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HubSpotCASE STUDY

Revenue Ops Overhaul

A Series-A SaaS team was leaking revenue — leads sat unrouted for hours, scoring was manual and no one knew which reps owned which accounts. We rebuilt the entire GTM engine inside HubSpot.

B2B SaaS−63% lead response time
ClientSeries-A SaaS Co.
IndustryB2B Software
PlatformHubSpot CRM
Timeline6 weeks
RoleRevOps Architect
HubSpotNode.jsAWS LambdaClearbitSlack
−63%
Lead response time
Rep productivity
98%
Routing accuracy
12h→0
Manual work / week
01

Client overview

A venture-backed B2B SaaS company (~40 employees) selling an operations platform to mid-market teams on an annual-contract model. Go-to-market was run by six account executives and two SDRs, with marketing generating roughly 400 inbound leads a month across paid, content and outbound channels.

02

The challenge

The team was running four disconnected tools with no single source of truth. Inbound leads sat in a shared inbox for up to 12 hours before being routed. Lead scoring was a spreadsheet last updated six months earlier. When a rep finally got a lead, half the enrichment data was missing or stale — meaning the first call was always cold.

03

Objectives

04

The solution

01

Audit & data model

Mapped every object, property and association in the existing HubSpot instance. Identified 23 redundant properties and three conflicting lifecycle stage definitions. Agreed a clean canonical model — and a role-based permission set for admins, reps and read-only reporting users — before touching anything.

02

Instant routing engine

Built a Node.js microservice on AWS Lambda that fires on every new contact. It enriches via Clearbit, scores via a weighted model (ICP fit × intent signals), then assigns via round-robin with territory overrides. P99 latency under 400ms.

03

HubSpot workflow layer

Replaced 40+ manual sequences with 12 tight, well-named workflows. Each one has a single trigger, explicit goal criteria and a Slack alert on completion so reps always know what fired and why.

04

SLA alerting & dashboards

Set up escalation alerts: if an MQL sits unworked for 30 minutes, the rep's manager gets a Slack ping. Built a live HubSpot dashboard tracking response time, routing accuracy and pipeline velocity — reviewed in every Monday standup.

05

Technical architecture

Inbound lead (web/ads)HubSpot forms & contactsAWS Lambda enrichment serviceClearbit APILead-scoring engineHubSpot workflowsSlack alertsReporting dashboard
06

Key features delivered

07

Results

08

Challenges

01

23 redundant properties, 3 conflicting lifecycle stages

Years of ad hoc field creation meant reporting could be interpreted three different ways. Resolved by shipping a canonical data dictionary and migrating existing records to it before any workflow went live — automating on top of dirty data would have just automated the mess faster.

02

Sub-second enrichment under real traffic

The Lambda function's cold starts occasionally pushed enrichment past the 400ms target during low-traffic windows. Provisioned concurrency during business hours resolved it without paying for idle capacity overnight.

03

Alert fatigue risk

Early SLA thresholds fired too often and reps started ignoring them. Tuned thresholds against actual working hours and deal value tiers so alerts stayed rare enough to act on.

09

Lessons learned

Final outcome

The team went from a reactive, spreadsheet-driven sales process to a system that routes, scores and escalates leads on its own. Reps spend their time selling instead of triaging, and managers can see pipeline health in real time instead of waiting for a weekly export.

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