CRM selection and systems advisory

This is the question worth answering before any other. Replacing a CRM is expensive, disruptive, and frequently solves nothing, because the thing that broke was never the software.

You probably need to optimise what you already have if

• The platform can do what you need but nobody configured it that way.
• Adoption is patchy because the stages do not match how the team actually sells.
• Reporting is unreliable because required fields were never enforced.
• The system is not connected to finance, the ERP or the inbox where work arrives.

You probably need to replace it if

• The platform genuinely cannot model your sales or service motion.
• Licence cost has drifted far beyond the value being returned.
• The data model blocks the reporting the business needs to run.
• Integration is impossible or economically absurd.

In our experience the first list is far more common than the second. The honest answer is often that you should spend a fraction of the replacement budget on configuration and training instead.

We score across nine weighted areas rather than comparing feature lists. Sales pipeline fit at 15 percent. Workflow automation at 15 percent. Marketing capability, service and support capability, AI capability, reporting and dashboards, integrations and data architecture, ease of use and adoption, and total cost of ownership, at 10 percent each.

Each platform scores 1 to 5 per area, weighted to a figure out of 100. For a typical operationally complex SME that produces indicative scores of HubSpot 86, Salesforce 82, Zoho 78, Microsoft Dynamics 72, Pipedrive 70 and Katalyst 64.

Those numbers are a starting point for a conversation, not a verdict. The weights change with your operating model, and that is the entire point: a business where service drives retention should not use the same weighting as one where marketing drives volume.

List price per user is the smallest part of the number. Twelve factors move the real total, and they are the ones that surprise people at renewal.

• Licence model, and whether it is per seat, per seat type or a flat platform fee.
• How many modules or hubs you actually need.
• Seat count and seat type, paid against free or view-only.
• Marketing contact tiers and list size.
• AI credits and metered usage.
• The automation tier, since workflow depth is usually gated to the higher plans.
• The reporting tier, since custom dashboards often are too.
• The service and support tier, for ticketing and SLAs.
• Integrations, connectors and API limits.
• WhatsApp, SMS and telephony usage charges.
• Mandatory onboarding and configuration fees.
• Implementation partner cost, and the Year 1 spike against the ongoing run rate.

Free: the CRM Fit Finder

An eight minute diagnostic covering twelve categories. It returns one of four routes: optimise what you have, augment it, replace it, or define the operating model first. A senior consultant reads every answer. Start the diagnostic.

Fixed price: the CRM audit

Three days, at a fixed price. We go into the live system, read the configuration, the data and the usage, and come back with a written recommendation: keep and optimise, right-size the licence, or replace, with the reasoning and the numbers behind it.

Build: optimisation

Where the answer is to keep and optimise, the build is quoted as a fixed price covering pipeline and lifecycle redesign, required-field discipline, automation, dashboards and the integrations that matter. Where the answer is to replace, we scope that separately and we will tell you if another firm is the better fit.

We quote fixed scope and a fixed fee. Never a day rate, because a day rate pays us to be slow.

• Milestone terms of 20/30/50. Twenty percent to start, thirty at the midpoint, fifty on completion.
• No platform licence from us. You pay Microsoft, Azure or HubSpot direct, at your own rates, and you own the tenant. If you stop working with us, nothing switches off.
• Support in blocks after handover, rather than a retainer you cannot exit.
• Quotes are valid for 30 days and carry the acceptance criteria in writing.

Where the shape of the work is not yet clear we start with a fixed-price discovery, and it converts into the build price if you go ahead. If we do not think there is a case, we say so and you keep the discovery output.

One principle runs through all of this. Get control of the process and the data first, then automate, then add AI. Automating a broken process makes it break faster and at greater volume.

It also means no parallel CRMs. Running the old system alongside the new one because nobody wants to force the decision is the single most reliable way to end up with two half-populated databases and no source of truth.

Allow around 90 days after go-live to prove adoption. If usage has not landed by then, the problem is design or training, and it will not fix itself.