Why did Trump Win the Election?

Igor PauletičInbound Marketing, Sales

Well, I don’t really know the answer to this question, but I do know his campaign used people that specialize in capturing data on the audiences he addressed. These specialists used sophisticated methods to segment the “ears,” so they could hear the version of the story they liked the best. They used Facebook not only as a source of demographic data, but also as a source of user behavior data: based on the data obtained, they created psychographic profiles of individual voters, whom they addressed through personalized content. To simplify, they did this merely by analyzing individual Facebook profiles and of course the model defining an individual’s “character” based on his or her likes. A similar approach is also said to have been used by Brexit supporters. Much has been written about Cambridge analytica providing assistance in both cases.

We can have the most influence with people we know pretty well

Marketing seems to be increasingly turning into a skill in managing (publicly available) data. In contrast to just a few years ago, when marketing campaigns were still shaped according to data obtained from doing business with existing clients and using their demographic data and business registers, and when we were targeting people within companies, now everything has been turned upside down.

Trump won the election with the help of his voters’ Facebook likes. Click To Tweet

Just as it’s already pretty much taken for granted that a successful B2B campaign demands expanding the company data obtained from public registers with contact information on people holding key positions in these companies, it will soon also be taken for granted that in order to design a campaign successfully we also need to start collecting and processing data on these people’s behavior in the social media and elsewhere on the publicly accessible internet. So we can start approaching them within a better context than we have so far. If we know what’s currently happening to individuals and where they are located, we can personalize (and automate) communication with them so that it has the best possible effect on their engagement. If we know their intent, our marketing messages can be significantly more effective and, first and foremost, more precise.

New data collection, segmentation, and marketing campaign methods

According to IBM, by the end of 2017, the volume of data available on any one of us will have increased by nearly 100%. Unfortunately, more than 80% of this data is unstructured and hasn’t been very useful so far. But times are changing and computer cognitive skills (machine learning or Al) now also help us collect and interpret such (huge amounts of) data. Technology that is already being used commercially (but is not yet available to a wider circle of Slovenian companies) can predict people’s characters, their areas of interest, hobbies, social circles, and the interests they share with others within their social circle. If we’re active enough in social media and leave many digital footprints behind, computers know us better than our own partners and families, let alone coworkers.

For the time being, I’m still taking all of this with a grain of salt. We’re definitely moving in this direction, but we still need some time. Especially a small country like Slovenia. Slovenian is spoken by only two million people and even the most advanced technologies currently understand only seven world languages.

We’re definitely gradually entering the era of new-generation marketing engines.

Over the past five years, FrodX has implemented more than seventy marketing automation systems. All of them are based on collecting data on the visitors to their own “digital backyards.” They thus collect data on the visitors’ behavior on the websites and in the emails and advertising campaigns of our individual clients. Based on the data on their activities, the system automatically launches actions that either serve more relevant content to an individual visitor (automatic emails, personalized website content, and so on) or alert the seller when to take action or how to approach an individual customer because he or she has already been sufficiently warmed up. This is a practically indispensable tool if we want to make content marketing more effective and, first and foremost, measurable in terms of sales results. Nonetheless, this approach has certain problems that marketing technology providers would like to solve.

Current marketing automation systems are too slow for transactions that demand instant buying decisions. Click To Tweet

The key problem is that every visitor who makes a first contact with a website is treated as a total stranger and so quite a lot of time and visits are needed to get to know him or her better. With activities that require a long buying decision process and include several participants in the buying decision, this doesn’t present a major problem. But it is a problem in cases that require instant buying decisions or where providers don’t want to build a long-term relationship with their customers through regular marketing activities.

Current marketing automation systems operate by introducing a cookie to the device upon first contact, which enables us to track the activities on that device. When the first conversion is made (for example, by completing a form to access premium content), this cookie is also connected with the user’s identity. In practice, this means that it is from this moment onwards we use marketing automation to collect data on prospects and predict their interests and purchase readiness. That’s all very fine, but you need to know that you need quite some time and several visits to collect a critical mass of data to be able to really effectively process an individual as a prospect. Another problem is that we can only take into account the data we have captured in the traffic and interactions in our own digital backyards. The marketing automation systems that are now considered mainstream (and are still fairly rarely used by Slovenian companies) don’t connect the identities that individuals reveal during a conversion, in which they download one of our files or sign up for a webinar by logging in through their social media accounts. Accordingly, these systems don’t provide data on how these individuals may be connected with people that are our competition’s employees or customers, or our customers’ partners, let alone predict and compare their sentiment towards us or our competitors. For now, more skilled sellers are identifying all of this by hand, when they are preparing for a personal approach to a customer. But in coming years, this will become a constituent part of activities performed by marketing engines that will also become affordable to large and medium-sized Slovenian companies.

An example of a new-generation marketing engine

Let me make up an example, so you can have a better idea of what I’m talking about. I’ve read that the largest Slovenian online store has 520,000 registered users. That’s more than a quarter of the total Slovenian population. If they could register through their Facebook account (which I would personally prefer because I wouldn’t have to come up with new passwords and so I always use options like these), the store could find out many things about their registered users (and even their Facebook friends) before they made even a single purchase.

Amazon, Facebook, and a wizard for finding the perfect gift for friends, all in one. Perfect! Click To Tweet

Let’s say that one of the purchasing moments of every individual is connected with giving birthday presents to friends. Facebook knows who your (close) friends are when they have their birthdays, and what they’re interested in. Some of them allow these personal data to be revealed to the public (consciously or not). Can you imagine receiving an email from Amazon informing you which of your (close) Facebook friends have their birthdays next week and what you could buy them based on their interests in life (and what they haven’t yet bought on Amazon by themselves)? Can you imagine that, not that far away in the future, you will also begin to be bombarded with such personalized ads? A personalized ad recommending you buy something seems to be the most personalization can do at the moment.

What the wizards for finding the perfect gift for a friend are asking you about today could also be found out by these systems themselves. If you look at my Facebook profile, it’ll soon become clear to you that you can’t really go wrong by getting me something golf-related, a bottle of good wine, a trip to a winemaker or a reservation at a good restaurant.

If technology used social media data to help Trump win the election, it may also help your business in the future.

How about we make the first step together today already? Call me at 00386 41 668 757.

 

[email protected]

About the Author

Igor Pauletič

Founder and CEO of FrodX, who uses his rich experience to assist customers to transfer the latest technological, operational, and social trends into their business operations. He mostly focuses on new product development, omnichannel sales architectures, and go-to-market strategies. As a team member, he fills the role of the idea generator and constantly challenges the status quo and established decision making patterns.