Analytics in Action


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Asset management firms have enjoyed robust growth and earnings over the past 25 years, benefiting from a steady inflow of assets into mutual funds. However, asset outflows since 2009 would suggest that future success will hinge much more on taking share from the competition. In the past, a unique or well-performing fund product would create sufficient differentiation to attract incremental assets. Today’s saturated market for new funds makes it more difficult for firms to create and sustain product-based differentiation. Faced with this more challenging environment, firms are realizing the imperative to achieve distribution excellence in the advice channel.

Achieving Distribution Excellence with Predictive Sales Intelligence

Proven weapons do exist to improve wholesaler productivity. Innovative asset management firms have realized that they can do far more to help their wholesaling teams make profitable decisions about how to spend their time and energy on a daily basis. These progressive firms are tapping the power of data and predictive sales intelligence to quantify advisor sales potential and reveal actionable insights about advisor behavior and needs.

Consider the dramatic productivity gains just from applying a predictive, data-driven model to the issue of coverage: How often to visit each advisor (if at all) each Quarter. A traditional approach might rely on a simple metric – “Previous Three Months of Gross Sales” – to rank advisors and then bucket them into deciles. Based on this information, wholesalers would generally be directed to cover the highest potential advisor deciles first, as represented by the leftmost columns in Figure 1. Not surprisingly, advisors in the top decile typically generate $27,000 in incremental sales per meeting, compared to the $10,000 average.

While this basic approach works, a predictive model to rank advisors performs significantly better: the advisors in the top decile would generate $45,000 in incremental gross sales per meeting; a sizable 68% improvement. The ability to laser-focus on the most attractive advisors is critical since wholesalers can cover only a fraction of advisors in their territories.

Optimizing advisor coverage represents just the tip of the iceberg. Firms can also provide wholesalers with deeper, more relevant insights into advisor behavior, attitudes and purchasing patterns that add up to the winning edge. Imagine gaining insight into the following types of segmentations:

  • What is the profile of your most valuable advisors?
  • Which advisors should be selling significantly more of your funds?
  • Which advisors will be most interested in your newest fund?
  • When are advisors much more likely to be receptive to engaging with you?
  • Why are some advisors not selling a specific fund, even though their sales history suggests they should?
  • Which advisors are information-intensive and enthusiastic about learning more on the latest fund details? (e.g., new fund manager, investment thesis, performance overview)
  • Which advisors are most likely to be influenced by peer results? (i.e., how they compare to other advisors in their office or firm)

Best of all, your firm already possesses the raw materials for sales intelligence: Data. Firms can readily tap into a goldmine of internal data about their advisors. For example, sales and redemption transaction histories provide insight into advisor behavior relative to overall market trends, specific asset classes, and peer advisors. Website click-stream and marketing- response data can also reveal an advisor’s underlying fund preferences and research objectives.

By correlating external data such as fund performance and advisor profiles (e.g., local office demographics, schools attended, professional associations) to advisor selling patterns, wholesalers can “predict” which messages will resonate most forcefully during the next meeting. Informed wholesalers sound more confident, credible and compelling.

To learn what it takes to implement predictive sales intelligence at your firm, click here.

Republished with author's permission from original post.

Ian J. Scott
Dr. Ian J. Scott is the VP of Customer Solutions for Lattice Engines. Prior to that, Ian served as CTO for Angoss. During his career, he has conducted quantitative risk assessment for UBS and also worked for CFM, a Paris-based hedge fund. Dr. Scott holds a Ph.D. in Physics from Harvard and a B.Sc. from McGill.


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