A CRM that works for your team — not the other way around.
If your sales team isn't logging, your data is wrong, and your follow-ups are falling through the cracks. We fix the system, not the habits.
How it works
Discover & Map
We audit your current processes and identify the highest-impact automation opportunities.
Design & Build
CRM failure is almost always a systems problem, not a people problem.
Monitor & Optimise
Your automation ships with monitoring, alerting, and a handover pack. We stay available for optimisation.
What's included
CRM failure is almost always a systems problem, not a people problem. When data entry is painful, enrichment is manual, and follow-up reminders require discipline, adoption collapses. We audit your CRM configuration against your actual sales process, eliminate the friction, and build the automation layer that keeps data clean and follow-ups consistent — without requiring your reps to do more admin. Typically delivered on HubSpot or Salesforce, but we work across the major platforms and can integrate with your existing telephony, email, and billing systems.
What you receive
- CRM audit — current configuration, data quality assessment, and gap analysis against your sales process
- Cleaned and deduplicated CRM data set with standardised field values
- Lead routing rules — territory, round-robin, or qualification-based assignment logic
- Automated enrichment pipeline using Clearbit, Apollo, or LinkedIn Sales Navigator API
- Follow-up sequence automations by deal stage and lead source with personalisation tokens
- Deal stage automation triggers — moving deals forward based on logged activities and external signals
- Sales ops dashboard showing pipeline velocity, follow-up compliance, and conversion rates by stage
Typical outcomes
- CRM data completeness lifted from typical <60% to >90% through automated enrichment and mandatory field enforcement
- Lead response time cut from hours to under 5 minutes through automated assignment and outreach triggering
- Zero manually missed follow-ups — every open deal in the pipeline has a scheduled next action
- Deal stage progression automated based on observable signals (email replies, meetings booked, documents signed)
- Sales manager visibility into pipeline health without chasing reps for status updates
- Reduced time-to-close through tighter handoff automation between SDR, AE, and onboarding
Technology we use
Ready to discuss your project?
Book a free sessionTools & integrations we work with
We integrate with your existing stack — no rip-and-replace required.
Common questions about CRM Automation.
Usually yes, but it requires a data remediation sprint before automation is valuable. We run deduplication, standardisation, and enrichment passes on your existing records. For very large datasets we build a pipeline that cleans records in bulk. Starting automation on dirty data just automates the wrong information faster.
Yes. HubSpot's Gmail and Outlook integrations log emails automatically when configured correctly. We set up two-way sync so reps working from their inbox still generate CRM activity without manual entry. For calls, we integrate your telephony platform (Aircall, JustCall, Dialpad) to auto-log calls and generate AI call summaries.
Predictive lead scoring in HubSpot or Salesforce requires meaningful historical data — typically 500+ closed-won and closed-lost deals with consistent activity logging. If you have that, we can build a model that performs well. If not, we start with rule-based scoring on explicit signals (job title, company size, page visits, email opens) and evolve to predictive scoring as data accumulates.
Yes. Bi-directional integration between CRM and downstream systems (PandaDoc, DocuSign, Xero, QuickBooks, NetSuite) is a standard part of CRM automation projects. When a deal moves to closed-won, the quote is countersigned, the invoice is raised, and the onboarding workflow is triggered — without anyone manually updating three systems.
Yes. CRM migrations are a distinct project but one we run regularly. The risk areas are data mapping edge cases, custom field loss, and historical activity preservation. We build a field mapping document, run a test migration on a subset, validate it, and then do the production cutover. We do not recommend migrating and building automation simultaneously.