<aside> 🛠️
I build the systems that turn marketing into pipeline: scoring and routing models, lifecycle architecture, full-funnel attribution, and the AI agents that run inside them. In production, not in a slide deck.
At Deque Systems I report to the CRO, and marketing sourced 60% of pipeline on a stack and a 460K-contact database I own end to end. Before that, I architected the GTM stack at Weaviate through a period of 3.5x ARR growth, and earlier I scaled an eCommerce business from $1M to $98M in annual sales.
I design the model, ship the workflow, and own the number it moves.
</aside>
<aside> 📈
of pipeline marketing-sourced at Deque Systems
</aside>
<aside> 🧭
attribution coverage from a full-funnel model I built from scratch
</aside>
<aside> ⚙️
fewer recurring ops hours after I architected Weaviate's GTM stack
</aside>
<aside> 🚀
annual eCommerce sales I scaled at HKC-US
</aside>
<aside> 📊
ARR growth supported by the lifecycle and MOps systems I built at Weaviate
</aside>
<aside> 🔀
increase in qualified lead assignment from my SAL → SQL → S2 model
</aside>
<aside> 🎯
SQL conversion rate, plus +20% SQL to opportunity, at Deque Systems
</aside>
<aside> 🧪
campaign conversion after I rebuilt Sumo Logic's digital properties
</aside>
Eight builds, grouped by what they do for the business. Every one is work I owned and shipped.
<aside> 🧮
Deque Systems · HubSpot, Amplitude, Salesforce
What I built: MQL and PQL lead scoring in HubSpot on a fit + engagement model with buying-group mapping, fed by Amplitude product and engagement signals.
Why it mattered: Deque sells to developers who self-serve in the product and to enterprise and government buying committees. Form fills alone would miss the developer activity that signals real intent.
How: I blended product and marketing signals so developer activity carries weight alongside form fills, then defined SDR/BDR handoff thresholds, enrichment at handoff, and disposition feedback so sales outcomes flow back into the model.
Result: SQL conversion rate up 26%. SQL to opportunity rate up 20%.
</aside>
<aside> 🧭
Deque Systems · HubSpot, Salesforce
What I built: A full-funnel deal attribution model, from the ground up, that unifies campaign, product, and sales signals into a single reporting model.
Why it mattered: To run a ~$2M marketing and ABM program budget with a straight face, spend, coverage, conversion, and attribution have to live in one operating view with the CRO.
How: One reporting model across marketing, product, and sales data, reviewed in monthly reporting and quarterly business reviews with the CRO.
Result: Attribution coverage up 44%. Marketing sourced 60% of pipeline.
[confirm: does this model use Salesforce Campaigns / campaign influence reporting? If yes, add one line on how.]
</aside>
<aside> 🔀
Weaviate · HubSpot, Salesforce
What I built: The lead lifecycle model (SAL → SQL → S2) with routing rules, enrichment at handoff, and speed-to-lead SLAs into SDR/BDR queues, then on to AEs. Plus the campaign taxonomy, UTM governance, and funnel stage definitions underneath it.
Why it mattered: Weaviate was in a period of 3.5x ARR growth. Marketing and sales needed one shared definition set for routing, scoring, and reporting, or qualified leads would stall between teams.
How: I owned HubSpot → Salesforce object and property mapping so both teams worked from the same definitions, and designed the SDR/BDR handoff end to end.
Result: Qualified lead assignment up over 200%.
[add metric: median speed-to-lead in minutes, and the routing tool used, e.g. LeanData or Chili Piper]
</aside>
<aside> ⚙️
Weaviate · HubSpot, BigQuery, Clay, Amplitude
What I built: The GTM stack for an open-source developer platform, with product usage telemetry piped into the CRM so trial and adoption signals drive routing, scoring, and outreach.
Why it mattered: I launched Weaviate's product-led growth motion. Sales needed to act on product usage and account activity instead of waiting on inbound forms.
How: HubSpot as the system of engagement, BigQuery for warehouse-backed reporting, Clay for automation and agent-assisted enrichment, and product-led sales playbooks on top.
Result: Recurring ops hours cut 40%.
[confirm: reverse ETL from BigQuery into HubSpot/Salesforce? If yes, name the tool and the use case]
</aside>
<aside> 🧹
Deque Systems · HubSpot, Salesforce
What I built: HubSpot → Salesforce data mapping and sync integrity across leads, contacts, accounts, and opportunities, plus the governance program for a 460K-contact database.
Why it mattered: Scoring, handoff, and pipeline reporting all break the moment the MAP and the CRM disagree. And with enterprise, public sector/FedRAMP, and developer segments in one database, consent and deliverability are not optional.
How: Routing field mappings, dedupe rules, and reconciled funnel definitions, built with Revenue Operations and Sales Operations. Consent, suppression, GDPR/CCPA, and DMARC/SPF/DKIM on the database side. I run the martech stack as a GTM systems roadmap, from vendor selection through renewal negotiation.
Result: MAP and CRM stay consistent for scoring, handoff, and pipeline reporting.
[add metric: number of martech tools consolidated and $ saved at renewal]
</aside>
<aside> 🤖
Deque Systems and Weaviate · HubSpot Breeze, Clay Claygents, Langfuse
What I built: Research, enrichment, and list-building agents running in production on HubSpot Breeze at Deque, with human review gates on anything customer-facing. At Weaviate, Claygent-driven enrichment and research workflows for target account programs.
Why it mattered: I treat AI as operating infrastructure, not a feature. Agents should do real work inside the stack and be held to the same standard as any other system dependency.
How: I authored and version a HubSpot Breeze prompt library with the same change discipline as code, and trace and evaluate agent output in Langfuse to catch quality drift before it reaches a prospect.
Result: At Weaviate, Claygent workflows replaced manual list-building for target account programs, part of the 40% cut in recurring ops hours. At Deque: [add metric: hours per week or % time saved by Breeze agents]
Next: I'm evaluating answer engine optimization (AEO) tooling and measurement, for how brand content surfaces inside AI search and LLM-generated answers.
</aside>
<aside> 🎯
</aside>
<aside> 🧪
</aside>
Earlier: At HKC-US I directed DTC and B2B eCommerce across multiple brands, scaling annual sales from $1M to $98M and earning Strategic B2B Partner status with Amazon, Wayfair, and Overstock. As an independent consultant through michaelkmorgan.com, I've built PLG and ABM frameworks where several clients saw SQL conversion improve 3 to 4x.