Personalization can be key to helping wealth management clients weather volatility—but it’s easier for some than others.
If you’re a family office serving a handful of members of a single wealthy family, personalization should be pre-baked into almost every move you make. But how do growing financial advisory firms with dozens, hundreds, sometimes thousands of clients, personalize timely messaging and content?
Technology has one answer through personalization as a service, or PaaS. In PaaS, messages and experiences are delivered that are built around information that a firm has learned about a client, prospect or group.
“Our goal is to help advisors engage with their audiences, engage with current clients and gain new prospects,” said Laura Kimball, vice president of product and machine learning at TIFIN Clout, an AI-driven content marketing platform. “Personalization for us comes in terms of the content that advisors are sharing and messages personalized for the advisor and their value proposition.”
An automated platform like Clout can help advisors scale their business by accessing content relevant to their clients at the right time, said Matt Wesche, chief product officer of Clout.
By matching content with client characteristics, Clout saves advisors time poring through CRM and notes kept elsewhere to find information about clients. It also sorts through and “reads” thousands of pieces of content, applying topic tags to them.
“We have the ability to be a force multiplier for the advisor in this case, and we’re also taking out the guesswork of tagging content,” said Wesche. “On top of that, our algorithms don’t get tired and they’re not having bad days as opposed to good days.”
Kimball added that algorithms like the ones developed by Clout are consistent—people often fail to follow the same rules consistently over large amounts of repetitions or time, and two or more people may follow two or more different interpretations of the same rule.
Wesche and Kimball presented two case studies illustrating the effectiveness of Clout’s ability to drive deeper personalization.
A Multi-Billion Dollar Fintech Platform
Clout was asked to use its algorithms to “read” 900 pieces of content from a multi-billion dollar fintech platform’s content library and apply appropriate tags to them. Clout then used content tags to match content with clients and prospects within the fintech’s ecosystem.
“These use cases are about these firms being better able to categorize their content libraries, either for advisors who send out content or for the search algorithms on their websites,” said Kimball. “We talked about APIs and having our algorithms able to power website search to deliver content relevant to that specific site visitor and figure out what pieces to deliver someone coming to the website for the first time in real time.”
On average, the Clout algorithms found six additional tags per article over the fintech’s original ad-hoc tagging strategy across 318 unique tags, and was able to recommend personalized content to segments like retirement, baby boomers and ultra-high net worth using Clout’s content tags.
Clout’s tags were also able to recommend content related to specific client funds and holdings as well.
“It’s not that more tags are better, but they enable firms to be more targeted in their delivery,” said Kimball. “In this case, if an advisor has clients invested in specific funds or a set of funds or stocks, or they’re trying to sell those investments, they could use the content tagged with the fund. There may also be some benefit with providing the advisor content around specific investments to help keep their clients informed and invested.”
At the end of the work, the fintech platform’s articles had an average of nine tags apiece, allowing it to deliver more closely personalized content to clients and prospects.
The Private Banking Division of a Fortune 50 Bank
This private banking division asked Clout to create personalization tags across their enterprise content library, including fiscal-year reports, prospectuses, PowerPoint templates, website articles and emails.
Clout was asked to run its tagging algorithms for financial topics, life events, investor affluence and financial personalities, compare the new tags to its existing content tags, and then train Clout’s algorithms to learn the bank’s specific tags to apply to new content.
“That works, the algorithm can learn to pick out words and basically embrace proprietary tags, but we didn’t end up implementing that functionality for this company—yet,” said Kimball. “We can do that with any large firm if they want to train the algorithms to their specific set of tags.”
Clout applied an average of 13 tags per document, an additional 12 tags per document compared to the banking division’s previous system, across 194 unique tags.
This represented a greater diversity and granularity of tags, allowing it to target a more diverse group of client interests and drill down more to sub-segments.
A Better Way
Clout clearly helps large enterprises like the fintech platform and the private banking division, wrangle content but it also works for smaller advisory practices, said Wesche.
“It’s an intelligence layer that is readily available to ingest content, whether that be marketing content, or other sources around your contacts and other things to really help you engage,” said Wesche. “Additionally, it can be used to help inform the advisor on where they should lean next, whether that be prospective calls or an annual review with the client. We’re in a world where you’re talking about knowing your audience more, understanding what is important to them, and you’re building a case of where you can create a niche for your office.”
Clout can empower firms to unlock automation, speed and growth for their content teams through its ready-to-use algorithms that are capable of reading and tagging existing articles with speed, precision and consistency.
“Let’s say an advisor has estate planning as a key focus area along with retirement planning and tax planning,” said Kimball. “Clout can send out campaigns to different groups on these three different topics, and then come back and say this specific, smaller group of people really leaned into the tax planning content—Clout could then recommend additional tax-planning content to send out to that group.”
