Growth and Retention Takeaways from The SME Forum

Past purchases, current assets, advisor team profiles, wholesaler activity, market intelligence, and digital engagement are all data points that contribute to a holistic view of an advisor and can indicate purchase and redemption intent. While asset managers are incorporating some of these signals into their distribution strategy, many aren’t effectively leveraging a full continuum of data.

How can asset managers utilize past, present, and future data to enhance their growth and retention strategies?

We discussed this question during a panel session at The SME Forum earlier this month with Duncan MacDonald-Korth, Alev Cieslinski, myself, and our moderator, Hazem Gamal within the context of the conference’s post-pandemic theme, “Return to a New World”. From this session, I’m sharing a compilation of stories and takeaways that resonated with me to help you, our subscribers, and readers, answer this question for your organizations.

SME Forum panelists

Look to marketing to take a larger role

Over the pandemic, wholesalers could no longer meet face-to-face. We saw marketing transformation accelerated in our client base and in the industry. More firms are incorporating data in their marketing strategies to help marketing and sales teams reach advisors with more relevant content.

Understand an advisor’s preferences and buying process

Duncan shared a candid story from an advisor:

“If I buy a high yield bond fund the first week of the month, whether it’s a quarter later or a month later, whenever that trade hits the tape I’ll get calls from thirty-five wholesalers in the same week trying to sell me the same product I already bought. It’s a waste of time and I don’t buy anything that way.”

Anonymous Advisor

This story highlights the risk of using one data point in a vacuum. This story also inspired the creation of AdvisorTarget, a service that tracks an advisor’s reading preferences to identify and deliver signals of interest to asset managers. Pre-pandemic, wholesalers gathered first-hand knowledge from advisors during in-person meetings and this distribution model worked well. In our new world, there has been a culture shift. There is less opportunity to engage with an advisor in this way and a greater need and value for insights from other sources, like AdvisorTarget, into the advisor’s behavior.

Tie data together for better targeting and more accurate engagement benchmarks and attribution

You’ve all heard the phrase, “right person, right time, right message.” When you have insights, like reading behavior, which signal a propensity for an advisor to buy or redeem, you want to act on that information before it goes stale. Relationships are also important. If this same advisor works on a team (also called buying unit), knowing the members of that team, the assets they hold with you (and others, thanks to data packs), and the activity you’ve had with them helps you identify the right person for the conversation. Tying advisor team and intent data together allows you to supply your sales and marketing team with who to connect with, what to talk about, and when. Duncan shared an example of an advisor that has millions of dollars in high yield bonds with your firm. With AdvisorTarget data, you learn they (or someone on their team) is reading a lot of bearish articles. This is a strong signal that a redemption might be coming. Since it’s cheaper to retain a client than gain a new one, your wholesaler can use this valuable information as a trigger to reach out.

Attribution (measuring the impact of a data investment, campaign, or segmentation strategy) validates past efforts and informs future direction. Alev shared a segmentation approach backed by a financial model that tracks engagement, growth, and retention. She found, for every percent increase in engagement (e.g., sales and marketing meetings), there was an increase in yield. The challenge with attribution is that you must make assumptions and use multiple data points. There is so much bot activity that opens/clicks aren’t strong signals for engagement. Alev noted that time spent, scroll depth, and repeat visits were good indicators, and you can benchmark against your own performance data over time. When you incorporate more data points, assign weights based on assumptions (e.g., a call with a salesperson has more weight than a click), and look at them over time you can attribute them to an outcome (e.g., sale, retention, etc.)

Two stories on ROI and attribution with team data:

  • In my previous role, we ran a high-net-worth campaign, targeting the top Barron’s list. As reports with sales came through, it appeared that wholesalers’ time wasn’t spent with the right people. A triangle of information—activity, transactions, and entity relationships—was needed to understand where business is coming from. Once we had that, we could more easily measure the impact and validate that we were targeting the right people.
  • When collaborating with a client on a case study to map behavioral intent activity to individual CRD transaction level, Duncan found a good correlation. A month later, after the client started bringing in advisor teams data, they looked at the intent and transactional data again and saw a 30% higher attribution rate.

Use a continuum of data: Past, present, and future

The last takeaways I’d like to share is from the end of our session. Hazem asked each panelist for our recommendations to asset managers on how to use a continuum of data effectively.

  • From Alev, start with the questions you’re looking to answer, purposefully look for data sources, and transform those sources to answer your questions with evidence.
  • I recommend you take advantage of third-party data that will help you better target and attribute outcomes to your efforts. Junior advisors are part of a team, they grow, and they start their own team or RIA. This happens regularly. When your wholesalers are out in the field, you hear about these movements. When they aren’t, you don’t. A third-party data source gives you more comprehensive and consistent team information.

“Recombine different data sets to draw unique insights that are relevant to where your product is strong, and you have the opportunity.”

Duncan MacDonald-Korth, AdvisorTarget
  • From Duncan, consider the opportunity and challenges that come with using a continuum of data. As you’re able to digest new forms of digital engagement you should combine them with other data points (e.g., flows, assets, data packs, wholesaler activity, etc.). Duncan’s comment above really hit the nail on the head. These different sets of data, when combined, can provide unique insights to opportunities you have with your clients. Each can help on their own, but together you get stronger analytical information about what a client is looking to do next.

Where to start?

If you would like to better leverage a continuum of data to enhance your growth and retention, we’d be happy to discuss. Contact us or connect with me!