VettaFi CMO Jon Fee recently hosted the webcast, “Turn Data Into Sales: Strategies for Asset Managers.” The hour-long presentation featured Microsoft Director Gaby Marano and J.P. Morgan Asset Management’s Global Head of Business Intelligence & Analytics Danius Giedraitis. This event covered a variety of topics centering around how organizations can evolve their data practices. Here are the six key takeaways:
1. Financial services lags behind other industries when it comes to using data
Organizations that take advantage of customer behavioral data outperform their peers by 95% when it comes to sales growth, according to McKinsey & Co. Despite this, many asset managers are underdeveloped in their data capabilities. “There are probably some things that are far along relative to other industries, but there’s a lot of opportunity to do things more thoughtfully,” noted Giedraitis.
Looking at the consumer side, many companies have extremely sharp data deployment. Food-ordering apps are able to track preferences and send push notifications about deals to their customers, while map apps immediately provide the quickest directions to a destination and account for traffic.
Financial services, particularly in distribution, have only scratched the surface of customer behavioral data. Investors who are actively researching commodities and alternatives, for example, are more likely to invest in diversifiers than an equity fund. Streamlining this data and providing it to sales gives the team an opportunity to pitch the right product to the right client — much like how Grubhub recognizes a customer’s preference for vegetarian takeout and tailors its recommendations accordingly.
2. More data does not always equal better outcomes
One common error organizations might make when beginning to implement new data practices is attempting to sponge up as much data as possible. Data can be a signal, but it can also be noise. When assessing key metrics for distribution performance and growth, the panel recommended focusing on six to eight metrics. Data-driven teams have a playbook on how to react depending on what these metrics do and a deep understanding of how they relate to one another. Once teams start employing more than eight key metrics, the data deluge can be distracting, especially if there’s no plan on how to proceed if the numbers fall above or below certain thresholds.
Additionally, organizations that are getting their feet under them when it comes to data lack the capacity to track and interpret a deluge of information. For such organizations, having a data partner is a smart investment that can save bandwidth for sales and marketing teams that might already be spread thin.
3. Data evolution takes time and organizational buy-in
It is important for an organization to know where it exists on the data maturity curve.
Moving along this curve takes time. Different parts of the company might not be ready to take on new tools, while other parts of the firm may be eager to leap forward. The reality is that good data practices are an organizational relay race in which every department is working in lockstep with every other department. This means transmitting and sharing the right data at the right time. Fee likened it to a “relay race,” in which marketing is handing the baton to sales smoothly and keeping up momentum. Getting to this place takes time, effort, and organizational buy-in. It's important to not skip steps and to bring everyone along as a firm moves from underdeveloped status in data use to optimized status.
4. Your ‘super users’ can lead the way
Of course, organizations are composed of people. Different people have different skills, talents, and interests. Some will be “super users” of data. These are people who have an understanding and interest in data, who are eager to experiment with new tools and procedures, even if those tools and procedures aren’t fully cooked.
Super users aren’t just early adopters — they’re the champions who can drive organizational buy-in for better data practices and tools. They provide critical feedback, help refine processes, and support colleagues who may be less comfortable with change. Since many professionals are too busy to experiment with new workflows, organizations need to present fully codified tools that are ready to implement. Super users play a key role in this by stress-testing solutions, guiding adoption, and ultimately easing the transition to more effective data practices.
5. The AI era is here, but it’s early innings
“I think the AI era is here, and it's here to stay,” said Marano. Distribution has always been impacted by tools and technology. Everything from phones to social media have changed the way sales and marketing do their work. Artificial intelligence is no different. Having AI that can tackle administrative tasks, take meeting notes, and free up employees to focus on mission-critical work can be a huge boon, but it's important to understand the technology is still in its early days.
In theory, AI will be able to remove the “no joy” parts of work so people can focus on the things that matter most to them. But the technology is still evolving. That said, Giedraitis warned that “every minute you wait is a minute that someone else is moving forward.”
Data teams experimenting with AI could be helpful for companies looking to evolve their data practices.
6. There is no silver bullet
There’s no denying well-implemented data practices can transform an organization and help it grow. Proper data usage can increase efficiency and drive substantial AUM growth. But it's important to understand there is no silver bullet to success. There’s no one metric or data stream that can instantly solve all of an organization's issues. Data requires multiple touch points, and it needs to be vetted for quality and deployed with thought and care. It's useful to also understand that data goes beyond just numbers. When a sales team has a meeting with someone, there are linguistic data points. Marketers can use behavioral data to look at what people are researching. Data isn’t just about numbers going up and down.
Importantly, you need to read the tea leaves and understand how everything relates to everything else. Clients will engage with products and services in multiple ways. Having a 360-degree view is essential.
