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CX & Digital Analytics

Analytics solutions that show how customers move through your business, providing data and insights that you can trust.

Tell us which platforms you run and where the numbers stop adding up. We will tell you where we would start.

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The Client’s Situation

When nobody trusts the numbers

Most organisations already collect a great deal of customer data, across websites, apps and campaigns. The trouble starts when two reports disagree, a tag quietly stops firing, or a definition changes without anyone noticing. Once people stop trusting the numbers they stop using them, and decisions drift back to opinion.

The platform is rarely the whole story. Some teams have invested in enterprise analytics without the expertise to use more than a fraction of it. Others have outgrown the tool they started with and need help choosing a replacement and implementing it properly. Behind both sit the same issues: data held in separate systems, implementations older than the current business, and reports that arrive too late to act on.

Cookie consent has added a newer gap. Customers who decline tracking leave blind spots in the data, and collection methods designed before consent banners existed struggle to keep up. Closing that gap means modernising how data is collected, within what customers have agreed to.

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What changes when the analytics can be trusted

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Numbers your teams stop arguing about.

Every release is tested before it goes live and validated afterwards, so the data behind a decision has been checked rather than assumed.

A view of the whole customer lifecycle.

Behaviour across websites, apps and campaigns brought together in one implementation, so you can follow a customer beyond a single visit. Consolidate customer data from all online and offline channels and devices into a single, unified profile to gain a clear view of each customer’s journey across every touchpoint.

More from the platform you already pay for.

Capability you licensed but never configured gets put to work. And if you have genuinely outgrown the tool, you get an independent appraisal of what to move to.

Collection built around consent.

Data collection designed for customers who decline tracking as well as those who accept it, so the blind spots are known, measured and as small as your customers’ choices allow.

A team that can answer its own questions.

Training built around your own implementation, so the people who need data can find it and report on it themselves.

What the work covers

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1

Data health checks and audits.

CX and digital data health checks, and audits of existing implementations against best practice and business requirements.

Enterprise Ai Knowledge Layer 03 Knowledge And Retrieval Design

2

Data collection design.

Requirements gathering, solution design, and the specification and production of data layers.

Ai Cost Management 04 Workload Optimisation

3

Implementation and integration.

Technical implementation of analytics across websites and apps, plus data integration, warehousing and modelling where analytics data needs joining with the rest of the business.

Agentic Ai 03 Capability Development

4

Reporting and analysis.

Reporting and visualisation, analysis that informs marketing decisions, and attribution across channels.

Training 04 Certification Preparation

5

Training and support.

Bespoke analytics training, upskilling for internal teams, and ongoing technical and analytical support across digital analytics and business intelligence.

Turn your data into a competitive advantage.

Whether you’re trying to prove marketing performance, modernise enterprise reporting, or build a stronger data strategy, we’ll help you create analytics that deliver measurable business value.

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Four steps from first workshop to live data

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We start with what the business needs to know.

Our solution consultants run workshops and interview stakeholders before anything technical happens. For an existing setup, that includes an audit of what is already being collected.

We design before anyone builds.

The requirements, the solution blueprint and the data layer specification are agreed first, so developers know exactly what to build and nobody discovers a gap after launch.

We deliver the complete solution or work alongside your development team.

Our experienced architects and developers can manage the entire implementation or collaborate seamlessly with your in-house team. From data layer implementation to analytics configuration, we align with your development processes and release schedule to ensure a smooth and efficient delivery. 

We check before and after every release

Quality control before anything goes live, then a validation afterwards confirming that each requirement is met and the data is arriving as expected.

What do our clients say?

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Questions we are asked

We implement, migrate and configure analytics for organisations whose customers move between websites, apps and campaigns, and most of those engagements turn into long-term partnerships. Our case studies show the work in detail, from a full best-practice implementation to multichannel reporting.

With an audit. We compare what is implemented against best practice and against your business requirements, then play back the findings with prioritised recommendations and the effort each would take. Nothing gets rebuilt until you have seen what is worth keeping.

Requirements first. Our consultants run workshops and interviews to capture what the business needs to know, and turn that into a business requirements document, a solution design reference and a data layer specification before anything is built. Implementation follows the design, and every release is tested before and after it goes live.

Typically three to six months. The main dependencies sit on the client side: stakeholder availability for discovery, access to systems, and development cycles for the data layer if your own developers or another partner are building it. We plan those in from the start, so the timeline reflects your release calendar rather than an optimistic estimate.

Yes. Support usually runs as a retained agreement: we agree priorities with you and work through them, with our analysts and technical consultants working as an extension of your team. Most of our analytics engagements continue well beyond go-live.

Through a training programme built around your own implementation rather than a generic course, so the people who need data can find it and report on it themselves. The aim is self-serve analytics across the business, with us on hand for the harder questions.

Yes, once the data underneath it can be trusted. Attribution is only as good as the collection behind it, so we start by checking that channels, campaigns and conversions are tracked consistently, then build attribution on the platform that suits your stack, including Adobe Mix Modeler where you run Adobe.

On the technical side, yes. We design data collection that respects consent choices, show you where consent is creating blind spots, and recommend how to reduce them within what your customers have agreed to. Decisions about the legal basis for collecting data belong with your legal and data protection teams, and we give them what they need to make them.

That depends on the shape of the work. Engagements start either as a defined project, such as an audit or a new implementation, or as a retained agreement, and we agree the price against a defined scope rather than quoting from a rate card.

Start by finding out what you can trust

Whether you are questioning the numbers, outgrowing your platform or planning a new implementation, the first step is the same: an audit of what you collect today, measured against what the business needs to know.

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Centar 2000
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Tell us which analytics platforms you use, what you are trying to measure, and where the numbers stop adding up. A consultant who runs these implementations will come back to you.

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