How advisers can improve client outcomes by embracing data

Betterment's Jon Stein offers 4 ways to bring a more data-driven approach to serving your clients

Dec 18, 2014 @ 12:01 am

By Jon Stein

If you want to bring a more data-driven approach to your work as a financial adviser, consider implementing some of these tools and processes.

(Related read: 4 ways automation is changing the way RIAs invest)

1. Create your own in-house data team.

Last year, our engineering leadership approached me with a proposal to form an in-house data team. For a growing company, that's a lot of resources to go into one standalone team.

But they convinced me that it would create the tightest possible feedback loop between what we could do for our customers and our technology. Traditionally, business intelligence tooling has been something that comes at a great upfront cost to an organization (it can reach into the millions of dollars). But I entrusted them to create a team in the most pragmatic way possible, and the result is our dedicated data group at Betterment called Polaris. (You can read more about Polaris' work here and here.)

Today, the team maintains a robust data source and analytics system for the company, allowing our engineers, product managers, and investment team to test hypotheses and iterate quickly.

2. Don't rely on found data.

Too many companies just try to mine the data that they already have: data that is a byproduct of other activities. For example, data from server logs about when customers log in. This can be termed 'found data.'

The problem with found data is that too often its very convenience is what drives the types of questions that your company asks and answers.

However, a better way to think about data is to start with the questions, not the data. Good analyses start with an important question and consider whether there is evidence for a conclusion.

Searching the most convenient data for insights offers many tempting opportunities to see interesting or unanticipated patterns, but these are not as likely to hold up in the future.

3. Define the questions and generate the data you want to analyze.

So, now you know you should start with questions, rather than found data. What kinds of questions do you want to answer?

As we're building a feature, we ask ourselves: What is worth measuring and tracking when the customer interacts with this? What kind of behavior do we want to know more about? If we do X, will we get Y? With every product and improvement we add to our service, we create a way to track and record actionable data.

4. Improve your customers' outcomes.

Using the robust measuring analytics and data collection system set up by our in-house team, we can see where customers are starting to behave in ways that could hurt their chances of reaching their financial goals.

Let's use our new Tax Impact Preview tool as an example of how this process worked.

We started with a hypothesis: Customers would be less likely to make an allocation change if they saw in advance the actual tax hit they would incur with short-term capital gains. Next, we created a demo and user-tested it. We incorporated feedback and then we built it, complete with data-tracking features so that we could measure results in the field.

After three weeks, our data showed that customers who considered making an allocation change — but who used the tool and saw that their estimated taxes would be greater than $5—were 62% less likely to follow through on the change. Statistically speaking, that is a huge improvement in behavior, and we're proud that we're able to provide a smart tool that helps customers make smarter decisions. It's just one example of how we're implementing data into our work as a financial adviser.

There are many ways to use data as a financial adviser—this is simply one example.

But the guidelines are the same: Dedicate resources, don't rely on convenience, ask the right questions, and put the data to work for your customers.

Jon Stein is the founder and CEO of Betterment.


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