• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • Articles
  • News
  • Events
  • Advertize
  • Jobs
  • Courses
  • Contact
  • (0)
  • LoginRegister
    • Facebook
    • LinkedIn
    • RSS
      Articles
      News
      Events
      Job Posts
    • Twitter
Datafloq

Datafloq

Data and Technology Insights

  • Categories
    • Big Data
    • Blockchain
    • Cloud
    • Internet Of Things
    • Metaverse
    • Robotics
    • Cybersecurity
    • Startups
    • Strategy
    • Technical
  • Big Data
  • Blockchain
  • Cloud
  • Metaverse
  • Internet Of Things
  • Robotics
  • Cybersecurity
  • Startups
  • Strategy
  • Technical

Obama Changed The Political Campaign With Big Data

Dr Mark van Rijmenam / 4 min read.
January 25, 2013
Datafloq AI Score
×

Datafloq AI Score: 64

Datafloq enables anyone to contribute articles, but we value high-quality content. This means that we do not accept SEO link building content, spammy articles, clickbait, articles written by bots and especially not misinformation. Therefore, we have developed an AI, built using multiple built open-source and proprietary tools to instantly define whether an article is written by a human or a bot and determine the level of bias, objectivity, whether it is fact-based or not, sentiment and overall quality.

Articles published on Datafloq need to have a minimum AI score of 60% and we provide this graph to give more detailed information on how we rate this article. Please note that this is a work in progress and if you have any suggestions, feel free to contact us.

floq.to/b37qV

During the 1,5 year prior to the Election Day in November 2012 in total over $ 1.5 billion was collected and spent during the Obama campaign. In addition, over 1.000 paid staff worked on the campaign, 2,2 million volunteers and in total more than 100 data analysis who ran more than 66,000 computer simulations every day. The objective of the campaign set out by Jim Messina was to measure everything. The idea was to demand data on everything that happened during the campaign in order to measure everything and ensure that they were being smart about everything.

One Metric

During a webinar organised by HP Vertica, Chris Wegrzyn – Director of Data Architecture of the DNC, explained that in order to do this, they had defined three major ways to influence the campaign:

  1. Registration: increase the amount of voters who were eligible to vote;
  2. Persuasion: Convince voters to vote for Obama;
  3. Turnout: Increase the turnout on the actual Election Day.

Each potential swing-state voter would be assigned one number, ranging from 0-100. There were four different scores based on the three different ways to influence:

  • The likelihood that they would support Obama;
  • The prospect that they would show up at the poll;
  • The odds that an Obama supporter who was an inconsistent voter could be nudged to the polls;
  • How persuadable someone was by a conversation on a particular issue.
  • This metric would be at the heart of the campaign and would influence the message send to a swing-state voter.

Fragmented Data Sources

In order to effectively manage all this during the campaign they divided the campaign team in different channels:

  • The Field channel (actively approach voters in the field);
  • Digital channel (focusing on recruitment of staff and volunteers and fundraising);
  • Comms / Press (focusing on the persuasion aspect);
  • Media (persuasion by buying media time);
  • Finance (fundraising).

The problem with these different channels was however, that all data was also managed fragmented and that an overview was difficult to achieve. That was when big data made its appearance in the campaign.


Interested in what the future will bring? Download our 2023 Technology Trends eBook for free.

Consent

During the previous campaign they had learned a lot already regarding new technologies and usage of social media and now it was time to move forward. The new technologies used in 2008 and analytics captured during that campaign allowed them in 2008 to build an unprecedented massive efficient measurable program and as such were all field staff evaluated based on data entered. From the introduction of new technologies and a data focus in 2008, it was now time to move to data modelling and deep analytics. In 2012 the objective was to build an analyst driven organisation and an environment for smart people to freely pursue their (data-driven) ideas.

Three Dimensions

The DNC determined three dimensions to focus upon:

  • Volume: according to big data standards, the amount of raw data they had, was small. They had under 10 TB to start with, but because they led their analysts pursue their data-driven ideas they created a tenfold of this in a short time frame.
  • Variety: there were many sources of data; much of it was new to the DNC. Because of the short time span, they did not have time to build ETL processes to bring it all together nicely.
  • Velocity, the data analysts, staff and volunteers created new data at high-speed and that needed to be taken care of.

MPP Database

In order to cope with all this they decided to use a MPP Database, a Massively Parallel Processing database built by HP Vertica. They used this because of familiarity and simplicity, as it uses an SQL Model. It has a high-speed performance, it is stable and it is very scalable, meaning it could easily grow with the needs of the DNC.

On top of this they had built a positive feedback loop, so that the engineers could build on top of each other. This proved to be a powerful tool and it led to unexpected innovations. Such as that potential voters could receive tailored news information on a topic they had said to be interested in when a volunteer had come by their house. Such an email would have been sent by the local field agent to keep things personal. This was all done automatically.

In the end, the decision to move to big data was a very good and once again, just as Obama did in 2008, the campaign changed the playing field and raised the bar for future campaigns. What will happen to the massive amounts of data collected is yet unclear. The Washington Post reported earlier that other Democratic candidates are eager to use that data for their own campaigns, however it is unclear whether the DNC has sufficient resource (financial and technological) to manage and maintain all data produced.

Categories: Big Data
Tags: campaign, Data

About Dr Mark van Rijmenam

Dr Mark van Rijmenam, CSP is a leading strategic futurist keynote speaker who thinks about how technology changes organisations, society and the metaverse. He is known as The Digital Speaker, and he is a 5x author and entrepreneur.

Primary Sidebar

E-mail Newsletter

Sign up to receive email updates daily and to hear what's going on with us!

Publish
AN Article
Submit
a press release
List
AN Event
Create
A Job Post

Related Articles

The Advantages of IT Staff Augmentation Over Traditional Hiring

May 4, 2023 By Mukesh Ram

The State of Digital Asset Management in 2023

May 3, 2023 By pimcoremkt

Test Data Management – Implementation Challenges and Tools Available

May 1, 2023 By yash.mehta262

Related Jobs

  • Software Engineer | South Yorkshire, GB - February 07, 2023
  • Software Engineer with C# .net Investment House | London, GB - February 07, 2023
  • Senior Java Developer | London, GB - February 07, 2023
  • Software Engineer – Growing Digital Media Company | London, GB - February 07, 2023
  • LBG Returners – Senior Data Analyst | Chester Moor, GB - February 07, 2023
More Jobs

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital engineer engineering environment experience future Google+ government health information machine learning market mobile news public research security services share skills social social media software strategy technology

Related Events

  • 6th Middle East Banking AI & Analytics Summit 2023 | Riyadh, Saudi Arabia - May 10, 2023
  • Data Science Salon NYC: AI & Machine Learning in Finance & Technology | The Theater Center - December 7, 2022
  • Big Data LDN 2023 | Olympia London - September 20, 2023
More events

Related Online Courses

  • Oracle Cloud Data Management Foundations Workshop
  • Data Science at Scale
  • Statistics with Python
More courses

Footer


Datafloq is the one-stop source for big data, blockchain and artificial intelligence. We offer information, insights and opportunities to drive innovation with emerging technologies.

  • Facebook
  • LinkedIn
  • RSS
  • Twitter

Recent

  • 5 Reasons Why Modern Data Integration Gives You a Competitive Advantage
  • 5 Most Common Database Structures for Small Businesses
  • 6 Ways to Reduce IT Costs Through Observability
  • How is Big Data Analytics Used in Business? These 5 Use Cases Share Valuable Insights
  • How Realistic Are Self-Driving Cars?

Search

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital engineer engineering environment experience future Google+ government health information machine learning market mobile news public research security services share skills social social media software strategy technology

Copyright © 2023 Datafloq
HTML Sitemap| Privacy| Terms| Cookies

  • Facebook
  • Twitter
  • LinkedIn
  • WhatsApp

In order to optimize the website and to continuously improve Datafloq, we use cookies. For more information click here.

settings

Dear visitor,
Thank you for visiting Datafloq. If you find our content interesting, please subscribe to our weekly newsletter:

Did you know that you can publish job posts for free on Datafloq? You can start immediately and find the best candidates for free! Click here to get started.

Not Now Subscribe

Thanks for visiting Datafloq
If you enjoyed our content on emerging technologies, why not subscribe to our weekly newsletter to receive the latest news straight into your mailbox?

Subscribe

No thanks

Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

Marketing cookies

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!