Your data has more potential than most businesses unlock. The gap is almost always in the foundations beneath it.
Most organisations have the raw ingredients of customer intelligence. The problem is that those ingredients sit in disconnected systems, arrive in inconsistent formats, and are difficult for business teams to actually use.
Transaction, profile and digital data sit in separate systems with no reliable way to join them, leaving teams working from incomplete and often conflicting pictures of the customer.
Data arrives late, breaks under change, or lands in inconsistent formats that require manual intervention. Teams spend more time fixing data than using it.
Technically the data exists, but it is locked in platforms that business teams cannot easily query or act on. The gap between raw storage and practical use is never bridged.
What we do
Design and build reliable pipelines that bring data from all relevant sources into a single, well-governed environment, on time and in a consistent, usable format.
Transform raw data into structured, business-ready models that make it easy for analytics, marketing and commercial teams to query, segment and act on.
Resolve identities across sources and touchpoints to create accurate, joined-up customer profiles that underpin segmentation, measurement and personalisation.
Connect disparate systems so data flows reliably between platforms, reducing manual effort and ensuring business teams always have access to a current, complete picture.
Create well-defined, accessible data products, curated for specific use cases, so marketing and analytics teams can move faster without depending on technical resource for every query.
Why Loop Horizon
Our advantage is context. We approach data engineering in the context of commercial outcomes: what teams need to segment, measure, activate and optimise. That prevents the common trap of building elegant pipelines that nobody can actually use.
Because we work across analytics, martech and marketing, we understand exactly how downstream teams will use the data we engineer. That shapes every structural decision we make, from modelling choices to access patterns and latency requirements.
Selected examples
Supporting the evolution of data foundations for omnichannel customer experience and marketing activation, helping clients move from fragmented data environments to connected, commercially useful structures that power personalisation and measurement at scale.
Helping clients connect digital, CRM and operational data into usable customer-level structures, enabling faster and more confident segmentation, insight and activation across marketing and commercial teams, backed by a 99.99% data match-rate on one major deployment.
Providing data engineering support that improves trust, accessibility and downstream usage, including completing a full Adobe-to-GA4 migration in four weeks against a live sale deadline, increasing confidence in the data that flows into analytics, reporting and activation.
Talk to us about connecting your data sources and making them commercially useful across your business.