why? Because you didn't know the behaviors of people and you didn't purchase the data from them directly to understand what's going on.
Jason Rigby (10:04):
Are you a long time residents of the Hamptons? How long have you owned your home for?
Alexander McCaig (10:09):
Are you permanent? Temporary? Where's your home? How much did you spend on it? There's so many things.
Jason Rigby (10:12):
Now let me, okay you don't qualify for this. Next.
Alexander McCaig (10:15):
Great.
Jason Rigby (10:16):
Yeah. Okay. You do. Okay there we go.
Alexander McCaig (10:18):
Think about how efficient all of our efforts become and democracies inefficient, because we have a bad job of aggregating people's voices and views. Even though it's designed to be slow and inefficient, you can make everything else efficient around it in terms of what decisions should be made.
Jason Rigby (10:33):
Right.
Alexander McCaig (10:33):
You don't have to speedily make the decision, but at least you can lead yourself in a proper direction that aligns with the United States as a collective.
Jason Rigby (10:40):
Yeah. Have you voted in the last three elections?
Alexander McCaig (10:43):
No. Why did you go out and vote in this one?
Jason Rigby (10:45):
Yes. Yeah. So easy.
Alexander McCaig (10:48):
That why is so important.
Jason Rigby (10:49):
We talked about that. We talked about that yesterday. The why.
Alexander McCaig (10:54):
Yeah. If you don't have the why, you don't know.
Jason Rigby (10:56):
Right.
Alexander McCaig (10:57):
Why is the real reason.
Jason Rigby (10:58):
Yeah. And there's a great Ted talk by Simon Sinek.
Alexander McCaig (11:02):
Start with why.
Jason Rigby (11:03):
Yeah. Start with why. And I think if you're a business leader, you need to watch that if you haven't or if you haven't read that book.
Alexander McCaig (11:08):
Well, it's hysterical because, he does a Ted talk and he writes a book on it and it's just so fricking obvious.
Jason Rigby (11:14):
Right, yeah.
Alexander McCaig (11:17):
When I talk to other business individuals, I will ask them why? It's like, "Why are you interested? Why do you want to do this? What's driving you?" Once you get the why's, then you can go the what, the where, and the how.
Jason Rigby (11:29):
Right.
Alexander McCaig (11:29):
Why, that's the real juice on the matter. Or even of yourself, you have your own self reflection, why am I doing what I'm doing? I don't know. I'm confused.
Jason Rigby (11:38):
It's extremely simple. If you can answer the why.
Alexander McCaig (11:40):
Yeah. Answer the why. And a why can be answered for all 330 million Americans.
Jason Rigby (11:45):
Yes.
Alexander McCaig (11:46):
At tartle.co. So if you want to be on the bleeding edge as a politician or political research, the only way you can do that by using tartle. You're not going to use it with Qualtrics, yoursurvey.com, newspapers, advertisements on TV, or calling people to ask them what their flavor is.
Jason Rigby (12:02):
Yes.
Alexander McCaig (12:02):
Right, or sending them some sort of hard mailing. It just doesn't work. And if you want to do it efficiently at an extremely low cost for a lot of people, tartle.co.
Jason Rigby (12:12):
Tartle.co. T-A-R-T-L-E.co.
Alexander McCaig (12:15):
Thank you. There we go.
Jason Rigby (12:16):
Thanks Alex.
Speaker 1 (12:24):
Thank you for listening to TARTLE cast with your hosts, Alexander McCain and Jason Rigby, where humanity steps into the future and the source data defines the path. What's your data worth?
