We are all baffled by Trump’s victory. As soon the results were out, I was more than perplexed to hear many a claims stating it is just a sheer piece of creative genius or simply good luck. Do these election results just defy science, logic and data? They are right in their own sense since many big data prediction houses forecasted a Trump slump. Here’s my two or may be a few cents what it means to modern day and
business overall.
Lesson 1: Benchmarking against the best is not the end – strive to disrupt
The Trumps constantly benchmarked their performance data against the best known to validate their efforts and ensured that they are on par against Nate Silverman’s of this era. However, they didn’t stop there and just rely on the polls data and predication models around it. They pushed harder to obtain real-time information to improve their agility.
Polls data and data from multiple digital touch points were stitched together for better decision-making. Benchmarks can be met through meticulous planning and implementing known best practices; the key is to build teams that constantly learn and challenge conventional wisdom and strive to disrupt.
Lesson 2: Smaller the data set, lesser the validity – deep dive to conclude
Elections are held once in every four years and that’s enough time for new biases to be formed and the beliefs to be changed. Thus, the known age-old data may easily lose its validity as data decays over time. Few months prior to the election, pollsters ask the public about their intentions, but this becomes a daunting task as many have shifted away from old-fashioned landline phones to mobile phones - to add to the challenge today as laws prohibit cold call-ins.
The Clinton camp may have been misled with the smaller data set they had accessed or may have over relied upon this population set. In statistics, this is classically known as the population specification or the selection error, the error that results from an incorrect definition of the population or universe from which the sample is to be selected. Explore new ways of extracting information about your prospects; doing the same thing over and over will never give you different results.
Lesson 3: Inattention bias happens in business too – identify cohorts
Psychology says we all at times suffer from inattention blindness. This is because the way we are wired. We tend to focus so attentively on a single task and we fail to notice the thing that’s in front of us in plain sight. The Trump camp was smart to identify that their voters were different and they set to study them. They found that they wanted reforms across law and order, wages and immigration. More interestingly, they found out a fluctuating set of voters who were not openly admitting their support for Trump and thus it may be skewing off public polls data.
In my opinion, the Clintons suffered from inattention blindness and failed to identify many cohorts of behavior. This, in the context of this election, turned out to be one of the key differentiators. The key learnings are 1. Relentlessly look for new cohorts, build hypothesis and run test cases and don’t stop, 2. Run your strategy by people whom you trust to overcome blindness.
Lesson 4: The right call to action (CTA) drives action – involve the prospects
The campaigns, taglines, content and slogans that contain a call to action (CTA) get their prospects to think instantaneously that they are part of the message; it relates to them and makes them believe that they could take some action in this regard. This actually delivers results. E.g., Sprite says, “Obey your Thirst”. Nike gets you to “Just
Do It”.
Well-crafted CTAs allow their consumers to co-create brand meaning. Trump’s “Let’s Make America Great Again” is a well round CTA that has all the winning elements, whereas the voters themselves interpret in their own way. It ignites emotions and a clear purpose. Clinton’s “Stronger Together” is somewhat inclusive but the desired end goal is illusionary.
Lesson 5: Survey respondents are liars at least half of them – minimize lies and maximize accuracy
Survey scientists claim as much as 50 percent of people in a survey population do give dishonest responses. One reason for the incorrect predictions may have been late decisions by the group of undecided voters. “Pollsters use the word ‘undecided’ but what that really would have meant is that they are unable to articulate their preference or they may not even know what it meant. Not surprisingly this could be a case where they would have simply lied to be socially accepted or being simply defensive.
If you depend on user surveys, a lot of attention should be diverted towards minimizing lies and maximizing accuracy, technically speaking, focus on correcting the hypothetical bias. We may try specific fixes that address the fact that the respondents may incorrectly predict their future actions or not do what they said that they would do. One simple tactic that could be used is to ask people how certain they are about their answer.
Lesson 6: Personalization differentiates you from the rest – segment in real time
In this digital era, you can identify user behavior almost in real time. Plotting changes in preferences and behaviors have never been easier. Historic data, search intent, social engagement and location tracking, etc., provide us with the blueprints of our prospects. It’s critical to identify these nuances and communicate with custom-curated messages in real-time to drive impact.
Parscale, the digital campaign chief, in an interview with Bloomberg said that “only the people we want to see it, see it”. He says they strategically selected African-American radio stations and placed adverts. In San Antonio, they created a South Park-style video animation of Clinton that says “Hillary Thinks African-Americans are Super Predators.” The display ads were delivered to selected segments of African-American voters through Facebook’s unpublished or dark posts as they are popularly known.
Trump’s campaigns are a testimony to data-driven segmentation and real-time messaging. Their hyper-targeted psychological approach was simply awesome. The Trump camp used real-time dashboards of data and on the fly updated models to include unlikely Trump voters and which in fact gave them the edge to perform well in the Rust Belt - the beat Nate Silverman at his own game by simply working with real-time data than using polls data that had a week’s lag.
Lesson 7: Great teams embrace bad news more than good news – reward the messenger
Trump’s staff knew that they were losing big time. The bad news was constantly been shared and encouraged within the camp. You probably might do it if you are the underdog. This real-time non rosy picture across the board helped the entire campaign team to dig deep and uncover numerous ways to mitigating the risks. Despite the public chaos they exactly knew who they should persuade.
The team identified a near 13 million voters across 16 fiercely competitive states that they believed to be persuadable, although these numbers become smaller and smaller daily as they change their minds, Parscale claims. Never shoot the messenger; we need employees who give us the bad news. Acting upon the bad news leads to more good and sustainable results.
Lesson 8 - Always have a Plan B - which you can implement
Trump paid his own campaign money to build this granularly segmented audience sets, he now owns this data! He can use this information for any purpose that he wants to. He could even sell its access to other campaigns or use it as the launch pad for a 2020 presidential rerun. These audience segments could merrily turn out to be the one for the Trump TV network too.
The Clintons probably can buy this day and use it as their plan be (no pun intended).
Lesson 9 – Smaller the agency, bigger the agility – take bit sized risks
Today the advertising space is being disrupted technology big time, our online and offline worlds converging. Marketing is virtually redefined everyday as technology acumen and real-time flexibility are the key drivers of success. Small agencies generally are younger, faster and less indebted to legacy work flows. Be it big or a small agency, it is equally a daunting task to develop and execute campaigns.
That being said, the smaller the agency, lesser they are chained to hard coded SOPs. They tend to dive in with you, have your best interested at hand rather than pushing you to their working minimums. Your success is their success and that’s what determines their future. They juggle tasks, play multiple roles based on needs of the hour, your target audience and not try to align everything to their internally crafted workflows.
The agency that Trump worked with Giles-Parscale, Inc is an absolute small-time agency out of San Antonio, Texas. They have previously developed Trump’s property website and built the campaign website for a mere US $ 1500! With sheer dedication towards the client’s interests in mind and with the flexibility to change course as data was gathered and make dynamic changes to the campaigns and build granular segments was phenomenal.
Business executives to understand that advertising today is about marketing to segment of one! Creating breakthrough campaigns and brands requires agility and a mindset to takes risks; fail fast and change course faster. This requires business to partner with agencies that are agile and not glued to legacy practices. Take bit sized risks with small agencies; see how they commit to give a lot, give at start and let them take a lot if they deliver.
Lessons come to an end – postmortems are easy
I am sure if President-Elect Trump was his own apprentice, he wouldn’t find any reason to fire himself. This piece was easy to write and postmortems are generally flood when something unexpected is seen. The due credit should go to the Trump camp. Kudos/respect. Let me know which lessons catch your attention the most.
(Dinesh Dino is Co-Founder/Managing Director of ReapDigital, a leading digital marketing agency. He has seen it all, from IT outsourcing right up to state-of-the-art analytics in his 15-year career in tech marketing. Dino was the force behind ReapDigital’s Centre of Excellence)
