Targeted ads. Pattern matching. Big Data. Ambitious wealth managers already use the tools making headlines for moving nations to attract assets . . . without even getting near the “Dark Web.”
Political consultancy Cambridge Analytica’s role in the presidential election remains controversial. This isn’t about what they did or who they were working for.
But the techniques are already in wide circulation. This isn’t witchcraft. It’s how opinion gets shaped in the social media age.
Whether you’re watching the way new asset classes emerge or simply trying to build your own book of business, you probably already know the basics.
For better or worse, the only really sketchy thing Cambridge Analytica did with Facebook is how they got the data. Everything else was practically standard marketing practice.
Gather and sort
It starts with access to the data trails people leave behind online. Companies track the sites you visit, what you search for and how you interact with the content — every little “thumbs up” button you click adds up.
In theory, the sites only use that data internally, mining just that tiny slice of your history to figure out what you want and how they can sell it to you.
What really happens is that enough sites share your data to start constructing a more robust profile of who you are and how you think. Compare that profile to enough other people and broad patterns start to emerge.
Once someone can see those patterns, they can build targeted marketing campaigns around predicted behaviors. That’s exactly what business development consultants tell anyone who wants to acquire new customers to do — and wealth managers are definitely included.
Segment your potential market into smaller populations. Tailor messaging to each one. Build a narrative that leads each prospect from the first tentative contact to signing the assets over.
That’s just modern customer relationship management. The process can practically be automated. The only limits are on the data you bring in and the ambition you bring to the table.
After all, account aggregation works on similar lines. The consumer signs over the passwords and all the transactions flow together. It’s convenient for the consumer. Of course the vendor can use the 360-degree view to build its own profiles and sell the results.
Anyone looking to market to a particular population just has to buy the leads. Even if the profiles are missing a few key elements here and there — email address, net worth, ZIP code, club affiliation, party affiliation — buy a few overlapping databases and you can generally finish the puzzle.
Once they’re in your database, your marketing systems get to work: serving the right ads, collecting the right subscriptions and waivers, taking them step by step to the moment where they sign as clients.
That’s not dystopian science fiction or even what Cambridge Analytica is accused of doing. It’s just the speed of modern business.
Brexit, Bitcoin and the (un)ethical marketer
Rumors now indicate that Cambridge Analytica used the data it harvested from British Facebook accounts to influence the 2016 vote to leave the European Union.
The company acquired 50 million account profiles under dubious circumstances, arguably against Facebook protocol. It then mined those accounts for patterns of thought, groups that would be easy to “nudge” across the Brexit line with a well-placed ad that looked like news.
Financial marketing networks did something similar to feed Bitcoin fever last year. Suddenly the Web was alive with hard sell content designed to “raise awareness” in crypto currency and get the retail volumes flowing.
It worked for awhile. The marketers picked the right keywords, gamed the topics that interest retail investors and created a boom at a reasonable price.
Companies that sell trading newsletters and other investment services have been running that game for ages. Whether it’s marijuana stocks, “energy metals,” nanotech or alternative fuels, an entire industry has evolved to get in front of susceptible audiences and guide their behavior toward buying into the stock.
Those methods were relatively unsophisticated. It was all about fear and greed: open with a shock headline about the imminent death of the dollar and close with an exclusive investment that can (theoretically) run rings around the best professional portfolio.
You’ve undoubtedly had to deprogram plenty of clients once they’ve been exposed to these ad campaigns. In my experience, doing it successfully is a matter of patiently tracking the claims and showing your clients where they break down.
It’s a lot of work. But the better you can educate your clients on how the major fallacies work, the stronger they’ll be on their own — and the less likely they’ll be to require intervention to keep them from moving out of mutual funds into Bitcoin, for example.
While Facebook and Google have already stepped up to ban the most abusive financial promotions, it’s really just slowing the flow of misinformation or “fake news,” if you like. Much like Facebook banning Cambridge Analytica after the fact, the damage has already been done.
I know you’re different because you actually want to provide better outcomes to people who aren’t clients yet. When you use modern data mining systems to approach prospects (qualified marketing leads), you’re hoping to enrich their lives, communicate a value proposition.
It might be worth letting them know. And if you can give them something valuable at the onset, you’ve already created a basis for trust and a stronger relationship down the road. That might be insightful, differentiated investment commentary. It might be a free consultation.
Basically it means giving them a taste of the rich communications your paying clients already receive, only without the actual portfolio and fees attached.
Previous generations of advisors ran columns in local newspapers or bought radio time. You can do that now on Twitter or via an email newsletter. (As always, keep compliance in the loop.)
After all, the goal is to influence people and make clients. The tools don’t have any moral weight one way or the other — what matters is how they’re used.
