From Chaos to Clarity: Transforming Data into Strategic Intelligence

Firms are investing in more tools, more feeds, and more data, but many still struggle to make their data actionable. Sales teams rely on stale records. Marketing teams can’t segment effectively. CRM systems become cluttered and overwhelming. The result? Missed opportunities.

So how do you integrate intelligence and make it useful?

I’ve spent most of my professional life exploring new ways to answer this question. It’s something that all organizations face, regardless of their industry, size, or technology. I’ve leveraged my marketing background and data knowledge to help multiple asset managers tackle this question, and here are the lessons I’ve found most helpful:

Transforming Data into Actionable Intelligence

Integrating intelligence means transforming data into a single source of truth.

Creating a single source of truth requires identifying the most reliable data for each field and surfacing it where it matters. For example, if a salesperson has a more current phone number than a vendor-provided record, the CRM should prioritize it.  Actionability begins with simple rules that reflect how your team actually works.

Automated dialers, segmentation and analytics tools, and CRM workflows all depend on accurate and complete data. Data gaps can sabotage segmentation efforts just as much as data inaccuracies. Along with establishing rules that prioritize your most trustworthy sources, it’s important to employ logic to proactively help fill in missing information. Ultimately, the goal is to build a data structure that feels intuitive and aligns with real-world workflows, empowering teams to act with confidence.

The Path from Integrating Intelligence to Gaining Value

Stale data is an issue almost all firms face. The estimated annual churn rate for financial advisors, recently analyzed by ISS Market Intelligence, is around 5%, which equates to roughly 25% of the workforce over a five-year period. That means a list you loaded of 10,000 contacts in 2020 could have 2,500 or more records with outdated information today, and a high probability that a team member’s outreach will land in a dead end.

Duplicates are similarly problematic, and in my experience, the biggest source of frustration with CRM usability. Duplicates are often the result of well-intentioned actions – for example, uploading a new list to support a sales deadline, or keeping an outdated contact to reference historical information, or a team member’s quick interaction with someone at a conference. In all these cases, you can end up with numerous records for the same individual, each containing conflicting details. It’s easy to see how the data mess multiplies.

To help clients overcome these issues, a combination of automation, third-party tools, and smart segmentation is recommended. The typical approach begins by making the problem more manageable: filtering records by last activity date, firm alignment, or recent sales engagement to identify which contacts are most worth cleaning up. Beginning with smaller, focused efforts allows for targeted improvements and helps gradually restore confidence in the data.

Elevate CRM Effectiveness with People and Technology

In an industry where client relationships matter, making your CRM a powerful tool starts with your team, not just the tech. In a world of constant change, the value of collaboration between teams cannot be overstated. Sales, marketing, and client service teams often have overlapping contacts with different details, and it’s important to align on key fields, use cases, and timing so your teams aren’t tripping on each other’s toes. CRMs fail when they’re hard to use, so another key to effectiveness is involving people in designing workflows that match their daily routines while acknowledging the data structure.

AI shows potential for deduplication, enrichment, and even predicting engagement, and as it becomes increasingly integrated into CRM and marketing efforts, the data supporting it must be accurate and aligned. When the data is clean, AI can enrich records, uncover patterns, and signal impact, but it’s only as good as the people guiding and interpreting it.

Starting Your Journey

For firms just beginning their data cleanup or CRM optimization journey, here are my three key pieces of advice:

Start Small: Pick a segment or field that really matters to your team, optimize it, and scale with confidence. Small wins can help your sales team regain confidence in the CRM and increase buy-in for larger efforts in the future.

Adapt and Track: Data clean-up and enrichment don’t happen all at once, and priorities change as time goes on. Keep a record of your data decisions and action steps so you can reference them in the future and repeat or revise as needed.

Know (and express!) your “Why”: Every data decision should tie to a strategic business goal, not just chasing the latest industry trend. When team members all understand the “why”, it helps create alignment and momentum towards the finish line.