Company Overview

This engagement was with a Melbourne-based IT services provider employing approximately 50 people. The company delivers managed IT support, cybersecurity solutions, and cloud infrastructure services to businesses across Australia. As a mid-market services firm, their growth depends on the ability to identify the right prospects, understand their technology needs, and engage them with relevant, well-timed outreach.

Despite having a functioning HubSpot CRM, the company's contact and company data was sparse and inconsistent. The sales team had thousands of records at their disposal but lacked the detailed information needed to segment audiences, prioritize high-value prospects, or personalize their outreach at scale. Leadership recognized that enriching their existing data — rather than simply acquiring more leads — was the highest-leverage investment they could make in their go-to-market operation.

The Challenge

The CRM contained 3,000 contact records with incomplete data. In many cases, records included little more than a name and email address. Critical fields like job title, LinkedIn profile URL, phone number, and seniority level were missing, making it nearly impossible for sales representatives to assess whether a contact was a decision-maker, a technical evaluator, or an end user. Without this context, every outreach attempt was essentially a cold call — even to contacts who had previously engaged with the company.

The company-level data was equally thin. Roughly 2,000 company records lacked enriched firmographic data — details like industry classification, employee count, annual revenue range, technology stack, and geographic specifics. Without firmographic data, the sales team could not build meaningful account lists, define ideal customer profiles, or create targeted campaigns for specific verticals or company sizes.

The combined effect of these data gaps was a sales team that could not effectively segment or prioritize their pipeline. Representatives spent time researching prospects manually — checking LinkedIn, visiting company websites, piecing together information one record at a time — instead of focusing on selling. Marketing campaigns were broadly targeted rather than precisely segmented, leading to lower engagement rates and wasted effort.

In addition to the data enrichment needs, the company wanted to improve their customer support operations. Their existing support workflow relied on manual ticket routing and response, which created delays and inconsistencies in the customer experience. Leadership was interested in implementing an AI-powered customer support agent that could handle common inquiries, reduce response times, and free up the support team for more complex issues.

Our Approach

We structured the engagement into two parallel workstreams: data enrichment through Clay and AI agent implementation through HubSpot.

Data Enrichment with Clay

The enrichment effort began with a detailed planning phase. We worked with the Managing Director to define the specific data points that would be most valuable for the sales and marketing teams. For contacts, we identified seven key data points to enrich per record — including job title, seniority level, LinkedIn profile URL, direct phone number, department, location, and professional background details. For companies, we similarly targeted seven firmographic data points per record — including industry, employee count, revenue range, headquarters location, technology stack indicators, founding year, and company description.

With the enrichment schema defined, we configured Clay to process the records in structured batches. Clay's waterfall enrichment approach was particularly well-suited to this project: rather than relying on a single data provider, the platform cascades through multiple sources to maximize fill rates and data accuracy. Each record was processed through the enrichment pipeline, with results mapped back to the corresponding HubSpot properties.

For the 3,000 contact records, enrichment transformed sparse entries into complete professional profiles. Sales representatives could now see at a glance whether a contact was a CTO, an IT Manager, or a Procurement Director — and tailor their outreach accordingly. For the 2,000 company records, the addition of firmographic data enabled the team to build segmented account lists based on company size, industry, and technology environment.

We documented the entire enrichment strategy so the internal team could run future enrichment cycles independently, including guidance on data refresh frequency, field mapping conventions, and quality validation checks.

AI Customer Support Agent

The second workstream focused on implementing an AI-powered customer support agent within HubSpot. We configured the AI agent to handle the company's most common support inquiries — questions about service status, onboarding procedures, password resets, and general IT troubleshooting guidance. The agent was trained on the company's existing knowledge base and support documentation, ensuring that responses were accurate and consistent with the organization's tone and technical standards.

The implementation included routing logic that allowed the AI agent to handle straightforward inquiries autonomously while escalating more complex or sensitive issues to a human support representative. This hybrid approach ensured that customers received fast responses for routine questions without sacrificing the quality of support for more nuanced problems.

We coordinated closely with the Managing Director throughout both workstreams, providing regular progress updates and incorporating feedback at each stage. The engagement also included ongoing support to fine-tune the AI agent's responses and address any edge cases that emerged after launch.

Tech Stack

• HubSpot CRM — Central platform for contact and company management, enriched data storage, and AI agent deployment
• Clay — Data enrichment platform used for waterfall enrichment of contact and company records across multiple data providers
• AI Customer Agent — HubSpot-native AI implementation for automated customer support response and ticket routing

Key Deliverables

• 3,000 contacts enriched — Each record updated with seven professional data points including job title, seniority, LinkedIn URL, and direct contact information
• 2,000 companies enriched — Each record updated with seven firmographic data points including industry, employee count, revenue range, and technology indicators
• AI agent implementation — A fully configured customer support agent capable of handling common inquiries and escalating complex issues to human representatives
• Enrichment strategy documentation — A comprehensive guide enabling the internal team to run future enrichment cycles independently
• HubSpot configuration — Updated property structures, field mappings, and workflow settings to support enriched data and AI agent operations

Business Outcomes

The enrichment effort delivered complete professional profiles for 3,000 contacts, transforming a database of names and email addresses into a segmented, actionable sales asset. Representatives could now filter contacts by seniority, department, and role — enabling targeted outreach that resonated with the specific responsibilities and pain points of each audience segment.

On the company side, firmographic data for 2,000 companies gave the sales and marketing teams the ability to build precise account lists, define ideal customer profiles with real data, and prioritize accounts based on size, industry, and technology fit. This had an immediate impact on the quality and relevance of outbound campaigns.

The AI customer support agent delivered an 80% reduction in support ticket response time. Customers received near-instant answers to common questions, while the support team was freed to focus on complex technical issues that genuinely required human expertise. This improvement in responsiveness strengthened client relationships and reduced the operational burden on the support function.

Together, the enrichment and AI initiatives gave the organization a foundation for more improved targeting across both sales and marketing — moving from broad, untargeted outreach to data-driven engagement strategies built on complete, reliable information.

What the Client Said

The client's Managing Director was closely involved throughout the engagement, coordinating on enrichment priorities and AI agent configuration to ensure the deliverables aligned with the company's growth objectives.