I'm Mike Nesci, a B2B Marketing & GTM Operations Professional

CRM & GTM Operations Infrastructure

Building scalable CRM systems through automation, data architecture, and operational workflows

Challenge

As marketing and sales processes became more complex, the HubSpot CRM needed to support increasingly sophisticated campaigns, lead management, sales processes, and reporting requirements. New business needs often required additional data, automation and reporting capabilities, making it important to build systems that could adapt without increasing manual administrative work.

Approach

My focus was on building a CRM foundation that could evolve alongside the business. Rather than solving each operational request independently, I looked for opportunities to create reusable systems that improved data consistency, reduced manual effort, and supported future GTM initiatives.

Whenever Marketing or Sales identified a new operational requirement, I evaluated how it could be incorporated into the CRM through custom properties, workflows, automation, or reporting rather than introducing additional manual processes. I treated the CRM as shared operational infrastructure, designing solutions that could be standardized and reused across campaigns, lead management processes, and Sales workflows.

Key Decisions

• Designed and managed custom HubSpot properties to support segmentation, reporting and automation
• Built automation workflows to manage contact properties, lifecycle data, segmentation and outreach processes
• Created workflows to maintain object associations and improve data integrity of across contacts, companies and deals
• Developed automated notifications and follow-up tasks based on key prospect activity, enabling Sales to respond quickly to high-value engagement
• Created new CRM properties and supporting workflows during a Pipedrive migration to preserve historical CRM data and maintain reporting continuity
• Exported and analyzed CRM data to support reporting, operational decisions, and ongoing process improvements

Results

• Reduced manual administration work through automation and standardized CRM processes
• Improved data consistency and relationship integrity across contacts, companies and deals
• Enabled faster Sales follow-up through automated notifications and task management
• Maintained reporting continuity through the Pipedrive-to-HubSpot migration
• Created reusable systems that reduced the time and effort required to support new campaigns and operational requirements
• Improved visibility into CRM and marketing performance through standardized reporting and data management

Lead Qualification & Segmentation Framework

Building a smarter lead qualification system through automation, behavioiural segmentation, and sales feedback

Challenge

The existing lead scoring process for a B2B healthcare interoperability software company relied primarily on standard engagement metrics, providing limited insight into which leads represented the strongest sales opportunities. As marketing campaigns expanded and inbound volume increased, it became increasingly important to identify higher quality opportunities and provide Sales with more meaningful context around each lead.

Approach

Rather than relying exclusively on quantitative engagement metrics, I wanted the framework to incorporate qualitative insights from Sales alongside behavioural data captured in HubSpot. I had seen some of this information captured in our CRM when investigating leads, and had heard useful feedback from Sales when discussing specific leads. My goal was to create a framework that could evolve over time by combining CRM automation with insights gathered directly from Sales. This meant treating lead scoring as an iterative process rather than a fixed model, continuously refining it as new patterns emerged.

Key Decisions

• Designed and built automated workflows in HubSpot to segment contacts by website behaviour, campaign source, lifecycle stage, and demonstrated product interest
• Developed behavioural segments that provided Sales with richer context around lead intent
• Analyzed qualitative Sales notes using AI tools to identify recurring patterns in customer fit, use cases, and buying intent
• Collaborated with Sales to continuously refine segmentation logic based on real customer conversations and evolving qualification criteria

Results

• Built a scalable lead qualification framework that combined behavioural, lifecycle, and qualitative sales signals
• Improved visibility into lead intent through behavioural segmentation
• Better aligned Marketing and Sales regarding lead qualification
• Created a repeatable process for refining lead scoring using both quantitative and qualitative data

Google Ads Overhaul and Optimization

Reducing acquisition cost while improving lead quality

Challenge

I took ownership of the Google Ads program for a B2B healthcare interoperability software company. Paid search was an important lead generation channel, but the account had evolved over time without a consistent structure, resulting in high acquisition costs and making ongoing optimization difficult.

Approach

I began by auditing the account structure to identify opportunities across keyword targeting, ad relevance, landing page experience, and conversion measurement. Rather than making broad changes all at once, I prioritized incremental improvements and continuously evaluated performance before moving to the next optimization cycle. This iterative approach made it possible to build on successful changes while minimizing unnecessary risk.

Key Decisions

• Reorganized campaigns around user intent and search intent
• Refined keyword targeting to prioritize higher-intent searches
• Optimized ad copy, landing pages, and conversion tracking through iterative testing

Results

• Reduced cost per acquisition by approximately 25%
• Improved the relevance and quality of inbound leads through more targeted keyword selection and campaign structure.
• Organized campaigns for better maintainability and ongoing optimization