Service operations automation for rapid advisor growth
The challenge they faced
As a leisure travel platform connecting travellers with experienced travel advisors, the team was struggling with inefficient service operations that hampered their ability to scale. The Service Hub lacked visibility into customer service performance, leaving leadership unable to understand why the team felt overwhelmed despite positive customer feedback. The absence of standardised processes created single points of failure when team members were absent, and manual workarounds had become entrenched–team members were spending approximately two hours per day writing manual auto-response emails rather than addressing root causes. Additionally, reporting was unreliable, with inaccurate data such as incorrect customer start dates making it impossible to track true performance metrics.
After internal staffing changes stabilised, the client recognised that temporary structural fixes–such as delegating quick tickets to outsourced support–were masking deeper inefficiencies rather than solving them. With ambitions to double their advisor base from over 5,000 to 10,000 in the coming year, the team knew their current Service Hub configuration would not support that growth. They reached out to Bluleadz to address the foundational problems: user and permission management, property organisation, ticket pipeline optimisation, and the creation of accurate reporting and standardised processes that could scale.
The strategy we mapped
We began by mapping the team's structure and access needs, then established a clean user base and custom permission sets to secure sensitive data while empowering each person to do their work. In parallel, we audited the current service process through discovery calls, identified where standardised playbooks and reusable content would save time, and designed a ticket pipeline that could scale to support the planned growth from over 5,000 to 10,000 advisors. The core constraint was moving from manual workarounds and siloed knowledge to reliable, documented processes–so we prioritised getting the ticket routing and core automation in place early, then layered in the playbooks, templates, and reporting that would let the team operate consistently without depending on any single person.
We cleaned up properties across the system, created new ones to capture fraud signals and process tracking, and set up automation to route tickets by subject line and manage task-driven reopens. By the project's end, discovery shifted to refining edge cases: we built exclusion rules to prevent misrouting when ticket subjects overlapped multiple teams, explored re-enrollment workarounds for member-data-change alerts, and added a process for outbound email to create tickets reliably. Throughout, training and hands-on troubleshooting kept the team moving–team members attended live sessions on playbook usage, template and snippet best practices, and custom views, and we wrapped with a recap to ensure everyone could maintain and iterate on the system independently.
The solutions we executed
Custom permissions and user management. We cleaned up inactive users and created three custom permission sets so team members access only the data their role requires. We also configured property-level permissions for up to ten properties, protecting sensitive information like fraud flags and billing details while letting each team member update what they need to do their job.
We rebuilt the ticket pipeline with eight baseline automations that route incoming requests to the right team based on subject line and ticket type, categorise them consistently, and reopen closed tickets when their related tasks are due. The routing automation considers ticket type, subject keywords, and team availability. We also created five ticket tags for visual organisation and defined a new subcategory to keep the Groups team's work separate from other support areas.
We built three playbooks to guide agent workflows: one for new member onboarding, one for discovery calls across different advisor segments, and one events FAQ to answer common member questions. We set up five message templates and five snippets with personalisation tokens so team members can send consistent, on-brand responses without starting from scratch each time.
We created two service dashboards with twenty reports each, covering ticket volume by advisor tenure, time to ticket resolution, first response times, SLA performance, and NPS tracking. We added a rep-level dashboard so each team member can see their own metrics and know exactly where they stand, giving the team certainty about performance and what to focus on next. The leadership team now has reliable visibility into why the team felt stretched–and proof that positive customer feedback reflects actual operational efficiency.
What changed after the engagement.
The team's Service Hub is now optimized to support growth from over 5,000 to 10,000 advisors. Custom permissions protect sensitive data while enabling each person to do their work without manual workarounds. Eight baseline automations route incoming requests to the right team based on subject line and ticket type, reopen closed tickets when related tasks are due, and categorize work consistently.
Three playbooks guide agent workflows for new member onboarding, discovery calls, and event FAQs. Five message templates and five snippets with personalization tokens let team members send on-brand responses at scale.
Two service dashboards with twenty reports each provide reliable visibility into ticket volume by advisor tenure, time to resolution, first response times, SLA performance, and NPS tracking. A rep-level dashboard shows each team member exactly where they stand, replacing uncertainty about performance with actionable metrics that prove the team's actual efficiency matches positive customer feedback.
Want results like these?
Tell us where your revenue engine is stuck — we'll map the fix in one call.