# Forget polling, there’s a better way to predict the next president and other trends

## Internationally recognized pollster says traditional polling and analytics aren’t as effective as measuring momentum.

Analytics is the science of curiosity, and mine has always been insatiable. I’ve spent most of my career trying to predict which political candidates will go the distance, which products will surge in the marketplace, and which ideas will capture the public imagination. In short, what do people want, why do they want it, and will they still want it tomorrow?

During many years in the political arena, I relied on conventional polling and analytics. I vividly remember the moment that changed in late 2015. I was sitting on the set of a TV studio when I started to panic. I was used to sharing my predictions about candidates, but in the early months of the 2016 election season, my analytics were crashing. The numbers didn’t seem to matter. The percentages were useless. Predictions were futile. A new kind of candidate, Donald Trump, had surged onto the scene and he defied every rule of politics I knew. He was using Twitter like a Kardashian. He was embracing controversy while his opponents were avoiding it like the plague. He was disrupting every known pattern for winning an election. And it seemed to be working. How the hell did I measure his momentum?

Suddenly, the age of polling—of analysis by the survey numbers—was over. Instead, we were living in the age of momentum as a metric. I saw that most political analysts were trapped in the past, regurgitating 20th-century models—doing things the way they’d always been done. And the numbers were failing them because their reliance on statistics (mass of support) ignored what drove the momentum (velocity). A formula to quantify this was needed, which is how I came up with the momentum factor, or “MFactor,” in my analytics.

It’s based on physics, which originated with Isaac Newton:

P=M*V. Where Momentum equal Mass * Velocity.

By the time of my realization, people were beginning to notice that the conventional polling model was showing serious cracks. Polling was expensive and it was time-consuming. As methodologies switched from in-person to telephone to the internet, the process became easier, but also less reliable. Who were the people taking polls on the internet? Pollsters were losing control. But it wasn’t just the operation of polling that was less effective. It was the nature of polling. With polls, you only get answers to the questions you ask from the people you ask. There’s a time lag, during which minds can change. Most important, while polls might give you a sense of mass—the percentage of people who say they favor one candidate over another—they do not measure velocity.

In 2016, polling models predicted that Hillary Clinton was sure to win. But those polls missed the momentum factor. Clinton had high mass but low velocity. There were signs of lagging energy in the final months of the campaign, as Clinton appeared to be playing it safe. Polling models did not catch up to this. Trump’s mass wasn’t as great as Clinton’s, but his velocity was off the charts. Velocity, in turn, gave Trump enough mass to win. Analysts missed the signs that he would win because they failed to measure his momentum.

The 2016 election was a turning point for me, not just with political analytics but with a larger scope of businesses and individuals who were using a new metric of cultural relevance. Social media analytics turned out to be rich and predictive of trends. Tools were starting to allow us to measure public sentiment in politics, business, or social movements. This was a way to supplement polling, to understand what was out there, which would then inform the questions that we wanted to ask.

There’s an old saying in polling: “The most important question is the one you don’t ask.” Because after you do all the analysis, you realize there’s still something you want to know. Unfortunately, in polling, you’re limited to the data set you collected. In
momentum analytics, you can keep broadening your scope of inquiry using multiple data sources. You just have to know where to look.

Through my company, Decode_M, we’ve utilized all the analytics at our disposal while tapping into the momentum mindset. Decoding momentum is how we quantify cultural relevance. Mass becomes the volume of the conversation and velocity is the speed in which it travels, and we’re able to chart that velocity further by diving into the deeper realms of sentiment, where attitudes are more nuanced.

These metrics are predictive of the future, even when it doesn’t seem evident. We’ve always known in politics and brands that it takes several impressions to change a person’s mind. Our metric allows us to pick up the changing minds earlier in the process. The evolution of our equation, incorporating unsupervised learning and natural language processing, allows us to spot the velocity of conversation that leads to a viral surge. Then we can quantify whether that surge is just a fad and if it will soon plunge or be more tenacious.

The most important thing you have to understand about momentum is that it is constantly moving. These five drivers are what fuel momentum:

1. Polarization: Discussions powered by strong points of view, or even controversy.
2. Innovation: Create something new and/or improved in a way that creates FOMO.
3. “Sticky”: Being memorable in an unexpected way.
4. Disruption: Challenging and changing the game.
5. Social Impact: Connecting to a larger purpose.

When you use this screen in politics, you can immediately see that the old measures, such as likability or agreeing with a candidate’s position, don’t make the cut in predicting success. The same holds true with product brands.

For an example of a momentum analysis applied to an app, we can look at TikTok, the video-sharing platform. Originally labeled  “for kids” much like Vine and Musical.ly, TikTok is currently the fastest growing social media network in the world, with U.S. users increasing fivefold in a span of 18 months. The app’s rising trajectory stems from becoming the “anti” social media platform. TikTok is inclusive, authentic, encouraging participation and imperfect expression while serving content the way digital natives want it: fast, fun and unfiltered.

This is how TikTok leaned into all five of the key drivers of momentum.

1. Disruption: As Facebook and Instagram aged up into channels fit for targeting and ad campaigns, they’ve turned off users by relegating them to mere consumers. TikTok captured youth and changed the game by filling feeds with content made by amateurs, embracing meme culture and celebrating copycats in all their TikTok dance glory, making it easy for anyone to create and engage.
2. Innovation: TikTok’s lottery-style model for content promotion broke the Kardashian mold of needing influence to become influential, enabling normal high schoolers to become overnight sensations.
3. Sticky: Programmed to learn from user behavior, TikTok pulls us into a TikTok hole by serving us a nonstop stream of video clips it knows we’ll enjoy, and further elicits engagement through built-in functionality that lets us immediately imitate what we see, adding to the conversation.
4. Polarization: In contrast to social media’s curated, Insta-worthy world, TikTok has created a community free of judgment and perfection, where misfits, shy, and average people can expose their real selves, and are even celebrated for it.
5. Social Impact: By letting people from all walks amplify the life hacks, dances, stand-up routines, and silly content they otherwise wouldn’t have a place to share, the TikTok platform provides a new way for newcomers to gain cultural relevance and find success.

The challenge for TikTok will be to keep the momentum going as its awareness (aka mass) increases. Already, we’ve seen signs of stagnation as the app is absorbed into mainstream culture, and it will take much more disruption and innovation to create enough velocity to drive a new wave of momentum.

This means innovating in ways that win over the next wave of users while keeping the interest of the early adopters. Monetizing content like Facebook and Instagram might turn off users who see the site as selling out. Also, as TikTok’s content continues to
expand beyond its core creators and outside of entertainment into areas like politics, will its original audience abandon it for the next shiny new app? Or, in the social media dogfight, will the giant platforms succeed in stealing TikTok’s thunder as they battle for share of momentum?