Marketing Automation & CRM
Marketing automation and CRM work is the setup and integration of the systems that manage your pipeline — lead capture, routing, nurture, scoring and reporting. Done well, it tells you which marketing produced revenue. Done badly, which is common, it produces confident dashboards built on data nobody trusts.
The problem
When nobody can answer the revenue question
The board asks which marketing produced revenue and there is no honest answer
There are reports. They disagree with each other, they disagree with what sales believes, and the number everyone ends up quoting is the one from whichever system is easiest to export. Budget decisions are being made on it anyway, because the meeting is on Thursday.
Leads sit
A form arrives on Friday afternoon and reaches a person on Tuesday, by which point the prospect has spoken to someone else. Nobody decided this would happen; it emerged from a routing rule written for an org chart that has since changed twice.
Two systems disagree about the same customer
The CRM has one version, the marketing platform another, billing a third, and each was correct at some point. Reporting picks one and presents it with confidence. Sales works from a fourth version held in someone's head, which is usually the most accurate.
What a real fix takes
These projects fail on adoption, not on configuration. It is entirely possible to build a technically excellent CRM that the sales team routes around within a month, and the result is worse than the spreadsheet it replaced, because now there is an authoritative-looking system containing partial data. That makes the design constraint how your salespeople actually work rather than how a process document says they should — every required field is a tax someone pays under time pressure, and each one you add makes the record less likely to be completed honestly. The other unglamorous truth is that data cleanup usually determines the shape and cost of the whole project, and it is the line item clients most want to shrink. Migrating bad data faithfully gives you the same problem in a more expensive system.
Outcomes
What changes
Leads that get followed up
Routing and alerting so enquiries reach the right person quickly, rather than waiting on someone noticing an inbox.
Reporting you believe
Consistent capture, deduplication, and attribution that reflects your actual sales cycle rather than last-click convenience.
Nurture that runs itself
Sequences for prospects who are interested but not ready, so long cycles do not depend on someone remembering to follow up.
Less manual work
Data entry, list management and handoffs automated — which also improves data quality, because manual re-entry is where data quality goes to die.
What we build
What we build
CRM implementation or cleanup
— object model, pipeline stages, required fields, deduplication, and the process discipline that keeps it clean afterwards.
Lead capture and routing
from forms, chat, calls and events into the CRM with source attribution intact through the whole path.
Lifecycle and scoring
definitions agreed between marketing and sales, so that "qualified" means one thing to both.
Nurture and lifecycle automation
— sequences triggered by behaviour rather than by a calendar.
Attribution reporting
appropriate to your sales cycle, including offline conversion feedback into ad platforms so they optimise toward revenue rather than form fills.
Integrations
between CRM, marketing platform, website, billing and support, so the customer record is one record rather than four that occasionally agree.
What you receive
What you receive
The configured system, in your own accounts, under your licences: object model, pipeline stages, capture and routing, lifecycle definitions, automation and integrations, with the migrated data in it.
Alongside it, the things that decide whether it survives the first quarter. The field and stage definitions written down, so "qualified" means the same thing in six months as it does at handover. The integration map, so the next person knows which system is authoritative for which record. And training delivered to the people who will actually use it, since adoption is the risk that decides these projects and it is not addressed by documentation alone.
How it works
How it works
- Weeks 1–2
Audit and design
Current systems, data quality, process, and where handoffs fail. The data quality assessment usually determines the shape of everything that follows.
- Weeks 2–4
Configuration
CRM structure, capture, routing, lifecycle stages, field standardisation.
- Weeks 4–6
Automation and integration
Sequences, scoring, system connections, reporting.
- Weeks 6–8
Migration, testing and training
Data cleanup and migration, end-to-end testing, and training.
Six to eight weeks is typical for a mid-market setup. The phase that reliably runs longer than planned is data migration, because the exceptions in the existing records surface all at once and each one needs a decision from someone who knows the history — and those people are usually busy for reasons unrelated to your CRM project.
Technology
What we work with
Platforms we work with, recommended against your situation rather than a default. We are not a reseller for any of them and hold no incentive to steer you toward one.
CRM: HubSpot suits marketing-led motions; Salesforce suits complex sales processes and larger teams; simpler tools are frequently the correct answer for smaller operations and get dismissed too quickly.
Marketing automation: your CRM's native tooling where it is sufficient, which it more often is than vendors suggest.
Integration: native connectors where they exist and hold up, and purpose-built integration where they do not — the deciding factor being what happens when a sync fails, which is the question nobody asks during evaluation.
Where the honest recommendation is to configure what you already own rather than buy something new, that is the recommendation.
Where this applies
Where this applies
Strongest where lead volume exceeds what a manual process can handle reliably, or where marketing cannot demonstrate its contribution to revenue — common in fintech, real estate and education, where enquiry volume is high and response speed is decisive.
Weakest at low volume with a short sales cycle. A spreadsheet and prompt follow-up genuinely outperforms an underused CRM, and we would rather say that than implement one.
Frequently the prerequisite for performance marketing rather than a parallel workstream, since paid optimisation is only as good as the conversion data feeding it.
Why us
One team, not three vendors
The usual way
- A strategy consultant, a development shop and a marketing agency, each scoped separately.
- Months spent getting three vendors to agree, and blame to allocate when something breaks.
- The model ships and adoption becomes somebody else's problem.
With Nexiour
- One team across strategy, engineering and growth. You skip the coordination tax entirely.
- We own the whole outcome — from the first audit to the system that is running.
- Delivery across the UK, UAE, Germany and India, with overlapping hours in four markets.
What it costs
How we scope and price
Fixed scope, quoted after an audit. Cost is driven by the state of your existing data, the number of integrations, and the complexity of your sales process.
Data cleanup is frequently the largest single element and we scope it explicitly rather than discovering it midway. Ongoing support is available separately.
FAQ
Frequently asked questions
It depends on sales process complexity, team size, budget and what you already run. We recommend based on your situation, and we are not a reseller for any platform.
Usually, though it takes real work — deduplication, standardisation, enrichment. The more important fix is the process that allowed it to degrade, because without that the same state returns within a year.
When volume is low enough that a spreadsheet and disciplined follow-up genuinely work — an underused CRM is worse than no CRM. When sales will not adopt it, because a system half the team routes around produces data that is confidently wrong. When the actual problem is that nobody agrees what a qualified lead is; that is a conversation between sales and marketing, and no configuration substitutes for it. And when you are buying a platform to fix a process nobody has defined.
Six to eight weeks for a typical mid-market setup. Simple configurations are faster; complex migrations with poor source data take longer, and we assess that before committing to a date.
Only if it makes their job easier, which is a design constraint rather than a training problem. We build around how they work and keep required fields to what is genuinely needed. Adoption failure is the dominant risk in these projects, not technical failure.
We can make it substantially better and honest about its limits. Perfect attribution does not exist, particularly on long cycles with many touchpoints. Anyone promising it is selling a dashboard rather than a measurement.
Yes, and it is increasingly the point — clean CRM data is what makes lead scoring, forecasting and conversational agents work at all. This work is often the prerequisite for the AI work rather than a separate track.
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