CRM Consulting & Implementation
A CRM that tells the truth about your pipeline.
CRM implementation built around how you actually sell, not how the software vendor wants you to sell.
Most CRM implementations fail because they are technology-first: someone buys HubSpot, follows the onboarding wizard, and ends up with a database of contacts and no pipeline. A working CRM is a revenue system, it should capture every lead, score it, route it, track it through every deal stage, and tell you which marketing channel closed the deal. I build that system.
Why CRM implementations fail and what to do differently
The most common CRM implementation failure is the one where the system gets configured, the team gets trained, and six months later fewer than half the users are logging in regularly. The reason is almost always the same: the CRM was configured around the software platform default model rather than the company actual sales process. Lifecycle stages that do not reflect how the business sells. Pipeline stages with no enforced qualification criteria so the same deal can sit in "Proposal Sent" for three months without prompting any action. Lead routing rules that require manual override to work correctly. Contact records with most fields empty because the intake form does not collect the right data. A working CRM is the output of a process that starts with understanding exactly how the company sells, designs an architecture that mirrors that process, and only then configures the software to enforce it. The technology is the last step, not the first.
The data quality problem that undermines most CRM deployments
A CRM with poor data quality is worse than no CRM at all. It creates false confidence: the pipeline report looks populated, but no one knows which opportunities are genuine. The lead source field is empty for a large portion of contacts. Deal stages have not been updated in months. The same company appears under three different spellings in the contact database. These data quality failures make every decision derived from the CRM unreliable. The data quality work starts at the source: form fields that capture the right qualification information at the point of submission, UTM tracking that preserves lead source data through every touchpoint before it reaches the CRM, and validation rules that prevent incomplete records from advancing through the pipeline stages. A CRM with clean data becomes the single source of truth the whole business trusts. A CRM with dirty data is a liability that misleads every decision made from it.
Adoption: the measure that determines whether a CRM delivers any value
CRM adoption is the final phase of every implementation project and the one most often underinvested. A system that is perfectly architected and configured but underused by the sales team delivers no value. Adoption is determined by three factors: whether the system reduces the effort of doing the job rather than adding to it, whether it gives the user information they want in exchange for the information they provide, and whether leadership uses it visibly and consistently enough that it becomes the default source of pipeline truth across the organisation. The adoption phase of a CRM engagement includes live role-specific training for every user, recorded walkthroughs for new team members joining later, a 30-day post-launch data quality review to identify where drop-off is occurring, and a dashboard that the leadership team uses in every pipeline meeting. When the CEO opens the CRM dashboard in the Monday meeting, the team learns to keep the CRM current.
Property structure, lifecycle stages, pipeline stages, and object relationships mapped before any configuration begins.
Clean import of existing contacts, companies, and deals with deduplication, normalisation, and property mapping.
Automated lead assignment rules based on company size, geography, product interest, or SDR availability.
Custom deal stages with entry/exit criteria, required properties, and automated tasks at each stage.
Form submissions, email sequences, and ad platform lead sync connected to CRM with UTM and source attribution preserved.
HubSpot or Looker dashboards showing pipeline by stage, source, and owner, plus conversion rates at each funnel step.
- 01Sales process audit: shadow two sales calls, review existing CRM data quality, and interview the sales team on their actual workflow.
- 02Architecture map: design the property structure, pipeline, and lifecycle model before touching the platform.
- 03Build in sprints: configure in two-week sprints with user testing after each, not a big-bang launch.
- 04Training: live training sessions for every CRM user, plus recorded walkthroughs for future hires.
- 05Adoption review: 30-day post-launch review of data quality and pipeline hygiene.
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