UHNW Wealth Intelligence
"Wealth intelligence" is the use of prospect data to better understand, connect with, and acquire clients, particularly high-net-worth (HNW) and ultra-high-net-worth (UHNW) clients. The history of this niche wealth management category provides a useful view into the identification of the global rich and some approaches firms use to service them.
The ultra-affluent do not represent the one percent but something more like 0.004 per-cent of the population (based on internal data compiled by Wealth-X), about how many people four football stadiums could accommodate. Yet they represent a shade more than the combined gross domestic product of China and the United States. They are responsible for about a third of all luxury purchases, philanthropic giving, and privately managed assets globally. It is both the most coveted and concentrated market for financial services. And from a data perspective, there has never been more publicly available information about this group. But accessing the UHNW audience, penetrating the noise that envelops them, and commanding their attention has grown only more challenging over time.
The need for accurate and actionable wealth data and intelligence has grown in importance. Advisors, however, must leverage it carefully while respecting privacy concerns. In addition, those who know the industry well understand that data without action is a distraction. Building an effective wealth intelligence apparatus requires that advisors integrate it into their daily workflows. In the end, the goal is to help advisors thoughtfully increase mind share and wallet share of this audience on the back of such data-driven strategies.
The Historic Landscape of Wealth Data
To understand the wealth intelligence landscape, first consider how the infrastructure for the collection of wealth data was laid by the U.S. government. The Bureau of Labor Statistics was founded in 1884, and for more than a century it provided the foundational dataset used to analyze, target, and market to the wealthy. The data was aggregated into Zip+4 geographic categories, each of which represented a typical cul-de-sac of American residential occupancy. Wealth was recorded in these surveys as "household income." This made household income the cornerstone data category available historically for wealth. But as most advisors and the ultra-affluent themselves know, the ultra-wealthy are focused on K-1s, not W-2s. As a result, the traditional household income lens largely excluded the UHNW as a category.
To this day, most marketing and advertising agencies and advisors still use the category of household income to determine their marketing strategies for engaging the UHNW. The default target, almost regardless of brand or firm, from Amex Black Card members to luxury automakers, is the "$250K household income" category. The reason? These firms continue to build their strategies and models on spending data and household income. Unfortunately, spending plus household income combined with house values does not equal net worth. This blunt and imprecise approach is symptomatic of larger structural challenges in assessing the wealth data landscape.
Deficiencies in traditional wealth data set the stage for the rise of new entities to uncover true HNW and UHNW audiences, where the main indicator of wealth was not household income but net worth. Further, observers noted that the UHNW individuals typically have two key dimensions of engagement: (1) their relational networks, which is their qualification lens and (2) their passions, hobbies, and interests. It’s within this coincident shift from household income to net worth, and in the movement from demographic data on "cohort" categories to "people intelligence," that the genesis of modern wealth intelligence began to take shape.
Wealth Engine to Wealth-X
Wealth Engine was an early player in building awareness around wealth intelligence as a category and was the established player in the marketplace for some years. It used wealth scoring based on traditional U.S. Census-based factors and integrated that with data from other sources to generate models, rankings, and scores. The challenge was that much of its data was not proprietary but aggregated from other providers that in turn updated their data infrequently.
Meanwhile, around 2009, the board of Forbes Media sought to incubate new revenue sources away from traditional media advertising models and that offered more annuitized recurring streams of income. The idea was to build on the existing subscriber list of Forbes as a database of affluent prospects and to then sell access to that database as a SaaS-based, e.g. Salesforce, annuitized subscription revenue model. Wealth-X was born from this effort at Forbes.
Wealth-X sought to create a new lexicon of wealth intelligence. By defining the UHNW segment as $30 million at minimum, combined with ground-up data built on individual dossiers, Wealth-X offered more granular information than was available previously. The platform also offered a different income-based metric, in contrast to the dominant Merrill Lynch Capgemini World Wealth Report approach, which defined the category as $30 million of investable assets and used top-down macro and survey data. Further, instead of the standard profiles used by the financial services, luxury, and nonprofit industries, Wealth-X borrowed from the intelligence community to develop individual dossiers on each UHNW individual. The Wealth-X database of dossiers, which ranged in length from 5 to 25 pages, were written by Wealth-X’s researchers and staff. The dossiers did not include personal contact information, ensuring the data was compliant with privacy standards. But the information was so detailed and intimate that some compliance departments at large global banks refused to believe it wasn’t drawn from clandestine sources.
The data was incorporated into advisory workflow as a sales tool to give context, history, and insight about an individual and to encourage "chemistry" in a meeting. But one question persisted among wealth intelligence clients: "How can we leverage the information for more proactive prospecting?" Wealth-X responded by launching a new product called the Future Client Map, which was based on the understanding that warm referrals are the primary driver for future client acquisition. Leveraging the intelligence agency analog again, Wealth-X created a strategy-consulting component of "known associates" to help answer the question, "How do I reach them?"
A USER GUIDE
Let’s move from history to utility—how distribution platforms and advisors might benefit by taking a prospecting approach that leverages this type of wealth intelligence. Here are some broad use-cases that may align with current advisor outreach.
Prospecting Situations
Referrals are the primary source of new clients for all advisors. Advisors can use the "known associates" section of dossiers to review clients’ connections and determine if there are potential prospects to whom they should be asking for referrals. Combining Windfall’s analysis of highest-probability conversion prospects along with Wealth-X’s "known associates" within a platform’s Salesforce environment is the ideal scenario.
The head of business development for a $500-million RIA runs an exercise where each advisor in the firm takes a key client and uses the "known associates" section of the Wealth-X dossier to map and identify someone to ask for a specific referral. The advisor notices that a key client sits on the board of a large nonprofit with a key prospect and asks the key client for an introduction.
An advisor receives an alert that a prospect just sold a company. This presents an opportunity to reach out and congratulate the prospect on the sale and offer further support or help. The actual net worth and liquidity figures allow the advisor to customize a potential offering versus guessing the amount netted from the transaction.
Superior Prospect Engagement
Understanding actual net worth and liquidity helps to determine the right approach. By using the hobbies and interests section from Wealth-X or the affinity clustering in CRM or Windfall to generate rich engagement, an advisor can focus on what is important to the prospect to build trust rather than merely making a pitch. This approach further empowers the advisor to earn the right to be heard.
An RIA reviews a dossier in the taxi on the way to a prospect meeting and discovers that net worth is substantially higher than originally thought. This leads to a different value proposition and offering. Because the RIA was able to identify specific passions and hobbies, the conversation is focused on the prospect’s love of art versus selling a product. The RIA is able to "create a coincidence" using a common connection.
An advisor is able to segment his prospects by affinity for exotic cars and then pinpoint the right clients and prospects for an invitation to an event at the prestigious Pebble Beach car show—rather than sending out a blast invitation to all audiences without distinction.
A Wealth Intelligence Diagnostic
As part of any engagement with wealth intelligence offerings, advisors should ask themselves some of the following diagnostic questions about the intended use of the data.
What type of wealth data and information is important for my business and growth? Is it net worth and liquidity or is a wealth score sufficient?
How important is data accuracy and specificity? How often do you need it updated?
Am I looking for an SaaS AI-screening solution with marketing capabilities or more of a sales tool for equipping sales professionals for prospect meetings?
Am I looking to enhance my existing data and CRM and then leverage that data and modeling for net new customer acquisition, or do I just want information on new potential sales prospects and existing clients?
How important is the ability to match my existing CRM data with external data sources and potential new application programming interfaces (APIs)?
Is digital targeting and advertising a key component of my growth strategy? Does my strategy include integration with existing media strategies?
Do I need real-time alerts and wealth triggers?
What am I prepared to invest based on the potential return on investment?
Enter AI: Windfall
Wealth-X eventually was folded into an evolving wealth and people intelligence roll-up and re-branded as Altrata. But it would not be long before additional innovation would come to the wealth intelligence space. Specifically, the area was ripe for artificial intelligence (AI) approaches. Windfall set out to be the leader at the intersection of wealth data, AI, and people intelligence by harnessing AI’s ability to ingest, scale, and analyze open-source data and ensuring incorporation into enterprise workflows.
Windfall includes household net worth and liquidity as well as more than 200 other data signals, such as ownership of boats, airplanes, multiple houses, and liquidity triggers. Windfall enables customers to segment and analyze their existing customer relationship management (CRM) data within a heat map with a dashboard view combined with the ability to activate that data through hundreds of digital media channels or direct mail. Windfall seeks to fill in the critical missing element: activation, now fully integrated into enterprise digital ecosystems. Within this platform advisors can build a highly accurate and targeted audience.