In the early days of navigation at sea, mariners were forced to travel close to the coastline, using landmarks to help them assess their position and keep them, their crews and their vessels from danger. 

While rudimentary, the process worked well if the sailor knew the territory. If they didn’t, they ran the risk of steering their boats into rocky and dangerous territory - and at that point it’s a bit late. That was the case, of course, until the simple lighthouse helped alert them to danger ahead.

Not unlike early sailors we often use very rudimentary techniques to assess risk because we only see the problem when it is, in fact, a problem.

We would benefit from our own lighthouse – or perhaps a more sophisticated way to spot danger ahead.

In our industry, of course, risk is less likely to look like a rock. So we’ll focus, instead, on one of the most fundamental sources of risk, and that’s flight risk. 

Before I jump in, I’ll acknowledge that you may not see flight risk as significant because loyalty is strong in the industry. However, your perspective changes the scope of the risk.

1. If an individual advisor loses two clients in a year, the impact may be modest. If each advisor in a large RIA loses two clients in a year, the impact to the organization is anything but modest.
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2. While loyalty is very strong, about 30% of clients say they have considered changing advisors in the last year. This is a ‘lurking risk’ that demands our attention.

Spotting and Managing Risk in Your Business

So let’s connect the dots and look at a different way to manage risk, from the most basic approach (Level 1) to the most sophisticated (Level 3).

Level 1: React

Today we typically react to 'outcomes'. If a client leaves it’s a bit like hitting the rocks and we have little choice but to react to the situation. 

We didn’t know there was a problem because we couldn’t see the rocks. And all our effort goes to fixing the immediate problem. It may work, however it requires significant effort (and creates an emotional drain) so it’s not the most productive use of time.  

Level 2: Respond

Let’s add a lighthouse to the equation. In our industry that means you have a process in place to identify clients at risk before they leave. The easiest way to do that is to measure satisfaction over time. 

A client who is dissatisfied (or even neutral) is at risk, and knowing that is like seeing a lighthouse in the distance. There’s danger ahead but we still have time to respond and change course. Better, but still not ideal.

Level 3: Anticipate

But what if, instead of reacting or responding to a problem that has already happened, we could avoid it all together? To get there we need to focus less on client outcomes (e.g., a client leaves or indicates dissatisfaction) and more on client signals. 

The Importance of Client Signals

Client signals are those things that may lead to a particular outcome, such as dissatisfaction. They tell you there is danger ahead before that danger becomes imminent. They give you an opportunity to respond.

Let’s look at an example that draws on the collective experiences of our clients.

1. As part of a process of on-going client feedback, we may choose to assess client satisfaction.
2. That allows you to identify clients at risk and follow up directly with those individuals. Tick that box.
3. Let’s assume, however, that we conduct further analysis and find that the extent to which clients feel engaged during review meetings is directly correlated with high/low satisfaction.
4. Further, let’s assume we track that data back to clients who have left to identify patterns of response prior to leaving. And we find these clients provided lower ratings on engagement during review meetings.

Now, with that new insight, two things happen.

1. You can focus your time and attention on improving the client review process, treating it as a ‘lever’ you can pull to drive satisfaction instead of trying to focus on clients who are already half way out the door.
2. You can begin to flag clients who provide a ‘muted’ rating on 'engagement during reviews' and focus on enhancing the process for that individual. He or she hasn’t identified as dissatisfied (at least not yet) but that lower rating is an important signal.

Let’s dig further into the same example.

1. Now we’ve discovered that the extent to which clients are engaged with review meetings is a signal of client loyalty.
2. On that basis we implement a targeted process to gather additional input following each client review over a six-month period.
3. As a result, we identify that the level of engagement with reviews is directly correlated to the level of involvement the client had in crafting the agenda and the length of the review meeting.

With that information, things get really interesting. Now you can not only flag clients who may be heading toward dissatisfaction, but you know the adjustments that will have the most significant impact.

From Data to Insight

Tracking those signals, however, demands good client data and a sophisticated level of analysis. And they may be different from one advisor and one firm to the next.  

At Absolute Engagement we work, primarily, with larger enterprises to help them capture and use input from clients. One of the benefits of scale is access to significant client data. 

But data isn’t enough. There is an art and science to analyzing that data to uncover real insights and translate those insights into action.

Your Early Warning System

We’ve found that the drivers of satisfaction and loyalty change from one business to the next. What is common, however, is that there is a set of factors that drive both.

In order to create a meaningful early warning system across the organization, you’ll need to gather the right input from clients, analyze it to understand how to take action and connect the dots to specific follow-up activities. 

Sound simple? 

Of course, it doesn’t. And that’s exactly why some firms stand out from the crowd. 

There was a time when the idea of a data-driven client experience was novel. Today it is table-stakes for any progressive firm. Any client experience that is not data-driven is driven by assumption. And if that is the case, the client experience will, at best, be outdated and at worst, miss the mark completely.

Thanks for stopping by,

Julie