Marketing Operations & CRM
Background
Built and integrated marketing infrastructure at Future Moguls Entertainment without a playbook — no existing CRM, no campaign architecture, no data governance. Designed and deployed the full ops stack from scratch: contact database architecture, lead scoring models, segmentation frameworks, nurture campaigns, and performance reporting — while managing live outreach to UMG, Sony Music, sync contacts, press, and venue buyers simultaneously.
Case 1: CRM Architecture & Infrastructure Build
CRM Architecture · Lead Lifecycle & Design · Segmentation · HubSpot · Marketing Infrastructure
Summary
FME's contact operations had outgrown informal tracking. With an expanding roster and active label relationships across UMG and Sony Music, I led the evaluation, proposal, and implementation of a centralized CRM — building the case for HubSpot internally, aligning stakeholders across A&R, catalog management, and legal, and overseeing the architecture and rollout.
What I did
The contact universe at FME spanned sync licensing contacts, A&R representatives, playlist curators, press, and venue buyers — each with a distinct relationship track and different definitions of progress. A generic out-of-the-box setup wouldn't serve the business, so I developed an internal brief outlining the gaps in our current process, the cost of fragmented contact management, and a recommended platform approach. Once HubSpot was approved, I led the architecture decisions: contact segmentation structure, custom lifecycle stages mapped to how FME actually moved relationships forward, pipeline views by audience type, and the intake governance that ensured data quality from day one.
Stakeholder alignment was ongoing throughout. A&R and catalog management had opinions on how contacts should be categorized; legal needed visibility into certain relationship types for contract tracking purposes. The final architecture reflected input from across the organization while maintaining a clean, operable structure.
The outcome
Leadership gained consistent visibility into the contact base by segment, stage, and activity for the first time. Campaign targeting became more deliberate, and the CRM became the shared operating foundation across departments — used daily by A&R, catalog, and the marketing team.
Extra: Navigating a Platform Fit Problem
HubSpot's default contact stages are built around a standard sales funnel — a structure that didn't reflect how FME tracked relationships with artists, labels, and industry contacts. Adopting it as-is would have meant stages nobody trusted.
I proposed a custom structure mapped to how FME's teams actually described progress — i.e., rather than "MQL → SQL," a curator contact moved through "Identified → Outreach Sent → Active Conversation → Placed." Getting sign-off required walking leadership through the tradeoff, but adoption was strong because the system reflected how people already worked.
Case 2: Data Hygiene & CRM Governance
Data Hygiene · CRM Governance · Deduplication · Contact Management · HubSpot
Summary
As FME's contact database grew across active label relationships and an expanding roster, inconsistent data entry and duplicate records began creating operational friction across departments. I led a structured cleanup initiative and put governance standards in place to prevent recurrence.
What I did
The problem wasn't isolated — contacts had been entered across multiple campaigns and outreach efforts by different team members without a consistent naming or tagging standard. The result was duplicate records, mismatched properties, and contacts sitting in the wrong lifecycle stages. Before any segmentation or scoring work could be trusted, the database needed to be audited and corrected.
I ran a full contact audit, identifying duplicates, incomplete records, and misclassified contacts by segment. Merges were handled deliberately — not bulk-deleted, but reviewed to preserve any interaction history attached to either record. Properties were standardized across the board, and contacts missing required fields were either completed or flagged for removal.
Once the database was clean, I drafted a data entry standard — a short internal document that defined how contacts should be created, what fields were required at intake, and who was responsible for ongoing maintenance by segment. It was reviewed with A&R, catalog management, and support staff before being adopted as the operating standard going forward.
The outcome
Segmentation and reporting became reliable. Campaign lists pulled clean data, and leadership could trust the numbers they were seeing in dashboards. The governance doc reduced re-entry errors and gave the team a clear reference point when questions about contact handling came up.
Extra: Demographic Score Inflation from Overlapping Job Titles
During the audit, I found a segment of contacts carrying inflated demographic scores traced back to how job title data had been entered. Contacts with dual-function titles — i.e., "VP and Director of Music Supervision" — were triggering two separate scoring rules simultaneously: VP scoring at 8, Director at 7, combining to a total of 15 from a single contact property field.
The fix was a scoring cap on the job title field — setting a maximum score that any contact could receive from that property regardless of how many rules matched, in this case 8. It's a straightforward configuration change, but without it, contacts like these would have surfaced as top-priority outreach targets based on a data entry pattern rather than actual seniority or fit.
Case 3: Lead Scoring Model
Lead Scoring · Behavioral Scoring · Demographic Scoring · HubSpot · Pipeline Prioritization
Summary
With a clean contact database and defined lifecycle stages in place, the next priority was building a scoring model that gave the team a reliable way to prioritize outreach — separating contacts who were actively engaging from those who simply fit the right profile on paper.
What I did
I designed a two-dimensional scoring model separating behavioral signals from demographic fit — keeping them distinct so the team could read each independently. A contact with a strong demographic score but no engagement told a different story than one with high behavioral activity and a partial profile match. Collapsing them into a single number would have obscured that difference.
Behavioral scoring tracked actions: email opens, clicks, repeat visits to key pages, and form submissions. Each action carried a weighted value based on how strongly it indicated intent. Demographic scoring was built around role, organization type, and market relevance — properties that indicated whether a contact was worth pursuing regardless of their current activity level.
Thresholds for each dimension were reviewed with A&R and catalog management before being finalized — the scoring model only works if the people acting on it trust what it's telling them. I documented the full scoring logic and left it accessible to the team so adjustments could be made as the contact universe evolved.
The outcome
Outreach prioritization shifted from gut instinct to a defensible, data-backed queue. The team spent less time deliberating over who to contact next and more time executing. Leadership had a clear framework for understanding why certain contacts were being prioritized — which made campaign planning conversations faster and more grounded.
Extra: Decay Logic for Stale Engagement
Early in the model's life, contacts from older outreach cycles were holding high behavioral scores based on activity that was months old — surfacing alongside genuinely active contacts and muddying the priority queue. I added score decay logic: behavioral scores above a set threshold would reduce incrementally after 60 days of inactivity, dropping a contact out of the active priority band until new engagement reset the clock. It kept the queue reflecting current intent rather than historical activity.
Case 4: Nurture Campaign Architecture
Nurture Campaigns · Segmentation · Email Marketing · Workflow Automation · HubSpot
Summary
With lifecycle stages and scoring in place, I designed and deployed segmented nurture campaigns that moved contacts through the pipeline based on behavior — replacing broad, un-targeted outreach with sequenced communication tied to where each contact actually was in the relationship.
What I did
FME's outreach had previously operated on a broadcast model — the same message going to the full contact list regardless of segment or engagement history. That approach was creating noise with high-value contacts and leaving lower-funnel relationships unattended. The fix required rebuilding outreach as a structured nurture system.
I mapped each segment — sync contacts, curators, press, venue buyers, A&Rs — to its own communication track with distinct messaging, cadence, and progression logic. Each track was built as an automated workflow triggered by lifecycle stage entry, with branch logic that responded to engagement signals. A contact who clicked through a pitch email moved to a different follow-up sequence than one who didn't open it. Contacts who went quiet were routed to a re-engagement track before being marked inactive.
Content for each track was developed in coordination with A&R and catalog management to make sure messaging reflected current priorities — active sync opportunities, new releases, or roster developments relevant to that contact type. Campaigns weren't set-and-forget; performance data fed back into content and cadence decisions on a rolling basis.
The outcome
Response rates on targeted sequences outperformed previous broadcast sends by about 15%. Pipeline movement became more consistent — contacts progressed through stages rather than stalling at the same points. The nurture architecture also gave leadership a cleaner view of where relationships stood across the full contact base at any given time.
Extra: Suppression Logic for Active Deals
Automated nurture emails don't know when a human relationship is already in motion. Once the campaigns were live, I flagged a straightforward risk — contacts already in active conversation with A&R or catalog management would keep receiving automated touchpoints unless we explicitly excluded them. An automated follow-up landing mid-negotiation could undermine a relationship that took months to build.
The fix was a suppression list tied to deal stage — anyone marked active in the pipeline was excluded from nurture sends until the deal closed or stalled. The automation runs around the people doing the real work, not over them.