Six portals, six problems, what actually changed.

Bookings flowed into HubSpot from a custom checkout, but nothing connected one booking to the next. Marketing could not tell a first-time guest from a superfan, and abandoned checkouts were leaking with no follow-up.

• Designed 32 booking-history fields on contacts and deals (last and previous tour, city, dates, repeat window).
• Built the workflow that stamps every closed-won booking with the customer's prior booking, then backfilled all 67,000 historical bookings.
• Rebuilt web behaviour tracking through GTM into HubSpot custom events and 143 dynamic lists, and fixed the checkout-abandonment capture that had silently stopped.

29% of walk bookings turned out to be repeats, and 7,531 of them happened within seven days of the previous booking, mostly in a different city. That audience now drives the cross-sell nurture. Abandoned-checkout emails fire again.

Forecasting ran in a BI tool fed by NetSuite and HubSpot, but HubSpot company records were too dirty to roll up: nameless companies, full country names in a two-letter code field on 13,344 contacts, contacts unattached to their company.

• Recovered company names from evidence the client already owned (contact records, domains, NetSuite exports) before spending a cent on enrichment, which we tested and rejected.
• Standardised country data on 649 company records and repaired 13,344 contact country codes, every change logged to a reversible manifest.
• Associated 606 orphan contacts to the company that owns their email domain and sourced 719 missing websites, each rated for confidence.

Company-level reporting and deal roll-ups work again. Every write was verified live after the fact, and the client received review sheets for the records we deliberately did not touch.

Deals carried flattened contact data fed by workflows, but most of it was empty. Nobody knew which of the nine pipelines was authoritative, GDPR subscription types did not exist, and six people were super admins.

• Ran the RevTech HubSpot audit across configuration, data governance, revenue architecture and automation, reading live state through the API rather than trusting screenshots.
• Found workflows matching on a property with a 0% fill rate, an active test workflow hardcoded to one email, and cloned workflows still writing to the wrong field.
• Delivered a prioritised remediation roadmap, then built lifecycle-stage automation and outbound sequences on the cleaned foundation.

A written map of what was broken and why, in the order to fix it, followed by a working lifecycle model and an outbound programme the sales team actually runs.

Partner relationships lived in a spreadsheet. When a sales director opened a deal, nothing in HubSpot said whether a partner already had that account as a client or prospect.

• Modelled partner coverage as company-to-company association labels, maintained by the partner manager in the HubSpot UI, so the source of truth stays where people work.
• Built a custom-coded deal workflow that reads the labels off the deal's company and writes a coloured relationship tag plus the partner names onto the deal.
• Reconciled and imported the partner account list, flagging duplicates and ambiguous matches for the client instead of guessing.

Every new deal now shows its partner relationship on the board, and the client owns the mechanism without touching code.

Each proposal was assembled manually from a legacy template. A new SaaS line needed its own revenue architecture, and the leads object had years of abandoned records nobody dared delete.

• Rebuilt the client proposal as a HubSpot quote template with custom cover, product table and standard terms, so quotes are generated from deal data.
• Designed the Revenue Hub architecture for the new SaaS product line, from product library to pipeline, documented and awaiting a seat decision before build.
• Cleaned 1,466 stale leads with client sign-off, leaving the live pipeline untouched and verified afterwards.

Proposals come out of HubSpot in minutes with consistent terms. The lead view shows only leads someone is working.

No lifecycle model, no lead-status definitions, and an SDR team with no rules for how fast to follow up or when to give up.

• Restructured the lifecycle stage pipeline to the Revenue Architecture stages, pre- and post-customer, with lead statuses gated on a company fit score.
• Built SLA tracking with breach alerts and accelerated SLAs for hot leads, a nurture auto-reset and a disqualification flow.
• Wrote the SDR GTM process guide and an AI agent configuration so the process is documented where the team works.

Leads move through defined stages with response-time SLAs, and management can see where the funnel stalls without asking the team.