How we improve predictive accuracy
Our techniques allow us to identify the likely voting behavior of "undecideds". We sample millions of voters. We do so over long-periods of time to reduce headline and media cycle fluctuations.
unumAI predicted the most competitive U.S. Senate and U.S. House races twice as accurately (winner) than survey polling leading up to the 2020 election. In U.S. Senate races, we were correct 93% of the time compared with 58% for public, survey polls.
unumAI predicted the right winner in competitive U.S. House races around the country twice as accurately as surveys, and 4.7 times more accurate in suburban U.S House races.
Political Case Studies
|Political Election Prediction by unumAI
The 2020 election cycle included some of the least accurate predictions made by survey pollsters in the last 40 years. Biden’s margin of victory was overestimated by 3.9 percentage points, and typical polling methods systematically underestimated the degree of Republican support in the country across all elections. This was the same story that inspired unumAI, one where the typical pillars of political science and voter research could not explain Republican favor, nor how Donald Trump defeated Hillary Clinton in 2016, despite all indications saying otherwise. In the end, campaigns lack helpful data because typical polling methods used for insights on voter preference are over-priced and unreliable. For voters and the public, the perception is that polling is misleading in the best of cases and part of the corrupt systems in the worst of cases. By fixing these problems, we seek to stop an erosion of trust in the democratic process.
|September 1, 2021|
|Political Message-Testing and Messaging Strategy by unumAI
Political candidates face the challenge of positioning themselves as the person for the moment, and the art of getting elected is matching their vision for the future with what goes on during a campaign to generate voter enthusiasm. Constituent polling on topical issues is the foundation for this path to election, but this primary research through surveys and focus groups is perceived by most candidates to be over-priced and unreliable. These drawbacks impeded the Jason Crow campaign during his 2020 reelection run, when novel coronavirus entered the United States and turned research on voter preference on its head. Traditional methods simply couldn’t keep up with the rapidly evolving conditions, and systematically underestimated important republican support due to social biases.
|March 1, 2021|
|2020 Election Recap – November 2020
Analytical recap of election prediction results for competitive races unumAI made predictions on this year.
|November 21, 2020|
|2020 Selected Races – October 2020
Newsletter report of October prediction results for competitive 2020 US elections, one month before election.
|October 8, 2020|
|2020 Selected Races – June 2020
Newsletter report of unumAI June prediction results for competitive 2020 US general and primary elections.
|June 26, 2020|
|2020 Colorado Senate – May 2020
Example of unumAI’s full recommended messaging report covering Colorado’s 2020 Senate election.
|May 30, 2020|
|2020 Selected Senate Races – April 2020
Newsletter report of unumAI April prediction results as compared to surveys for competitive 2020 US elections.
|May 1, 2020|
Unum is Latin for “one” and is taken from the original United States’ motto, “E Pluribus Unum,” which translates to, “Out of many, one.” Aristotle attributes this idea of democracy to Pythagoras who says that the bonds of society, government, and politics are based on those of family and friendship.
Nobody lies to Google, but we are susceptible to lying to ourselves, to our friends and family, and to pollsters.
People lie to pollsters because they believe that their political views are private or, they don’t feel comfortable telling a stranger which candidate represents their moralistic world-view for fear of being judged.
These deceptions show up in undecided responses in survey polling. Our methodology removes “undecideds” from the equation by probabilistically predicting their voting-day intentions and behaviors by what they search for.
unumAI was 1.6 times better than survey polling in predicting the winner and was 2.95 times better than survey polling in predicting the margin between the top-2 finishers when compared to traditional polls across 2020 battleground U.S. Senate general election races.
unumAI was 2.1 times better than survey polling in predicting the winner and was 1.23 times worse than survey polling in predicting the margin between the top-2 finishers when compared to traditional polls across 2020 battleground U.S. House general election races.
For 2020 battleground House elections in suburban areas, unumAI was 4.69 times better than survey polling in predicting the winner and was 1.05 times better than survey polling in predicting the margin between the top-2 finishers when compared to traditional polls. For 2020 battleground House elections in urban areas, unumAI was 1.24 times better than survey polling in predicting the winner and was 1.05 times worse than survey polling in predicting the margin between the top-2 finishers when compared to traditional polls.
Source: Google Trends