3 Go-to-Market Challenges in Asset Management

Observations and Takeaways from April’s SME Forum Event – “Latent Leverage: Getting More With What You Have”

Driving greater return from go-to-market investments is imperative across the asset management industry. Increasing the yield on data, technology, content, activation, and talent investments will be critical to overcoming pressing industry issues. From continued margin pressures, significant structural challenges, slow industry progress to digital, non-traditional in-person engagement, and the emergence of new fintech disruptors, next-generation distribution capabilities are critical.

Steven Lewis and I had the opportunity to attend last month’s Sales and Marketing Enablement (SME) Forum in Newport Beach, CA with representatives from a number of asset management firms and industry partners. For two days we listened to compelling, candid, in-depth discussions about industry challenges, best practices, and innovative strategies.

These sessions are always candid, refreshing, and thought-provoking. It’s even more inspiring to see where these firms have come, and where they are going, unveiling their aspirations and ideal states.

Below we share some of our observations and key takeaways from these discussions.

1) Data is at the Center of NextGen Distribution…But Still a Gap

Throughout the conference, it was agreed that clean, consistent, connected data is critical to enhancing customer engagement and distribution. According to our research (and unearthings from this event), data still has its challenges. For one, ¼ of firms said poor data quality was their #1 challenge in data and measurement. In addition, 2/3 of surveyed firms said a lack of third-party data to enhance firm/advisor profiles was an issue.

Observations

• Bringing Data Together from Disparate Systems
  A common theme in each of the four breakout sessions I attended was the ongoing challenge of bringing data together from disparate systems in a way that provides full visibility into advisors/buying units/firms. Many firms are investing in data warehouses like Snowflake, and are working to bring the data together internally (the “build” option) to drive measurement, insight, and analytics. Anecdotally, no firms claimed that they have yet successfully achieved that goal―though progress is being made! Nearly all have data initiatives underway and may are now actively looking for “Chief Data Officer” roles to elevate data as a strategic asset.
• Buying Unit / Third-Party Data
  During the plenary session on Customer Data Platforms, 1 or 2 asset managers indicated they had purchased a third-party CDP (the “buy” option as defined by the CDP Institute). Many firms are still struggling with teams and buying unit data that allow them to better target their marketing and sales activities to the right decision-makers and influencers. Connecting transactional sales data to sales activity continues to be a challenge, and third-party data packs are still an underleveraged investment for many firms.

Moving Forward: Firms’ Strategic Actions

• Leaders in this space must continue to invest in a flexible and modern data strategy and architecture that supports a data- and insight-driven approach to customer engagement.
• 71% of firms said they were increasing focus and investment in data and measurement in 2022 according to our survey. Anecdotally, this is a focus area for many of the SME Forum participants as well.

2) Interest and Investment in Analytics Expands…With Mixed Results

The asset management industry still has a way to go when it comes to leveraging analytics to guide customer engagement. Our research revealed 52% of firms say the lack of well-defined segments and personas is a top advisor insights challenge. In addition, 50% also said limited use of predictive analytics and AI to target customer engagements is a challenge.

Observations

• Segmentation Must Be A Joint Sales and Marketing Effort
  Anecdotally, most firms appear to be leveraging some version of a firmographic segmentation, including dimensions such as sales volume, market share, asset class utilization, channel, or geography. Others are leveraging team data―either first- or third-party―to segment based on buying unit roles and addressing their communications and coverage based on those roles and responsibilities. We have heard mixed results on success with those programs, with the best results seeming to come from a combination of third-party teams’ data, combined with first-party updates by sales in a managed process. Many participants highlighted a disconnect between sales and marketing, and the resulting inconsistent application of segmentation across the two organizations, creating dissonance in the advisor experience.
• Prescribing the “Next Best Action” Requires a Definition Before a Strategy
  While the “Next Best Action” sessions were highly attended, what quickly became clear is that there is not a clear and consistent definition of “Next Best Action” in the asset management industry (which is similar to many other industries by the way!). That said, many agreed conceptually, that Next Best Action relates to the use of data, insight, and technology to prescribe the Next Best Action for a given prospect or customer―at the advisor and/or firm-level―in the context of a specific customer experience. But there were numerous NBA use cases that emerged. Most often mentioned use cases―the recommended next best action to move a prospect or customer towards a sale. But listening closely it was often heard, that mandated or overly prescriptive Next Best Actions are often rejected by sales. In addition, calculating ROI on Next Best Action is still a challenge for most firms. There were a number of interesting discussions around measuring the benefits of NBA, which included the usual suspects – A/B testing, gross/net sales, sales productivity, CSAT/NPS, customer lifetime value, average holding period, and customer retention.
• Artificial Intelligence (AI)/ Machine Learning (ML) – An Aspirational State
  Like the earlier sessions on Next Best Action, this session began with a lot of discussion around the definition of AI/ML and specific use cases for AI/ML in the asset management industry. The data scientists in the group pointed to the strict definition of AI as “the processes and algorithms that are able to simulate human intelligence, including mimicking cognitive functions such as perception, learning and problem-solving. Machine learning and deep learning (DL) are subsets of AI.”By that strict definition, there were very few participants in the session that could point to true AI/ML efforts underway at their firm – though it was certainly identified as a widely used buzzword! One CTO discussed how ML was used to identify RIA networks that were utilizing model portfolios to drive their investment decisions. Several other firms identified interesting pilots they were running that leveraged natural language processing and sentiment- and topic-analysis to help identify trends and inform their data-driven sales and marketing motions. Amazon Connect, and its Contact Lens ML analytics capabilities, were mentioned as a useful tool in the customer service arena supporting ML in the call center. The Azure Open AI Service and the new GPT-3 natural language model were highlighted as potential opportunities for asset managers to leverage these leading-edge technologies through cloud solutions. It is great to see these innovative use cases emerging, but on the whole, AI/ML is still an aspirational goal for most firms vs a current state capability―for all the reasons identified earlier―but one where there is a great deal of interest moving forward.  Hybrid selling has changed the sales coverage model, requiring greater emphasis on analytics and “AI-augmentation” of the sales process.

Moving Forward: Firms’ Strategic Actions

• Asset managers of all sizes must develop robust segments and personas to guide customer experience and engagement and to develop relevant content and personalized messaging aligned with buyers’ journey
• Firms must leverage data and analytics to identify growth opportunities and defection risk ― in tightly-defined and well-measured use cases
• Expand use of third-party data—including experimentation with behavioral and intent signals as they begin to mature

3) Sales-Led Culture Is Still Strong in Asset Management…Making Activation a Challenge

According to our survey, 20% of firms indicated that influencing seller behavior through the delivery of advisor insights is a top challenge. And in that same realm of getting insights to sales (sometimes Marketing gleaned), the disconnect between sales and marketing continues―with 45% saying that this is a Top 3 challenge.

The sales-led culture is still very strong at most asset management firms today. But improved activation and adoption of data-driven sales motions are one of the greatest sources of near-term latent leverage. Several common breakpoints emerged in the discussion groups, along with some interesting best practices on how to close the gaps.

Observations

• Getting to the Trifecta: Right Buyer, Right Message, Right Content
  Oftentimes sales lack the knowledge of specific buyer types and easy access to the appropriate content to execute a recommended “next best action.” While many firms have invested in content management tools like Seismic, few have aligned the content to specific personas and stages in the buyer’s journey, complicating the ability of busy salespeople to execute the appropriate sales motion. This actionability gap can be closed with a shared segmentation, suggested messaging, and recommended content. This requires “connecting the dots” across multiple platforms and aligning around consistent personas and a shared buyers’ journey.
• Lead Prioritization
  Lead prioritization or next best action without appropriate transparency and context is less likely to be activated by sales. Several firms indicated that they no longer exposed lead scores, but rather provided context and detail for why a specific lead or action was recommended. Some were using a star system for grading leads vs. a numeric. These reason codes help to avoid the “lost in translation” phenomenon where sales have no relevant context to support and confirm the recommended engagement, and as a result, recommendations are often ignored.
• Influencing Seller Behavior
  Analytically-based recommendations must be effectively integrated into existing sales processes vs. activity that occurs outside of the traditional sales process. Long excel lists of marketing-generated leads tend to be ignored. Instead, those focusing on embedding analytical insights into existing tools and processes enhanced productivity within existing processes, vs a new process. Several firms indicated they had their analysts go on the road with their sales teams so they had a better understanding of what the sales teams actually did, how they spent their time, and how they engaged with the tools and technology. This helped create a much more collaborative, and ultimately successful approach to embedding insight into the sales process.
• Continuous Feedback Loop on Sales Enablement
  Many firms indicated that their data-driven recommendations were “optional,” meaning the salesperson retained ultimate authority over the client engagement and making the decision around data-driven actions. Instead, they focused on measuring performance, getting feedback from sales to make improvements on the process and the activation, and building support among early adopters of data-driven sales motions to begin to change the sales organization culturally as these programs began to gain demonstrated traction.

Moving Forward: Strategic Actions

• Embed data-driven sales motions into existing processes and provide sellers with sufficient context to understand why a particular action is being recommended.
• Develop a shared, comprehensive firm- and advisor-level customer master that will help ensure sales and marketing alignment and visibility and transparency into the full customer lifecycle.
• Firms should revisit their performance scorecards for enablement and set shared objectives across sales, marketing, and service with common KPIs and metrics across teams to help align activities.

Thanks again to the SME Forum for letting us be a part of and listen to this engaging two-day event! These candid and open discussion forums around industry go-to-market issues, with industry participants and industry vendors participating in an open dialogue, provide a great opportunity to collaborate on the industry’s next-gen distribution enablement solutions.

We are eager to see how technology, analytics, and strategies progress as asset management firms move into a new digital generation, and to participate in the next Forum!