Automating the hand-off from sale to field
When a deal is booked, the automation locates or creates the client in AroFlo, attaches the site and contact, and raises the job in the correct state entity. The AroFlo job number is written back to the deal within minutes, so the sales team never leaves its CRM.
Extending the pipeline to completion
A quote advances the deal, a revised value updates it, and an invoiced job closes it out as work completed. Stages move only forward and no deal is processed twice, so the sales team sees the position in the field without telephoning for it. A historical sweep backfilled every past deal, giving reporting an accurate baseline from day one.
Capturing enquiries at the source
Every website enquiry is read automatically and mapped field by field into a new deal, including the contact, site details and project description, ready for the team within minutes of submission.
Reconciling years of historical data
A staged matching engine worked through companies, contacts and deals, confirming the safest matches first and never guessing the doubtful ones. Confirmed matches received permanent linking identifiers in both systems so that records can no longer drift apart, redundant stub companies were removed, and every run produced a row-by-row audit report.
Reporting leadership can rely on
Two live dashboards cover pipeline health, sales won by owner, invoicing and conversion. Definitions were agreed with the team rather than assumed, periods align to the financial year, and every figure was verified against source data before being treated as final.
Institutionalising the follow-up cadence
Six workflows drive call and task reminders on a timed cadence after every quote, prompt estimators by email, and track response-time KPIs automatically, so that no quote is left unattended in the pipeline.
Making failures visible
A synchronisation error writes a note on the affected deal and alerts the right person automatically, a weekly report records every run in both directions, and edge cases have a self-service path in the sync application so the team can resolve them directly.
Chapter 03
The difference
Precision over volume
In live CRM data, a single incorrect merge causes more damage than ten missed matches and is costly to unwind. Matching was therefore locked to exact identifiers, and anything uncertain was flagged for human review rather than guessed: fewer automatic matches, none of them wrong. The same discipline identified a subtle constraint in HubSpot’s duplicate rules at design time, before it could corrupt records at scale.
Capability transfer, not dependency
The follow-up workflows were deliberately built by RCR’s own team, guided by a step-by-step build guide and reviewed by White Oryx at every stage. Together with a plain-language reference for the sales team and a full technical explainer produced in RCR’s own brand, the client now owns an asset it understands and can extend independently.
Sustained through operation
The engine runs around the clock under an ongoing care plan, and every report provided to RCR passes a strict accuracy review before it is sent: figures are reconciled against the actual run, and preliminary numbers are never presented as final results. The figures hold when they are checked.