Building Beta Systems’ North American Demand Engine from the Ground Up
How I established the marketing operations foundation, implemented HubSpot, connected marketing activity to pipeline, and reduced inbound lead response time from more than four hours to under one hour.
At a Glance
Company: Beta Systems Software
Role: Marketing Operations Manager
Scope: North American marketing operations and demand generation infrastructure
Core platforms: HubSpot, Demandbase, AI-assisted automation
Primary outcome: Reduced average inbound lead response time from more than four hours to under 60 minutes
Overview
When I joined Beta Systems, North America was working to build a more systematic demand generation capability inside an organization that had historically grown through sales-led motion. The gap wasn’t campaign volume — it was the operational foundation required to capture demand, evaluate it consistently, move it through the funnel, and connect marketing activity to pipeline. My mandate was to build that foundation from the ground up: HubSpot implementation, lifecycle and lead management, executive reporting, ABM support though Demandbase, and an AI-assisted routing system that cut inbound response time from over four hours to under one hour.
The Challenge
The problem wasn’t a lack of marketing activity. It was the absence of a connected system for turning that activity into measurable pipeline.
Lead stages and ownership weren’t consistently defined, so inbound leads sat in manual review while sales handoffs depended on whoever happened to notice them. Marketing had no reliable way to track a lead through the funnel, and leadership had limited visibility into what marketing was actually contributing to pipeline. Account-based programs existed, but targeting and follow-up weren’t operationally connected to each other.
Adding more campaigns on top of that would have produced more activity without more clarity. The first priority wasn’t volume — it was building a system marketing, sales, and leadership could all trust.
My Role
As Marketing Operations Manager, I was responsible for building the North American marketing operations capability from the ground up: implementing and administering HubSpot, designing lifecycle stages and lead management, building automation and routing, supporting ABM through Demandbase, establishing campaign governance, and building the executive reporting that connected marketing activity to pipeline. The harder part wasn’t configuring the software — it was translating what the business actually needed into an operating model people would use without being told to.
What I Found
A form submission could create a lead, but the organization still had no reliable way to answer the basic questions that follow: was this person a real buyer, where did they belong in the lifecycle, what should own the follow-up, and how fast would that follow-up happen. These weren’t isolated workflow gaps — they were pieces of one lead management system that didn’t yet exist. Fixing any single piece in isolation would just move the bottleneck somewhere else. The fix had to connect data, lifecycle stages, automation, routing, ownership, and reporting at the same time.
What I Built
A HubSpot Foundation
I implemented HubSpot as the operational center of the North American marketing engine — lifecycle stages and funnel definitions, lead and contact management, campaign operations, automation, segmentation, ownership and routing rules, sales notifications, executive dashboards, and the governance to keep all of it maintained. The goal wasn’t just to launch HubSpot. It was to make sure every stage of the buyer journey had a clear definition, an owner, and a next action.
An AI-Assisted Inbound Lead Routing System
Inbound response was the clearest opportunity. The existing process required manual review at every step, which created delay between a prospect raising their hand and sales starting follow-up — average response time was more than four hours.
I built an AI-assisted routing process inside HubSpot that captured new inbound inquiries, evaluated the available lead and company data against the target buyer profile, updated lifecycle stages and properties, assigned ownership, created follow-up tasks, and notified the right rep — with fallback logic for anything the system couldn’t route confidently, and reporting to keep the whole thing measurable.
Getting the routing logic right wasn’t immediate. Accurately assigning leads to the correct business unit took about two weeks of prompt iteration before I trust the system in production. Even after launch, it didn’t catch everything — a smaller set of submissions still required manual routing when the system couldn’t confidently determine ownership. That manual layer wasn’t a gap I tolerated; it was the fallback logic doing its job, catching the cases where a confident automated guess would have been the wrong call.
AI handled the evaluation step, but it didn’t operate without boundaries. Deterministic workflow rules, validation checks, exception handling, and human review were all still part of the system — that combination is what made it faster without turning routing into a black box.
The result: average inbound lead response time dropped from more than 4 hours to under 60 minutes.
Lifecycle Management and Sales Handoffs
Faster routing wouldn’t have mattered if marketing and sales didn’t agree on what each lead stage meant. I established lifecycle definitions and handoff processes that gave both sides a shared language for qualification, ownership, and follow-up responsibility — replacing informal tribal knowledge with something visible and repeatable.
Campaign Operations and Automation
I built the repeatable infrastructure — segmentation, campaign setup, automation, data management, reporting — needed to execute consistently instead of reinventing the operating model with every new campaign. That reusable infrastructure mattered as much as a single campaign that ran on top of it.
Account-Based Marketing Support
I supported ABM through Demandbase by connecting account targeting and engagement signals to the broader lead management and sales follow-up process. ABM doesn’t work as a disconnected list of target accounts — it needs to be wired into account selection, engagement, contact activity, ownership, and follow-up as part of the same system, not a separate campaign type.
Funnel and Executive Reporting
Before this, leadership had limited real-time visibility into how marketing activity moved through the funnel or contributed to pipeline. I built executive dashboards connecting activity, lifecycle progression, and pipeline performance — designed to answer the questions leadership actually asks: how much demand is coming in, how has it’s being routing, where it’s getting stuck, and what marketing is contributing to pipeline. This was North America’s first real-time view into funnel performance and marketing’s pipeline contribution.
How the System Worked Together
None of these pieces mattered much on their own. Campaigns and forms captured demand. HubSpot standardized the data. Lifecycle rules placed each lead in the funnel. AI-assisted evaluation helped prioritize inbound inquiries. Routing automation assigned ownership. Takes and alerts triggered follow-up. Sales activity advanced the record. Dashboards made the whole thing visible to marketing and leadership at once.
The point wasn’t any individual workflow or dashboard — it was that a lead moving through the system now had a traceable answer to every question that mattered: who they are, whether they’re a fit, where they are in the journey, who owns the next action, whether it happened, and what it produced.
Results
Built the North American marketing operations function from the ground up
Implemented HubSpot as the foundation for lifecycle management, automation, campaign operations, and reporting
Reduced average inbound lead response time from more than four hours to under one hour
Established clearer lifecycle stages, routing rules, ownership, and sales handoffs
Built executive dashboards connecting marketing activity to funnel performance and pipeline contribution
Introduced AI into a governed, practical marketing operations use case
Supported account-based marketing through Demandbase
The more important result than any single number was building a system that could be trusted — one where marketing, sales, and leadership were finally looking at the same data and getting the same answer.
Lessons Learned
More campaigns do not fix an operating-system problem
When leads aren’t moving, sales doesn’t trust marketing output, or leadership can’t see what’s driving pipeline, the instinct is often to run more campaigns. That usually just adds volume inside the same broken system. The better starting point is figuring out where clarity, ownership, data, and process are actually missing.
Automating a weak process makes the weakness move faster
Before automating lead management, you have to define lifecycle stages, qualification criteria, routing logic, ownership, and exception handling. Automation should operationalize good decisions — not compensate for decisions nobody’s made yet.
AI works best inside a governed system
The routing process succeeded because AI handled one narrow, valuable task inside clearly defined boundaries. Rules, fallbacks, validation, reporting, and human oversight were still essential. The goal was never to remove people from the process — it was to remove unnecessary delay while keeping judgement and accountability intact.
Reporting should help people make decisions
A dashboard isn’t useful because it has a lot of metrics on it. It’s useful when it helps someone see what’s happening, where the system is breaking, and what to do next.
Marketing operations earns trust through reliability
Marketing gains credibility when leads are handled consistently, sales knows what to expect, leadership can see the connection to pipeline, and the system keeps working without constant intervention.
Closing
The Beta Systems engagement reinforced something I keep coming back to: most marketing performance problems aren’t caused by a lack of activity. They’re caused by disconnected systems, unclear ownership, and processes that can’t reliably turn activity into action. My work is fixing those connections — across technology, data, automation, marketing, sales, and leadership — so marketing becomes measurable, scalable, and trusted.
