[The pandemic environment inexorably drove us to operate in the digital realm. This shift to digital accelerated the process of searching for digital tools and learning how to use them; gave us a much greater understanding and appreciation for data in all its forms as the true backbone to sales and marketing; and ushered in the need to creatively experiment on how to extend more digital connections for deeper engagement with clients.
For asset management firms, looking at new data sources, crunching through expanded advisor information, and using advanced analytics and AI, have led away from traditional territory management business models to a serious rethinking of their entire sales/marketing operations and hybrid strategies. The formation of business intelligence teams and new operating models are focused on engaging advisors in new, more data-driven ways.
To better understand the potential behind the changing nature of asset managers’ new working relationship with advisors, we reached out to Institute member Nathan Stevenson, CEO of ForwardLane — an AI-powered insight automation platform that dramatically accelerates the productivity between asset managers and their advisor clients. They can accomplish this by synthesizing vast quantities of collective firm intelligence and market data to provide accurate signals and next-best-action recommendations for consultants to engage. We wanted to explore what this means for asset managers and how this also addresses what advisors really want. This new application of technology for digital engagement has opened the door to a more valuable “Connected Experience” for asset managers and their advisor clients.]
Bill Hortz: What does it mean for asset managers to have a “connected experience” with advisors and what does it bring to both parties?
Nathan Stevenson: The connected experience is about pulling together data around the advisor from marketing, sales, business intelligence, and data science sources such that advisors receive personalized relevant engagement. For asset managers and hybrid sales teams, it means streamlining data inside of your CRM system so that asset manager representatives have the best sales intelligence from across the organization, and this sales engagement data is shared back with marketing, sales management, and business intelligence groups to develop focused advisor engagement strategies.
Hortz: Is there any research you can share with us that quantifies the need for this kind of personalized digital engagement strategy for driving future asset management growth?
Stevenson: A CAPCO research report on 11 Trends to Watch in Asset Management for 2021 outlines the competitive trends at play for asset managers with the digital client experience, scaling up artificial intelligence, deploying data strategies across sales and distribution, and exploring partnerships with Fintech companies as top trends driving the growth of data-driven asset management.
In our own research and analysis, we have found that meeting prep and time-to-insight can be conducted up to 6.5X faster, shifting the needle from time spent in data analysis to advisor engagement. Roubini ThoughtLab takes this further showing bottom line impacts with “digitally advanced firms seeing rises of 8.6% in revenue, 11.3% in productivity, and 6.3% in market share.”
Hortz: How many data points can you isolate currently on advisor clients?
Stevenson: We are able to connect together useful information inside of CRM notes, CRM data, transaction patterns, data pack data, marketing campaigns, website visits, event-based data such as webinar signups, customer support tickets, sentiment analysis on this data and content from marketing that may be relevant for advisors.
In some cases, for example data packs, there are over 300 data fields to review for one advisor. When you think about connecting this information with products discussed, buying behavior, and other predictive analytics we can provide, you are providing higher value to an advisor when you speak with them with specific, relevant engagement.
Hortz: How exactly can this data be used to interpret an advisor’s behavior and guide your engagement strategy?
Stevenson: We can combine signals that analyze transactions historically in terms of size and frequency to proactively identify trends, propose a cross-sell based on buying trends, and also uncover product discussions that have not yet converted by reading CRM notes with ForwardLane’s proprietary NLP (natural language processing) and cross-checking against transactions. Together we combine engagement signals into a “Growth Collection,” which can quickly identify new opportunities.
Also, an advisor’s behavioral profile can be further inferred from engagement activity and frequency across the asset managers digital sites. For example, an advisor may have reduced the size and frequency of purchases for a growth fund that can be seen in transaction patterns. NLP analysis of CRM notes might detect a discussion on value funds, negative sentiment around the tech sector, and the advisor may have visited specific pages on their website related to value funds being a trend to follow.