Can Marketers and Analysts Learn Anything from Trump's Win?

Data wasn't dead this election. We just all took it at face value.

“Data’s alive and kicking. It’s just how you use it and how you buck normal political trends to understand your data.” A quote from Matt Oczkowski, director of product for the Donald Trump's data team at Cambridge Analytica, on how their team reworked its models according to predict a plausible Trump victory.

Not dissimilar to what we do everyday as marketers, we try to keep a pulse on our customers and the industry. The good news is that there is no shortage of information that is now publicly available. Traditionally we were reliant on specialized research organizations like the Nielsens and ComScores of the world, but now EVERYONE has data. Which gives us access to the validation that we need to choose this media vendor, target this audience or launch in this market. Similar to what we saw from all the polls, this is the same type of study that projected an almost certain Hillary Clinton victory.

Often in this age of intelligence, however, we are now victims of the data that is thrown in our faces. Whether that is success metrics in case studies, demographic data or estimated impressions, we are left to trust the numbers. Most of these can traditionally hold up in major markets where the saturation and quick turnaround makes it easy to get quantifiable results or statistical significance. But in reality this only accounts for a small subset of our total population that may not hold true.

My work through the years has afforded me a glimpse into working with brands that aren't just in major metros, but operate stores in the most rural areas where populations are under 2,000. As we found during the election, in aggregate there is a massive amount of population that isn't as accessible but has massive potential. What I have learned is that it takes a great deal of work to understand and use data that can be truly impact the work that we do - and project results.

It's easy if you can afford to hire a company like Cambridge Analytica or if you have a department dedicated to dissecting this information and extracting insights. But, for most of us, it comes down to asking the right questions and doing some leg work on our own. Here are a few tips:

1. If you don't already, collect as much unique and aggregate customer data as possible across all touchpoints so you have a benchmark for your brand and target customer. At a baseline, this means requiring tracking, tagging all of your efforts consistently and building out [or purchasing] a CRM that can handle this information.
2. Always ask for the details behind the numbers. That means getting access to as much information as is available, like methodology, respondent details, media spends and targeting information. For example, it's easy to say a product received 50,000 app downloads, but they never tell you that is was backed by a $500k media buy. If you can, always get the raw data set that you can manipulate yourself.
3. Do the work! Put it through your brand's lens. Once you have the information, you need to align it with your audience, goals and projections for the business. Only then can you realistically understand if can potentially be successful. This might mean looking at it differently than everyone else, the same way Oczkowski's team successfully re-evaluated the model.
4. Don't ignore small data sets that, when combined, can be impactful.
5. If you don't have the right data, go get it.

As disappointed or happy as each of you might be this morning, there's always something that we can learn and apply moving forward. I hope this gives you a different way to analytically digest a very emotional night for all.