The Connected Experience for Asset Managers and their Advisor Clients

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, has 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.]

Hortz: What does it mean for asset managers to have a “connected experience” with advisors and what does it bring to both parties?

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 together 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.

The advisor may additionally be part of a cross-sell campaign list sent by marketing. Two engagement plans here can then be proposed. The first to reduce redemptions by sharing timely news and portfolio manager commentary via email and in a follow-up call. The second an up-sell can be positioned with value options with in-depth commentary by the research team and an invitation to a webinar to learn more. Together this meets the advisor’s needs while enabling the firm to retain and grow assets at the firm. It’s a win-win outcome.

Hortz: How do you categorize all this data into what you call “signals?

Stevenson: ForwardLane has developed a signal library to automate analysis and meeting prep work for asset manager representatives. We work together with asset managers to blend off-the-shelf signals with custom signals that meet each firm’s requirements. A custom master algorithm is then configured based on experts and users in the firm, so that each it is entirely customized to each asset management firms thinking and best practices. We categorize signals based on whether or not they are going to help them grow and gather assets, help in cross-selling or upselling products and services, and aid in reducing redemptions by enhancing retention.

Hortz: How does your AI-based platform determine and offer recommendations on next best actions for asset managers with their advisor clients?

Stevenson: Next best actions (NBAs) in ForwardLane are powered by Signals. So, a Signal that shows an emerging markets fund mentioned in CRM notes, but not transacted, may have proposed NBAs of “Share product fact sheet and PM commentary”, “Invite to emerging markets webinar”, “Schedule follow-up call”. We aggregate, rank, and score user behavior and the algorithm will sort the NBAs based on those that are most popular with sales professionals at the firm – effectively surfacing best practices.

ForwardLane has new Flow automation coming for Salesforce which will be a game-changer, effectively enabling NBAs to be linked to Flow Builder automations that run across the Salesforce ecosystem and can also tie into external systems with webhooks.

Hortz: Can you share some brief examples of how some of your asset management clients are developing advisor engagement and messaging strategies by working with the many different types of data from your centralized platform?

Stevenson: A key use case is enabling hybrid sales teams to prioritize which advisors to reach out to, analyzing all the data around each advisor every day, and then summarizing the findings and delivering this into Salesforce through our native component. This may entail surfacing data pack insights to see that there is a shift in flows to a strategy, a discussion in CRM around products in that category, and a marketing campaign with related collateral, all meshed together by ForwardLane.

An initial call to an advisor is made with the asset manager representative knowing there is a new fund allocation at that office, that discussions in CRM point to buying intent, and marketing identified them for a new campaign based on segmentation. A next best action might be to 1.) Share fund fact sheet and latest PM commentary 2.) Invite the advisor to a webinar and 3.) Provide indication of interest back to Marketing, which can then automatically place the advisor into a digital re-marketing campaign. Positively and proactively surrounding the advisor with useful, relevant, timely, and interesting insights based on their specific needs.

Hortz: Any other thoughts or recommendations from your experience that you would like to share?

Stevenson: Shifting your mindset and looking at “data” differently creates tremendous opportunity. Automation is everywhere, and now this is possible in fund distribution by weaving together data from across the organization and activating it so that it is in the hands of asset manager representatives in a prioritized and focused way. These capabilities are available today and can be deployed inside of 3 months for cloud-based firms. Moving to become an insight-based organization ensures you are always relevant, precisely focused, and highly productive thanks to AI-based automation and analysis. I invite asset managers to contact us to discuss your digital acquisition goals and learn more:

Related: Value Creation, Innovation, and Democratization for Asset Managers