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Two Ways Financial Marketers can use AI & Machine Learning

by Graig Norden
on December 6, 2017

Two Ways Financial Marketers can use AI & Machine Learning

“[Artificial intelligence and machine learning], so hot right now.”
-Jacobim Mugatu, Zoolander

Okay, so maybe the evil fashion mogul was referring to Owen Wilson’s Hansel, but these two disciplines of data science are having their own moments on the proverbial runway.

For simplicity, we will adhere to Forbes’ definition that “machine learning is a current application of artificial intelliegence based around the idea that we should really just be able to give machines access to data and let them learn for themselves.” The following chart shows search history over the last three years for these terms and, for some context, the S&P 500 Index, as measured by search traffic on Google:

Artificial Intelligence.png

The y-axis, according to Google, represents “search interest relative to the highest point on the chart for the given region and time. A value of 100 is the peak popularity for the term. A value of 50 means that the term is half as popular. Likewise a score of 0 means the term was less than 1% as popular as the peak.”

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It’s no surprise that when there are major global events, there are spikes in interest related to how the stock market is behaving. But if we ignore these outliers, it may come as a surprise that artificial intelligence and, to a lesser extent, machine learning, are generating similar levels of interest as the unofficial barometer of the investment management industry. Over the last year, in fact, the average “interest score” of artificial intelligence was 30.7, while the S&P 500 measured 40.3. And that gap is closing. This is probably a reflection of the growing applications for data science.

Here are two immediate ways that financial marketers can incorporate these disciplines into their work:

  1. Lead Generation: HubSpot’s inbound marketing software has a predictive analytics feature that is built on machine learning capabilities. By analyzing all of the touchpoints between your firm and its leads and clients, it finds commonalities between those prospects that became clients and those that haven’t yet. Everything that is integrated with HubSpot -- your firm’s social media accounts, video hosting platform, advertising networks, etc -- is incorporated into HubSpot’s determination of your best current prospects. This is a substantial competitive advantage because you have pristine insight into who your best prospects are and the most effective ways to pursue them. Try doing that in Excel.
  2. Content Strategy: Harvest Exchange, like Netflix, uses AI to recommend content to subscribers based on what they viewed in the past. According to Evan Spiegel, co-founder of Snap, “research shows that your own past behavior is a far better predictor of what you're interested in than anything your friends are doing. This form of machine learning personalization gives you a set of choices that does not rely on free media or friend's recommendations and is less susceptible to outside manipulation.” Investment managers must emulate the likes of Netflix and Amazon in terms of how they engage with investors. Part and parcel of that is having a comprehensive content strategy that supports user personalization, which is best done with the use of data science.

If you are not a data scientist, it doesn’t mean that you are destined for the Derek Zoolander Center For Kids Who Can't Read Good And Wanna Learn To Do Other Stuff Good Too. But you might be if you aren’t beginning to incorporate AI into your work.