How Advisors Can Mine Big CRM Data for AUM Gold

In recent years, ‘big data’ has become such a buzzword: across industries, everyone is hoping to take advantage of data analysis to identify their most profitable business activities or ideal client types for growth. While the concept of big data is nothing mysterious or complicated, knowing how to approach it to benefit your business can be overwhelming. The data is there, and most financial advisors naturally have the statistical mind to analyze it.

With just a bit of effort, it is possible to create a useful profile or “persona” of your most profitable client type(s) and then develop a more efficient approach to targeting new prospects who are likely to become ideal future clients.

However, according to our 2013 National ByAllAccounts ‘Traits of Successful Advisors’ Survey, 50% of advisors do not target clients by any particular characteristic. Many cited investable income (35%) or geographic location (21%) to select new prospective individual clients.  Do you employ targeting? Do you know what kind(s) of clients are the most profitable for you? Identifying which clients you are best at serving and then developing a profile for them puts you on the path from being a generalist to a specialist (read James Carney’s blog: To Succeed, Advisor CEOs, Compete to Be Unique, Not the Best)

Below are four tips to determining – and growing - your sweet spot.

1. Decide your business goals and metrics first, and only pay attention to data that is relevant. Stay focused.

One issue with big data is that it sometimes feels just too big. It’s overly optimistic to expect you will analyze all your data and extract all your insights right away, so it never hurts to prioritize your project goals. Then you can focus on a few meaningful numbers to discover data trends.

For example: assume your primary business goal is to grow revenue by acquiring more ideal clients in 2013. First, determine how you measure “ideal.” Is large AUM the key? Number of referrals? Demographics (business owners vs. corporate employees)? Choose a few metrics, but don’t get buried in every possible data value. Now dive into your CRM and see who else has these characteristics. What other commonalities do you see? Where / how did you attract these clients? Go do that again!

2. Data quality matters.

Data analysis will show you that the old saying is true: “garbage in, garbage out!” Raw data often needs to be enhanced in order to become useful information. Therefore, data cleansing / database hygiene must be completed before analysis.

For example: you meet several promising prospects at a convention. You know their company names and basic contact information, but have no idea yet what their total investable assets are. Don’t just plug random dummy values into your CRM, like “not sure yet” for one and “?” for another. Determine a consistent placeholder value, like “unknown” that can be updated later, and use it for now – or leave that filed blank. Using consistent values across records makes your future CRM search and analysis simpler.

3. Data analysis is all about telling a story.

What is most important with data analysis is the story – the simple, distilled “takeaway” behind the raw data. Strive to present data in a way that allows clients and colleagues to easily understand the story you have uncovered and grasp the insight. Spreadsheets are vital tools to the process of analysis, but might not be sufficient. Develop simple statements to help clarify your findings and tell the “story” of your analysis.

For example: “analysis of 2012 client revenue shows that our most profitable clients invest heavily in alternatives and require higher touch, plus have 65% more investible assets than clients who do not invest in alternatives.”

4. Keep it actionable.

Data analysis is a waste of time if you don’t act on it. A great discovery should be a few (not a long list) of actionable recommendations that are likely to improve efficiency of your communications efforts, better target ideal clients, and finally to grow business.

For example: “given that our most profitable clients invest heavily in alternatives, we will develop positioning that showcases our expertise in advising in these asset types and develop a one pager to hand out to prospects.”

All in all, don’t wait to explore your valuable database and incorporate data analysis into your to-do list. It’s time to make use of your CRM to monitor customer preferences and analyze market conditions or changes in the industry that may affect your bottom line.

You May Also Be Interested In…

Bring Big Data Power to Your Client Accounts (Blog post by Martin Dickau, CTO, ByAllAccounts)

Our Data Aggregation Advantage (Complimentary Whitepaper)

"Creating Your Ideal Client Profile: Optimize Your Client List to Maximize Profitability" (Webinar Replay featuring Rosemary Smyth, MBA, ACC, Author) 

comments powered by Disqus