Your CRM should know what marketing did.

Four things, in order: cleaning and structuring the customer data, connecting the tools that hold parts of the customer, feeding commercial outcomes back to the platforms that buy media, and reporting cost against closed revenue. The middle two are what people picture when they ask for integration, but the first determines whether any of it works and the last is what makes the investment visible. A good engagement leaves you with one customer record, documented syncs, a working feedback loop into your ad accounts, and a report that finance recognises.

Because bidding algorithms optimise toward whatever you tell them is valuable. If the only signal you send is a form submission, they will find you people who fill in forms — including the ones your sales team dislikes. When qualified stages and closed revenue flow back in, the same budget starts hunting for buyers instead. For any business with a sales cycle, this single change usually outperforms months of keyword and audience tinkering, and it is the reason we treat the feedback loop as core integration work rather than a reporting nicety.

Clean first, but only the parts that matter for the decisions ahead. Integration copies whatever quality already exists, faster and to more places — and the evidence on cost is unambiguous: Validity's 2025 research found 37% of organisations losing revenue directly to data quality and roughly 16 deals a quarter lost to bad records. In practice we deduplicate, fix the fields needed for joining spend to outcomes, and add entry validation, then build. Historic records nobody will report on can wait, and often should.

We use a native connector wherever it is honest about what it does and the field mapping survives real use. Many are excellent for the common path and quietly unhelpful at the edges: partial field coverage, no retry on failure, silent overwrites, or a sync direction you cannot control. So we test them against your object model before committing, and build the integration properly where the connector would leave gaps. Fewer moving parts is always the goal — custom code is a maintenance cost, and we only take it on where it earns its keep.

Consent state travels with the record. We capture it at the point of collection, store it in the CRM, and make every downstream sync and conversion upload respect it rather than checking a box once at the front door. Data sent to ad platforms is hashed first-party data, limited to the fields the platform genuinely needs, with retention rules set deliberately. We document what flows where, which is what makes a privacy review straightforward later, and we design so that a change in consent tooling does not require rebuilding the pipeline.

You value the leading stages. Waiting for closed-won on a six-month cycle starves the bidding algorithms of signal, so we map the earlier stages that reliably predict revenue — qualified, demo held, proposal sent — and assign each a value based on historic conversion to close. The platforms get fast, honest feedback; the board still sees closed revenue. Every month we compare the predicted values against what actually closed and adjust, so the model stays anchored to reality rather than drifting into optimism.

Less, and that is usually the fastest way to win their support. Most of the fields sales currently types by hand — source, campaign, first touch, sometimes the company name twice — get populated automatically once the tools are connected. Routing and lifecycle automation removes the manual triage. What we do ask for is agreement on definitions and about an hour a week from someone who owns the pipeline, because a CRM nobody inside the company owns will drift back within a quarter regardless of how well it was built.

Often, and it tends to produce the best result. We usually take the marketing-facing layer — ad platform APIs, web and call data, conversion feedback, marketing definitions — while your team keeps governance, security review and anything touching finance systems. Everything we build is documented and version-controlled so it survives handover, and we work in your repositories and sandboxes rather than ours. Where there is no in-house capability, we run the whole layer and train whoever will inherit it.

The first engagement is normally fixed-scope: audit, cleanup, object model, the core integrations and the conversion feedback loop, priced up front so you approve a number rather than an open-ended retainer. Ongoing support is a monthly fee scoped to the monitoring, reporting and iteration you want. We do not price this work as a share of media spend, because the two are unrelated and tying them creates the wrong incentive. Scope depends mostly on how many applications hold customer data and how bad the duplicates are, which is exactly what the audit establishes.

In practice, anything with an API and most things without one. The common list is CRM and marketing automation, ecommerce and billing, accounting and invoicing, ERP and inventory, call tracking, scheduling and booking apps, chat and helpdesk, and the ad platform APIs. Where a cloud service exposes no usable API we look at webhooks, scheduled exports or a middleware layer — and we will tell you when the honest answer is that a particular integration is not worth its maintenance cost. We prefer fewer, better connections that carry real interactions over a diagram full of arrows nobody monitors.

Yes, and for subscription or invoiced businesses it is usually necessary. Revenue truth lives in the accounting or billing service, not in the CRM, so if refunds, credit notes, cancellations and payment history never reach your reporting, channel efficiency will look better than it is. We sync the records that change the number — invoiced revenue, collected revenue, churn events, subscription upgrades — and reconcile them against pipeline. Where an ERP or accounting platform is sensitive, we keep the flow one-directional into reporting rather than writing back, which is both safer and enough for the decisions marketing needs to make.

The plumbing should be fully automated: syncs, field population, conversion uploads, routing and alerting all run without anyone remembering to do them, and errors reach a person rather than a log nobody reads. Automating that is where the real efficiency gain sits, because it removes the recurring manual export work most teams have quietly absorbed. What stays human is judgment: agreeing definitions, deciding which stages carry value, reading the monthly reconciliation, and choosing what to change. We automate the tasks and keep the decisions visible.

We can, and many clients prefer it because the loop closes faster when the team reading the pipeline is the team changing the campaigns. Our paid search, paid social, CRO and analytics teams all work from this integrated data. It is equally fine to buy the integration alone while other agencies buy your media — we hand over the documentation and report on their performance from the same clean numbers, because a data layer only one agency can read is not worth much.