1. Digital Marketing and Election 2016 in the US

2. EVERY CAMPAIGN IS DIFFERENT
There is no single blueprint that will always work; need to take learnings that can be applied but not as a single way forward

3. WHAT MADE 2016 DIFFERENT?

4. WHAT MADE 2016 DIFFERENT
There was a fundamental misunderstanding of the landscape of the US electorate
Assumptions made from 2012 were disproved in 2016
Multitude of candidates
Instinct to imitate Obama’s 2008 & 2012 campaigns
Different media consumption landscape than 2012

5. WHAT WE DO

6. Data Science, Behavioural Psychology, and Sentiment Analysis
WHAT WE DO + +
Data Science, Behavioural Psychology, and Sentiment Analysis
Big Data
Targeted Engagement =
BEHAVIOR CHANGE
There are three main components to our work with clients; first we have a data set of several thousand data points on individuals in the us. This is an aggregation of publicly available data that is then used as the basis of our big data work. We then work with client’s first party data as well as conduct our own vast amounts of consumer research to produce specific models and analytics for our clients. From there this data can be used by clients in multiple ways, one of which being digital marketing.

7. DATA RESEARCH ENGAGEMENT
We worked with the trump campaign in three key ways: data science, polling and research, and engagement through digital marketing.

8. CAMPAIGNS: THE ULTIMATE START-UP
When we consider a US presidential campaign, in many ways it’s the ultimate start-up – it starts from scratch with zero infrastructure and resources and is forced to go from in an exceedingly short amount of time; as this graph indicates, even faster than some of the foremost tech startups.

9. 50% + 1%
Compounding this issue is that fact that a majority of the market share must be reached; it is not enough to just produce 10%; it must be 50% +1 or it’s a loss.

10. CAMPAIGN STAGES
Campaigns generally follow three primary phases: donors – need capital and resources to build staff and invest in technology, and ultimately begin advertising. Then the persuasion portion begins; talking to key voters about issues they care about. Finally get out the vote: ensuring the those that are supporting the campaign actually show up and cast a vote for the candidate.

11. RESEARCH AND DATA
Focusing on what the research and data process looked like. Again since this was such a unique candidate and year and time and resources were scare, simple partisanship was not going to make it; we were brought in to identify what specifically a trump voter looked like and identify where they were and how to talk to them.

12. RESEARCH METHODOLOGY: RESEARCH WAVES
Friday
Saturday
Sunday
Monday
Tuesday
Wednesday
Thursday
RESEARCH
WAVE 1
DATA MATCHING
& MODELLING
RESEARCH
WAVE 2
This started with large amount of consumer research in each battleground state; collecting large amounts of responses from key voters that then were matched back into our database and became a training set for our models. The research was typically occurring in 7 day waves; this in itself is a remarkably fast turnaround due to how critical time was. While the research results were being analyzed and utilized, the research team was simultaneously out in the field conducting the next wave.
LIST MAKING & STRATEGY

13. MODELS MENU LIST PHASE 1 PHASE 2 PHASE 2-ISSUES
JUNE-JULY
AUGUST-NOVEMBER
AUGUST-NOVEMBER
Candidate specific and generic donor preference
Issue preferences
Candidate preferences (including 3rd party)
Turnout likelihood
A suite of over 20 models was produced during this time, again matching the key phase needs of the campaign; first donor models, then candidate preference, turnout likelihood, and issue preference

14. CANDIDATE PREFERENCE = DJT - HRC
SEGMENTATION
CANDIDATE PREFERENCE = DJT - HRC
TURNOUT
0.2
-0.2*
0.4
0.7
CoreTrump
Core Clinton
Deterrence
GOTV
Disengaged
Clinton
Trump
Deadbeat
PERSUASION
Such that each voter in these battleground states was scored on a scale of -1 to 1 about a few key things: their candidate preference, their likelihood to vote, and the specific issues they cared about.

15. CUSTOM TOOLKIT STATE RANKINGS PRIORITY CITIES PATHS TO VICTORY
In addition to voter contact universes which we’ll talk about next, the analytics from these models were used to assemble a toolkit that met key organizational needs within the campaign:
Priority state rankings were calculated using polling margin and number of electoral votes
Priority cities were identified combining priority state ranking and size of persuasion audience within city
Demographics and Issues were fed back to campaign to aid DJT in effectively targeting city audiences during his rallies.
Paths to Victory calculated by weighting polling distributions by the electoral college counts for each state and determining which state wins could combine to allow DJT to gain at least 270 votes.
Based on all the possible paths (winning and non) we calculated a distribution of likelihoods for different total electoral college counts → likelihood of winning.

16. ENGAGEMENT
One way in which the data was activated: digital marketing

17. TRUMP FOR PRESIDENT: DIGITAL MARKETING
MEDIA PLATFORMS
Social Platforms
Programmatic
Ad Networks
Publishers
Search Engines
AD TYPES
Video
Display
Social
High-Impact
Native
Audio
Search
DEVICES
Desktop
Mobile
Tablet
OTT
We used our ad tech ecosystem of over 30 partners from across

18. DIGITAL MARKETING PHASES
July August September October November
LIST BUILDING/FUNDRAISING
EVENT PROMOTION, VOLUNTEER RECRUITMENT, APP PROMOTION
PERSUASION
ABSENTEE/EARLY VOTING
The marketing followed a few key phases, again mirroring the overall campaign phases: list building and fundraising, activating supporters, persuasion, then voter turnout..
VOTER TURNOUT

19. INFRASTRUCTURE
Data pipelines: payment processors, web forms, databases
Reporting and tracking: ad spend platforms, analytics platforms
Data integrations: offline data onboarding, online data management
Before any of this could start, a key infrastructure issue had to be tackled: not the most glamorous start, but when an organization is moving this fast, it will be continually behind and never able to fully optimize on the results if these building blocks don’t start from the beginning.

20. PERSUASION DIGITAL MARKETING: PROCESS
Ingested data and audience profiles from the data team
Devised communications to best engage with these individuals
Executed digital ad buys across 30+ inventory sources
To translate the data science work into an actual media placement, we began a cyclical process: polling and research would be out in the field collecting hard id’s on which to train the models, matched back into the database, data science team would extrapolate the models. Wednesday night briefing – download from the week that would inform creatives and media plan

21. PERSUASION DIGITAL MARKETING: PLANNING
Sample Battleground State Briefing
Persuadable Voters: 450,000
Gender: Male - 45 %, Female - 55%
Top Issues: National Security, Jobs, Wages, Education, Taxes
In addition to the PII, the briefing would come to use like this: granular details about the location of the target audience, demographic and ethnic make up, issues they cared about

22. PERSUASION DIGITAL MARKETING: PLANNING
Sample Media Plan:
Operationally this would then become executed like this: picking media platforms

23. TARGETING METHODS STUDY
Result: net increase in lift for the same amount of budget by using multiple data-informed targeting methods
1:1
MATCHES
HYPERLOCAL
GEO
DEMO/PERSONA
Data matching: sought to challenge relying too heavily on 1:1 matches. Undertook a study to determine if for the same amount of budget, we could produce a net increase in impact by leveraging a tiered approach

24. Communicating to undecided voters
ADVERTISING PHASES: PERSUASION
Communicating to undecided voters

25. PERSUASION: NATIVE Politico Native Ads
Sponsored content pieces saw 2-4% higher engagement than display or video; average engagement time of 4 minutes
Political advertising is often boring or overly negative; sought to produce engaging content. Takes additional time and particular legal hurdles with approvals, but results showed significantly increased engagement times.

26. High-impact/interactive ads
PERSUASION
High-impact/interactive ads
High-impact interactive made a more memorable experience but also resulted in incremental data collection

27. PERSUASION: SEARCH Search Query: Trump Iraq War
Establish Facts and Messaging
Search Query: Hillary Trade
Expose Positions and Record
Search Query: Trump Economic Plan
Drive Traffic To Relevant Issue Pages
Persuasion search is a way of reaching people that are actively raising their hands for more info. A few different tactics depending on timing, and expensive to needs to be chosen wisely.

28. TESTING AND MEASUREMENT: PERSUASION
Sample studying findings:
Set up a testing sandbox to hold controls within audiences and measured change in recall, favorability, and intent to act
Tested ad formats, messaging tone, and issues
Deployed the results from the test on the general population
Each test resulted in learnings that improved performance by several percentage points

29. Acquiring email addresses, fundraising, engaging supporters
ADVERTISING PHASES: ACTIVATION
Acquiring addresses, fundraising, engaging supporters

30. PROGRAMMATIC PMP’S
Executed roadblocks, takeovers, and premium buyouts through PMP
Minimized turnaround time by over 50%
Executed buyouts and premium inventory buys programmatically to save turnaround time and allow flexibility in creative
For all buyouts, first tested with a small amount with smaller risk, then determined if it was the correct audience/timing for a buyout

31. New ad type to stand out among clutter of display
PROGRAMMATIC NATIVE
New ad type to stand out among clutter of display
In the spirit of trying everything: new programmatic ad type considered to be native.

32. TWITTER CONVERSATIONAL
Promote chatter and social engagement with pre-populating hashtags
Twitter’s conversational ads to ensure that Mr. Trump’s messages and hashtags were trending and being see in the overall chatter. The below ads generated over 30,000 uses of these hashtags during the first debate, creating enough volume that tweets using these hashtags displayed in the platform in search results for Hillary Clinton.

33. SNAPCHAT LIST BUILDING
Snapchat’s new webview ads received $2-3 CPA’s, engaging a key millennial audience
Snapchat was used a number of ways, including a national geofilfter and persuasion video ads – but also tried the new webview ads for list building. Surprising results – engaged millennials at a efficient cost

34. SUPPORTER MOBILIZATION
App installation:
Recruited nearly 100,o00 active users of the official campaign app
Crowd building:
Promoted hundreds of events online, sometimes driving crowds with a day’s notice.
Volunteer Recruitment:
Recruited hundreds of volunteers in key battleground regions to support field operations
Digital is not just for blasting people with messaging – moving to a new city – looking around for social recommendations. Campaign sought to meet people there in multiple ways to maximize resources

35. Encouraging voters to show up
VOTER TURNOUT
Encouraging voters to show up

36. Website providing individuals with voting information
VOTER TURNOUT
GOTV Ad Landing Page
Website providing individuals with voting information
Campaign and RNC had a site with voting tools powered by google civics api to help people request ballots and find polling location; was the landing page for the ads

37. Multiple ad types including mobile interstitial and search
VOTER TURNOUT
Multiple ad types including mobile interstitial and search
Multiple ad types used depending on the platform

38. HIGH SOV ITEMS: YOUTUBE MASTHEAD
YouTube Mastheads
Displayed different versions of the masthead depending on location of the site visitor
Bought out the youtube masthead on election day; since it’s a buyout it could not be audience targeted, but used location

39. TESTING AND MEASUREMENT: ACTIVATION
Ran advertising to individuals that we knew were supporters and needed to ensure they voted
Maintained an offline integration with ballot results aggregators to ingest live ballot results into ad platforms to exclude voters and follow up on individuals that had not yet turned in their ballots
Conducted offline attribution and held a control of individuals that were not exposed to the ads; study showed an incremental lift of multiple percentage points
GOTV measurement: are we actually increasing participation and spending wisely?
Lift is enough to make a significant difference considering the small margin in multiple states

40. DIGITAL MARKETING LESSONS FROM ELECTION 2016
Prioritize infrastructure: data pipelines, reporting, online data management
Invest in design talent: data can’t replace excellent content
Digital is not just messaging: meet people online for multiple reasons; not just messaging
Throw out playbook: try everything and challenge assumptions