New behavioral analytics capabilities

New behavioral analytics capabilities

In brief

Asset managers are now using new behavioral analytics capabilities to make science-based improvements to their client journeys. They are exploiting the Behavioral Benchmark to convert previously unavailable business intelligence into commercial value.

Welcome back to our blog series on what you (the asset manager) can do with the Behavioral Benchmark.

Across five articles, we explore how you can now dollarize asset management business intelligence, cater for regional differences in behavior, make science-based improvements to your client journeys, connect your distribution strategies, and alleviate clients’ survey fatigue.

Science-based improvements

As the time series behind the quarterly Behavioral Benchmark lengthens, asset managers are graduating from just measuring and comparing their effects on client behavior to also exploiting new behavioral analytics capabilities.

Specifically, they now know the effects they need to create in order to stand out from the average firm. To give some examples … to justify the effort needed to create thought leadership, what is a good visit length, scroll depth, and conversion to event attendance? What are above-average RFP and pitch success rates? And what is a suitable volume of client meetings and their potential effect on client retention?

These are all examples of previously unavailable insights into client behavior that are enabling asset managers to make science-based decisions about where on the client journey they want to improve or differentiate.

Extracting commercial value

Because client behavior is dollarizable, asset managers are converting the benchmark’s outputs into commercial value.

For example, if you have a sales pipeline of USD 5bn with a weighted average fee of 35 basis points and, on average, you win 5% fewer pitches than the competition, you just lost USD 875,000. With that money, you could have strengthened your sales training or improved sales support.

Similarly, if you take 90 days to onboard clients but the others do it in 60, you just gave up 30 days of revenue. Across an onboarding pipeline of USD 500,000,000 that would cost you about USD 200,000 that you could have spent on strengthening your onboarding capability.

And what about lifetime value? If your revenue from a book of business is USD 10,000,000 and your average institutional client tenure is only 80 months compared to a benchmark average of 100 months, your competitors are making USD 2,000,000 more than you that they can reinvest into their retention strategies.

Every time you think this way, you will create more distance between your firm and the trouble that may await those asset managers that fail to respond fast enough to market headwinds. As a result, we believe the winners will be those who extract commercial value from new behavioral analytics capabilities.

New behavioral analytics capabilities

Starting with the basics, the Behavioral Benchmark helps asset managers know the different ballparks other firms operate in and how they compare. We achieve this by identifying where on the client journey firms’ effects on their clients’ behavior are either widely dispersed or tightly grouped.

For example, it turns out that the greatest differences are in the marketing and sales stages of the client journey, so asset managers are now adjusting their strategies to respond to new information. In one case, a firm strengthened its digital content strategy to optimise average time spent on thought leadership pages and average scroll depth.

You will be able to drill-through into sophisticated visualizations and analytics of your absolute and relative effect on different client behaviors, as well as compare your performance over time against statistical trendlines.

In another case, an asset manager strengthened its link between thought leadership and event attendance to minimise ‘client leakage’ between those who consume content online and those who take the next step of deep-diving into a topic at an event. And in a third instance, a firm changed its client engagement approach with the goal of closing the gap between its product-per-client ratio and the benchmark average.

These are all examples of science-based improvements asset managers have made in response to participating in the Behavioral Benchmark.

Planned forecasting capability

Lastly, if you carry on doing the same thing, you are likely to continue to create the same effect in clients. To define this link between past and future behavior, we are preparing to help asset managers predict their effect on client behavior. Specifically, we have built a prototype forecasting capability and early tests indicate that we may be able to forecast with between 86% and 95% accuracy. We intend to test this for another year before going live in 2023.

The full series of blogs

In our opinion, not all asset management business intelligence is equal, so we hope you have enjoyed learning about these new behavioral analytics capabilities and that we have got you thinking about how you can use client behavior to make science-based improvements to your client journey.

Here are the other blogs in the series:

Book a demo with the founder of the Behavioral Benchmark if you would like to see it in action.

Picture of Adam Grainger

Adam Grainger

Behavioral analytics | Business intelligence | Asset management
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