By: Peter Hans
Co-Founder & CEO – Harvest Exchange Corp.
PAICR Gold Sponsor – Harvest
In the investment management world, “data” has historically meant “capital markets data”—used to create an investment thesis or structure an allocation model. But in recent years the topic of “big data” has been top-of firms’ minds. Why? Because in a digital world, there are significant opportunities for investment managers to leverage behavioral data so they can better engage with their clients. And under the right circumstances, that data can also be used to better align the interests of an asset manager and their clients.
Here are a few examples of how data can be used to achieve such goals:
1. Personalize the client experience
The future of finance is digital, as stated by the Financial Times. Frankly, this statement is consistent with trends we are seeing at Harvest, which demonstrate over and over again that hedge fund managers, analysts at a public pension plan, financial advisors, and individuals are conducting investment research online. Using artificial intelligence and machine learning makes it possible for the likes of Netflix and Amazon (and Harvest) to better organize content in order to improve the user experience. But without user data, this wouldn’t be possible and would lead to the user having to sort through things that are irrelevant to them. It should come as no surprise then that 70% of the content consumed on Netflix is the result of a recommendation by their algorithms.
2. Quality over quantity
While digital marketing has allowed investment managers to seamlessly distribute their message at scale, it has also led to an environment of unsolicited spam and ever-shrinking attention spans. However, there’s no need for such a shotgun approach. Instead, behavioral data can be used to transform a manager’s previously volume-driven approach to a highly targeted relevance-driven strategy. Harvest was built with this in mind and seeks to help financial organizations better engage with their clients. We do this by prioritizing what an individual, or group of individuals, cares about and interacting with them accordingly. In essence, we seek to filter out the noise for the reader and create an environment where less is more, both for the asset manager seeking new clients and for a client seeking a new solution.
3. Intelligence for humans, not robots
While Harvest uses behavioral data as inputs into its algorithms, for asset managers the same data offers an insight into the next human interaction. For example, knowing in real time whether certain targets are engaged with thought leadership on energy infrastructure, or reading your firm’s view on the yield curve, can provide extremely valuable qualitative information for a manager’s sales team. Additionally, understanding what your target audience demographics are interested in, what they aren’t, and how those trends are changing can also be used as inputs into deciding your upcoming marketing priorities. In short, asset management has always been a relationship-driven and deeply personal business. The availability of technology-empowered behavioral data does not have to mean full automation and the elimination of the human element. In fact, this data can be used to materially strengthen the human element so that a manager can achieve their desired outcome and their client enjoys a better user experience.
In the end, most people are growing weary from the deluge of information they are bombarded with on a daily basis. But with data being used for good, that deluge can be replaced with a stream of information that users will find relevant, interesting, and actionable. For investment managers, data can be applied to better align their interests with their clients. This includes the use of data to personalize the client experience, the ability to emphasize quality over quantity in their communications strategy, and by creating more meaningful conversations with their clients.