Customer data. Connected to action.
Bring customer information from your website, store, CRM and campaigns into a usable foundation. K4ST scopes CDP implementation and custom customer-data solutions for agencies, connecting that foundation to segmentation, personalisation and AI-assisted marketing.
Discuss a CDP project
A CDP connects first-party customer data from agreed sources and organises it into profiles that can support analysis and marketing activation. Identity rules determine which records belong together. Consent and channel preferences determine how those profiles may be used.
A CRM usually centres on sales and relationship workflows; analytics describes behaviour; campaign tools send messages. A CDP can connect these systems. Not every business needs a new platform: discovery may identify that improving existing data and workflows is the better starting point.
Map events and records, standardise key fields, check freshness and flag missing or duplicate data.
Define how approved identifiers link records, with clear matching rules and controls to reduce incorrect profile merges.
Create audiences using consented behaviour, lifecycle stage, product interest and purchase history where available.
Connect eligible audiences to agreed campaign tools and test triggers, timing, exclusions and suppression rules.
Explore content variations, recommendations, summaries or predictive scoring where data quality and volume support them.
Define a baseline, attribution limits and experiments; review data quality, campaign outcomes and operational reliability.
Connect purchase and engagement data to post-purchase education, replenishment reminders or win-back journeys. Use consent, exclusions and frequency limits.
Join form, website and CRM events to help teams route enquiries and trigger appropriate follow-up. Define ownership and approval before activation.
Adapt content and channel choice to an agreed customer stage. Use controlled tests rather than assume that personalisation always improves results.
Give each end-client a clearly separated view of agreed data and campaign outcomes. Define permissions and reporting requirements before integration.
Map consent and communication preferences to each relevant source and destination. Agree suppression and deletion workflows before launch.
Define roles, least-privilege access and client separation. Select data residency, retention and security controls appropriate to the deployment.
Set human-review points, permitted data inputs and output checks. Do not send raw customer data to AI services without explicit project approval.
Document ownership, audit needs, failure alerts and recovery procedures. Legal review and compliance obligations remain part of the client’s governance.
A project can include technical safeguards, but this page does not promise certification or compliance with a particular law. Requirements and responsibilities are agreed before implementation.
Integration availability is confirmed during discovery. We assess APIs, supported connectors, event collection, authentication, rate limits and data export rights before promising a connection. Third-party fees, messaging charges and ad spend are separate. No platform partnership or certification is implied.
Agree the use case, success criteria, data owners, constraints and the agency’s approval process.
Document sources, identity rules, consent handling, architecture and the first audience or journey.
Configure the selected platform or develop scoped components using approved access and test data.
Check event accuracy, profile matching, exclusions, permissions, failed syncs and journey behaviour.
Activate a limited, approved use case with monitoring, rollback criteria and a measurable baseline.
Provide documentation and training. Agree any further rollout, maintenance or optimisation separately.
CDP and custom data work is custom-quoted. The estimate depends on data sources, integrations, identity complexity, data volume, use cases, hosting and support. Discovery, implementation and ongoing support are shown separately when applicable.
No. We can scope an assessment, implementation of an existing platform or a custom build. The starting point is your client’s use case and current systems.
Yes. The engagement can be structured as white-label delivery, with your agency retaining client ownership and setting the communication and approval process.
This page describes implementation and custom-development services. Software licences, hosting, support and ownership of custom components are defined in the proposal.
Potential use cases include content assistance, recommendation logic, segmentation support and propensity scoring. Feasibility depends on the available data; AI is not required for every workflow.
No fixed uplift is promised. We agree relevant metrics, a baseline and a testing approach. Outcomes also depend on consent coverage, data quality, offers, creative and channel execution.
Timing is estimated after discovery. Source access, integration complexity, data cleanup and client approvals can materially change the schedule.
Start with system names, a business goal and a high-level description of the data. Do not send passwords, API keys or customer records through the enquiry form. Secure access and data-sharing arrangements come later.
Monitoring, maintenance, connector changes and optimisation can be scoped as an ongoing engagement. Availability and responsibilities are agreed explicitly.
Tell us the current systems, the customer journey you want to improve and whether you prefer an existing platform or a custom solution.