Stephen W.

I design, optimise, and automate customer support and CX operations so they scale cleanly, consistently, and profitably. With 20+ years across B2B SaaS, enterprise support, customer success, and operational transformation, I specialise in CX systems architecture, workflow automation, and customer operations design. I take fragmented workflows, bloated backlogs, manual processes, weak reporting, disconnected tools, and reactive support environments and turn them into structured operating models that teams can actually run. My work covers the full customer operations stack: • CRM • support platforms • onboarding workflows • contracts and e-signature • payments and refunds • knowledge and self-service • chat and AI escalation • automation and reporting If your team relies on spreadsheets, manual updates, disconnected systems, inconsistent macros, or individual knowledge, I redesign the system underneath it. What I deliver • CX and support operating model design • Zendesk architecture, triggers, macros, forms, routing, fields, and reporting • Intercom workflows, product tours, tooltips, help content, chat flows, and self-service • HubSpot CRM setup, companies, contacts, deals, properties, pipelines, and onboarding workflows • DocuSign workflow design, template structure, field mapping, signing flows, and CRM handoff • Stripe-related payment, refund, and support workflow design • Make and n8n automation using APIs, webhooks, and middleware • Manual process reduction across support, refunds, bookings, onboarding, and escalations • Backlog health analysis and capacity modelling • AI escalation and chatbot failure analysis • Knowledge systems aligned to KCS principles • Data-led reporting that surfaces risk early Platforms and systems Hands-on experience across: • Zendesk • Intercom • HubSpot • DocuSign • Stripe • Make • n8n • Jira • Oracle RightNow • Google Sheets and operational trackers • CRM, booking, support, contract, payment, and internal tool integrations Tools are implementation layers. The goal is operational clarity, cleaner workflows, less manual effort, and reliable data. Typical outcomes • Reduced ticket handling time and manual rework • Fewer duplicate, noisy, or avoidable tickets • Cleaner automation and macro architecture • Better routing and escalation control • Stronger CRM and support data quality • Clearer onboarding, contract, payment, and support handoffs • Reduced dependency on spreadsheets and individual knowledge • Better backlog control and utilisation visibility • Early warning indicators for churn, service risk, and operational drift AI escalation and automation leakage I also help teams understand where AI, chatbots, and support automation are failing. This includes analysing AI-escalated conversations to identify where the bot lost intent, missed a handoff request, failed to classify the issue, or created a poorly structured ticket. Typical findings include: • avoidable human escalations • missing intent capture before handoff • poor field population • weak routing or classification • chatbot loops and fallback failures • automation leakage where the customer still ends up in a manual journey The output is a practical improvement plan covering bot flows, routing, ticket fields, triggers, macros, knowledge content, and reporting. Signals I am also the creator of Signals, a CX health analysis engine that detects operational risk signals such as backlog stagnation, routing delays, silent tickets, ageing escalations, and automation leakage before they impact customers. Engagement approach Most engagements begin with a CX systems diagnostic. This reviews your customer journey, CRM structure, support workflows, automation maturity, backlog health, AI escalation quality, manual process load, and reporting integrity. The output is a clear improvement roadmap with prioritised actions. From there, I implement the highest-impact changes first. Structured. Data-led. Practical. If you want to redesign how your customer experience operation actually functions, not just configure software, we should talk.